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... ONLINE FIRST This is a provisional PDF only. Copyedited and fully formatted version will be made available soon. ISSN: 0015-5659 e-ISSN: 1644-3284 A unique variation of the jugular veins and its clinical significance Authors: McKenzie Young, Alexis Zavitsky, Jillian Niceley, Gabriella Battiston, Sumathilatha Sakthi-Velavan DOI: 10.5603/fm.98618 Article type: Case report Submitted: 2023-12-23 Accepted: 2024-02-13 Published online: 2024-02-23 This article has been peer reviewed and published immediately upon acceptance. It is an open access article, which means that it can be downloaded, printed, and distributed freely, provided the work is properly cited. Articles in "Folia Morphologica" are listed in PubMed. Powered by TCPDF (www.tcpdf.org) CASE REPORT A unique variation of the jugular veins and its clinical significance McKenzie Young et al., Variant veins of the neck McKenzie Young, Alexis Zavitsky, Jillian Niceley, Gabriella Battiston, Sumathilatha SakthiVelavan Division of Biomedical Sciences, Marian University College of Osteopathic Medicine, Indianapolis, IN, 46222, USA Address for orrespondence: Sumathilatha Sakthi-Velavan, Associate Professor of Anatomy, Division of Biomedical Sciences, Marian University College of Osteopathic Medicine, 3200 Cold Spring Rd, Indianapolis, IN 46222, USA; e-mail: ssakthivelavan@marian.edu, tel./fax : +1(317) 955-6245 ABSTRACT The authors report a rare variation of the anterior jugular and internal jugular veins in a 78-year-old male donor. An enlarged and curved left anterior jugular vein (AJV) was formed as the continuation of the left common facial vein (CFV). The left AJVs diameter was wider than the internal jugular vein (IJV) and measured around 5 mm greater than the IJVs diameter and a channel connected the two veins. The right AJV and CFV continued from the two divisions of the right facial vein. The right AJVs diameter was smaller than the right IJVs diameter. The right external jugular vein was absent. No concurrent pathology supported the abnormal dimension of the left AJV and the findings were indicative of a variant anatomy. These variations have rarely been reported and have important clinical correlations. Failed IJV cannulation may result if the variant neck veins are missed. However, variant veins may serve as collateral channels and patch material in IJV reconstruction, carotid angioplasty, and ventricular-jugular shunts. Keywords: jugular veins, anatomical variation, catheterization, venous anastomoses, communicating vein, bilateral variation INTRODUCTION 1 The veins of the head and neck drain the brain, face, and neck [1]. The anterior jugular vein (AJV), formed by the confluence of submandibular veins near the midline, drains into the external jugular vein (EJV) or subclavian vein (SCV) [2]. The internal jugular vein (IJV), the continuation of sigmoid sinus, terminates by uniting with the SCV to form the brachiocephalic vein [2]. The facial vein (FV) unites with the anterior division of the retromandibular vein (RMV) to form the common facial vein (CFV) which drains into the IJV [2]. The posterior division of the RMV unites with the posterior auricular vein to form the EJV which drains into the SCV [2]. Anatomical variations of neck veins are common because of the regions robust vascular network [3]. A clear understanding of the venous variations helps prevent complications like pneumothorax, muscular damage, and carotid artery puncture during procedures [1, 4]. Commonly reported variations in the superficial neck veins include the EJV (most variable), posterior EJV, AJV, and the thyroid veins [1]. Studies reported 26% of 104 patients had either a unilateral or bilateral IJV variation, 0.3 to 2.0% of 330 patients had facial vein (FV) variations, and 6 of 35 (17.1%) donors had CFV variations [3, 5, 6]. This case report explores a unique course and drainage of the AJV and CFV bilaterally, and their clinical significance. CASE REPORT An atypical variation in the formation, dimensions, and the drainage of the left anterior jugular vein was observed in a 78-year-old male donor during routine dissection in the anatomy laboratory. Detailed dissection preserving the veins and related neurovasculature was implemented. The origin, drainage, and tributaries of other neck veins, were explored. The IJV was traced to the cranial cavity and the intracranial sinuses were examined. The enlarged neck veins were opened and the lumina were examined for thrombosis or other pathology. The veins were painted blue with acrylic paint (Apple Barrel Matte Bright Blue Acrylic Craft Paint) and photographed. The vein circumferences were measured using digital calipers at the level of the thyroid cartilage, and diameters were calculated using the equation, circumference/ (Table 1). The left AJV was found to be greatly enlarged and curved on the anterolateral aspect of the neck. It was formed as the continuation of the left CFV and a communicating vein connected it to the left IJV (Figs. 1, 3B). The left AJV united with the left EJV before draining into the SCV at the level of the clavicle. The left IJV was smaller than the left AJV and its counterpart on the right. A communicating vein connected the left AJV and IJV. The left EJV was the continuation of the posterior division of the RMV, while the anterior division of RMV joined the facial vein to form the CFV. The right jugular system differed from the left. The right AJV appeared normal and measured smaller than the left AJV. The right FV terminated as two divisions (Figs. 2, 3A). The posterior division continued as the right CFV, while the anterior division continued as the AJV. Like the left 2 side, a communicating channel connected the AJV and IJV. The right IJV appeared dilated. The right EJV was absent. The lumina of neck veins showed no pathology. DISCUSSION The head and neck veins begin developing in the embryo during week 4 from the cardinal venous system [2]. The ventral pharyngeal vein (VPV), which drains the mandibular and hyoid arches, is the first recognizable vein [2]. The VPV drains into the anterior cardinal vein, which becomes the IJV [2]. Several venous channels from face and neck drains into the IJV [2]. A capillary plexus from the neck forms the EJV [2]. The convergence of the superficial submandibular veins forms the AJVs, which empty into the EJVs [2]. The variant anatomy noted in this case may be due to the lack of or malformation of the venous anastomotic channels. Nayak reported a case in which the FV continued as the AJV in the presence of a communicating vein between the AJV and IJV, unilaterally [7]. Kumar and Baidya reported a case in which the CFV continued as the AJV with no communicating vein between the IJV and AJV, unilaterally [8]. However, this case is unique since bilateral variations with the left CFV and the anterior division of the right FV continuing as the left and right AJV respectively were present. The dimensions of the IJVs and left AJV in this case were noteworthy. Tartire et al. found that the right IJV was larger than the left in 75 to 80% of 190 adult patients [9]. The mean diameter of the right IJV was 17 5 mm, and the mean diameter of the left IJV was 14 5 mm at the level of the cricoid cartilage [9]. In this case, the right IJV was larger than the left IJV, supporting the study. However, the right IJV had a larger than normal diameter above the cricoid cartilage, and the left IJV had a smaller than normal diameter (Table 1). Hojaij et al. reported that the AJVs diameter was 5 mm in 40% of 30 cadavers studied; however, the AJV is typically smaller than the other jugular veins [2, 10]. In this case, the left AJV was larger than the other jugular veins on the left (Table 1) which was likely due to its communication with the other veins. Enlarged superficial veins may indicate a pathological process [7, 11]. Additionally, if the AJV is larger than the EJV, then thrombosis of the EJV may be present [7, 11]. However, no evidence of thrombosis was found in this case, which is suggestive of a variant anatomy [11]. It is likely that the enlarged right IJV and left AJV formed secondary to the smaller left IJV to provide adequate drainage of the head and neck. An absent EJV, as noted on the right side of this donor, may be due to the lack of or malformation of anastomotic channels, such as that between the cephalic vein and FV [2, 12]. In the case of an absent EJV, the veins that typically form the EJV open into the IJV as noted in this case [12]. Catheter mispositioning or failed IJV cannulation may result if the variant superficial veins are not noted [11]. Utilizing ultrasound may help differentiate the IJV from a prominent AJV during 3 cannulation, to prevent unintentional injury [11]. A discernible AJV may serve as a collateral pathway for intracranial venous drainage [11]. Specifically, in the case of unilateral occlusion of brachiocephalic vein and when performing IJV reconstruction, an enlarged AJV is considered useful [11, 13]. Normally, the union of the CFV and IJV is just superior to the carotid bifurcation, providing the surgeon with a consistent landmark [4]. Adequate and accurate access to the bifurcation is essential because it is the most common location of atherosclerosis [14]. When the left CFV does not unite with the IJV, as noted in this case, it cannot be used as an accurate landmark. During carotid angioplasty and endarterectomy, the anterior border of IJV may be helpful in locating the incision site to open the carotid sheath [4]. While an enlarged IJV helps in an easier localization of incision site, it poses an increased risk of injury to the IJV compared to a procedure with a normal or smaller IJV. During cannulation, the right IJV is preferred because it provides direct access to the superior vena cava, is more commonly the dominant hand side, has a lower complication rate, and is typically larger than the left IJV [9]. The larger than normal right IJV, as noted in this donor, provides easier access for cannulation. CONCLUSIONS The presence of variant head and neck veins, reported in this case, can complicate patient care while also providing alternatives if other pathologies or variations are not noted. Without knowledge of a patients variant anatomy, the physician may not be successful in cannulation, catheterization, carotid angioplasty and endarterectomy, and other procedures. Article information and declarations Ethics statement The Marian University Institutional Review Board declared that the study did not need review or approval and cleared the study since the research was on a cadaver (IRB#B23.109). Author contributions McKenzie Young: Study conception, design, dissection, data collection, manuscript preparation and review and preparation of figures 1, 2, and 3. Alexis Zavitsky: Study conception, design, dissection, data collection, manuscript preparation and review and preparation of table 1. Jillian Niceley: Study conception, design, manuscript preparation and review and preparation of Table 1. Gabriella Battiston: Study conception, design, manuscript preparation and review. 4 Sumathilatha Sakthi-Velavan: Conceptualization, guidance, reviewing, editing and funding acquisition. Acknowledgments The authors would like to thank the donor and his family for their generosity so that anatomical research could be performed. The authors also thank Marian University College of Osteopathic Medicine for the support in conducting the research. Conflict of interest The authors declare no conflict of interest. Funding The study was supported by the Marian University Research & Scholarship Administration. REFERENCES 1. Dalip D, Iwanaga J, Loukas M, et al. Review of the variations of the superficial veins of the neck. Cureus. 2018; 10(6): e2826, doi: 10.7759/cureus.2826, indexed in Pubmed: 30131919. 2. Standring S. Development of the head and neck. In: Standring S. ed. Gray's anatomy: the anatomical basis of clinical practice. Elsevier Churchill Livingstone, Edinburgh 2021: 273 291. 3. Bertha A, Rabi S. Anatomical variations in termination of common facial vein. J Clin Diagn Res. 2011; 5(1): 2427. 4. Gupta V, Tuli A, Choudhry R, et al. Facial vein draining into external jugular vein in humans: its variations, phylogenetic retention and clinical relevance. Surg Radiol Anat. 2003; 25(1): 3641, doi: 10.1007/s00276-002-0080-z, indexed in Pubmed: 12819948. 5. Bondaz M, Ricard AS, Majoufre-Lefebvre C, et al. Facial vein variation: implication for facial transplantation. Plast Reconstr Surg Glob Open. 2014; 2(7): e183, doi: 10.1097/GOX.0000000000000134, indexed in Pubmed: 25426366. 6. Lin BS, Kong CW, Tarng DC, et al. Anatomical variation of the internal jugular vein and its impact on temporary haemodialysis vascular access: an ultrasonographic survey in uraemic patients. Nephrol Dial Transplant. 1998; 13(1): 134138, doi: 10.1093/ndt/13.1.134, indexed in Pubmed: 9481729. 7. Nayak BS. Surgically important variations of the jugular veins. Clin Anat. 2006; 19(6): 544 546, doi: 10.1002/ca.20268, indexed in Pubmed: 16372344. 8. Kumar S, Baidya R. Termination of the common facial vein into the anterior jugular vein: a rare case report. Int J Anat Res. 2018; 6(3.2): 55015503, doi: 10.16965/ijar.2018.255. 9. Tartire D, Seguin P, Juhel C, et al. Estimation of the diameter and cross-sectional area of the internal jugular veins in adult patients. Crit Care. 2009; 13(6): R197, doi: 10.1186/cc8200, indexed in Pubmed: 20003190. 5 10. Hojaij FC, Santos L, Moyses R, et al. Anatomy of the anterior jugular veins: anatomical study of 30 cadavers. Arch Head Neck Surg. 2022; 51: e20220005, doi: 10.4322/ahns.2022.0005. 11. Schummer W, Schummer C, Bredle D, et al. The anterior jugular venous system: variability and clinical impact. Anesth Analg. 2004; 99(6): 16251629, doi: 10.1213/01.ANE.0000138038.33738.32, indexed in Pubmed: 15562044. 12. Cvetko E. A case of left-sided absence and right-sided fenestration of the external jugular vein and a review of the literature. Surg Radiol Anat. 2015; 37(7): 883886, doi: 10.1007/s00276-014-1398-z, indexed in Pubmed: 25432662. 13. Katsuno S, Ishiyama T, Nezu K, et al. Three types of internal jugular vein reconstruction in bilateral radical neck dissection. Laryngoscope. 2000; 110(9): 15781580, doi: 10.1097/00005537-200009000-00034, indexed in Pubmed: 10983966. 14. De Syo D, Franji BD, Lovricevi I, et al. Carotid bifurcation position and branching angle in patients with atherosclerotic carotid disease. Coll Antropol. 2005; 29(2): 627632, indexed in Pubmed: 16417173. 6 Figure 1. Left head and neck venous system, 1 thyroid cartilage, 2 internal jugular vein, 3 external jugular vein, 4 posterior division of retromandibular vein, 5 retromandibular vein, 6 anterior division of retromandibular vein, 7 facial vein, 8 common facial vein, 9 anterior jugular vein, 10 subclavian vein, 11 communicating vein between IJV and AJV, 12 common trunk of superior and middle thyroid veins, 13 brachiocephalic vein, 14 common carotid artery, 15 submandibular gland. 7 Figure 2. Right head and neck venous system, 1 thyroid cartilage, 2 internal jugular vein, 3 retromandibular vein, 4 facial vein, 5 common facial vein, 6 anterior jugular vein, 7 communicating vein between IJV and AJV, 8 common carotid artery, 9 submandibular gland. 8 Figure 3. A. Schematic of right head and neck venous system, B. Schematic of left head and neck venous system. 1 submandibular gland, 2 omohyoid, 3 sternocleidomastoid, 4 internal jugular vein, 5 external jugular vein, 6 posterior division of retromandibular vein, 7 retromandibular vein, 8 anterior division of retromandibular vein, 9 facial vein, 10 common facial vein, 11 anterior jugular vein, 12 subclavian vein, 13 communicating vein between IJV and AJV, 14 common trunk of superior and middle thyroid veins, 15 brachiocephalic vein, 16 common carotid artery, 17 posterior division of facial vein, 18 anterior division of facial vein. 9 Table 1. Jugular vein measurements. Diameter at the level of Diameter at the level of angle Left AJV IJV EJV Righta AJV IJV thyroid cartilage of mandible 8.91 mm 3.82 mm 5.10 mm 2.55 mm 1.91 mm 15.92 mm 11.46 mm a) No EJV was observed on the right side. AJV anterior jugular vein; EJV external jugular vein; IVV internal jugular vein 10  ...

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... Breast Cancer Research Edwards et al. Breast Cancer Research (2024) 26:34 https://doi.org/10.1186/s13058-024-01791-z Open Access RESEARCH PTHrP intracrine actions divergently influence breast cancer growth through p27 and LIFR Courtney M. Edwards1,2, Jeremy F. Kane1,2, Jailyn A. Smith2,3, Dja M. Grant1,2,4, Jasmine A. Johnson2,3, Maria A. Hernandez Diaz2,3, Lawrence A. Vecchi III2,3, Kai M. Bracey5, Tolu N. Omokehinde1,2, Joseph R. Fontana2,6, Breelyn A. Karno2,6, Halee T. Scott2,6, Carolina J. Vogel7,8, Jonathan W. Lowery7,8,9,10, T. John Martin11,12 and Rachelle W. Johnson1,2,3* Abstract The role of parathyroid hormone (PTH)-related protein (PTHrP) in breast cancer remains controversial, with reports of PTHrP inhibiting or promoting primary tumor growth in preclinical studies. Here, we provide insight into these conflicting findings by assessing the role of specific biological domains of PTHrP in tumor progression through stable expression of PTHrP (-36-139aa) or truncated forms with deletion of the nuclear localization sequence (NLS) alone or in combination with the C-terminus. Although the full-length PTHrP molecule (-36-139aa) did not alter tumorigenesis, PTHrP lacking the NLS alone accelerated primary tumor growth by downregulating p27, while PTHrP lacking the NLS and C-terminus repressed tumor growth through p27 induction driven by the tumor suppressor leukemia inhibitory factor receptor (LIFR). Induction of p27 by PTHrP lacking the NLS and C-terminus persisted in bone disseminated cells, but did not prevent metastatic outgrowth, in contrast to the primary tumor site. These data suggest that the PTHrP NLS functions as a tumor suppressor, while the PTHrP C-terminus may act as an oncogenic switch to promote tumor progression through differential regulation of p27 signaling. Introduction Parathyroid hormone-related protein (PTHrP) is a pleiotropic hormone encoded by the PTHLH gene located on chromosome 12, with nine exons and at least three identified promoters [1]. In humans, alternative splicing gives rise to three mature isoforms containing 139, 141, or 173 amino acids, and the first 111 amino acids of the PTHrP sequence are highly conserved among different mammalian species [2]. Regulation of PTHrP is complex and tissue-specific, with the molecule containing numerous cleavage sites and post-translational modifications [1]. The PTHrP polypeptide contains an intracellular *Correspondence: Rachelle W. Johnson rachelle.johnson@vumc.org 1 Graduate Program in Cancer Biology, Vanderbilt University, Nashville, TN, USA 2 Vanderbilt Center for Bone Biology, Vanderbilt University Medical Center, Nashville, TN, USA 3 Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA 4 Meharry Medical College, Nashville, TN, USA 5 Department of Cell and Developmental Biology and Program in Developmental Biology, Vanderbilt University, Nashville, TN, USA 6 Vanderbilt University, Nashville, TN 37232, USA Marian University College of Osteopathic Medicine, Indianapolis, IN, USA Bone and Muscle Research Group, Marian University, Indianapolis, IN, USA 9 Academic Affairs, Marian University, Indianapolis, IN, USA 10 Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, USA 11 Bone Cell Biology and Disease Unit, St. Vincents Institute of Medical Research, Fitzroy, VIC, Australia 12 Department of Medicine, The University of Melbourne, St. Vincents Hospital, Fitzroy, VIC, Australia 7 8 The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the articles Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the articles Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Edwards et al. Breast Cancer Research (2024) 26:34 trafficking and secretion signal, a domain that controls binding to and activation of the classical parathyroid hormone type 1 receptor (PTH1R), and a mid-molecule domain that regulates placental calcium transport. Additionally, the molecule possesses a domain historically termed the nuclear localization sequence (NLS) from amino acids 6794 which regulates nuclear import based on studies carried out in chondrocytes [3], and a carboxy-terminal (C-terminal) domain (beginning at residue 107), to which a number of biological activities have been ascribed [4, 5]. Beyond its well-characterized endocrine and paracrine roles in inducing hypercalcemia of malignancy [6, 7] and tumor-induced bone disease [811], PTHrP regulates the growth of numerous tissues through its intracrine (intracellular) effects on cell survival, proliferation, apoptosis, invasion, and migration, which can occur independent of PTHrP:PTH1R binding on the cell surface [1215]. PTHrP acting through its classical NLS (67-94aa) alters proliferation in peripheral tissues including vascular smooth muscle [1618], where PTHrP also has a smooth muscle relaxing effect [19, 20]. Though less well studied, PTHrP also plays an important role in tumor development. In patients, PTHrP is detectable in most primary breast tumors [11] and serum PTHrP levels are elevated in the majority of patients with hypercalcemia due to breast cancer bone metastases [21, 22]. However, studies have not identified a direct association between elevated serum PTHrP levels in patients and enhanced primary breast tumor growth. The role of PTHrP in primary breast cancer progression remains highly controversial. Some clinical studies demonstrate that PTHrP expression in the primary tumor correlates with improved patient survival and formation of fewer bone metastases [23, 24], while others report that PTHrP is associated with worse patient outcomes [11, 25, 26]. Conflicting data from pre-clinical studies have further confounded the field; genetically similar mouse models that spontaneously form mammary carcinomas have produced directly conflicting results suggesting that PTHrP can inhibit [27] or promote breast tumorigenesis [28]. Thus, the prognostic role for PTHrP in primary breast tumor progression remains largely unclear. In contrast to its uncertain role in the primary tumor, PTHrP has a well-defined deleterious effect on patient outcomes in later stages of disease progression, where its expression drives bone colonization and metastatic tumor growth [11, 26, 29]. Bone disseminated breast cancer cells secrete osteolytic factors like PTHrP, which induces receptor activator of nuclear factor-B ligand (RANKL)-dependent osteoclastogenesis through PTH1R activation on osteoblasts [30]. In human MCF7 breast cancer cells, which normally lie dormant in bone [9, 3133], overexpression of PTHrP (1-139aa) reprograms Page 2 of 17 the cells to become highly osteolytic and dramatically increases bone tumor burden in vivo [9]. Our studies suggest that this potentially occurs through PTHrPmediated suppression of the breast tumor suppressor leukemia inhibitory factor receptor (LIFR) [32, 34, 35] and other pro-dormancy factors [30, 3336]. Our group, and others, have reported evidence that PTHrP can regulate breast tumor progression independent of paracrine or autocrine activation of PTH1R or downstream canonical cAMP signaling [37, 38]. This suggests that PTHrP acts in an intracrine manner to influence breast tumor cell behavior. In support of this, PTHrP (38-94aa) containing the calcium transport region and NLS has been shown to bind to chromatin [39], and full-length secreted PTHrP (-36-139aa) has been shown to localize to the LIFR proximal promoter [40]. In this study, we sought to determine how the intracrine activity of the PTHrP NLS (67-94aa) regulates breast tumor growth and how this effect may be co-regulated by the C-terminal region, since a role for these domains had not been examined in breast cancer cells. In vitro expression of endogenous PTHrP is quite low [32] and there are no reliable antibodies to detect its endogenous isoforms or biological domains. Thus, we rely on an engineered system of expressing truncated mutant proteins with deletion of the PTHrP NLS and C-terminal domains. Our findings begin to provide insight into some of the conflicting preclinical data in the literature, which may provide a framework for targeting PTHrP and its downstream signaling mediators in breast cancer. Results Human breast cancer cells generated to express full-length PTHrP or truncated peptides To determine how PTHrP and its biological domains regulate breast tumor progression, we generated MCF7 human breast cancer cell lines that stably express different domains of the PTHrP molecule (collectively referred to herein as PTHrP mutant cell lines). The plasmids express full-length secreted PTHrP (termed FLSEC, -36-139aa), or truncated forms lacking the classical NLS alone (termed DNLS, -36-6795-139aa) or NLS and C-terminal domain (termed DNLS + CTERM, -36-67aa) with a C-terminal HA tag that is absent in the MSCV control (Fig. 1A). We were unable to generate a mutant with deletion of the secretion signal since these cells do not survive in vitro. We validated plasmid expression at the protein level using an anti-HA antibody and at the mRNA level with qPCR primers targeted to amplify different regions of the Pthlh gene (Fig. 1B-E). To verify expression of the plasmids and characterize the intracellular localization of the PTHrP peptides, we performed immunocytochemical staining for the C-terminal HA tag (Fig. 1F). We confirmed an absence of HA Edwards et al. Breast Cancer Research (2024) 26:34 Page 3 of 17 Fig. 1 Validation of plasmids expressing specific PTHrP domains. (A) Pthlh overexpression construct design and validation in MCF7 cells by (B) western blot for the C-terminal HA-Tag and qPCR for the (C) mid-region, (D) nuclear localization sequence (NLS), and (E) C-terminal domain. MSCV = control, FLSEC = full-length secreted, DNLS = NLS deleted, DNLS + CTERM = NLS and C-terminal domain deleted. Predicted molecular weights: FLSEC PTHrP (-36139aa) = 21.2kD, DNLS PTHrP (-36-67aa)(95-139aa) = 18kD, DNLS + CTERM PTHrP (-36-67aa) = 12.8kD. GAPDH = loading control. (F) Immunocytochemical staining for HA-Tag (green) and DAPI (blue). All panels = 100X and scale bars = 25 m. (G) Secreted PTHrP (1-34aa) levels measured by ELISA from conditioned media of cells described in (A). (B-E & G) n = 3 independent biological replicates. Graphs represent mean SEM. (C) **p < 0.001 vs. MSCV or *p < 0.05 vs. FLSEC by one-way ANOVA with multiple comparisons. (D) **p < 0.001 vs. FLSEC by one-way ANOVA with multiple comparisons. (E) **p < 0.001 vs. DNLS by one-way ANOVA with multiple comparisons expression and fluorescence staining in the MSCV control cells as these plasmids do not contain a C-terminal HA tag. Full-length secreted PTHrP localized to both the nucleus and cytoplasm. Deletion of the NLS alone or NLS and C-terminal domain did not preclude nuclear entry as each PTHrP mutant protein was present in the nucleus as well as cytoplasm (Fig. 1F & Supplementary Fig. 1), regardless of whether they expressed the classical NLS. Therefore, these truncated PTHrP peptides likely gained entry into the nucleus independent of this recognized NLS. While we cannot modulate relative amounts of the PTHrP peptides as it is not possible to accurately Edwards et al. Breast Cancer Research (2024) 26:34 engineer our model system in this manner, we observed no statistically significant difference in PTHrP levels secreted by the PTHrP mutant cell lines compared to controls as measured by an enzyme-linked immunosorbent assay (ELISA) for PTHrP (1-34aa) (Fig. 1G). Thus, altering expression of the NLS or the C-terminal domain does not affect PTHrP secretion by MCF7 cells. Additionally, differences in phenotypes between the PTHrP mutant cells are likely not due to paracrine effects of secreted PTHrP since we and others have previously shown that PTHrP does not activate PTH1R or downstream cAMP signaling in breast cancer cells [37, 38]. The PTHrP NLS and C-terminal domain oppositely regulate breast tumor progression Next, we sought to determine how PTHrP and its biological domains regulate primary breast tumor growth in vivo. Overexpression of full-length PTHrP (-36-139aa) did not significantly alter time to tumor palpation or tumor size compared with controls (Fig. 2A-C and A: p = 0.0497 Log-rank, p = 0.0012 Gehan-Breslow-Wilcoxen; 2B: ANOVA p < 0.0001). Strikingly, deletion of the PTHrP NLS alone resulted in tumors that formed significantly earlier and grew larger than controls, while deletion of both the NLS and C-terminal domains completely reversed this phenotype such that the tumors grew significantly slower and smaller (Fig. 2A-C). To confirm that the PTHrP mutant plasmids were still expressed in vivo, we performed immunofluorescence staining of the primary tumors for the C-terminal HA tag, which was appropriately present in all tumors except the MSCV group, since the MSCV control plasmid does not contain an HA tag (Supplementary Fig. 2). We next assessed whether the changes in tumor size were due to increased proliferation, or reduced cell death. Deletion of the PTHrP NLS alone significantly increased the percentage of Ki67 + positive cells (Fig. 2D) and mitoses (Fig. 2E) in the primary tumors while deletion of both the NLS and C-terminal domain resulted in significantly decreased mitoses (Fig. 2E). There was no difference in cleaved PARP staining in any of the PTHrP mutant cell lines compared to MSCV controls (Fig. 2F). Collectively, these data suggest that the PTHrP NLS regulates breast tumor growth by increasing tumor cell proliferation without impacting apoptosis, but this function is abolished when the PTHrP C-terminus is deleted. p27 is differentially regulated by the PTHrP NLS and C-terminal domains in breast cancer To better understand the in vivo phenotype and mechanism by which the PTHrP NLS and C-terminal domains differentially regulate breast cancer cell proliferation, we performed RNA sequencing on the PTHrP mutant cell lines. We identified several hundred significantly Page 4 of 17 altered genes ( log2 fold change 1 or log2 fold change 1, p < 0.05) that were differentially expressed across the PTHrP mutants (Fig. 3A, Supplementary Data 1). Gene Set Enrichment Analysis (GSEA) of these data revealed that in cells lacking the PTHrP NLS, there was a significant enrichment for genes that are upregulated in MCF7 cells overexpressing the oncoprotein and cell cycle promoter, cyclin D1 (Fig. 3B), indicating that the PTHrP NLS modulates the expression of cell cycle regulators to alter proliferation in MCF7 breast cancer cells. Furthermore, cells expressing PTHrP lacking both the NLS and C-terminal domain were positively enriched for genes involved in the p53 pathway (NES = 1.53, FDR = 0.053). We also examined enriched cancer Hallmark pathways, which revealed an increase in additional cell cycle-related pathways, including G2M Checkpoint and Mitotic Spindle genes (Fig. 3C&D). Based on these RNA sequencing data which pointed to differences in genes encoding cell cycle regulatory proteins, and since p21 and p27 are known to be regulated downstream of PTHrP in other cell types [1618], we investigated these cell cycle factors as a mechanism by which the PTHrP NLS and C-terminal domain oppositely influence breast tumor growth. Immunocytochemical staining revealed that while overexpression of full-length PTHrP (-36-139aa) did not alter p27 levels (Fig. 3E), p27 expression was significantly lower with deletion of the NLS alone compared to control cells. Furthermore, expression of p27 was significantly increased with deletion of both the NLS and C-terminal domain, exceeding levels in both MSCV controls and NLS-alone deleted cells (Fig. 3E). Immunofluorescent staining of the primary breast tumors similarly revealed no change in p27 with overexpression of the full-length PTHrP molecule, but p27 protein levels were significantly decreased with deletion of the NLS alone compared to controls, and oppositely increased with deletion of both the NLS and C-terminal domain (Fig. 3F). Interestingly, in vivo p27 protein levels still remained lower than controls with deletion of both domains (Fig. 3F). When we assessed p21 protein expression, we found inconsistent staining patterns between in vitro cultured cells and in vivo tumor sections; however, we did see a modest increase in p21 staining in tumors expressing full-length secreted PTHrP, suggesting p21 may be regulated downsteam of the intact PTHrP molecule in the context of the tumor microenvironment (Supplementary Fig. 3A&B). Together, these in vitro and in vivo findings suggest that p27 is oppositely regulated by the PTHrP NLS and C-terminal domain in breast cancer, with much lower levels in fast-growing tumors. The difference in p27 expression may therefore contribute to the differential proliferation and breast tumor growth effects observed in vivo. Edwards et al. Breast Cancer Research (2024) 26:34 Page 5 of 17 Fig. 2 Deletion of the PTHrP NLS alters breast cancer cell proliferation and primary tumor growth. (A) Time to tumor palpation, (B) tumor volume over time by digital caliper measurement and (C) final tumor weight in mice inoculated with MSCV, FLSEC, DNLS, or DNLS + CTERM cells into the mammary fat pad. n = 710 mice/group. (D) Ki67 staining and quantification from tumors in (A-C). (E) Quantification of mitoses (# mitotic figures/total cells in 40X field) by DAPI staining from tumors in (A-C). (F) Cleaved PARP staining and quantification from tumors in (A-C). All panels = 40X and scale bar = 50 m. (A) *p < 0.05 vs. MSCV by one-way ANOVA with multiple comparisons or #p < 0.05 DNLS vs. DNLS + CTERM by unpaired t-test. (B) ****p < 0.0001 vs. MSCV by one-way ANOVA with multiple comparisons or **p < 0.01 vs. DNLS by unpaired t-test. (C) **p < 0.01 vs. MSCV by one-way ANOVA with multiple comparisons or ***p < 0.001 vs. DNLS by unpaired t-test. (D) **p < 0.01 vs. MSCV by one-way ANOVA with multiple comparisons. (E) *p < 0.05 vs. MSCV by one-way ANOVA with multiple comparisons or *p < 0.05 vs. DNLS by unpaired t-test. Graphs represent mean SEM PTHrP regulates downstream LIFR signaling to alter p27 expression in vitro We previously demonstrated that PTHrP localizes to the proximal promoter region [40] and downregulates breast cancer cell expression of leukemia inhibitory factor receptor (LIFR) [32], which is a known breast tumor dormancy regulator in bone [32, 36], breast tumor suppressor, and lung metastasis suppressor [34, 35]. The downstream signaling mechanisms by which LIFR regulates breast tumor growth remain incompletely understood. While LIFR is a cell surface receptor, it can also be internalized to the cytoplasm once bound by the LIF ligand [41]. Although overexpression of full-length PTHrP (-36-139aa) has been shown to downregulate Edwards et al. Breast Cancer Research Fig. 3 (See legend on next page.) (2024) 26:34 Page 6 of 17 Edwards et al. Breast Cancer Research (2024) 26:34 Page 7 of 17 (See figure on previous page.) Fig. 3 PTHrP lacking the NLS and C-terminal domain regulates proliferation by altering expression of p27. (A) Number of genes identified by RNAseq with log2fold change > 1 and p < 0.05. (B) GSEA plot from DNLS cells showing enrichment of Cyclin D1 gene signature in MCF7 cells. (C) GSEA plot from DNLS + CTERM cells showing enrichment of genes that regulate the G2M checkpoint. (D) Top twenty enriched Hallmark pathways from FLSEC, DNLS, and DNLS + CTERM cells. (E) Immunocytochemical staining and quantification of p27 in MSCV, FLSEC, DNLS, or DNLS + CTERM cells. n = 3 independent biological replicates. All panels = 40X, scale bar = 25 m. (F) Immunofluorescence staining and quantification for p27 in primary tumors from mice inoculated with MSCV, FLSEC, DNLS, or DNLS + CTERM cells. All panels = 40X, scale bar = 50 m. (E) **p < 0.01 or ****p < 0.0001 vs. MSCV by one-way ANOVA with multiple comparisons or ****p < 0.0001 vs. DNLS by unpaired t-test. (F) *p < 0.05 or ***p < 0.001 vs. MSCV by one-way ANOVA with multiple comparisons or **p < 0.01 vs. DNLS by unpaired t-test. Graphs represent mean SEM LIFR in vitro [32, 36, 38], we observed no difference in LIFR protein expression in vivo with overexpression of the full-length PTHrP molecule (Fig. 4A). Deletion of the PTHrP NLS alone modestly suppressed LIFR levels compared to MSCV controls while deletion of both the NLS and C-terminal domain significantly increased expression of LIFR compared to tumors lacking the NLS alone, which restored levels close to that of the control tumors (Fig. 4A). This pattern of increased LIFR expression with deletion of the PTHrP NLS and C-terminal domain (compared to NLS alone deletion) mirrored the previously observed trend in tumor p27 expression. Thus, we hypothesized that PTHrP may regulate tumor cell proliferation through p27 signaling downstream of LIFR, resulting in altered breast tumor cell proliferation. To investigate this further, we treated the PTHrP mutant cells with a commercially available LIFR inhibitor (EC359) that blocks receptor/ligand interactions. Effective LIFR inhibition was confirmed by decreased phosphorylation of the downstream LIFR signaling factor, pERK (Fig. 4B & D). We did not observe changes in cell cycle phases with LIFR inhibitor treatment of the PTHrP mutant cells (Supplementary Fig. 4A). In the vehicle treated group, p27 remained significantly higher in cells expressing PTHrP lacking the NLS and C-terminal domain compared to those lacking the NLS alone (Fig. 4C). After 24 h of low dose LIFR inhibitor treatment (50nM), this difference was no longer significant (Fig. 4B & C). High dose treatment of LIFR inhibitor (100nM) for 24 h completely reversed the induction of p27 in cells lacking the PTHrP NLS and C-terminal domain such that p27 expression was significantly lower than even control MSCV cells (Fig. 4B & C). Together, these data suggest that PTHrP may induce p27 through a LIFR-dependent mechanism. Treatment of the PTHrP mutant cell lines with the LIFR inhibitor for 1 or 6 h did not elicit the same effect on p27 as the 24-h treatments, such that there was no change in the pattern of p27 protein levels compared with vehicle treated cells (Supplementary Fig. 4B-E). This lack of effect with shorter treatments suggests that p27 is likely an indirect downstream target of LIFR. LIFR is a known dormancy regulator in breast tumor cells in the primary [32, 36, 38] and bone metastatic sites [32]. LIFR signaling activates multiple downstream signaling pathways in breast cancer, including ERK [42]. Since a high p38/ERK signaling ratio promotes tumor dormancy [43, 44], we also analyzed phosphorylated p38 levels in the PTHrP mutant cells, with and without LIFR inhibition. While phosphorylated p38 and the p38/ERK ratio were unchanged in the untreated cells expressing full-length or NLS alone-deleted PTHrP, both p38 and the p38/ERK ratio increased in cells expressing PTHrP lacking the NLS and C-terminal domain, compared to controls (Fig. 4D-F). This suggests that PTHrP lacking the NLS and C-terminal domain preferentially activates p38 signaling, which may induce a more quiescent phenotype. This is consistent with the significantly reduced primary tumor growth (Fig. 2A-C, DNLS + CTERM group). Interestingly, there was a significant increase in phosphorylated p38 and the p38/ERK ratio in the LIFR inhibitor treated cells compared to vehicle treated cells (Fig. 4F). This suggests that the LIFR inibitor may preferentially decrease ERK signaling, which in turn increases p38 activity. Loss of the PTHrP NLS enhances bone metastasis formation despite persistently elevated p27 expression Given the well-established role of PTHrP in promoting metastasis formation [811], we investigated how the NLS and C-terminal domain alter signaling and behavior of bone-disseminated tumor cells using a mouse model of bone colonization in which the PTHrP mutant tumor cells were inoculated through the left cardiac ventricle. We specifically examined whether elevated p27 expression is sustained in bone-disseminated breast tumor cells that express PTHrP lacking the NLS and C-terminal domain and if this alters proliferation, as in the primary tumor. Four weeks post-intracardiac inoculation, qPCR was performed on homogenized femora for human CDKN1B (gene name for p27), and normalized to ACTB (human tumor housekeeping gene) and Hmbs (mouse housekeeping gene) to quantify p27 specifically in bonedisseminated human tumor cells. CDKN1B was significantly higher in the homogenized femora from mice with bone-disseminated tumor cells that expressed PTHrP lacking the NLS and C-terminal domain only (Fig. 5A), confirming that even in the distant metastatic site, the truncated form of PTHrP induces more p27 in tumor cells than other PTHrP peptides. We observed the same trend in p27 expression in the primary tumor. Surprisingly, although p27 levels were higher in the homogenized femora of mice inoculated with tumor Edwards et al. Breast Cancer Research (2024) 26:34 Page 8 of 17 Fig. 4 PTHrP differentially regulates p27 through LIFR in breast cancer cells. (A) Immunofluorescence staining and quantification of LIFR in primary tumors from mice inoculated with MSCV, FLSEC, DNLS, or DNLS + CTERM cells. All panels = 40X and scale bars = 50 m. (B) Western blot analysis of p27, pERK, ERK, p-p38, p38 and tubulin (loading control) protein levels in MSCV, FLSEC, DNLS, or DNLS + CTERM cells treated with vehicle (DMSO) or LIFR inhibitor (EC359, 50nM or 100nM) for 24 h. Densitometry for western blot analysis of (C) p27, (D) pERK/ERK and (E) p-p38/p38 described in (B). (A) **p < 0.01 vs. DNLS by unpaired t-test. (C) *p < 0.05 vs. DNLS by unpaired t-test or *p < 0.05 vs. MSCV by one-way ANOVA with multiple comparisons. (D & E) *p < 0.05 vs. MSCV by one-way ANOVA with multiple comparisons or *p < 0.05, **p < 0.01, ***p < 0.001 versus vehicle by two-way ANOVA. Graphs represent mean SEM cells that express PTHrP lacking the NLS and C-terminal domain, there was significantly elevated osteolytic bone destruction (Fig. 5B-D) and tumor burden (Fig. 5E) in the contralateral limb, as measured by flow cytometric analysis of CD298 + tumor cells, a validated marker for human tumor cells in the bone marrow [45]. The level of metastatic tumor growth and bone destruction was similar in mice inoculated with tumor cells expressing PTHrP either lacking the NLS alone or the NLS and C-terminal domain. This was in striking contrast to the primary tumor site where these cell lines expressing truncated forms of PTHrP elicited opposite effects on breast tumor growth (Fig. 2A-C). Thus, when the NLS and C-terminal domains are deleted, PTHrP induction of p27 persists Edwards et al. Breast Cancer Research (2024) 26:34 Page 9 of 17 Fig. 5 Truncated. PTHrP induces CDKN1B in the bone metastatic site, but enhances osteolysis and tumor burden. (A) qPCR analysis for CDKN1B (p27) normalized to ACTB as a marker of total tumor burden in the bone marrow of mice inoculated with MSCV, FLSEC, DNLS, or DNLS + CTERM cells via intracardiac injection. n = 810 mice/group. (B-D) Total osteolytic lesion area and lesion number (per mouse) based on radiographic analyses for mice described in A. White arrows indicate osteolytic lesions. (E) Flow cytometric quantitation of percent CD298 + tumor cells in the bone marrow of mice described in A. (F) qPCR analysis for RANKL/OPG (Tnfsf11 / Tnfrsf11b) in whole homogenized femurs from mice described in (A). n = 810 mice/group. *p < 0.05, **p < 0.01, or ****p < 0.0001 vs. MSCV by one-way with multiple comparisons. Graphs represent mean SEM in the bone metastatic site. However, in contrast to the primary tumor, induction of p27 downstream of PTHrP in disseminated tumor cells is not sufficient to prevent colonization of the bone and metastatic outgrowth, both of which are elevated by truncated PTHrP peptides lacking the NLS. To determine whether the increase in tumor burden was due to increased osteoclast-mediated bone resorption, we assessed the RANKL/OPG ratio in whole, homogenized femurs across all groups as a marker of osteoclasts. Surprisingly, we only observed a significant increase in RANKL/OPG when the PTHrP NLS domain was deleted, and not in the NLS + C-terminal deleted group. These data suggest that loss of the PTHrP NLS stimulates osteoclast-mediated bone resorption, but loss of the PTHrP NLS and C-terminus does not. We also examined liver histological sections for metastatic tumor burden, but there were no lesions observed in any of the groups. Furthemore, in vitro we observed no difference in migratory potential of cells expressing full-length PTHrP or its truncated forms versus control cells (Supplementary Fig. 5). Together, these data suggest the PTHrP NLS and C-terminal domains may selectively Edwards et al. Breast Cancer Research (2024) 26:34 enhance the ability of breast cancer cells to colonize, survive and proliferate specifically in the bone rather than broadly affecting their ability to migrate from the primary tumor and disseminate to other organs. Discussion PTHrP is a critical driver of tumor-induced bone disease and an important regulator of breast tumorigenesis, cancer progression, and tumor dormancy [28, 32, 46, 47]. Here we investigated the intracellular actions of PTHrP through its NLS and C-terminal domain in breast cancer progression. An important finding is that deletion of the classical PTHrP NLS (67-94aa) does not preclude entry of PTHrP into the nucleus. This indicates that the truncated PTHrP peptides can translocate into the nucleus independent of this recognized NLS. Indeed, one study has reported that PTHrP (1-141) can be endocytosed and translocated into the nucleus via a non-PTH1R cell surface receptor [48], though the mechanism has not been fully elucidated. We are actively investigating alternative mechanisms by which PTHrP enters the nucleus when the classical NLS is deleted. These findings indicate that our study outcomes are likely due to differences in the binding partners or direct interactions of truncated PTHrP with other molecules, rather than the subcellular localization of the truncated peptides. We are also further investigating how the intracellular location alters binding partners of truncated PTHrP peptides to regulate downstream breast cancer cell signaling. Our data demonstrate that the biological domains of PTHrP have distinct functions in breast cancer. These findings are consistent with studies from the skeletal field, which ascribe multiple biological functions to PTHrP domains, particularly through regions outside of the PTH1R-binding domain. Indeed, a knock-in mouse model (PthrpD/D) lacking the midregion, NLS, and C terminal domain (67-137aa) revealed that the intracrine actions of PTHrP are crucial for normal skeletal development and the differentiation of osteogenic and hematopoietic precursors [49]. Most PthrpD/D mice exhibit severe skeletal abnormalities, growth retardation, and die within 5 days. Injection with exogenous PTHrP fails to rescue the lethal phenotype providing further evidence that the effects of PTHrP on these physiological processes are primarily mediated by intracrine signaling. Another in vivo study demonstrated that knock-in mice expressing truncated PTHP (1-84aa) display abnormal skeletal growth and early lethality due to decreased cell proliferation, early senescence, and increased apoptosis in multiple tissues [1618]. Together, these studies demonstrate the importance of the PTHrP NLS and C-terminal domain in regulating tissue development via intracrine signaling, and our data now identify distinct Page 10 of 17 functions of these domains in the pathologic setting of breast cancer. While a large body of evidence indicates that PTHrP has deleterious effects during late stages of breast cancer by promoting bone metastasis, tumor-induced osteolysis, and exit from dormancy, PTHrPs role early in disease progression is highly controversial [27, 28, 32, 46, 47]. Prior preclinical studies reported directly conflicting evidence suggesting that PTHrP inhibits primary breast tumorigenesis in some models [27], while promoting tumor growth in others [28]. Our in vivo findings offer interesting insight into the complex role that PTHrP plays in breast tumor progression. Our data indicate that PTHrP lacking its classical NLS sequence dramatically accelerates breast tumor growth and proliferation in the primary tumor site, suggesting that this domain actually functions to suppress breast tumor growth. Surprisingly, this phenotype is completely reversed if breast cancer cells express PTHrP lacking both the NLS and C-terminal domain, suggesting that the C-terminal domain may possess oncogenic activity that opposes the influence of the NLS. Thus, we are actively pursuing studies to determine how expression or deletion of the C-terminus alone impacts breast cancer growth and bone colonization. Importantly, our data shed light on the conflicting preclinical studies suggesting that PTHrP can promote or inhibit breast tumorigenesis. These controversies may be in part due to the presence of different predominant truncated peptides of PTHrP containing the NLS or C-terminal domain. Unfortunately, these forms are not discernible by commercially available amino-terminal antibodies. While studies have not identified the same engineered fragments as in our model presented here, it is feasible that fragments lacking the classical NLS (67-94aa) or the NLS and C-terminal domain (107-139aa) may naturally circulate in pre-clinical mouse tumor models and patients. In fact, the PTHrP sequence has numerous known and putative mono- and multi-basic cleavage sites [4, 50]. Importantly, PTHrP peptides containing the N-terminal domain (1-36aa), mid-regions (38-94aa), (3895aa) and (38-101aa), as well as the C-terminal domain (107-139aa) have been detected in preclinical mouse models [21, 51] and from the plasma and urine of human patients with solid tumors [21, 51]. While very few studies have investigated a role for these and other PTHrP fragments in breast cancer, some limited studies have identified how their expression alters breast tumor cell behavior, breast tumor growth, and patient outcomes. The PTHrP mid-region fragment (38-94aa) containing a portion of the classical NLS is reported to inhibit in vitro proliferation of MDA-MB-231 human breast cancer cells [52] while another fragment from amino acids 87106 reportedly stimulates proliferation in vitro [53]. Edwards et al. Breast Cancer Research (2024) 26:34 In patients with breast cancer, loss of nuclear localized but not cytoplasmic PTHrP in the primary site has been associated with poor clinical outcomes [54]. Another study identified PTHrP (1248) as a predictive biomarker of breast cancer bone metastasis such that levels of the peptide were significantly increased in the plasma of patients with clinical evidence of bone metastases versus patients without [55]. Together, these studies provide further evidence of domain-specific selectivity for how PTHrP and its truncated isoforms function in vitro versus in vivo. While there were no changes in cell cycling observed in vitro, our in vivo studies demonstrate a modest increase in proliferation with deletion of the NLS alone, which persisted in the primary tumor but not bone. These differences in proliferation in vitro versus in vivo may also be attributed to PTHrP-induced signaling changes in the breast cancer cells that alter their interaction with surrounding stromal cells, including recruitment of immune cells into the tumor microenvironment, which vary substantially by tumor site. The present study sheds important light on the biological role for the classical NLS and C-terminal domain in regulating breast tumor growth in vivo. Examination of cleaved PARP in the primary tumor demonstrated no alterations in apoptosis underlying the differences in tumor burden with expression of PTHrP lacking the NLS alone or both the NLS and C-terminal domain. We also examined levels of cleaved caspase-3 to more broadly assess apoptosis. One limitation in our model is that expression of caspase-3 is low at baseline in MCF7 cells, making it difficult to detect further reductions, particularly in cells expressing PTHrP lacking the DNLS. Importantly, the tumors assessed in our study were analyzed at endpoint, but it is possible that more dramatic changes in apoptosis occurred early in tumor progression. Indeed, the majority of tumors expressing PTHrP lacking the NLS and C-terminal domain were small in size and nearly undetectable at endpoint. The ability to measure apoptotic or proliferative markers from all tumors may have demonstrated a greater difference to further explain the alterations in tumor burden. Cyclin dependent kinase inhibitor proteins are regulated downstream of the PTHrP NLS and C-terminal domain in non-breast cancer cell lineages [1618]. Our studies demonstrate that p27 is oppositely regulated by the PTHrP NLS and C-terminal domain in breast cancer and may be an important downstream signaling factor mediating how these domains differentially alter breast tumor growth (Fig. 6). Specifically, the PTHrP C-terminal domain appears to function as an oncogenic molecular switch able to induce proliferation and promote primary breast tumor formation through a partially LIFRdependent mechanism that suppresses p27 expression. Page 11 of 17 It should be noted that there are significant differences in tumor burden and p27 between control tumors and tumors expressing PTHrP that lack the NLS, but a nonsignificant decrease in LIFR (~ 50% reduction). Thus, the data are consistent across our in vivo study, but do not always result in statistically significant changes. This suggests that LIFR is not the only driver of p27 in our model. Future studies utilizing breast cancer cells expressing PTHrP with deletion of the C-terminal domain only will be needed to confirm this. Interestingly, although CDKN1B (gene name for p27) remained elevated by the bone-disseminated tumor cells expressing PTHrP lacking the NLS and C-terminal domain, the cells readily colonized the bone marrow. We thought this may be due to an increase in osteoclast-mediated bone resorption, which we assessed by measuring RANKL/OPG levels in whole, homogenized femora. We were surprised that RANKL/OPG was only elevated when the PTHrP NLS was deleted, and not when the NLS and C-termainal domain were deleted, since both groups had similar levels of bone destruction and bone metastatic tumor burden. This finding suggests that the mechanism of tumor outgrowth caused by the PTHrP fragments is likely distinct, and that the osteoclast-mediated osteolysis must have occurred early in disease progression in the tumors lacking the PTHrP NLS and C-terminus, since measurements were assessed at endpoint. Follow-up studies to identify the distinct mechanisms of tumor outgrowth in bone that are caused by each PTHrP fragment are underway. In our studies, pharmacologic LIFR inhibition revealed an unexpected trend whereby breast cancer cells treated with the inhibitor had significantly elevated phosphorylated p38 and a p38/ERK signaling ratio compared to vehicle treated cells, regardless of PTHrP mutant expression. This effect was further elevated when the PTHrP NLS and C-terminal domain were deleted. LIFR is known to activate STAT3, ERK, and AKT signaling, among numerous other signaling pathways in breast cancer [32, 42, 56]. It has been postulated that LIFR signaling promotes tumor dormancy specifically through STAT3 activation [32]; however, the oncogenic ERK and AKT pathways can still be activated by LIFR-binding cytokines [42]. Our data here suggest that the EC359 LIFR inhibitor may preferentially decrease LIFR-mediated ERK signaling, shifting the balance towards p38 activity and suppression of cell proliferation in vitro. Since LIFR activates multiple singaling pathways in breast cancer cells [42], we also sought to analyze alterations in STAT3 and AKT signaling in the presence and absence of LIFR inhibition via western blot analysis; however, activation of these pathways was too low at baseline to quantify discernable changes in pSTAT3 and pAKT. Recently, small molecule inhibitors and neutralizing antibodies targeting LIFR have been investigated as a Edwards et al. Breast Cancer Research (2024) 26:34 Page 12 of 17 Fig. 6 Model of PTHrP domain-specific actions in breast cancer progression and bone colonization. In the primary breast site (top left panel, left of arrows), PTHrP lacking the NLS and C-terminal domain decreases tumor cell proliferation through p27 induction driven by the tumor suppressor leukemia inhibitory factor receptor (LIFR). PTHrP lacking the NLS and C-terminal domain also preferentially induces p38 phosphorylation and signaling to inhibit cell cycling downstream of LIFR activation. In the breast, truncated PTHrP lacking the NLS alone (top left panel, right of arrows) downregulates LIFR expression (denoted by transparent coloring) and prevents induction of p27 expression and activation of p38 signaling (denoted by dashed arrows, dotted outlines and transparent coloring) to drive cell proliferation and tumor growth. In bone disseminated tumor cells (bottom panel), LIFR expression is downregulated and the induction of p27 by PTHrP lacking the NLS and C-terminal domain persists, but is not sufficient to repress metastatic outgrowth (denoted by dashed inhibitor line), in contrast to the primary tumor. In the bone, tumor cells expressing PTHrP peptides lacking the NLS or NLS and Cterminal domain readily proliferate into metastatic tumors. Image created with Biorender.com strategy to inhibit breast tumor growth and metastasis in preclinical studies [57, 58]. Although anti-LIFR agents do show evidence of effectively limiting primary breast tumor growth, caution should still be exercised in their use as a breast cancer therapy since inhibiting LIFR signaling could inadvertently increase metastatic outgrowth in bone where the LIFR:STAT3 pathway suppresses proliferation of disseminated breast tumor cells [32, 5961]. It will therefore be important to define the downstream pathways that are disrupted by individual LIFR antagonists. Furthermore, it is still unclear how the PTHrP NLS and C-terminal domains may differentially regulate other downstream LIFR signaling pathways. Concluding remarks In summary, these data reveal important insights into how the PTHrP NLS and C-terminal domain divergently control breast cancer progression through p27 signaling in the primary tumor and bone metastatic site. As a potent regulator of breast tumor growth and distant metastatic progression, PTHrP has the potential to be leveraged as a therapeutic target for the treatment of breast cancer at multiple stages of disease progression and possibly for the prevention of bone metastasis formation. However, it is critical that this work be approached with attention to the PTHrP peptides present and their ability to differentially activate downstream signaling pathways. Edwards et al. Breast Cancer Research (2024) 26:34 Materials and methods Cell culture and reagents Cells PTHrP mutant cell lines were established in the laboratory of one of us (TJM) at St. Vincents Institute of Medical Research, as previously described [61]. Briefly, the following constructs were synthesized by Integrated DNA Technologies (IDT) (Coralville, IA, USA): Pthlh(36-139), Pthlh (1-139), Pthlh(-36-67), Pthlh(-36-139). Xho1/ EcoR1 enzyme digestion and ligation was performed to clone the constructs into the murine stem cell virus (MSCV)-zeo plasmid. Each plasmid except for the MSCV control was tagged with a human influenza hemagglutinin (HA) epitope at the C-terminal end. DNA sequencing was performed by the Australian Genome Research Facility. Phoenix cells were then transfected with the mutant plasmids and used to infect MCF7 cells which were placed under antibiotic selection with Zeocin to establish stable lines. The resulting PTHrP mutant cells were cultured in DMEM supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin (P/S). All cell lines were regularly tested for mycoplasma contamination. Proliferation assays Cells were plated at 1 106 cells per 10cm2 plate and allowed to adhere for 46 h. Adherent cells were then trypsinized and mixed with 0.4% trypan blue solution. Viable cells were determined based on dye exclusion and counted using a TC20 Automated Cell Counter (BioRad). Proliferation of PTHrP mutant cells was monitored daily for four days by trypsinizing and counting viable cells. LIFR inhibitor treatment Cells were plated at 1 106 cells/ 10cm2 plate and allowed to adhere overnight. The following day, cells were treated with EC359, a leukemia inhibitory factor receptor (LIFR) inhibitor (50nM or 100nM; MedChemExpress; Catalog No. HY-1,201,420) or vehicle (0.1% dimethyl sulfoxide, DMSO) for 1, 6, or 24 h in full-serum media. RNA extraction and real-time qPCR RNA was extracted from cells using TRIzol (ThermoFisher) and prepared for real-time qPCR analysis as previously described [32]. Human primers for b2M [32] and CDKN1B (p27) were previously published. The following primers were designed using PrimerBlast (NCBI) against the human genome and validated by dissociation: ACTB (F- CATGTACGTTGCTATCCAGGC), R- CTCCTTAA TGTCACGCACGAT). Mouse primers for HMBS were previously published [32]. The following primers were designed using PrimerBlast (NCBI) against the mouse genome (Mus musculus) and validated by dissociation: Page 13 of 17 PTHrP mid-region (F- CATCAGCTACTGCATGACA AGG, R- GGTGGTTTTTGGTGTTGGGTG), PTHrP NLS (F- AACAGCCACTCAAGACACCC, R- GACCGA GTCCTTCGCTTCTT), PTHrP C-terminal region (F- A AAAGAAGCGAAGGACTCGG, R- GCGTCCTTAAGC TGGGCT). Western blotting Cultured cells were rinsed twice with cold 1X PBS and harvested in RIPA lysis buffer (Sigma) containing protease and phosphatase inhibitors (Roche). Protein lysate (20g) was loaded onto an SDS-PAGE gel under reducing conditions and transferred to nitrocellulose membranes. Membranes were probed with antibodies against HA-Tag (Cell Signaling, C29F4, Catalog No. 37T4S, 1:1000), LIFR (Santa Cruz, C-19, Catalog No. sc-659, 1:1000), p21Waf1/ Cip1(Cell Signaling, Catalog No. 2947 S, 1:1000), p27 Kip1 (Cell Signaling, Catalog No. 3686 S, 1:1000), phospho-p38 MAPK (Thr180/Tyr182) (Cell Signaling, Catalog No. 4511, 1:1000), p38 MAPK (Cell Signaling, Catalog No. 8690, 1:1000), phospho-ERK1/2 Thr202/Tyr204 (Cell Signaling, Catalog No. 9101, 1:1000), ERK1/2 (Cell Signaling, catalog number 9102, 1:1000), Calnexin (AbCam, Catalog No. ab22595-100UG, 1:900), GAPDH (Cell Signaling 14C10, Catalog No. 2118 S, 1:5000), HDAC2 (Cell Signaling, D6S5P, 1:1000), -tubulin (Antibody & Protein Resource at Vanderbilt University, Catalog No. VAPRTUB, 1:5000), or Vinculin (Millipore, Catalog No. AB6039, 1:1000). Nuclear and cytoplasmic extraction Nuclear and cytoplasmic extracts were obtained from cultured PTHrP mutant cells using the NE-PER Nuclear and Cytoplasmic Extraction Reagents Kit (Thermo Scientific, Catalog No. 78,835) according to the manufacturers instructions. Briefly, 5 106 cells were plated in full serum DMEM and allowed to adhere overnight. The following day, adherent cells were trypsinized and centrifuged at 500 x g for 5 min, and the pellet was suspended in PBS. Cells were then transferred to a new microcentrifuge tube and centrifuged at 500 x g for 3 min. Supernatant was discarded and 500 l of ice-cold CER I with 5 l of protease inhibitor was added to the cell pellet and vortexed. The cell suspension was incubated on ice for 10 min. Ice-cold CER II (27.5 l) was then added to the tube, vortexed, and incubated on ice for 1 min. Next, the sample was vortexed and centrifuged at 16,000 x g for 5 min. The supernatant (cytoplasmic extract) was immediately transferred to a clean pre-chilled tube and stored at -80oC. The cell pellet was suspended in 250 l of icecold NER, vortexed for 15 s, and placed on ice. Vortexing was repeated every 10 min for a total of 40 min. The tube was then centrifuged at 16,000 x g for 10 min. Finally, the Edwards et al. Breast Cancer Research (2024) 26:34 supernatant (nuclear extract) was transferred to a clean pre-chilled tube and stored at -80oC. Immunocytochemistry For analysis of HA-tagged PTHrP peptides, cells were seeded onto a 4-well culture slide at 6 105 cells/ well and allowed to adhere overnight. The following day cells were washed twice with 1x PBS and fixed with 10% formalin for 15 min. Cells were then washed three times with 1X PBS for 5 minutes each, permeabilized in 0.25% TritonX in 1X PBS for 10 min and washed twice with 1X PBS for 5 minutes each. Next cells were blocked in a 3% mix of donkey horse serum (DHS)/ bovine serum albumin (BSA) for 1 h at room temperature, washed twice with 1X PBS for 5 minutes each and finally incubated with HATag antibody (Cell Signaling, C29F4, Catalog No. 37T4S, 1:500) diluted in DHS/ BSA mix for 1 h at room temperature. Afterwards, cells were washed three times with 1X PBS for 5 minutes each and incubated in goat anti-rabbit IgG (H + L) Alexa Fluor 488 secondary antibody (Thermo Fisher, Catalog No A-11,034, 1:1000) diluted in DHS/ BSA mix in the dark for 1 h at room temperature. Cells were then washed three times with 1X PBS for 5 minutes each. Lastly, the chamber was removed from each slide before mounting coverslips with VECTASHIELD HardSet Antifade Mounting Medium with DAPI (Vector Laboratories). Fixed cells were imaged on a laser scanning confocal microscope Nikon A1r based on a TiE motorized Inverted Microscope using a (I) 60X lens, NA 1.4, run by NIS Elements C software with sections imaged in 0.23 m slices or (II) 100X lens, NA 1.49, run by NIS Elements C software with sections imaged in 0.23 m slices. For analysis of p21 and p27, 8 105 cells were seeded onto glass coverslips coated with 5 g/ml human fibronectin (Millipore) 12 h prior. The following day, cells were washed with 1X PBS, fixed with 10% formalin for 15 min, washed three times with 1X PBS for five minutes each and permeabilized with 0.25% Triton-X for 10 min. Afterwards, cells were washed twice with 1X PBS for 5 minutes each and blocked with DHS/ BSA mix for 1 h at room temperature. Cells were then washed twice with 1X PBS for 5 minutes each and incubated in p21Waf1/ Cip1(Cell Signaling, Catalog No. 2947 S, 1:1000) or p27 Kip1 (Cell Signaling, Catalog No. 3686 S, 1:1000) diluted in DHS/BSA mix for 1.5 h at room temperature. Afterwards cells were washed three times with 1X PBS for 5 minutes each and incubated in goat anti-rabbit IgG (H + L) Alexa Fluor 488 secondary antibody (Thermo Fisher, Catalog No A-11,034, 1:1000) diluted in DHS/ BSA mix in the dark at room temperature. Finally, cells were washed three times with 1X PBS for 5 minutes each before mounting on glass slides with VECTASHIELD HardSet Antifade Mounting Medium with DAPI (Vector Laboratories). Images were collected on an Olympus Page 14 of 17 BX41 Microscope equipped with an Olympus DP71 camera using the 40X plain objective. For p21 quantitation in Image J, total nuclei and positive staining cells were counted manually to calculate the percent of positive staining cells. For p27, the fluorescence intensity was quantified using ImageJ with manual cell contouring and measurement of the Raw Integrated Density which was averaged across all cells from 3 separate images. Enzyme-linked immunosorbent assay To prepare conditioned media, PTHrP mutant cells (1 105) were plated in full-serum media in a 24-well plate and allowed to adhere for 24 h. Afterwards, the fullserum media was changed to 600 l of reduced serum media (DMEM + 2% FBS + 1% P/S) and cells were incubated for 24 h. Conditioned cell media was then harvested and centrifuged at 1500 rpm for 10 min at 4 C. The supernatant was treated with protease inhibitor (Sigma, P8340, 1:100) before further analysis. Undiluted conditioned media was added to 96-well ELISA plates to measure secreted PTHrP levels according to the manufacturers protocol (Creative Diagnostics, Catalog No. DEIA2034). For the final analysis, calculated PTHrP concentrations measured by the ELISA were normalized to the total protein concentration (mg/ml) in each sample measured by BCA assay (Thermo Fisher). Cell cycle analysis Cell cycle analysis was performed by seeding 150,000 cells per well into 6-well plates for each cell line. After 24 h, cells were treated with 50nM EC359, 100nM EC359, or DMSO vehicle for 48 h. After 48 h, 150,000 cells were removed from each treatment group and live stained with Hoescht 33342 (AbCam) at a concentration of 10 g/mL for 1 h at 37 C. Stained cells were analyzed on a 4 Laser Fortessa by the Vanderbilt Flow Cytometry Resource Core. Flow cytometer data were analyzed using FlowJo software to gate for G0/1, S, and G2 phases. Each bar represents data from 3 independent experiments. Migration assay Scratch assays were performed by seeding 400,000 cells of each mutant cell line (MSCV, FLSEC, DNLS, and DNLS + CTERM) into one well of a 6-well plate. After 24 h, three scratches were made in each well with a pipette tip. Images were taken at 100x on an inverted microscope at 0 h (immediately after scratch), 24 h, and 48 h. Percent closure was determined via analysis with ImageJ. Each replicate is expressed as an average of three scratches per well. Each data point represents three independent experiments. Edwards et al. Breast Cancer Research (2024) 26:34 Animal studies and imaging Animals Experiments were performed under the regulations of the Animal Welfare Act and the Guide for the Care and Use of Laboratory Animals and approved by the Vanderbilt University Institutional Animal Care and Use Committee (IACUC). For the mammary fat pad study, 17-estradiol pellets (0.36 mg/pellet; Innovative Research of America, Catalog No. SE-121) were subcutaneously implanted into female athymic nude mice 24 h prior to tumor inoculation [61]. The following day, 5 105 tumor cells from each pooled cell line in 20 l PBS + 50% matrigel (Fisher Scientific) were inoculated into the fourth mammary fat pad (n = 10 mice injected per group). Tumor volume was assessed by caliper measurement. Several mice had to be sacrificed early due to estrogen-induced toxicities resulting in MSCV = 8 mice, FLSEC = 7 mice, DNLS = 10 mice, DNLS + CTERM = 9 mice in the final analysis. For the intracardiac inoculation study, 6-week-old female athymic nude mice (Jackson, Catalog No. 7850) were injected with 1 105 tumor cells from each pooled cell line as previously described [63] (n = 810 mice injected per group). The mice were subcutaneously implanted with a slow-release 17-estradiol pellet (0.36 mg/pellet; Innovative Research of America, Catalog No. SE-121) 24 h prior to tumor cell injection [63]. Radiography Radiographic (x-ray) images were obtained as previously described [64]. Briefly, a Faxitron LX-60 (34 kV for 8 s) was used to acquire x-ray images and images were quantified for osteolytic lesion number and area using ImageJ software. Histology Upon sacrifice of the mice, dissected tumors were fixed in 10% formalin for 48 h and stored in 70% ethanol until being paraffin-embedded for further analyses. Tissue sections were deparaffinized by heating the slides to 50 C and placed in xylene for 5 min and then 3 min. Next, slides were soaked in 100%, 95%, and then 75% ethanol for 3 min each. Slides were slowly changed to deionized water and rinsed twice in water. The slides were immersed in 10 mM TRIS (pH 9.0) and 1 mM EDTA heated to 150 C for 20 min. After cooling at room temperature for 20 min, slides were rinsed twice with water and then three times with 1X PBS followed by blocking with 10% BSA in PBS for 2 h. Sections were stained with Ki67 (Thermo Fisher; Catalog No. RM9106S0, 1:500), cleaved PARP (Asp214) (Cell Signaling Technology, Catalog No. 5625T, 1:500), HA-Tag (Cell Signaling, C29F4, Catalog No. 37T4S, 1:1000), p21Waf1/Cip1(Cell Signaling, Catalog No. Page 15 of 17 2947 S, 1:1000), or p27 Kip1 (Cell Signaling, Catalog No. 3686 S, 1:1000) in 3% BSA in PBS overnight at 4 C. The following day, sections were washed three times with 1X PBS and incubated in goat anti-rabbit IgG (H + L) Alexa Fluor 488 secondary antibody (Thermo Fisher, Catalog No A-11,034, 1:1000) in 3% BSA/PBS in the dark at room temperature for 1 h. Finally, sections were washed three times with 1X PBS and coverslips were mounted using VECTASHIELD HardSet Antifade Mounting Medium with DAPI (Vector Laboratories). For LIFR staining, after blocking in 10% BSA for 2 h, slides were incubated in FITC-LIFR (Santa Cruz, Catalog No. sc-515,337, 1:50) in 3% BSA/PBS overnight at 4 C. The following day, sections were washed three times with 1X PBS and coverslips mounted using VECTASHIELD HardSet Antifade Mounting Medium with DAPI (Vector Laboratories). All images except for Ki67 were collected on an Olympus BX41 Microscope equipped with an Olympus DP71 camera using the 40X plain objectives. For LIFR quantitation, 40X images were used and an area measuring 1900 1180 pixels was selected to measure the Raw Integrated Density. The Raw Integrated Density from 3 representative images was averaged for each mouse and these values are reported in the figure. For p21, p27, and cleaved PARP, the quantitation was performed using ImageJ analysis of the 40X images. Positive staining nuclei and total cell counts were determined using color thresholding in ImageJ and the number of positive staining nuclei was divided by the total number of nuclei present to calculate the percent positivity. For Ki67 quantification, fixed samples were imaged on a laser scanning confocal microscope Nikon A1r based on a TiE motorized Inverted Microscope using a 60X lens, NA 1.4, run by NIS Elements C software. Sections were imaged in 0.4 m slices. Positive staining nuclei and cell counts were determined using color thresholding in ImageJ and the number of positive staining nuclei was divided by the total number of nuclei present to calculate percent Ki67 positivity. Flow Cytometry One hindlimb (inclusive of bone marrow and tumor cells) was crushed with a mortar and pestle to obtain the bone marrow. PBS (1mL) was added to the crushed bone marrow and spun down and washed with PBS to remove bone debris. Bone marrow (5 105 cells) was stained in 100L of PBS with LIVE/DEAD Fixable Green Dead Cell Stain Kit @488nm (Thermo Fisher Scientific, Catalog Number L34970, 1:1000) for 15 min on ice at 4 C in the dark. Cells were washed with PBS and resuspended with 100L of 1% BSA in PBS with CD298 antibody (BioLegend, Cat #341,704) for 30 min on ice at 4 C in the dark. Edwards et al. Breast Cancer Research (2024) 26:34 Flow Cytometry Analysis Flow cytometry experiments were performed in the VUMC Flow Cytometry Shared Resource using the 5-laser BD LSRII and 4-laser BD Fortessa LSRII. Data was analyzed using FlowJo software (FlowJo, LLC) where bone marrow samples were gated based on forward scatter and side scatter geometry, and PE-CD298 (+) cells were gated using live cells (LIVE/DEAD-Green negative) as previously validated in tumor-bearing bone marrow samples [45]. MCF7 breast cancer cells were used as a positive control for CD298 stain. Statistics and reproducibility For all experiments, n per group is as indicated by the figure legend and the scatter dot plots indicate the mean of each group and error bars indicate the standard error of the mean. All graphs and statistical analyses were generated using Prism software (Graphpad). Statistical significance for all in vitro and in vivo assays was analyzed using an unpaired t-test, one-way ANOVA with Sidaks multiple comparisons test or two-way ANOVA with multiple comparisons, as indicated in the figure legends. For each analysis p < 0.05 was considered statistically significant, and *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Supplementary Information The online version contains supplementary material available at https://doi. org/10.1186/s13058-024-01791-z. Supplementary Material 1 Supplementary Material 2 Supplementary Material 3 Author contributions C.E.M. wrote the main manuscript text, performed experiments, analyzed data, and prepared all figures. J.F.K., J.A.S., D.M.G, J.A.J, M.A.H.D., L.A.V.III, K.M.B., T.N.O., J.R.F., B.A.K., H.T.S., and C.J.V. performed experiments and analyzed data included in Figs. 1, 2, 3, 4 and 5. J.W.L. and T.J.M. generated resources and reagents for experiments and provided project input. R.W.J. wrote and edited the manuscript text, prepared figures, analyzed data, and secured funding for the project. All authors reviewed the manuscript. Funding This work was supported by DoD Breakthrough Award W81XWH-22-1-0090 (R.W.J.). This project was also supported by scholarship funds from NIH award P30CA06848 Vanderbilt-Ingram Cancer Center Support Grant and NIGMS T32GM007347. Data availability Data that support the findings of this study are available from the corresponding author upon reasonable request. Declarations Ethical approval Experiments were performed under the regulations of the Animal Welfare Act and the Guide for the Care and Use of Laboratory Animals and approved by the Vanderbilt University Institutional Animal Care and Use Committee (IACUC). Page 16 of 17 Competing interests The authors declare no competing interests. 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... Editorial 17 January 2024 DOI 10.3389/fendo.2024.1347765 TYPE PUBLISHED OPEN ACCESS EDITED AND REVIEWED BY Ralf Jockers, Universite Paris Cite, France *CORRESPONDENCE Michela Rossi michela1.rossi@opbg.net 01 December 2023 08 January 2024 PUBLISHED 17 January 2024 RECEIVED ACCEPTED CITATION Rossi M, Lowery JW and Del Fattore A (2024) Editorial: Genetic and molecular determinants in bone health and diseases. Front. Endocrinol. 15:1347765. doi: 10.3389/fendo.2024.1347765 Editorial: Genetic and molecular determinants in bone health and diseases Michela Rossi 1*, Jonathan W. Lowery 2,3,4,5,6 and Andrea Del Fattore 1 1 Bone Physiopathology Research Unit, Translational Pediatrics and Clinical Genetics Research Division, Bambino Ges Childrens Hospital, IRCCS, Rome, Italy, 2 Division of Academic Affairs, Marian University, Indianapolis, IN, United States, 3 Department of Physiology & Pharmacology, College of Osteopathic Medicine, Marian University, Indianapolis, IN, United States, 4 Bone & Muscle Research Group, Marian University, Indianapolis, IN, United States, 5 Indiana Biosciences Research Institute, Indianapolis, IN, United States, 6 Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, United States KEYWORDS bone, osteoclast, osteoblast, bone disease, gene COPYRIGHT 2024 Rossi, Lowery and Del Fattore. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Endocrinology Editorial on the Research Topic Genetic and molecular determinants in bone health and diseases Alterations of bone remodeling impact skeletal integrity lead to excessive or impaired bone resorption as well as reduced or disorganized bone formation (1, 2). This Research Topic focuses on the identication of genetic and molecular determinants involved in both bone health and diseases. In this editorial, we highlight studies on rare diseases presented in the Research Topic with the aim of better understanding their etiopathogenesis and opening the way for the identication of new therapeutic approaches. Xiang and Zhong summarized the recent studies regarding the molecular and cellular mechanisms leading to the progressive osteolysis and angiomatous proliferation in Gorham-Stout disease (GSD), which is a very rare disease that is also known as Vanishing Bone Disease. GSD is characterized by severe osteolytic bone destruction but lacks specic diagnostic markers and therapy (3). The information presented by Xiang and Zhong provides an important update on the condition and presents ideas for new therapeutic approaches for this rare disease. Cinque et al. published an elegant study on hypophosphatasia (HPP), a rare genetic disease affecting bone and teeth mineralization with multisystemic manifestations involving the nervous system, musculoskeletal apparatus, and kidneys, due to ALPL mutations. The authors reported the genetic analysis performed on 33 patients, identifying eight novel variants of ALPL gene. These results associated with the detailed clinical description increase the knowledge of this rare condition. Osteogenesis imperfecta (OI), also known as brittle bone disease, is a clinically and genetically heterogeneous disorder of connective tissue and is identied by bone dysplasia and fragility (4). In this Research Topic, Paduano et al. reported the results obtained by next-generation sequencing (NGS) analysis of 10 patients, comprising 7 male and 3 female patients from 7 families, all from the Puglia Region in South Italy. The authors identied novel rare pathogenic variants in type I collagen-encoding genes (COL1A1 and COL1A2). 01 frontiersin.org Rossi et al. 10.3389/fendo.2024.1347765 10 years of age then plateaus until old age, with a trend of bone turnover markers similar to that of humans. In conclusion, the papers published in this Research Topic underline how investigating bone diseases and animal models represent a way to nd new determinants of bone physiology and also allow the identication of new therapeutic approaches. In another study regarding OI, Lim et al. described the effects of a missense variant of MBTPS2 which encodes the site-2 protease, a Golgi transmembrane protein that activates membrane-tethered transcription factors in aborted male fetus with micromelia particularly of the lower limbs, a narrow thorax, and defective ossication of calvarium. The authors performed in vitro studies on mutated MBTPS2 primary broblasts and found perturbations in fatty acid metabolism and collagen production. Sundqvist et al. report a case study on rare, chronic nonbacterial osteomyelitis (CNO). They described a female patient with CNO with systemic inammation, advanced malnutrition and complete deciency of myeloperoxidase (MPO). The authors reported that, although the patient did not nd benecial effects after treatment with nonsteroidal anti-inammatory drugs, corticosteroids, bisphosphonates or IL1-receptor antagonists (anakinra), the administration of TNFa blockade (adalimumab) resulted in instant resolution of the inammatory symptoms suggesting that the disease was TNFa-driven. Bone tissue is tightly connected with other organs to regulate whole physiology (5). In this Research Topic the interplay bone-liver has been reported. Huang et al. investigated whether serum liver enzymes are causally associated with bone and joint-related diseases using Mendelian randomization (MR) designs. Indeed, the positive causality between ALP and the risk of osteoporosis and rheumatoid arthritis was indicated. Moreover, the authors reported that higher levels of alanine transaminase (ALT) were associated with the risk of hip and knee osteoarthritis while no causal relationship between GGT and bone and joint-related diseases was revealed. Moreover, two further papers reported new advances in bone remodelling, using animal models. Verlinden et al. investigated how neuropilin 2 (NRP2) in osteoblasts regulates trabecular bone mass in male mice. NRP2 is a non-tyrosine kinase transmembrane glycoprotein receptor. The authors generated two different genetic models lacking Nrp2 expression in osteoblasts or osteoclasts to identify its role in the bone remodelling activity. Although loss of Nrp2 in the osteoclast lineage did not result in a bone phenotype, loss of Nrp2 in osteoblast precursors and mature osteoblasts leads to reduced cortical crosssectional tissue area and lower trabecular bone content in male mice. Li et al. performed the evaluation of bone turnover markers and DEXA (Dual-Energy X-Ray Absorptiometry) analysis in cynomolgus monkeys at different ages to establish an animal model for age-related osteoporosis in non-human primates. The authors nd that, in cynomolgus monkeys, peak BMD occurs at age Author contributions MR: Writing original draft, Writing review & editing. JL: Writing original draft. AD: Writing original draft, Writing review & editing. Funding The author(s) declare nancial support was received for the research, authorship, and/or publication of this article. MR is supported by the Fondazione Umberto Veronesi. This work was also supported by the Italian Ministry of Health with the Current Research funds. Conict of interest The authors declare that the research was conducted in the absence of any commercial or nancial relationships that could be construed as a potential conict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the nal decision. Publishers note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their afliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. References 1. Unnanuntana A, Rebolledo BJ, Khair MM, DiCarlo EF, Lane JM. Diseases affecting bone quality: beyond osteoporosis. Clin Orthop Relat Res (2011) 469 (8):2194206. doi: 10.1007/s11999-010-1694-9 3. Rossi M, Buonuomo PS, Battafarano G, Conforti A, Mariani E, Algeri M, et al. Dissecting the mechanisms of bone loss in Gorham-Stout disease. Bone. (2020) 130:115068. doi: 10.1016/j.bone.2019.115068 2. Feng X, McDonald JM. Disorders of bone remodeling. Annu Rev Pathol (2011) 6:12145. doi: 10.1146/annurev-pathol-011110-130203 4. Martin E, Shapiro JR. Osteogenesis imperfecta:epidemiology and pathophysiology. Curr Osteoporos Rep (2007) 5(3):917. doi: 10.1007/s11914-007-0023-z 5. Yuan W, Song C. Crosstalk between bone and other organs. Med Rev (Berl). (2022) 2(4):33148. doi: 10.1515/mr-2022-0018 Frontiers in Endocrinology 02 frontiersin.org  ...

... Bone Reports 20 (2024) 101735 Contents lists available at ScienceDirect Bone Reports journal homepage: www.elsevier.com/locate/bonr Am I big boned? Bone length scaled reference data for HRpQCT measures of the radial and tibial diaphysis in White adults Stuart J. Warden a, b, *, Robyn K. Fuchs b, c, Ziyue Liu b, d, Katelynn R. Toloday a, Rachel Surowiec e, Sharon M. Moe b, f a Department of Physical Therapy, School of Health and Human Sciences, Indiana University, Indianapolis, IN, United States of America Indiana Center for Musculoskeletal Health, Indiana University, IN, United States of America College of Osteopathic Medicine, Marian University, Indianapolis, IN, United States of America d Department of Biostatistics, School of Medicine, Indiana University, Indianapolis, IN, United States of America e Department of Biomedical Engineering, Purdue University, Indianapolis, IN, United States of America f Division of Nephrology and Hypertension, Department of Medicine, School of Medicine, Indiana University, Indianapolis, IN, United States of America b c A R T I C L E I N F O A B S T R A C T Keywords: Bone allometry Bone strength Cortical bone Normative data Osteoporosis Cross-sectional size of a long bone shaft influences its mechanical properties. We recently used high-resolution peripheral quantitative computed tomography (HRpQCT) to create reference data for size measures of the radial and tibial diaphyses. However, data did not take into account the impact of bone length. Human bone exhibits relatively isometric allometry whereby cross-sectional area increases proportionally with bone length. The consequence is that taller than average individuals will generally have larger z-scores for bone size outcomes when length is not considered. The goal of the current work was to develop a means of determining whether an individual's cross-sectional bone size is suitable for their bone length. HRpQCT scans performed at 30 % of bone length proximal from the distal end of the radius and tibia were acquired from 1034 White females (age = 18.0 to 85.3 y) and 392 White males (age = 18.4 to 83.6 y). Positive relationships were confirmed between bone length and cross-sectional areas and estimated mechanical properties. Scaling factors were calculated and used to scale HRpQCT outcomes to bone length. Centile curves were generated for both raw and bone length scaled HRpQCT data using the LMS approach. Excel-based calculators are provided to facilitate calculation of z-scores for both raw and bone length scaled HRpQCT outcomes. The raw z-scores indicate the magnitude that an individual's HRpQCT outcomes differ relative to expected sex- and age-specific values, with the scaled z-scores also considering bone length. The latter enables it to be determined whether an individual or population of interest has normal sized bones for their length, which may have implications for injury risk. In addition to providing a means of expressing HRpQCT bone size outcomes relative to bone length, the current study also provides centile curves for outcomes previously without reference data, including tissue mineral density and moments of inertia. 1. Introduction Bone strength is influenced by the amount and quality of material present in addition to how the material is distributed (Fuchs et al., 2019). The distribution of bone material is colloquially referred to as bone structure or size and is often assessed via cross-sectional bone images acquired using 3D imaging modalities such as computed to mography and magnetic resonance imaging. High-resolution peripheral quantitative computed tomography (HRpQCT) is a powerful imaging modality capable of providing non-invasive measures of bone cross- sectional properties, along with volumetric bone mineral density (vBMD) and micro-finite element (FE) estimates of bone strength (Whittier et al., 2020). HRpQCT is principally used to assess structure at sites rich in trabecular bone (e.g., distal radius), with outcomes predicting incident fracture (Mikolajewicz et al., 2020; Samelson et al., 2019) and revealing the effects of aging, disease, and intervention (Lespessailles et al., 2016). However, there is growing interest in assessing more proximal sites containing a higher proportion of cortical bone (Cheung et al., 2014; Hughes et al., 2018; Kazakia et al., 2014; O'Leary et al., 2021; Orwoll * Corresponding author at: Department of Physical Therapy, School of Health and Human Sciences, Indiana University, 1140 W. Michigan St., CF-120, Indian apolis, IN 46202, United States of America. E-mail address: stwarden@iu.edu (S.J. Warden). https://doi.org/10.1016/j.bonr.2024.101735 Received 9 December 2023; Accepted 4 January 2024 Available online 6 January 2024 2352-1872/ 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). S.J. Warden et al. Bone Reports 20 (2024) 101735 et al., 2022; Patsch et al., 2013; Warden et al., 2022a; Warden et al., 2021a). Most bone loss during aging occurs from within the cortical compartment (Zebaze et al., 2010), and assessment of cortical bone-rich diaphyseal sites may provide unique insight into bone changes occurring in disease states and with lifestyle and pharmaceutical interventions. We recently used a second-generation HRpQCT scanner to create reference data for cortical bone outcomes obtained at 30 % of bone length proximal from the distal end of the radius and tibia (Warden et al., 2022b). The data can be used to calculate z-scores to indicate the number of standard deviations an individual's outcomes vary from ageand sex-matched median outcomes. However, the reference data did not take into account the impact of bone length on cross-sectional bone size. There has long been a fascination with the relationship between bone length and cross-sectional size. Galileo (Galilei, 1638) predicted that bones in different sized animals would exhibit positive allometry. That is, he predicted bone size would increase to a relatively greater extent than length in order to maintain the same strength. More recently, skeletal allometry in mammals, including humans, has been reported to be more modest with the relationship between bone length and crosssectional size being closer to isometric (Biewener, 2005; Ruff, 1984). Specifically, the bones of taller people are generally expanded versions of bones of people who are shorter, with bone cross-sectional area increasing proportionally as bone length increases. The net result is that taller-than-average individuals will generally have larger z-scores for bone size outcomes using currently available reference HRpQCT data, and vice versa for shorter individuals. The goal of the current study was to develop a means of determining whether an individual's cross-sectional bone size is suitable not only for their age and sex, but also their bone length. The primary aims were to: 1) explore the relationship between bone length and HRpQCT measures of radial and tibial diaphysis size in adults and 2) generate bone length scaled age- and sex-specific reference data for the HRpQCT measures across adulthood. In doing so, the current study also aimed to provide centile curves for outcomes previously without reference data, including tissue mineral density and moments of inertia. The ultimate goal was to provide calculators to enable the computation of subject-specific per centiles and z-scores for both raw and bone length scaled HRpQCT outcomes. maneuvers without arms from standardized chair (seat height = 45 cm) were performed to assess physical function, as we have previously detailed (Warden et al., 2022c). Self-reported physical function was assessed using the physical functioning domain of the National Institutes of Health Patient Reported Outcomes Measurement Information System (PROMIS-PF), performed via computerized adaptive testing. PROMIS scores are standardized and expressed as T-scores with a population mean of 50 and standard deviation of 10 (Cella et al., 2007). Spine and total hip aBMD were assessed by dual-energy x-ray absorptiometry (DXA) (Norland Elite; Norland at Swissray, Fort Atkinson, WI). 2.2. High-resolution peripheral quantitative computed tomography (HRpQCT) The non-dominant arm and contralateral leg were imaged using an HRpQCT scanner (XtremeCT II; Scanco Medical, Bruttisellen, Switzerland). Phantoms were imaged daily to confirm scanner stability. Bone length was measured in triplicate using a segmometer (Realmet Flexible Segmometer, NutriActiva, Minneapolis, MN) and as described by Bonaretti et al. (Bonaretti et al., 2017). Per convention, ulna length (mm) was measured as a surrogate for radial length. The skin overlying the distal apex of the ulnar styloid was marked and the elbow placed on a rigid surface. The Euclidean distance between the surface and styloid mark was measured. Tibial length (mm) was measured between skin marks placed at the distal tip of the medial malleolus and medial knee joint line. Short-term precision for repeat mark placement and length measures of the ulna and tibia in 15 individuals tested on two consec utive days showed root mean square standard deviations of 2.8 mm (1.1 %) and 6.3 mm (1.7 %), respectively. Scans were acquired and reconstructed as previously described (Warden et al., 2021a). Subjects laid supine with their limb immobilized using an anatomically formed carbon fiber cast. The scanner operated at 68 kVp and 1.47 mA to acquire 168 slices (10.2 mm of bone length) with a voxel size of 60.7 m. After performance of a scout view, reference lines were placed at the medial edge of the distal radius articular surface and center of the distal tibia joint surface. Scan stacks were centered 30 % of bone length proximal to the reference lines. The 30 % location was chosen as it is accessible in most individuals when using the manufac turer's standard forearm and leg casts on a second generation HRpQCT scanner. Assessment of more proximal sites requires use of custom casts and different reference line landmarks to stay within the z-axis limits of the scanner. Scans were scored for motion artifacts on a standard scale of 1 (no motion) to 5 (discontinuities in the cortical shell) (Sode et al., 2011). Scans scoring 3 were repeated when time permitted. Scans with a motion artifact of 4 or 5 were excluded from analyses. A manufacturer provided evaluation script using a dual threshold technique was used to contour the outer periosteal surface and inner trabecular/medullary compartment. Manufacturer provided evaluation scripts were used to obtain outcomes (Table 1). A standard cortical bone script was used to obtain CtvBMD, CtAr, CtPm, CtTh, and CtPo. The script utilized a low-pass Gaussian filter (sigma 0.8, support 1.0 voxel) and fixed thresholds of 320 and 450 mgHA/cm3 to extract trabecular and cortical bone, respectively. Only cortical outcomes were recorded as diaphyseal sites contain limited trabecular bone. The manufacturer's bone midshaft evaluation script was used with a low-pass Gaussian filter (sigma 0.8, support 1.0) and outer threshold of 450 mgHA/cm3. The evaluation provided outcomes for the whole bone (i.e. cortical and any trabecular bone) as the script was run with a single outer contour and without an inside clock-wise (i.e. negative excluding) contour. Outcomes obtained were TotDen (identified as Mean1 in the manu facturer's script), TMD (identified as Mean2 in the manufacturer's script), TA, BA, BA/TA, IMIN, IMAX, and pMOI. Stiffness and failure load were estimated by FE analysis (Scanco Medical FE software version 1.13). Each voxel within the segmented images was assigned a modulus of 10 GPa and Poisson's ratio of 0.3. Axial compression was applied and failure load estimated when 5 % of elements exceeded 1 % strain (Arias- 2. Methods 2.1. Participants HRpQCT scans were performed on 1856 adults (aged 18 years) between 12/2017 and 12/2022 within the Musculoskeletal Function, Imaging, and Tissue Resource Core (FIT Core) of the Indiana Center for Musculoskeletal Health's Clinical Research Center (Indianapolis, Indi ana). Participants were recruited to the core by investigators seeking standardized musculoskeletal outcomes for their research subjects, as well as from the local community via self-referral. The FIT Core has Institutional Review Board approval from Indiana University to assess all-comers who provide written informed consent. To be eligible for inclusion in the current dataset, participants were required to: 1) self-identify as being of White ancestry, 2) be ambulatory and 3) have no self-reported diabetes, liver or kidney disease, past or present history of cancer, thyroid disorders, cystic fibrosis, or rare bone disease (e.g., osteopetrosis or X-linked hypophosphatemia). Individuals with the later conditions were excluded due to their overrepresentation in the FIT Core cohort resulting from investigator-initiated trials and their known or potential impact on HRpQCT outcomes (van den Bergh et al., 2021). Height (m) and weight (kg) were measured without shoes using a calibrated stadiometer (Seca 264; Seca GmbH & Co., Hamburg, Ger many) and scale (MS140-300; Brecknell, Fairmont, MN), respectively. Grip strength using a JamarPlus+ digital hand dynamometer (Sammons Preston, Bolingbrook, IL) and time to complete five sit-to-stand 2 S.J. Warden et al. Bone Reports 20 (2024) 101735 2005). Participant characteristics were described according to decade stage of life (1829, 3039, 4049, 5059, 6069, and 70+ yrs). Spearman partial correlation controlling for age was used to assess the relationship between HRpQCT outcomes and bone length. Scaling factors were calculated for HRpQCT outcomes exhibiting a Spearman partial correlation (on age) with bone length of R2 0.05. Scaling factors were calculated using the simple allometric linear regression model, Y = X, applied in natural logarithmic form as: Table 1 HR-pQCT outcomes. Outcome Abbreviation Units Description Total density (Mean1)b TotDen mgHA/ cm3 Tissue mineral density (Mean2)b TMD mgHA/ cm3 Cortical vBMDa CtvBMD mgHA/ cm3 Total areab TA mm2 Bone areab BA mm2 Cortical areaa CtAr mm2 Bone area/total areab BA/TA % Cortical perimetera CtPm mm Cortical thicknessa Cortical porositya CtTh mm CtPo % Minimum second moment of areab IMIN mm4 Maximum second moment of areab IMAX mm4 Polar moment of inertiab pMOI mm4 Stiffnessc kN/mm Failure loadc N Average density of all voxels within the periosteal contour, including tissue and voids (i.e. medullary cavity and pores) Average density of all voxels within the periosteal contour with a density >450 mgHA/cm3 (excludes medullary cavity and pores) Average density of all voxels within the segmented cortical compartment (includes pores) Area within the periosteal contour, including tissue and voids (i.e. medullary cavity and pores) Area within the periosteal contour with a density >450 mgHA/cm3 (excludes medullary cavity and pores) Average cross-sectional area of the segmented cortical compartment (includes pores) Proportion of voxels within the periosteal contour with a density >450 mgHA/cm3 Average length of the outer periosteal surface within the segmented cortical compartment Thickness of cortical bone including any pores Percentage of void voxels from the total cortical voxels in the segmented cortical compartment Estimated ability of all the components within the outer contour with a density >450 mg/ cm3 to resist bending on the direction of least bending resistance Estimated ability of all the components within the outer contour with a density >450 mg/ cm3 to resist bending on the direction of most bending resistance Estimated ability of all the components within the outer contour with a density >450 mg/ cm3 to resist torsional loading Total reaction force divided by the applied displacement within the finite model Failure load indirectly estimated from linear finite element model loge Y = loge + loge X + loge with Y the HRpQCT outcome of interest, X the predictor variable (i.e., bone length), the scaling exponent or power (scaling factor), the proportionality constant, and the multiplicative error. HRpQCT out comes exhibiting a Spearman partial correlation with bone length of R2 < 0.05 (i.e., <5 % of the variation explained) were considered to have low explanatory value. Scaling factors were used to scale HRpQCT outcomes as: / Yscaled = Yraw (X/X0 )SF with Yscaled the scaled value for the HRpQCT outcome, Yraw the original measured value for the HRpQCT outcome, X the bone length, X0 the sexspecific median bone length within the study population, and SF the scaling factor () from the linear regression model. Bone length (X) was normalized to sex-specific median bone length (X0) so that the scaled value retained the same units and were in a similar value range as the original measured value for the HRpQCT outcome. Sex-specific reference centile curves for raw and scaled HRpQCT outcomes were generated using the LMS method (Cole and Green, 1992) with R package GAMLSS (version 5.2.0) (Rigby and Stasinopoulos, 2005). The LMS method uses Box-Cox transformation to achieve normality at a given age (Box-Cox Cole and Green [BCCG] distribution). Nonparametric smooth curves are fit to the parameter values across the age range using penalized likelihood with penalty on the second derivatives. Centile curves and z-scores were calculated from the estimated parameter curves. LMS-derived z-scores are not suited for identifying extreme values because the LMS transformation method to achieve normality constrains maximum obtainable z-scores. Modified z-scores are provided for scores greater than +2 to address this. In modified zscores, the HRpQCT outcome is expressed relative to the sex- and agematched median in units of half the distance between 0 and + 2 zscores, as per the approach used for growth charts (Centers for Disease Control and Prevention, n.d.). 3. Results 3.1. Participant and scan characteristics Scans from 1426 participants (1034 females, 392 males) were included following exclusion of 430 participants due to: 1) race not White (n = 247, including 87 with a self-reported ineligible disease) and 2) race White, but self-reported ineligible disease or illness (n = 183). The final cohort included females and males ranging in age from 18.0 to 85.3 yrs. and 18.4 to 83.6 yrs., respectively. Participant characteristics stratified by decade of age are detailed in Table 2. Total hip and/or spine aBMD t-score was 1 to 2.5 and 2.5 in 336 (32.5 %) and 20 (1.9 %) females, respectively. One hundred fifty (38.3 %) and 21 (5.4 %) males had a total hip and/or spine aBMD t-score 1 to 2.5 and < 2.5, respectively. HRpQCT reference data in females was generated from 1023 and 919 scans of the radius and tibia, respectively (Table 2). Lower scan numbers than participants was due to: 1) scan not performed due to time con straints (n = 5 radius and 59 tibia scans); 2) excessive motion artifact (n = 26 radius and 9 tibia scans), and; 3) participant size (e.g. leg too large for the carbon fiber cast; leg too long to place the reference line and scan a Acquired using the manufacturer's standard cortical bone script, a low-pass Gaussian filter (sigma 0.8, support 1.0 voxel) and fixed thresholds of 450 and 320 mgHA/cm3 for cortical and trabecular bone, respectively. b Acquired using the manufacturer's bone midshaft evaluation script, a lowpass Gaussian filter (sigma 0.8, support 1.0 voxel) and fixed threshold of 450 mgHA/cm3. c Acquired using the manufacturer's FE analysis with voxels assigned a modulus of 10 GPa and Poisson's ratio of 0.3. Failure estimated when 5 % of elements exceeded 1 % strain. Moreno et al., 2019). 2.3. Statistical analyses All statistical analyses were performed for females and males sepa rately as skeletal proportions and cross-sectional properties differ across sexes independent of height and weight (Kun et al., 2023; Nieves et al., 3 S.J. Warden et al. Bone Reports 20 (2024) 101735 Table 2 Participant characteristics stratified by decade of agea. Characteristic Females n Height (m) Ulna length (cm) Tibia length (cm) Weight (kg) BMI (kg/m2) Physical function Grip strength (kg) 5 sit-to-stand test (s) PROMIS-PF (T-score) Bone densitometry Spine aBMD z-score Total hip aBMD z-score HRpQCT scans included (n) Radial diaphysis Tibial diaphysis Males n Height (m) Ulna length (cm) Tibia length (cm) Weight (kg) BMI (kg/m2) Physical function Grip strength (kg) 5 sit-to-stand test (s) PROMIS-PF (T-score) Bone densitometry Spine aBMD z-score Total hip aBMD z-score HRpQCT scans included (n) Radial diaphysis Tibial diaphysis Age group (yrs) 1829 3039 4049 5059 6069 70+ 184 1.66 (1.611.70) 25.5 (24.426.4) 37.0 (35.438.3) 71.5 (59.076.8) 25.9 (21.727.7) 113 1.66 (1.621.70) 25.4 (24.626.2) 36.9 (35.737.9) 71.4 (60.079.6) 25.9 (21.629.5) 126 1.64 (1.611.68) 25.3 (24.526.1) 36.5 (34.838.0) 74.1 (60.487.1) 27.6 (21.933.0) 224 1.63 (1.601.67) 25.3 (24.426.3) 36.7 (35.137.9) 74.1 (60.683.6) 27.7 (22.831.5) 286 1.63 (1.591.67) 25.2 (24.326.0) 36.7 (35.238.1) 73.5 (62.382.5) 27.8 (23.231.1) 101 1.62 (1.581.65) 25.3 (24.625.9) 36.5 (35.137.9) 69.3 (59.476.9) 26.5 (22.729.3) 27.9 (23.532.0) 8.6 (7.19.9) 58.0 (52.463.5) 29.5 (26.032.5) 8.7 (7.210.1) 57.1 (51.263.5) 26.8 (22.331.1) 9.0 (7.410.5) 54.7 (48.759.6) 25.3 (21.628.3) 9.3 (7.710.6) 52.5 (47.157.8) 23.9 (21.026.8) 10.3 (8.611.5) 50.5 (47.154.7) 21.8 (17.725.0) 10.9 (9.012.8) 48.6 (44.653.6) 0.37 ( 0.320.95) 0.76 (0.061.51) 0.42 ( 0.130.90) 0.64 (0.061.24) 0.32 ( 0.531.13) 0.47 ( 0.411.30) 0.04 ( 0.790.78) 0.27 ( 0.570.94) 0.39 ( 0.521.23) 0.27 ( 0.360.89) 1.07 (0.421.85) 0.66 (0.131.18) 182 162 112 103 123 115 224 195 283 257 99 87 105 1.79 (1.741.83) 28.2 (27.128.8) 40.1 (39.041.5) 85.2 (73.991.6) 26.5 (23.528.6) 45 1.77 (1.741.81) 27.6 (26.828.7) 39.1 (38.040.7) 85.2 (75.193.0) 27.3 (24.630.7) 37 1.78 (1.731.84) 27.9 (26.729.0) 39.5 (37.741.0) 88.4 (79.395.8) 28.0 (24.730.8) 41 1.76 (1.721.83) 27.9 (27.028.9) 39.4 (37.841.2) 88.8 (76.9100.3) 28.5 (24.431.4) 95 1.78 (1.741.81) 28.1 (26.929.2) 40.0 (38.341.3) 88.2 (76.197.2) 27.8 (24.230.4) 69 1.75 (1.701.79) 27.8 (26.928.9) 39.5 (37.640.7) 87.0 (75.895.8) 28.4 (25.131.4) 47.6 (40.755.5) 8.5 (7.09.6) 60.1 (55.864.7) 47.4 (40.454.9) 8.2 (6.19.6) 58.7 (53.166.2) 48.3 (43.053.2) 8.8 (7.39.4) 57.1 (50.564.5) 44.6 (42.048.6) 9.0 (7.39.9) 53.3 (47.760.6) 41.3 (32.948.1) 9.8 (7.911.1) 53.4 (49.257.3) 31.6 (24.839.2) 11.7 (8.913.2) 48.0 (45.251.6) 0.05 ( 0.630.59) 0.04 ( 0.860.80) 0.29 ( 0.900.05) 0.28 ( 1.10.25) 0.07 ( 1.020.55) 0.12 ( 0.800.49) 0.06 ( 0.580.72) 0.09 ( 0.810.52) 0.90 (0.011.66) 0.25 ( 0.550.88) 0.56 ( 0.221.19) 0.12 ( 0.680.30) 104 90 44 41 37 32 40 37 91 81 68 55 aBMD = areal bone mineral density; BMI = body mass index; HRpQCT = high-resolution peripheral quantitative computed tomography; PROMIS-PF = physical function domain of the National Institues of Health Patient-Reported Outcomes Measurement Information System. a Data are median (interquartile range), except for frequencies. stack within the constraints of the z-axis of the scanner; presence of a local tomography artifact due to absorbing tissue outside of field of view) (n = 47 tibia scans). Reference data in males was generated from 384 and 336 scans of the radius and tibia, respectively (Table 2). Lower scan numbers than par ticipants was due to: 1) scan not performed due to time constraints (n = 6 radius and 31 tibia scans); 2) excessive motion artifact (n = 2 radius and 1 tibia scans) and; 3) participant size (n = 24 tibia scans). load) (all partial correlations = 0.280 to 0.452) (Table 3). Bone length explained 7.9 % to 20.5 % of the variance in the estimated mechanical properties. The highest scaling factors at both sites and in both sexes were for bone length's relationship with the estimated ability to resist bending (IMIN, IMAX) and torsion (pMOI) (all scaling factors = 1.652 to 2.113). Estimated ability to resist compression forces (stiffness and failure load) scaled to length at both the radius and tibia with scaling factors ranging from 0.934 to 1.019 in females and 0.685 to 0.984 in males. 3.2. Correlations and scaling factors 3.3. Centile curves There were negative relationships between density outcomes (Tot Den, TMD, CtvBMD) and bone length at both the radius and tibia in females and males (all partial correlations = 0.191 to 0.055) (Table 3). However, correlations did not rise to the level of R2 0.05 required for density data to be scaled to bone length. Similarly, bone length had low value in explaining radial and tibial BA/TA, CtTh or CtPo in either sex (all R2 < 0.05). Bone length explained 8.7 % to 13.6 % of the variance in radius areas (TA, BA, CtAr) and 9.9 % to 19.3 % of the variance in tibial areas (TA, BA, CtAr) in both sexes (Table 3). Areas in females scaled to length with scaling factors ranging from 0.934 to 1.009 for both the radius and tibia. Areas in males scaled to length with scaling factors ranging from 0.685 to 0.888 at the tibia and 0.856 to 0.984 at the radius. There were positive relationships at both sites and in each sex be tween bone length and the estimated ability to resist bending (IMIN, IMAX), torsion (pMOI), and compression forces (stiffness and failure Centile curves for raw CtvBMD, CtTh and CtPo outcomes, which did not satisfactorily scale to bone length, have previously been published (Warden et al., 2022b). Similar curves for TotDen, TMD, and BA/TA at the radius and tibia are presented in Supplemental Files 1 and 2, respectively. The fitted median centile curve for TMD peaked between 35 and 40 years of age in both sexes before declining thereafter. The decline in females was more precipitous, especially between 40 and 60 years of age. HRpQCT raw values for outcomes correlating with bone length at R2 0.05 (TA, BA, CtAr, CtPm, IMIN, IMAX, pMOI, stiffness, failure load) were converted to scaled values using the scaling factors and the ratio of the individual's bone length to sex specific median bone length (females = 25 cm for radius and 37 cm for tibia; males = 28 cm for radius and 40 cm for tibia). For example, for a female with a radial bone length of 24.2 cm and raw IMIN outcome of 514 mm4, the scaled IMIN would be 4 S.J. Warden et al. Bone Reports 20 (2024) 101735 females and an additional 82 radius (+27 %) and 88 (+35 %) tibia scans in males. Beyond an expanded dataset, the current study provides cen tile curves for HRpQCT outcomes previously without reference data, including TotDen, TMD, TA, BA, BA/TA, IMIN, IMAX, and pMOI. In addition, we explored the relationship between bone length and HRpQCT outcomes, developed a means of scaling outcomes for bone length, and generated centile curves for bone length adjusted outcomes. To facilitate the utility of the latter curves, Excel-based calculators (Supplementary Files 5 and 6) were developed to calculate age- and sexmatched percentiles and z-scores for both raw and bone length adjusted outcomes. Many of the HRpQCT outcomes at the radial and tibial diaphysis in both sexes were related to bone length, consistent with established in terrelationships between bone length and cross-sectional size (Biewener, 2005; Ruff, 1984). Size outcomes (TA, BA, CtAr, CtPm) positively correlated with bone length confirming that individuals with longer bones also had wider bones. As bones with larger cross-sectional size have material distributed further from bending axes, bone length also correlated with estimates of bone rigidity and strength (IMIN, IMAX, pMOI, stiffness, failure load). There were no relationships between bone length and TotDen, TMD, CtvBMD, and BA/TA as the later HRpQCT outcomes are already expressed relative to bone size. There was no relationship between CtTh and bone length. This is consistent with previous work (Bjrnerem et al., 2013) and likely re flects a means of minimizing the energy costs of larger and heavier bones. Bending resistance increases to the fourth power of the radius of a bone. By placing material further from its central axis and increasing its radius, a larger bone is disproportionately stronger for the same mass and energy cost. The more distant distribution of material relatively thins the cortex such that CtTh does not correspondingly increase with the increase in size of longer bones. Despite the relatively thinner CtTh, compressive strength is preserved via the increase in CtAr as bone length increases (Seeman, 2003). Scaling factors were calculated for outcomes for which bone length explained at least 5 % of variance (i.e., R2 0.05). There is no accepted cut-off in the literature. Our cut-off was chosen based on the rationale that a lesser relationship implied bone length had limited explanatory value, and is a more liberal cut-off than (for example) the 10 % cut-off implemented when adjusting DXA Z-scores for height in children (Zemel et al., 2011). Outcomes expressed in linear dimensions (e.g., CtPm) exhibited negative allometry, with scaling factors around 0.5 indicating disproportionately lower increases in size relative to in creases in bone length. Relatively isometric allometry (scaling factors around one) was observed for outcomes expressed in squared linear dimensions (e.g., TA, BA, CtAr), indicating bone cross-sectional area measures increased proportionally as bone length increased. Outcomes to the fourth power of linear dimensions (e.g., IMIN, IMAX, pMOI) exhibited positive allometry with scaling factors around two. The latter indicates estimated bone rigidity had disproportionately greater in creases relative to increases in bone length. The scaling factors were used to scale HRpQCT outcomes to bone length, and centile curves were generated for both raw and bone length scaled HRpQCT data. The centile curves can be used to calculate zscores. Excel-based calculators are provided to facilitate this process (Supplementary Files 5 and 6). The raw and scaled z-scores indicate the magnitude that an individual's HRpQCT outcomes differ relative to ex pected sex- and age-specific values. The difference between the two zscores being that the scaled z-score also considers bone length. The consideration of bone length enables it to be determined whether an individual has normal sized bones for their bone length. For example, consider a 43-year-old female with a tibial length of 33.5 cm and tibial pMOI of 15,000 mm4. Their raw z-score for pMOI using the Excel-based calculator equates to 0.738 indicating they have lower than expected torsional rigidity for their sex and age. This may be sug gestive of reduced cross-sectional bone development and an increased risk of injury, such as a bone stress injury (Warden et al., 2021b). Table 3 Spearman partial (on age) correlation between bone length and HRpQCT out comes, and scaling factors (SF) for outcomes exhibiting correlation with an R2 > 0.05. Site and HRpQCT outcome Female Spearman Male R 2 SF Spearman R2 SF Radius TotDen TMD CtvBMD TA BA CtAr BA/TA CtPm CtTh CtPo IMIN IMAX pMOI Stiffness Failure load 0.067 0.109 0.088 0.376 0.369 0.367 0.048 0.356 0.170 0.010 0.418 0.325 0.371 0.370 0.363 0.004 0.012 0.008 0.141 0.136 0.135 0.002 0.127 0.029 0.010 0.175 0.105 0.138 0.137 0.132 1.009 0.934 0.934 0.503 2.095 1.852 1.951 0.966 0.934 0.120 0.144 0.145 0.329 0.303 0.296 0.082 0.329 0.138 0.008 0.353 0.284 0.320 0.291 0.280 0.014 0.021 0.021 0.108 0.092 0.087 0.007 0.108 0.019 <0.001 0.125 0.081 0.103 0.085 0.079 0.984 0.866 0.856 0.530 1.989 1.858 1.912 0.865 0.829 Tibia TotDen TMD CtvBMD TA BA CtAr BA/TA CtPm CtTh CtPo IMIN IMAX pMOI Stiffness Failure load 0.055 0.191 0.182 0.439 0.409 0.406 0.002 0.444 0.207 0.027 0.393 0.443 0.452 0.424 0.432 0.003 0.036 0.033 0.193 0.168 0.165 0.000 0.197 0.043 <0.001 0.154 0.196 0.205 0.179 0.187 0.999 0.959 0.949 0.544 1.831 2.113 2.009 1.007 1.019 0.218 0.209 0.222 0.419 0.328 0.314 0.147 0.172 0.070 0.159 0.374 0.397 0.418 0.318 0.328 0.048 0.044 0.049 0.176 0.107 0.099 0.022 0.415 0.005 0.025 0.140 0.158 0.175 0.101 0.107 0.888 0.702 0.685 0.508 1.652 1.755 1.713 0.700 0.719 514.5/(24.2/25)2.095 = 550.7 mm4. Centile curves fitted to scaled TA, BA, pMOI, and failure load out comes are presented for the radius (Fig. 1) and tibia (Fig. 2). Centile curves fitted to scaled CtAr, CtPm, IMIN, IMAX, and stiffness outcomes are provided in Supplemental Files 3 (radius) and 4 (tibia). 3.4. Percentile and z-score calculator, and centile curve plotter Excel-based calculators were developed for both the radius (Sup plemental File 5) and tibia (Supplemental File 6). Entry of basic de mographic information (sex, date of birth, scan date, and bone length) and one or more HRpQCT outcome (Fig. 3A) results in plotting of sexspecific centile curves (Fig. 3B). The centile curves are based on the curves fitted using the LMS approach fitted to raw data (TotDen, TMD, CtvBMD, Ct.Th) or bone-length scaled data (TA, BA, CtAr, CtPm, IMIN, IMAX, pMOI, stiffness, failure load), depending on whether the outcome was related to bone length at R2 0.05. Beneath each curve, the raw entered and bone length scaled value for the HRpQCT outcome is pro vided along with the associated z-score and percentile (Fig. 3C). The raw z-score and percentile are derived from curves fitted to the raw reference data, whereas the scaled z-score and percentile are derived from curves fitted to the scaled reference data. 4. Discussion The current study expands our previously published reference data for HRpQCT outcomes at the cortical bone rich radial and tibial di aphyses (Warden et al., 2022b). We included data in the current analyses from an additional 173 radius (+20 %) and 171 tibia (+23 %) scans in 5 S.J. Warden et al. Bone Reports 20 (2024) 101735 Fig. 1. Bone length scaled data and fitted centile curves for total area (A, E), bone area (B, F), polar moment of inertia (C, G), and estimated failure load (D, H) at the radial diaphysis for females (top row) and males (bottom row). Fig. 2. Bone length scaled data and fitted centile curves for total area (A, E), bone area (B, F), polar moment of inertia (C, G), and estimated failure load (D,H) at the tibial diaphysis for females (top row) and males (bottom row). However, the individual also has a tibial length that is lower than the median 37 cm for females. When bone length is considered, a scaled pMOI of 18,314 mm4 is calculated (15,000/[33.5/37]2.009) and a scaled z-score of 0.002 obtained indicating relatively normal torsional ri gidity for their bone length. Scaled HRpQCT outcomes will be higher and lower than raw HRpQCT outcomes for individuals with bone lengths shorter and longer than median values in the current reference cohort, respectively. This is because scaled values were normalized to sex-specific median bone length. The latter was performed so that scaled outcomes would retain the same units and be within the same range as raw outcomes. However, the scaling approach in our cohort does raise the question of whether the bone lengths in our cohort are representative. Percutaneous measures of ulna (used as a surrogate for radius length) and tibia length are increasingly being performed prior to HRpQCT to enable the scanning region to be positioned relative to bone length, which has advantages over scanning at a fixed distance offset (Bonaretti et al., 2017; Ghasem-Zadeh et al., 2017; Okazaki et al., 2021; Shanb hogue et al., 2015). However, measured mean or median bone lengths are either not reported (Shanbhogue et al., 2015), not dichotomized by sex (Bonaretti et al., 2017; Shanbhogue et al., 2015) or acquired in a race and/or ethnicity with a different stature (Okazaki et al., 2021), negating the ability to compare to lengths acquired in the current study. GhasemZadeh et al. (Ghasem-Zadeh et al., 2017) did report forearm lengths in White females (25.7 cm) and males (28.1 cm) which compare favorably to our measured lengths of 25 cm and 28 cm in females and males, respectively. Similarly, comparable lengths of 24.7 cm and 27.5 cm have been reported in another cohort of White females and males, respec tively (Madden et al., 2012), and the 40 cm tibial length in males in our study matches the 40.2 cm measured in 18-year-old U.S. military re cruits (Nieves et al., 2005). In the absence of a wealth of percutaneously measured bone length data in the literature, a feasible proxy is to compare the heights of our individuals to population norms. Height and bone length are closely related, so much so that bone length is frequently used to estimate an individual's height. The average height within each decade of age in our cohort (Table 2; females = 1.621.64 m, males = 1.751.79 m) matches that of the U.S. White adult population (females = 1.62 m, males = 1.77 cm) (Fryar et al., 2021). The comparable height provides confidence that our measured median bone lengths are representative of the broader U. S. White population. We assessed other outcomes to explore the comparability of our 6 S.J. Warden et al. Bone Reports 20 (2024) 101735 principally developed for distal bone sites with a greater proportion of trabecular bone. The ability of the model to estimate failure load in other loading directions and at the cortical bone rich diaphysis remains to be established. Finally, we had more limited inclusion of males and older (age >70 yrs) adults and our data are specific to White individuals living in the Midwest of the United States. HRpQCT outcomes vary by race potentially requiring the generation of separate reference data for other races (van den Bergh et al., 2021). In summary, the current study expands our previous dataset by providing reference data for additional HRpQCT outcomes, including TotDen, TMD, TA, BA, BA/TA, IMIN, IMAX, and pMOI. More importantly, the study provides a means of scaling outcomes for bone length and provides reference data for bone length adjusted outcomes. The refer ence data enable HRpQCT outcomes in an individual (or population of interest) to be expressed relative to the reference cohort to determine if they are big boned for their age, sex and bone length. Supplementary data to this article can be found online at https://doi. org/10.1016/j.bonr.2024.101735. CRediT authorship contribution statement Stuart J. Warden: Conceptualization, Data curation, Formal anal ysis, Funding acquisition, Investigation, Methodology, Project admin istration, Supervision, Writing original draft, Writing review & editing. Robyn K. Fuchs: Conceptualization, Data curation, Formal analysis, Writing review & editing. Ziyue Liu: Formal analysis, Writing review & editing. Katelynn R. Toloday: Investigation, Writing review & editing. Rachel Surowiec: Data curation, Investi gation, Methodology, Writing review & editing. Sharon M. Moe: Conceptualization, Funding acquisition, Supervision, Writing review & editing. Declaration of competing interest Fig. 3. Screenshots of the Excel-based calculator for tibia outcomes (available in Supplemental File 5). Following entry of basic demographic information and one or more HRpQCT outcome (A), centile curves are plotted (B), and sex- and age-specific raw and bone length scaled z-scores and percentiles are calcu lated (C). None. Data availability Data will be made available on request. cohort to the broader population, including DXA-derived bone out comes, performance on physical function tests, and self-reported phys ical function (Table 1). DXA z-scores at the hip and spine were slightly higher than zero in females and approximated zero in males. Grip strength in our cohort according to decade stage of life mirrored refer ence values for individuals residing in the U.S. (Wang et al., 2018), whereas time to complete five sit-to-stand maneuvers matched or was slightly slower (Bohannon, 2006; Bohannon et al., 2010). Self-reported physical function (PROMIS-PF T-score) was slightly above the popula tion mean of 50, depending on sex and decade stage of life. These cu mulative data suggest our cohort had slightly above-to-normal general bone health and equivalent or a slightly higher level of functioning than the general U.S. population. Our study has several strengths, but it is also not without limitations. Data were obtained at a single center and variability in machine per formance at other centers may influence outcomes. The outcomes are specific to the sites scanned and the scanning, segmentation, and anal ysis procedures used. We used the manufacturer's bone midshaft eval uation script with a single outer contour and without an inner clockwise (i.e., negative excluding) contour. This means that outcomes using this script (including TotDen and TMD) include any trabecular bone present at the scan sites. This approach was selected as we wanted to include any trabecularized cortical bone, which increases with age (Zebaze et al., 2010). The micro-finite element model used to estimate bone strength is specific to axial compressive loading and was Acknowledgements This contribution was made possible by support from the National Institutes of Health (NIH/NIAMS P30 AR072581), and the Indiana Clinical Translational Science Award/Institute (NCATS UL1TR00252901). 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... MEDICAL EDUCATION ONLINE 2024, VOL. 29, 2336331 https://doi.org/10.1080/10872981.2024.2336331 RESEARCH ARTICLE Exploration of the integration of microbiology and immunology emerging topics into undergraduate medical education Margaret E. Bauera, Samina Akbar Shawn Staudahere and Yuan Zhao b , Timothy J. Bauler c , Jessica Chacond, Erin E. McClelland b , f a Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, IN, USA; bBiosciences Division, Marian University College of Osteopathic Medicine, Indianapolis, IN, USA; cHomer Stryker M.D. School of Medicine, Western Michigan University, Kalamazoo, MI, USA; dMedical Education, Texas Tech University Health Sciences Center El Paso, Lubbock, TX, USA; eEducational Affairs, Sam Houston State University College of Osteopathic Medicine, Conroe, TX, USA; fMolecular and Cellular Biology, Sam Houston State University College of Osteopathic Medicine, Conroe, TX, USA ABSTRACT Purpose: Medical school educators face challenges determining which new and emerging topics to incorporate into medical school curricula, and how to do so. A study was conducted to gain a better understanding of the integration of emerging topics related to microbiology and immunology in the undergraduate medical curriculum (UME). Methods: An anonymous survey with 17 questions was emailed to medical school faculty who teach immunology and/or microbiology through the DR-Ed listserv, the American Society for Microbiology (ASM) Connect listserv, and attendees of the Association of Medical School Microbiology and Immunology Chairs (AMSMIC) Educational Strategies Workshop. Participants were asked about experiences, perceptions, and the decisionmaking process regarding integrating emerging topics into UME. Results: The top emerging topics that were added to the curriculum or considered for addition in the last 10 years included COVID-19, Zika virus, mRNA vaccines, and Mpox (formerly known as monkeypox). Most respondents reported lectures and active learning as the major methods for topic delivery, with most faculty indicating that formative assessment was the best way to assess emerging topics. Content experts and course directors were the most cited individuals making these decisions. Top reasons for incorporating emerging topics into curricula included preparing students for clinical treatment of cases, followed by demonstrating the importance of basic science, and opportunities to integrate basic science into other disciplines. Challenges for incorporating these topics included making room in an already crowded curriculum, followed by content overload for students. Conclusions: This study describes the rationale for integrating emerging topics related to microbiology and immunology into UME, and identifies the current new and emerging topics, as well as the main methods of integration and assessment. These results may be used by medical educators to inform curricular decisions at their institutions. Future studies will include developing innovative learning modules that overcome barriers to integration. Introduction Modern preclinical medical curricula are increasingly integrated, as integration is firmly established as being beneficial to learning [13]. Horizontal integration in preclinical medical curricula has led to replacement of traditional discipline-based courses by organ systembased courses and other innovative curricula [1]. Accordingly, the preclinical curriculum is an intricate puzzle with many pieces, all of which must efficiently work together under severe time and resource con straints to deliver the optimal content for medical stu dents. Medical educators who are part of the preclinical curriculum team of scientists and clinicians that teach medical students are continuously challenged to deter mine the depth of science medical students need to CONTACT Yuan Zhao yxz028@shsu.edu City Central Avenue, Conroe, TX 77304, USA ARTICLE HISTORY Received 2 June 2023 Revised 27 September 2023 Accepted 25 March 2024 KEYWORDS Emerging topics; microbiology and immunology; undergraduate medical curriculum; integration of basic science; clerkship readiness know. Some scientific disciplines required by medical students, including microbiology and immunology, are constantly changing, for example as infectious organisms emerge or evolve and novel immune-based treatments are approved based upon new scientific knowledge. With limited curricular time, medical school micro biology and immunology educators may struggle to determine when and how to incorporate new and emer ging topics into the curriculum. This is complicated by the fact that many of these topics are taught in courses where they are not the course director or lead. New and emerging (and re-emerging) topics were defined for this study as content that has not traditionally been taught or emphasized, but due to scientific/medical advances, increased numbers of patient cases, and/or Molecular and Cellular Biology, Sam Houston State University College of Osteopathic Medicine, 925 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. 2 M. E. BAUER ET AL. increased public awareness of the topic, should be con sidered for addition to the preclinical medical curricu lum. Consideration of emerging topics, such as COVID-19 and novel Food and Drug Administrationapproved cancer immunotherapeutics, is required of microbiology and immunology educators more than some other basic science disciplines, as the fields of infectious diseases and applied immunotherapies change over time. Determining which emerging topics should be added to the preclinical medical curriculum is a careful balancing act for microbiology and immunol ogy educators. New content is particularly relevant and exciting for a medical learner, and all stakeholders want physicians to have the most up-to-date scientific and medical knowledge. However, the rate of acquisition of new medical and scientific knowledge means that including everything into the curriculum is impossible, as curricula are already overcrowded [4]. Consensus learning objectives for microbiology and immunology were published in 2009, which were intended to define the minimal content medical students needed for competency [5]. The frequency of medicallyrelevant changes within the fields of microbiology and immunology since 2009 demonstrates that relying on consensus documents to determine whether a new topic should be added to the curriculum is impractical. Thus, there is no established method by which faculty may determine how to integrate new emerging micro biology or immunology content. The only published article about emerging microbiology topics described the frequency at which applied microbiology content, such as hospital infection control, antimicrobial steward ship, and global health were incorporated into curricula of allopathic medical schools in 2016 [6]. No published studies have investigated emerging topics in immunol ogy in preclinical medical curricula. The aims of this study were to determine which factors are considered by microbiology and immunol ogy educators in the United States before they incorpo rate a new and emerging topic into their curriculum, define the microbiology and immunology topics con sidered new and emerging at a single snapshot in time (2022), and explore best practices of how these topics are being integrated. These results will be useful for educators to consider when incorporating emerging topics in their discipline-specific portions of the pre medical curriculum at their respective institutions. Methods Exempt status for the research project was granted by the Institutional Review Board of each investigators institu tion (Western Michigan University IRB: WMed-2022 0962, Marian University IRB: IRB S22.172, Indiana University Human Research Protection Program: 17130, Sam Houston State University IRB: IRB-2022321, Texas Tech University: E23034). A 17-question anonymous survey (Appendix I) was constructed using Qualtrics (Provo, UT) and emailed to faculty who teach immunology and/or microbiology at allopathic and osteopathic medical schools using the DR-Ed listserv, the American Society for Microbiology (ASM) Connect listserv, and the attendee list of the 2022 Association of Medical School Microbiology and Immunology Chairs (AMSMIC) Education Strategies Workshop. The survey asked participants about experiences, per ceptions, and the decision-making process regarding integrating emerging topics into Undergraduate Medical Education (UME). Demographic data on the type and size of medical school was also collected for analysis. A total of 69 participants agreed to respond to the survey, with 40 giving informed con sent and completing all questions (not including two open-ended questions). Our analysis was confined to the 40 complete responses from U.S. medical schools. The survey question types fell into three categories: multiple choice, ranking, and a slider scale. For the ranking questions, respondents ranked a set of choices. In the slider scale question, respondents moved a slider to choose between 1 (lowest) and 5 (highest). For a complete list of survey questions see Appendix I. The type of question determined the statistical analysis used for each question. Chi-square tests were used to determine if there was a significant difference between allopathic and osteopathic respon dents. For multiple selection multiple choice ques tions, contingency tables were generated to examine conditional relationships between the choices (i.e., how often one choice occurred in the presence of another choice). A t-test was used to determine if there was a significant difference between the two choices in the slider scale question where participants were asked to grade the importance of public percep tion and clinical impact in the decision to include an emerging topic in the curriculum. Inter-rater reliabil ity for the ranking questions was measured using Kendalls W [7] and statistical significance was mea sured using a follow-up Chi-square test. Data proces sing, statistical computations, and visualizations were performed with Python 3.11 using the pandas, scipy, and seaborn libraries. Narrative responses (n = 37) from the open-end question how do you define an emerging topic in microbiology and immunology were analyzed using constant comparison analysis [8] and classical content analysis [9]. Qualitative sta tistics were computed using Dedoose 9.0.90. Results The 40 respondents of the study were from 31 med ical schools across the United States. Among the 31 schools, 19 (61%) were allopathic medical schools and 12 (39%) were osteopathic medical schools. MEDICAL EDUCATION ONLINE Relatively more osteopathic schools were represented in this study compared to the current U.S. totals of 155 (80%) allopathic and 38 (20%) osteopathic schools. The participating institutions have a variety of different campus environments, with an average incoming class size ranging from 49550 per cam pus, the number of campuses ranging from 19, and the ratio of microbiology and immunology faculty to campuses ranging from 0.8:1 to 20:1. Among the 40 respondents, 15 (37.5%) report teaching microbiology only, 10 (25%) teach immunology only, and 15 (37.5%) teach both disciplines. To test for differences in responses to the multiple choice and single-selection questions between faculty at allopathic and faculty at osteopathic medical schools, chi-square tests were conducted, and no sig nificant differences were identified for any of the questions ( 0:05. Emerging topics for UME curriculum Medical school educators were asked to provide their definition for an emerging topic in microbiology and immunology. Qualitative analysis of the responses showed the most common code was new topic and knowledge. Among 15 responses that were mapped to this code, nine specifically mentioned new or reemerging infectious diseases or organisms. Three responses mentioned immunology related topics. The second most common code was impact on patient health and clinical practice; nine responses were mapped to this code. The third common code 3 was increasing clinical incidence; six responses were mapped to this code. Other less common codes included not on licensing exam yet and recently or not yet in the textbook. To summarize, the respon dents defined emerging topics in microbiology and immunology as a new topic or knowledge related to new and emerging infectious diseases and new appli cations of immunology that have impacted patient health and medical practice with increasing clinical incidence. Next, microbiology and immunology educators were provided with a list of emerging topics and asked which of these have been added or consid ered for addition to the curriculum in the last 10 years. The list was developed by the authors, who are content experts of microbiology and immu nology, and consulted colleagues (five) in the field. Survey respondents selected between 211 topics (M = 6.8, SD = 2.5); with the exception of siderophores to treat cancer, each topic was selected by at least 20 (50%) of the respondents (Figure 1). The popularity of the selected topics align with our perception of the prevalence of recent media coverage. Some educators also wrote in their own topics, but none of these were noted by more than one respondent. Reasons for incorporating emerging topics into the UME curriculum Participants were asked to separately rank medically relevant and public perception factors that suggest an Figure 1. Selected emerging topics added or considered for addition to the undergraduate medical education curriculum, N = 40. 4 M. E. BAUER ET AL. emerging topic warrants inclusion in the curriculum. Agreement amongst respondents was found to be sta tistically significant for both the medically relevant fac tors (Kendalls W = 0.52, 2 (4, N = 40) = 83, p < 0.001) and public perception factors (Kendalls W = 0.57, 2 (5, N = 40) = 114, p < 0.001). Among medically relevant factors, significant number of cases/deaths worldwide and regionally/locally were ranked as the top two choices, respectively (Table 1). Newly-approved treat ments and newly-changed management guidelines were ranked as less relevant clinical factors for including new and emerging topics into the curriculum. Among the public perception factors, national and local news coverage were ranked as the top two reasons, respec tively, for an emerging topic to be considered for addi tion to the curriculum. Social media posts and commercials for treatments or vaccines were the third and fourth ranked public perception reasons for curri cular addition, respectively, with family inquiries as the least relevant rationale (Table 2). To compare the relative importance of public opi nion vs clinical impact in the decision to include an emerging topic into medical curricula, participants were asked to use sliding scales (from 1-least impor tant to 5-most important). Clinical impact (M = 4.64, SD = 0.44) was rated as significantly more important than public opinion (M = 2.59, SD = 0.85) by survey respondents with a two-tailed paired t-test result of t (39) = 13.5, p < 0.001. Notably, every participant rated clinical impact higher than public perception (Figure 2). Medical educators were also asked to rank the educational rationale for discussing new microbiol ogy and immunology content in UME. Agreement amongst respondents was found to be statistically significant (Kendalls W = 0.52, 2 (4, N = 40) = 83, p < 0.001). The top-ranked reason for incorporating emerging topics into the curriculum was preparing students for treating cases in the clinic, followed by seizing additional opportunities to demonstrate the importance of basic science, and to integrate basic science into other disciplines (Table 3). Satisfying student interest in a topic and preparing students for standardized medical exams were deemed less important, and using the emerging topic to add addi tional basic science content to the curriculum was ranked least important of the options provided. Decision making process for integrating emerging topics in the UME curriculum Respondents were also asked to select who is involved in deciding if an emerging topic should be incorporated into the curriculum; 36 (90%) selected content experts and 32 (80%) selected course directors, whereas only five (12.5%) selected curriculum committee, two (5%) selected associate dean of education or similar role, and two (5%) selected department chair. Additionally, open-ended responses included case writing team, dis cipline team, and committee specific for reviewing and approving pre-clerkship learning objectives, with each selected by a single respondent. Content experts and course directors were not only selected most often, 29 (72.5%) respondents selected both. Also, all five respon dents that indicated a role for the curriculum commit tee also selected content expert and course director. Similarly, both respondents that selected associate dean of education selected content expert and course Table 1. Ranking of clinical impact or important triggers in suggesting an emerging topic warrants inclusion in undergraduate medical education curriculum (mean was calculated as the average ranking for each choice, 1 is the top choice), N = 40. Rank Choice 1 2 3 4 5 Mean Significant number of cases/deaths worldwide Significant number of cases/deaths seen in region/local community Newly approved treatment Newly changed management guidelines *Other-Open ended response 24 6 5 2 3 10 18 6 6 0 4 7 21 8 0 2 9 7 20 2 0 0 1 4 35 1.6 2.48 2.83 3.45 4.65 *Top ranked open-ended responses included: issues that affect healthcare delivery, mass media coverage, and illustrating important principles. Table 2. Ranking of public perception or popular media coverage in suggesting an emerging topic warrants inclusion in undergraduate medical education curriculum (mean was calculated as the average ranking for each choice, 1 is the top choice), N = 40. Rank Choice Its on the national news nightly Local news stations are covering the topic See regular social media posts See commercials for new treatment or vaccine Family members ask you about it *Other-Open ended response 1 31 1 0 4 1 3 2 6 19 10 2 3 0 3 2 11 10 9 8 0 4 1 6 9 14 9 1 5 0 3 10 9 18 0 6 0 0 1 2 1 36 Mean 1.32 2.77 3.55 3.7 4.08 5.58 *Top ranked open-ended responses included: covered in prominent medical journals, important in the clinical media, students have not indicated much specific interest. MEDICAL EDUCATION ONLINE 5 Figure 2. Ratings of clinical impact versus public perception in the decision to include an emerging topic in the curriculum. Due to overlapping data, the size of each point indicates the number of respondents who selected each score pair. The diagonal dashed line represents an equal rating for clinical impact and public perception with points above the line indicating that the participant rated clinical impact higher than public perception, N = 40. (survey question 10 was used for this data). Table 3. Ranking of reasons for incorporating emerging topics into curriculum (mean was calculated as the average ranking for each choice, 1 is the top choice), N = 40. Rank Choice 1 2 3 4 5 6 7 Mean Prepare students for seeing cases in the clinic 24 7 2 3 4 0 0 Integrate basic science into other disciplines (like ethics of cost of treatment, vaccine hesitancy, public health, 9 7 11 5 5 3 0 etc) Demonstrate the importance of basic science 3 14 12 5 5 1 0 Satisfy student interest in the topic 1 6 4 10 11 8 0 Prepare students for standardized/board exams 2 6 4 7 6 14 1 Allows more basic science to be taught 0 0 6 10 9 14 1 *Other-Open ended response 1 0 1 0 0 0 38 1.90 2.98 2.95 4.20 4.38 4.85 6.75 *Top ranked open-ended responses included: help students understand and contextualize a topic in the media. director. Together, this suggests that the decision to include emerging topics is most often made at the content expert and course director level, and when higher levels of leadership are involved, content experts and course directors remain involved in the decisionmaking process. Teaching methods and assessments for emerging topics We next asked several questions about which teaching modalities and assessment strategies are used when adding emerging topics to the curriculum. First, respon dents were asked to select the single best teaching modality for emerging topics. The most common choice was lecture with 18 (45%) respondents, then active learning methods (case-based learning and dis cussion) with 12 (30%), team-based learning (TBL) with 4 (10%), problem-based learning (PBL) with 2 (5%), asynchronous modules with 2 (5%), and other with 2 (5%). While lecture was the top choice, when all three active learning choices are combined, there is a tie with 18 (45%) for lecture and 18 (45%) choosing one of the three active learning choices. Interestingly, of the active learning methods, case-based and discussion were cho sen far more frequently than TBL and PBL. For the best method of assessment, formative assessment was cho sen by 18 (45%) respondents, summative examinations by 10 (25%), low-stake summative (quizzes) by 5 (12.5%), and no assessment by 4 (10%). Multiple freetext responses also commented that the teaching and assessment methods should depend on the new and emerging topic itself, and the level of depth required to adequately cover the topic (data not shown). Challenges for integrating emerging topics in the UME curriculum Medical educators were also asked to rank the obsta cles and challenges that may make integrating 6 M. E. BAUER ET AL. Table 4. Challenges for incorporating emerging topics in the curriculum (mean was calculated as the average ranking for each choice, 1 is the top choice), N = 40. Rank Choice Making room in an already full course or curriculum Content overload for students Content not covered yet on board exams Time constraints for faculty Curriculum committee has to approve all such changes *Other-Open ended response 1 29 6 4 1 0 0 2 4 18 10 7 1 0 3 5 12 6 14 3 0 4 1 4 11 15 8 1 5 1 0 9 3 27 0 6 0 0 0 0 1 39 Mean 1.52 2.35 3.27 3.30 4.60 5.95 Open ended responses included: student resistance due to new/emerging topics not covered by board exam and faculty being unfamiliar with new topics. emerging topics in the UME curriculum a challenge. Agreement amongst the respondents for this question was statistically significant (Kendalls W = 0.72, 2 (5, N = 40) = 143, p < 0.001). Making room in an already full course or curriculum was the leading challenge identified by respondents, with concerns about con tent overload for students the second most important challenge identified (Table 4). Concerns about lack of assessment on national examinations, faculty timeconstraints for new content development, and admin istrative concerns were deemed less important barriers. Discussion How and when to incorporate new and emerging topics into undergraduate medical school curricula is a challenge frequently faced by medical school faculty. While the COVID-19 pandemic made micro biology and immunology faculty particularly aware of the need to regularly reevaluate and update their content, there have been many other significant infectious disease outbreaks and immune-based ther apeutics that have become important in the past decade. In this study, microbiology and immunology educators from medical schools across the country were surveyed to define these new and emerging topics, evaluate what factors they consider before incorporating a new and emerging topic into their curricula, how this content should be taught and assessed, and what challenges must be overcome. Efforts to integrate emerging topics in other dis ciplines have been addressed in previous studies. For example, in 2022, after talking to various stake holders, Sullivan et al. conducted a comprehensive analysis to determine where and how to insert climate change and health into their curriculum [10]. They devised a 6-step model based on Thomas et al to achieve horizontal and vertical integration of climate change and health into the curriculum [11]. Other groups have conducted multi-institution surveys to determine what emerging topics should be taught. One study published in 2013 surveyed medical schools in the United Kingdom and Ireland on teach ing of biological weapons and bioterrorism [12]. Of the 34 medical schools that answered their survey, only 6 (17.7%) had specific teaching on biological weapons and bioterrorism in the curricula, but most schools did not. From free responses, the reasons for why this topic was not part of the curriculum included that the teaching schedule was too busy, or the topic was not compulsory. In addition, some regarded this field of study as a postgraduate subject that was not appropriate for undergraduates, and it would be very rare for a junior doctor to see these types of cases. All 40 medical educators that participated in this study have included or considered including emer ging topics in their curriculum, demonstrating that faculty recognize the importance of teaching emer ging topics. There is some correlation between the prevalence and recency of an infectious disease or immune-based therapy and the percentage of respon dents who indicated they had considered the topic for integration. For example, COVID-19 was the most selected topic (n = 37, 92%); given its recent global significance, this result was not surprising. Somewhat less frequently identified was Zika virus (n = 32, 80%), a pathogen whose expanded geographic distribution during the 20142015 epidemic revealed a previously unappreciated effect on fetal development [13]. Similarly, mRNA vaccines (n = 30, 72%) were ranked higher than Chimeric Antigen Receptor (CAR)-T cells (n = 27, 68%), as mRNA vaccines were broadly distributed worldwide during the COVID-19 pan demic, while CAR-T cells, FDA-approved in 2017, are an effective cancer therapy targeted for a narrower population [14]. Given that survey respondents were all medical educators, the finding that the 15 rating of clinical significance was higher (and statistically significant), than public perception in determining which emerging topics to add to the UME curricula, was unsurprising. However, respon dents still ranked public perception or media cover age 2.59 on the 15 scale, suggesting that indicators of social impact remain important contributing fac tors in this decision. For example, some topics of lesser clinical significance may be included to address student interests or concerns arising from nonmedical sources of information. MEDICAL EDUCATION ONLINE Respondents to our study suggested lectures (n = 18, 45%), case-based learning, and discussions (n = 12, 30%) as the best methods for teaching emer ging topics. It was interesting that TBL/PBL were chosen less frequently. This may be because educators find it easier to add a slide or case to an existing lecture than create an entirely new TBL/PBL. Additionally, because these are new and emerging topics, there may be insufficient verified clinically relevant information to create a new TBL/PBL. With the trend of UME moving toward integrative models and the adaptation of virtual learning due to the recent pandemic, some additional ideas for inte grating emerging topics include introducing them through asynchronous learning modules, small case studies, or TBL activities in system-based courses. Several studies have reported innovative ways to teach individual emerging topics. Chiu et al. share their experience in developing and implementing a student-led virtual COVID-19 course, while Kemp et al. describe a collaborative self-directed learning COVID-19 elective [15,16]. In another study, Kabelitz et al. report on the formation of an Education Committee of the International Union of Immunological Societies (IUIS). This committee administers three to four one-week courses per year, that focus on the most relevant topics and health issues facing specific countries or regions around the world [17]. The optimal curriculum design and teaching methods for emerging topics likely vary based on the impact of the disease or immunother apeutic and the depth of the scientific literature on the topic. For example, for COVID-19 it is reasonable to explore the opportunity in the curriculum to have multiple, focused active learning sessions, as well as develop the connection between various concepts and disciplines, such as public health and ethics. Some other emerging topics, such as immune checkpoint inhibitors, may merit simply replacing a small frac tion of an existing lecture on cancer immunothera pies due to a reduced worldwide impact. Although a new or emerging topic may be impor tant and exciting to scientists, and faculty may desire to devote hours of teaching to the topic, it is not feasible for every program to identify space in the curriculum to offer an independent session or course for emerging topics. As UME curricula prepare future physicians for lifelong learning and promote the cul ture of self-identification, including in the curriculum all content that might be relevant to physicians in future decades should not be the goal of medical educators. In fact, based on the survey, the biggest challenge for incorporating emerging topics in UME is making room in an already full course and curri culum. The concerns of curriculum overload for UME has lasted over a century [4,1820]. Several solutions have been proposed to address the issue 7 and a few studies report the successful implementa tion of a less comprehensive curriculum, which usually involves a huge multidisciplinary team effort [2123]. When deliberate curriculum planning can not take place, purposeful and creative integration of new/emerging topics in curriculum may require removing older, classic topics with less medical rele vance from the curriculum entirely. Content experts and course directors are the major decision makers regarding what and how to incorporate new topics in the curriculum, per our survey data. In the future, faculty development and encouragement of scholarly design and dissemination of education materials and/ or modules for these new topics will be very benefi cial for the medical education community and may alleviate the burden of content development. This study was subject to several limitations. First, there were strong selection effects as the sur vey was not distributed randomly. A medical educa tion conference attendee list and two educationfocused listservs were used to distribute the survey. While there was diversity in the sample, methods to correct selection effects, such as post-stratification, were not used due to a limited sample size. Also, faculty who attend educational conferences and sub scribe to medical education-focused email list servs likely have distinct viewpoints compared to faculty who do not. In addition, several respondents came from the same institution, and respondents may teach only microbiology, only immunology, or both. There are also limitations for the rank-based questions. Differences between ranks are subjective for each respondent, making absolute comparisons between ranked items impossible. For instance, a respondent may rank their first choice nearly equal to their second choice, or they could consider their first choice far above their second; a ranking question cannot distinguish between these two pos sibilities. Due to these limitations, this study was not designed to test a specific hypothesis, but instead its purpose was to describe how education-focused faculty incorporate and teach emerging topics in microbiology and immunology. Another limitation is this study defined the new and emerging microbiology and immunology topics at a specific moment in time, Fall 2022. Accordingly, COVID-19 was the most-frequently selected topic. While the study also identified Mpox as a highlyrelevant new topic, barring a recurrence of an Mpox outbreak five years from now, Mpox would likely not be included in the curriculum of 75% of respondents in 2027. This limitation also demonstrates the impor tance of faculty defining the process of how and when new and emerging topics are added to (or removed from) the curriculum, because the medically-relevant microbiology and immunology topics are regularly changing. 8 M. E. BAUER ET AL. The core curriculum of the UME should ensure the competency of medical graduates to deal with the common or important clinical problems that they are likely to encounter in future clinical practice [24]. As we reflect on the COVID-19 pandemic that has dee ply impacted all aspects of medical school education, we conclude that it is important to include emerging topics in the medical school curriculum to prepare students for changes in clinical practice and the needs of future doctors. Acknowledgments We would like to thank our institutional librarians, Christopher Bishop (Marian University, Hackelmeier Memorial Library) and Cecelia J. Vetter (Ruth Lilly Medical Library, Indiana University), for their help with literature reviews. We would also like to thank our colleagues who provided input on an early draft of the survey. Disclosure statement No potential conflict of interest was reported by the author(s). Funding The author(s) reported there is no funding associated with the work featured in this article. Data availability statement Complete survey data used/analyzed in this study are avail able from the corresponding author on request. ORCID Samina Akbar http://orcid.org/0000-0002-7641-2306 Timothy J. Bauler http://orcid.org/0000-0002-5170-0125 http://orcid.org/0000-0002-3657Erin E. McClelland 7528 Yuan Zhao http://orcid.org/0000-0001-5608-4088 References [1] Brauer DG, Ferguson KJ. The integrated curriculum in medical education: AMEE Guide No. 96. 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From the Carnegie Foundation for the advancement of teaching. Bull Number Four. 2002;80(7):594602. [19] Rappleye W. Medical education: final report of the Commission on medical education. New York: Association of American Medical Colleges Commission on Medical Education; 1932. [20] Swanson AG, Anderson MB. Educating medical students. Assessing change in medical educationthe road to imple mentation. Acad Med. 1993;68(6):S146. doi: 10.1097/ 00001888-199306000-00014 MEDICAL EDUCATION ONLINE [21] Deon M, Crawford R. The elusive content of the medical-school curriculum: a method to the madness. Med Teach. 2005;27(8):699703. doi: 10. 1080/01421590500237598 [22] Slavin S, DEon MF. Overcrowded curriculum is an impediment to change (part B). Can Med Educ J. 2021;12(5):15. doi: 10.36834/cmej.73813 9 [23] Arja SB, Arja SB, Venkata M, et al. Integrated curricu lum and the change process in undergraduate medical education. Med Teach. 2018;40(5):437442. doi: 10. 1080/0142159X.2018.1441988 [24] Burge SM. Undergraduate medical curricula: are students being trained to meet future service needs? Clin Med. 2003;3(3):243246. doi: 10.7861/clinmedicine.3-3-243 10 M. E. BAUER ET AL. Appendix I Survey Questionnaire (1) Please answer the following demographic questions regarding the school you are affiliated with. a. Name of the school b. Average incoming class size/year c. Number of Campuses d. Number of faculty who primarily teach microbiology/immunology content (all campuses combined) (2) Do you primarily teach Microbiology, Immunology, or both? a. Microbiology b. Immunology c. Both (3) How is the pre-clerkship microbiology and immunology taught? (Select all that apply) a. Stand-alone microbiology course or stand-alone immunology course b. Combined microbiology and immunology course c. Part of foundational sciences course d. Combined with other disciplines (e.g., Hematology, etc.) e. Integrated into organ systems course f. Part of fully integrated curriculum (no separate micro/immuno course) (4) What major modalities are used to teach the pre-clerkship microbiology/immunology content? (Select all that apply) a. Lectures (including active learning components as part of an overall lecture) b. Asynchronous modules c. Team-based learning (TBL) d. Problem-based learning (PBL) e. Other active learning Case-based learning, discussions, etc (5) How do you define an emerging topic in microbiology and immunology? [open response] (6) Please identify emerging topics you added to your curriculum or considered adding to your curriculum in the last 10 years. (Select all that apply) a. COVID-19 b. Monkeypox c. Zika d. Ebola e. Re-emergence of vaccine-preventable diseases (measles, polio, etc) f. mRNA vaccines g. CAR-T cells h. Checkpoint inhibitors i. Fecal microbiota transplant j. Siderophores to treat cancer k. Others [open response] (7) Who is involved in the decision to incorporate an emerging topic into the curriculum? (Select all that apply) a. Content expert b. Course director c. Department chair d. Curriculum Committee e. Associate Dean of Education or similar administrative entity f. Others [open response] (8) What levels of clinical impact or important triggers suggest an emerging topic warrants inclusion in the curriculum? (Please rank order) a. Newly-approved treatment b. Newly-changed management guidelines c. Significant number of cases/deaths worldwide d. Significant number of cases/deaths seen in region/local community e. Others [open response] (9) What level of public perception or popular media coverage suggests an emerging topic warrants inclusion in the curriculum? (Please rank order) a. See regular social media posts b. Its on the national news nightly c. Family members ask you about it d. Local news stations are covering the topic e. See commercials for new treatment or vaccine f. Others [open response] (10) On a sliding scale, please indicate your opinion of the relative importance of public opinion vs clinical impact in the decision to include an emerging topic into your curriculum. (5-likert scale, 1-least important, 5-most important) a. Clinical impact b. Public perception or popular media coverage (11) What is the major modality that you think would be best to teach these emerging topics? a. Lectures (including active learning components as part of an overall lecture) b. Asynchronous modules c. Team-based learning (TBL) d. Problem-based learning (PBL) e. Other active learning Case-based learning, discussions, etc f. Other [open response] (12) What is the best way to assess these newly emerging topics? a. No assessment b. Formative only MEDICAL EDUCATION ONLINE 11 c. Low-stakes summative (quizzes) d. Summative examinations e. Others [open response] (13) If you add a major emerging topic into the curriculum, does something else have to be removed? If yes, who is involved in the decision of what topic to remove? [select all that apply] a. Content expert b. Course director c. Department chair d. Curriculum Committee e. Associate Dean of Education or similar administrative entity f. Others [open response] g. Nothing needs to be removed (14) Rank the reasons for incorporating emerging topics into the curriculum. a. Demonstrate the importance of basic science b. Allows more basic science to be taught c. Integrate basic science into other disciplines (like ethics of cost of treatment, vaccine hesitancy, public health, etc) d. Satisfy student interest in the topic e. Prepare students for seeing cases in the clinic f. Prepare students for standardized/board exams g. Others [open response] (15) Rank the obstacles/challenges that work against adding emerging topics into the curriculum. a. Making room in an already full course or curriculum b. Curriculum committee has to approve all such changes c. Time constraints for faculty d. Content not covered yet on board exams e. Content overload for students f. Other: Please specify (16) What are the resources you use to develop the session with emerging topics? (Select all that apply) a. Textbook b. Journal articles c. CDC guidelines d. UptoDate or similar resources e. Others: Please specify (17) Is there anything else you want to tell us about integrating emerging microbiology and immunology topics into medical curricula, preclerkship or clerkship?  ...

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