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ImportanceUnderstanding the global barriers to otolaryngology–head and neck surgery (OHNS) care is crucial in addressing disparities in access to care, particularly in low-income and middle-income countries (LMICs).ObjectiveTo characterize barriers to comprehensive otolaryngology care across World Bank income groups.Design, Setting, and ParticipantsUsing an online cross-sectional survey that was administered by the Global OHNS Initiative via international and national professional societies, personal contacts, and social media, this study captured the perceptions of otolaryngologists regarding barriers to OHNS care at the levels of the country, health sector, clinician, and patient. Participants included otolaryngologists from the 194 World Health Organization member states and Taiwan. Eligibility criteria included a medical degree and specialized training in managing conditions of the ear, nose, and throat. The nonresponse rate was not recorded. The data collection period spanned from October 2022 to June 2023.ExposuresExposures included World Bank income group classification.Main Outcomes and MeasuresThe primary outcomes were Likert scale responses regarding frequency of barriers to OHNS care. The a priori hypothesis was that LMICs would report more frequent barriers to OHNS care.ResultsThe study involved 146 otolaryngologists (47 female individuals [32%]), with 69 (47%) from high-income countries and 77 (53%) from LMICs. Male individuals represented 45 high-income country respondents (65%) and 54 LMIC respondents (70%). Barriers were reported across income groups at all levels of the health system, with a higher frequency in LMICs. Several barriers were reported to be more substantial in LMICs, such as the national volume and distribution of otolaryngologists, financial compensation for clinicians, and patient stigma, and others were common across income settings, such as the availability of operating rooms and inflexible working hours. Common concerns included national and health sector barriers: OHNS workforce, referral networks, government support; clinician barriers: excessive clinician workloads, understaffing, poor administration support; patient barriers: distance to health care facilities, financial burdens such as medical costs and foregone wages, stigma, and health literacy.Conclusions and RelevanceThe results of this cross-sectional study suggest that there are barriers to otolaryngology care globally that affected all levels of the health care system. This work may inform prioritization of otolaryngology within research and policy, and it emphasizes the need for effective strategies to expand access to otolaryngology care, particularly in lower-income settings.

Abstract Background: Epidemiologic studies commonly obtain important exposure and outcome information from patient self-report although these may be influenced by imperfect understanding and/or faulty recall. The Voyage Study is a large-scale, prospective cohort study of long-term health outcomes among participants with a valid multi-target stool DNA (mt-sDNA) test order (N=150, 047). The purpose of this analysis was to evaluate the validity of participant reported mt-sDNA tests, colorectal cancer (CRC), and/or aerodigestive cancers (ADC, including cancers of the head, neck, oral, esophageal, lung, liver, stomach, pancreas, anus) among respondents. Methods: Participants from across the Unites States enrolled in the study completing questionnaires at enrollment and 1 year. The year 1 questionnaire collected data on completion and outcome of their mt-sDNA test, follow up colonoscopies and other procedures as well as a diagnosis of CRC or ADC. The study team contacts those who reported either CRC or ADC for permission to obtain copies of medical records. Records are then reviewed by a trained nurse abstractor and evaluated for validity. Mt-sDNA test results were available from Exact Sciences. Results: At the time of this analysis, year 1 questionnaire data were available on 135, 035 participants. Abnormal mt-sDNA results (n=12, 928) were self-reported by 13, 420 participants with 96.3% accuracy. Of the 111, 556 self-reported normal results, 93.4% (n=104, 150) were reported correctly. The validation process for the Voyage Study is ongoing with 860 self-reported CRC and 318 self-reported aerodigestive cancer diagnoses to date. Complete data are available on 155 individuals with a self-report of a new CRC diagnosis and 63 individuals with a self-report of aerodigestive cancer. Abstraction confirmed 47% (n=73) of those reported as true CRC diagnoses. Participants were better at correctly reporting at least one aerodigestive cancer (73%, n=46). Discussion and Conclusions: Patient reported medical record validation poses a unique challenge in today’s world. The process of requesting participant authorization followed by institutional requests to release the medical records to the research team is slow and painstaking. We found that patients are able to correctly report their mt-sDNA tests but found a relatively low proportion of reported cancer diagnoses reported correctly. This underscores the need to continue to validate key outcomes rather than relying solely on participant responses. As the number of outcomes validated increases, the study team will look at a variety of social and economic factors to better understand what contributes to or hinders an accurate self-report. Citation Format: Emily J. Kirsch, Jessica A. Grimm, Shawn M. Stoddard, Winnie Z. Fan, Kandace A. Bohn, Kathleen J. Yost, Lila J. Finney Rutten, Janet E. Olson. Patient reported outcome validation within the Voyage Study cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7354.

Abstract Glioblastoma (GBM), the most aggressive primary brain tumor in adults, presents significant challenges due to its universal recurrence and limited survival rates, exacerbated when proximal to the lateral ventricles (LV). The subpopulation of brain tumor-initiating cells (BTICs) plays a pivotal role in tumor initiation and invasiveness, interacting with the microenvironment, particularly the cellular components in the subventricular zone (SVZ). Some mechanisms of intercellular communication present in the SVZ include paracrine, autocrine, direct cell contact, gap junctions, nanotubes, and more recently extracellular vesicles (EVs). EVs are membrane-bound particles released by cells that are central to intercellular communication. They have the ability to carry bioactive proteins, RNA, and other molecules that influence recipient cell behavior.This study investigates the role of EVs in GBM's communication with non-cancer cells. Our findings indicate that BTIC-derived EVs promote migration and proliferation (*p < 0.02, ****p <0.001) in neural progenitor cells (NPCs) in vitro, highlighting the EVs' role in altering the microenvironment. To identify the protein cargo contained in GBM-derived EVs, we utilized the innovative proximity-labeling system TurboID. We successfully induced TurboID expression in primary-cultured human BTICs from GBM patients, enabling the unbiased biotinylation of proteins in EVs. We isolated biotinylated proteins from BTIC lysates and BTIC-EVs, preserving the integrity of EVs, and conducted proteomic analysis via mass spectrometry. Our method marks the first implementation of TurboID for unbiased global labeling of EV protein cargo in primary GBM cells. This approach facilitates the investigation of EV-mediated communication and potential therapeutic targets, contributing to the understanding of GBM's complex interactions with the brain's microenvironment and the identification of biomarkers for improved diagnosis and treatment response. Citation Format: Marissa Russo, Emily Norton-Ramos, Maria Jose Ulloa Navas, Alfredo Quinones-Hinojosa, Hugo Guerrero-Cazares. Elucidating glioblastoma-derived extracellular vesicle cargo using TurboID: Implications for tumor microenvironment adaptation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6579.

Abstract Introduction: The standard of care for metastatic hormone-sensitive prostate cancer (mHSPC) has evolved with the expanded approval of androgen receptor pathway inhibitors (ARPIs) alongside androgen deprivation therapy (ADT). ADT alone has been shown to affect cognitive function. However, the cognitive impact of distinct treatment combinations remains unclear. We investigated the association between first-line systemic treatments and the trajectory of subjective cognitive function among mHSPC survivors in the International Registry for Men with Advanced Prostate Cancer (IRONMAN). Methods: This analysis included 2435 newly diagnosed mHSPC patients enrolled across 15 countries between July 2017 and August 2024. Treatments were reported by site personnel and physicians. For this analysis, we focused on first-line systemic treatment and classified treatment groups at enrollment as ADT monotherapy (referent), ADT + ARPIs, or ADT + chemotherapy. Subjective cognitive function was assessed via the EORTC QLQ-C30 Cognitive Function subscale, with patient-reported scores (range 0-100) collected at enrollment and every 3 months for up to 5 years; higher scores reflect better cognitive function. Associations were estimated using linear mixed effects models with clustering by study site and country to examine differences at enrollment and across trajectories of subjective cognitive function by first-line treatment, adjusting for demographic and clinical factors. Results: Median age at enrollment was 70 years, with a median follow-up of 1.7 years. 724 (30%) participants were treated with ADT monotherapy, 1317 (54%) with ADT + ARPIs, and 394 (16%) with ADT + chemotherapy. Mean cognitive function scores at enrollment were 85.4 (Standard Deviation [SD] 19.5) for participants treated with ADT monotherapy, 86.7 (SD 17.3) for ADT + ARPIs, and 86.7 (SD 18.0) for ADT + chemotherapy. Cognitive function scores decreased by -0.60 points (95% Confidence Interval [CI] -0.72, -0.48) per year among those treated with ADT monotherapy, with similar rates observed for those treated with ADT + chemotherapy. Participants treated with ADT + ARPIs had a slower decline in cognitive function, with scores decreasing by -0.36 points (95% CI -0.60, -0.08) per year. Conclusion: In this international cohort of mHSPC survivors, subjective cognitive function scores were generally high at enrollment but declined over time. There was no evidence of worse cognitive function in those treated with ADT + ARPIs nor ADT + chemotherapy over time compared to ADT monotherapy. Cognitive functioning is a key component of survivorship, and defining cognitive trajectories associated with first-line treatment can inform supportive interventions, patient treatment decision-making, and clinical guidelines. Citation Format: Michelle O. Sodipo, Alicia K. Morgans, Erica T. Warner, Emily M. Rencsok, Lauren E. Howard, Colleen B. McGrath, Anna Siefkas, Konrad H. Stopsack, Christopher Sauer, Robert Drecier, Emilio Esteban, Hassan M. Dogo, Ademola Popoola, Charles Waihenya, Anders Bjartell, Kim Chi, Sebastien Hotte, Richard Cathomas, Deborah Enting, Scott Tagawa, Michael Ong, David Lorente, Elisabeth Heath, Rana McKay, Stefanie Fischer, Heather H. Cheng, Young E. Whang, Frederic Pouliot, Simon Crabb, Monica Chatwal, Miguel A. Climent, Raymond McDermott, Ian D. Davis, Camille Ragin, Folakemi Odedina, Natalie Greaves, Simone Badal, Simon Anderson, Sharon Harrison, Karen Autio, Laurel Cannon, Marie Grant, Alyssa Chan-Cuzydlo, Travis Gerke, Hannah D. McManus, Philip W. Kantoff, Daniel George, Sebastien Haneuse, Lorelei A. Mucci, on behalf of the IRONMAN Registry. First-line therapies and subjective cognitive function trajectories among international metastatic hormone-sensitive prostate cancer survivors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3630.

Abstract Introduction: The binding of Programmed Death-Ligand 1 (PD-L1) on the surface of tumor cells to PD-1 on T cells prevents T-cell-mediated anti-cancer immune responses. Immune checkpoint blockades that target the PD-L1/PD-1 interaction have improved survival rates but have several critical limitations. Post-translational modifications (PTMs) of PD-L1, such as glycosylation, are crucial for its stability and engagement with PD-1. Thus, targeting PD-L1 PTMs may be a novel method to improve immune checkpoint blockade efficacy. The mevalonate pathway (MVP) generates various substances involved in PTMs process. Here, we explore the effect of MVP in altering the PTMs of PD-L1 and its impacts on cell surface PD-L1 function. Methods: The triple-negative human breast cancer (TNBC) cell lines MDA-MB-231 and BT549 were treated with the HMG-CoA reductase inhibitor lovastatin (LOV) with or without the addition of IFN-γ and/or MVP intermediates for 48 hours. PD-L1 transcription was evaluated by qPCR. Alterations in PD-L1 size were detected by Western blotting. PD-L1 surface levels were measured by flow cytometry. HMG-CoA reductase (HMGCR) knockdown was performed to validate the non-off-target effect of LOV. The binding of PD-1 protein to the cell surface PD-L1 was measured by PD-1/PD-L1 binding assay. PD-L1 glycosylation levels were measured by Concanavalin A (Con A) lectin binding assay with immunoprecipitated PD-L1 protein. Results: LOV treatment caused a significant molecular weight shift of PD-L1 from approximately 45 kDa to 40 kDa and reduced the cell surface PD-L1 levels. However, PD-L1 transcription was not affected by LOV. HMGCR knockdown produced similar changes, indicating LOV's impact on PD-L1 was not due to off-target effects. The addition of MVP intermediates mevalonate (MEV) or geranylgeraniol, but not farnesol prevented LOV-induced changes in PD-L1 molecular weight and surface levels. Interestingly, the addition of 25-hydroxycholesterol, but not dolichol, partially prevented LOV-induced decreases in PD-L1 surface levels. Geranylgeranyl transferase inhibitor GGTI-286, which prevents protein geranylgeranylation, also altered PD-L1 molecular weight and decreased surface levels. In addition, LOV impaired the binding of PD-1 protein to tumor cells' surface PD-L1, which was reversed by the addition of MVP substrate MEV. Con A lectin-binding of immunoprecipitated PD-L1 showed that the LOV did not reduce the N-glycosylation level of PD-L1. Conclusions: This study reveals the involvement of the MVP in regulating PD-L1 PTMs and highlights the MVP as a potential therapeutic target to modulate PD-L1’s molecular weight and function and improve the efficacy of immunotherapy interventions, presenting a promising avenue for further investigation. Citation Format: Ruoheng Zhang, Emily J. Koubek, Jessie L. Reed, Jeffrey D. Neighbors, Joel M. Reid, Raymond J. Hohl. The role of the mevalonate pathway in post-translational modifications of PD-L1 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4265.

Abstract Breast cancer risk assessment tools are widely used in clinical practice to guide decisions regarding screening timing and modality, lifestyle interventions, genetic testing, preventive therapy, and risk-reducing surgery. Although a number of tools designed for the general population are used in practice, they face a series of challenges including: (i) modest discriminatory ability due to lack of a unified model that flexibly incorporates a comprehensive set of risk factors; (ii) inability to produce subtype-specific risk estimates, relevant for tailoring screening and/or preventive strategies (e.g. prophylactic endocrine therapy that is effective only for hormone receptor positive tumors); (iii) lack of data from diverse populations to build models that work well for all women; and, (iv) scarcity of opportunities for comparative validation of different models. The Breast Cancer Risk Prediction Project (BCRPP), a collaboration currently including 20 prospective cohorts from the National Cancer Institute’s Cohort Consortium, is addressing these challenges by harmonizing, sharing, and analyzing data on over 1.8 million women, over 115, 000 of whom have developed breast cancer. The BCRPP is developing a comprehensive tool that will predict breast cancer risk, overall and by subtypes, across major racial and ethnic groups in the United States. This tool incorporates known and emerging risk factors (e.g. reproductive history, anthropometry, smoking, alcohol intake, medication use, mammography, family history, and measured genotypes). In parallel to model building and validation efforts, BCRPP investigators are developing privacy-preserving web and mobile interfaces to deliver the risk tools to patients and clinicians. Here we present descriptive data on participating cohorts (e.g. dates of enrollment, ages at enrollment, length of follow up, numbers of cases by subtype), summarize missing data patterns and our approach to model development and validation that accounts for heterogeneity in missingness patterns across cohorts, and describe data governance procedures and data sharing infrastructure (including pooled and federated analyses, to account for policy limitations on sharing individual data). Descriptive information and procedures for requesting and accessing data are available via the BCRPP data platform (https://epidataplatforms.cancer.gov/bcrpp/). Although originally assembled for risk model development, these data on a large and diverse sample of women with extensive harmonized risk factors and covariates can be a resource to address other outstanding questions in breast cancer epidemiology across time, the lifecourse, and diverse populations. Citation Format: Peter Kraft, Laura Beane-Freeman, Julie Palmer, Ellen O'Meara, Jeanine Genkinger, James Lacey, Thomas Rohan, Lauren Teras, Marian L. Neuhouser, Kala Visvanathan, Celine Vachon, Roger Milne, Christopher Haiman, Yu Chen, Heather Eliassen, Cari Kitahara, Katie O'Brien, Emily White, Garnet Anderson, I-Min Lee, Archie Campbell, Renee Fortner, Ylva Lagerros, Sven Sandin, Mia Gaudet, Montserrat Garcia-Closas, Nilanjan Chatterjee. The Breast Cancer Risk Prediction Project: a resource of 1.8 million women with diverse backgrounds from 20 prospective cohorts to improve breast cancer risk prediction and advance breast cancer epidemiology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3583.

OBJECTIVE This study aimed to develop an artificial intelligence (AI) model for automatically detecting Hounsfield unit (HU) values at the L1 vertebra in preoperative thoracolumbar CT scans. This model serves as a screening tool for osteoporosis in patients undergoing spine surgery, offering an alternative to traditional bone mineral density measurement methods like dual-energy x-ray absorptiometry. METHODS The authors utilized two CT scan datasets, comprising 501 images, which were split into training, validation, and test subsets. The nnU-Net framework was used for segmentation, followed by an algorithm to calculate HU values from the L1 vertebra. The model’s performance was validated against manual HU calculations by expert raters on 56 CT scans. Statistical measures included the Dice coefficient, Pearson correlation coefficient, intraclass correlation coefficient (ICC), and Bland-Altman plots to assess the agreement between AI and human-derived HU measurements. RESULTS The AI model achieved a high Dice coefficient of 0.91 for vertebral segmentation. The Pearson correlation coefficient between AI-derived HU and human-derived HU values was 0.96, indicating strong agreement. ICC values for interrater reliability were 0.95 and 0.94 for raters 1 and 2, respectively. The mean difference between AI and human HU values was 7.0 HU, with limits of agreement ranging from −21.1 to 35.2 HU. A paired t-test showed no significant difference between AI and human measurements (p = 0.21). CONCLUSIONS The AI model demonstrated strong agreement with human experts in measuring HU values, validating its potential as a reliable tool for automated osteoporosis screening in spine surgery patients. This approach can enhance preoperative risk assessment and perioperative bone health optimization. Future research should focus on external validation and inclusion of diverse patient demographics to ensure broader applicability.