Citations

Abstract Background: Mantle cell lymphoma (MCL) is an aggressive and rare B-cell non-Hodgkin lymphoma with poor prognosis, even with treatment. Despite its clinical importance, the etiology of MCL remains largely unknown. Some studies have reported a positive association with family history, suggesting that genetic factors could contribute to risk. Methods: To identify germline genetic variants associated with risk, we conducted the first genome-wide association studies (GWAS) and GWAS meta-analysis for MCL, comprising 1,163 cases and 61,271 controls. The most significant loci were taken forward for replication in three independent studies, including 576 cases and 771,773 controls. To identify potential target genes and pathways of discovered loci, we conducted F-MAGMA, colocalization, and transcriptome-wide association study (TWAS) analyses. To gain insight into underlying regulatory mechanisms, we performed integrative epigenomic analyses using DNase I hotspots and histone mark ChIP-seq data across diverse cell types applying the FORGE2 framework. Results: In the joint analyses, we identified eight genome-wide significant loci (P<5x10-8) associated with MCL risk, several of which were located near genes with known DNA repair (ATM), telomere (TERT), or RNA-binding functions (RBM20). Further analyses using F-MAGMA, which uses DNase-seq data to prioritize genes from GWAS, identified genes that were significantly associated with risk, including SP140, a chromatin reader and immune regulator of pathogen response. This gene also displayed strong colocalization with our lead variant in whole blood (COLOC posterior probability PP4=0.97). TWAS demonstrated significant associations with SP140 and ACTA2, which has been linked to cell proliferation (P<3x10-6). Enrichment for DNase I hotspots was observed in B and T lymphocytes (q-value<0.05), providing evidence for a role in immune cell-specific regulatory regions. Enrichment for enhancer-associated histone mark H3K4me1 was observed in B cells (q-value<0.01), highlighting a role for immune cell-specific enhancers. Transcription factor (TF) motif enrichment analysis pointed to TFs critical for B-cell development and differentiation, notably TCF3 and EP300 (q<0.01 for both), suggesting an association between B-cell lineage regulation and MCL risk. Finally, genome-wide SNP-based heritability was estimated to be 17%, underscoring the importance of common variants in MCL risk. Conclusion: Our study provides novel insight into the inherited susceptibility of MCL by identifying eight significant loci and estimating substantial common variant heritability. These findings highlight a role for several distinct biological pathways -specifically DNA repair, telomerase function, and B-cell differentiation- in the etiology of MCL, offering new targets for mechanistic investigation. Citation Format: Charles E. Breeze, Alyssa Clay-Gilmour, Hanla A. Park, Ólafur B. Davíðsson, Angelica Macauda, Brenda M. Birmann, Elizabeth E. Brown, Murat Güler, Michelle A. T. Hildebrandt, Alexandra Nieters, Krystle Ong, Jojo Biel-Nielsen Dietz, Karin E. Smedby, Karl Smith-Byrne, Rosalie Griffin, Sophia S. Wang, Susan Slager, James R. Cerhan, Jonathan N. Hofmann, Qing Lan, Nathaniel Rothman, Ingrid Glimelius, Henrik Hjalgrim, James Mckay, Sonja I. Berndt. Genome-wide association study of mantle cell lymphoma identifies novel loci suggesting a critical role for B-cell chromatin readers and DNA repair mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3602.

Abstract Background. Genome-wide association studies (GWAS) have identified 35 genetic susceptibility single-nucleotide polymorphisms (SNPs) for multiple myeloma (MM) in individuals of European ancestry (EA) and shown strong genetic correlation between MM and its precursor, monoclonal gammopathy of undetermined significance (MGUS). We evaluate the contribution of the 35 MM variants to MGUS susceptibility overall and by prognostic subgroups. Methods. The study included 20,756 participants (14,486 controls, 1,883 with MGUS, and 2,163 with MM) from the Mayo Clinic. Logistic regression assuming an additive model estimated odds ratios (ORs) and 95% confidence intervals (CIs) for individual SNPs and for the MM-PRS, adjusted for age, sex, study, and principal components. The PRS was a weighted sum of 35 SNPs with effect estimates from the largest MM GWAS and was modeled continuously (per SD) and by quintiles (Q1-Q5). SNPnexus annotated variants that replicated in MGUS (P < 0.05 and OR > 1.01) versus those that did not (P > 0.05 and OR < 1.01). Results. The 35-SNP MM-PRS was strongly associated with MM risk and modestly with MGUS. Compared with the middle quintile (Q3), MM odds rose from OR=0.55 (CI=0.46-0.65, P=2.2e-11) in Q1 to OR = 1.82 (CI=1.59-2.09, P=6.2e-18) in Q5. MGUS showed a similar, attenuated pattern (Q1 OR = 0.74, CI=0.64-0.84, P=6.4e-6 / Q5 OR=1.36, CI=1.21-1.53, P=3.4e-7). Each SD increase in PRS corresponded to OR=1.52 (CI=1.45-1.59, P=1.3e-66) for MM and OR = 1.22 (CI=1.18-1.27, P=1.0e-23) for MGUS. Higher PRS values were linked to larger M-protein ((0.1-1.5 g/dL: OR=1.40, CI=1.18-1.65, P=5.8e-12) vs <0.1 g/dL: OR = 1.19, CI=1.13-1.24, P=5.8e-12)) and abnormal free light chain (FLC) ratio ((OR = 1.33, CI=1.21-1.46, P=1.0e-9) vs normal ratio (OR=1.19, CI=1.14-1.25, P=1.4e-13)). Ten risk loci replicated in MGUS, mapping to genes involved in plasma-cell function, immune regulation, and DNA repair and enriched for Rho GTPase signaling, NF-κB-mediated apoptosis, and RNA polymerase II transcription, implicating early plasma-cell activation and transcriptional control. The 12 non-replicating loci, including PHC3, ATG5, and NFIC, mapped to genes involved in chromatin remodeling, autophagy, and SUMOylation, suggesting roles in stress response and genomic maintenance. Conclusions. The MM-PRS captures shared heritability between MM and MGUS and correlates with MGUS subtype and severity. Replicating variants highlight immune and cell-cycle pathways relevant to MGUS onset, whereas non-replicating loci cluster in DNA-repair and stress-response processes, underscoring their potential role in progression. Citation Format: Alyssa Ione Clay-Gilmour, Angelica Macauda, Cristine Allmer, Danelle Moonen, Aaron D. Norman, Nicholas Boddicker, Janet E. Olson, Elizabeth E. Brown, Vincent S. Rajkumar, Esteban Braggio, David Murray, Susan Slager, Shaji Kunnathu Kumar, Celine Vachon. Implications of multiple myeloma polygenic risk scores (PRS) for MGUS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3603.

Abstract Background: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide. Prognostic models for HCC primarily rely on tumor burden and liver function, with limited consideration of inherited genetic contributions to survival variability. Identifying germline variants associated with survival could refine prognosis and reveal biological mechanisms underlying disease progression. Methods: We conducted a genome-wide association study (GWAS) of overall survival among 864 patients with HCC from the M.D. Anderson Cancer Center cohort. Genotyping, quality control, and imputation procedures followed previously described protocols (PMID: 38381705). Associations between genetic variants and overall survival were assessed using Cox proportional hazards models adjusted for age, sex, and the first five principal components. Genome-wide significance was defined as P < 5×10-8. Functional annotation and pathway enrichment analyses (MAGMA) were employed to investigate the biological relevance of the identified loci. Results: After quality control, 8,525,017 single-nucleotide polymorphisms (SNPs) were analyzed. We identified seven new loci associated with HCC survival at the genome-wide significance level. Five out of seven loci are associated with anthropometric traits and hematological measurement traits, reflecting metabolism, hematopoiesis, immune function, and inflammation. A variant in the 3′ untranslated region (UTR3) of STX7 showed a genome-wide significant association with overall survival (HR = 3.23; P = 2.56 ×10-8). Carriers of the risk allele had significantly shorter survival times compared with noncarriers. Pathway analysis revealed enrichment in biologically relevant processes, including liver growth and regeneration (growth hormone and Interleukin-6 (IL-6) signaling pathway), implicating hepatocyte proliferation and IL-6/STAT3-mediated inflammatory signaling. Immune-related pathways, such as regulation of T cell activation and myeloid leukocyte migration, highlight the role of germline variation in immune surveillance. Moreover, pathways governing vascular remodeling and metabolic stress response (e.g., JAK activation, mitochondrial dynamics) suggest that inherited determinants of microenvironmental structure and hepatocyte resilience influence patient outcomes. Conclusion: This germline GWAS of HCC survival identifies seven new genome-wide significant loci and implicates pathways involved in liver regeneration, inflammation, and tissue remodeling. These findings support a role for inherited genetic variation in shaping HCC prognosis and underscore the potential of integrating germline genetics into prognostic modelling and therapeutic target discovery. Citation Format: Younghun Han, Jinyoung Byun, Lewis R. Roberts, Katherine A. McGlynn, Manal M. Hassan, Christopher I. Amos. Identification of survival-associated germline variants in hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3606.

Abstract Introduction: COE has become the gold standard in addressing health disparities. COE’s value is emphasized by NIH and leading cancer-related organizations e.g., AACR. The Alliance for COE (The Alliance) mission is to advance the art, science, and impact of COE; promote community health and wellness; and reduce cancer burden and disparities. Methods: This abstract builds on the Alliance’s Science of Community Outreach and Engagement (SoCOE) Conference a NCI R13 funded series. SoCOE Conference is organized by 10 NCI-designated Cancer Centers to provide a platform for COE academic-clinical-policy-community stakeholders to share best practices for solution-focused community responsive cancer prevention, diagnostics, therapeutics and survivorship research and practice. Results: > 500 researchers, clinicians, policymakers, healthcare administrators, with >12% being survivors and/or advocates, participated in our SoCOE Conferences. The delegates’ recommendations are: Decentralize who/entities that hold all the power in science and clinical research (trials). Communities hold valuable, necessary wisdom and resources to inform and guide science Include multisectoral partners early and always Community capacity building and compensation with gratitude Mentoring of junior COE researchers, clinicians, policymakers, healthcare administrators, survivors and advocates with humility is a must Develop virtual communities to share best practices across cancer centers and within regions Develop working groups to identify and explore commonalities across COE work in rural/urban, diverse/homogenous spaces Publish Science of COE papers on various topics related to COE Frameworks and evidenced-solutions Provide community reports on best practice guide that can be widely available to be shared locally and in-person, and digitally Partner and learn from COE teams working with other cultural/ethnic groups Attend to, measure and remedy societal/social drivers of health disparities that mirror barriers to care, and research engagement and participation. Discussion: Informed by our community advisory boards and the findings for our SoCOE Conferences, we present the pillars of the Alliance to tackle population cancer burden and disparities: Training future COE leaders/advocates, Advocating for public health policies/guidelines, Increasing access to cancer prevention and care that will also increase access to studies, Engaging and partnering with multisectoral stakeholders and communities, Building community capacity, Advancing COE science through catchment-relevant research, and Leading bi-directional communication and information and resource sharing between catchment area communities and cancer centers. The expectation and impact of COE can only be achieved if COE teams are valued, supported cancer center members with community advisory boards and community as cancer centers’ priority population. Citation Format: Kimlin Ashing, CHARNITA ZEIGLER-JOHNSON, Hayley S. Thompson, Kim Rhoads, Nadine Barrett, Lisa Carter Bawa, Timiya S. Nolan, Monica Baskin, Vanessa B. Sheppard, Marvella E. Ford, Erica Phillips, Lorna H. McNeill, Folakemi T. Odedina. Advancing the science, practice and impact of COE [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7577.

Abstract Background: Prostate cancer (PCa) is the leading cause of cancer-related deaths globally and disproportionately affects men of African ancestry. African men often present at younger ages and with more aggressive disease, and approximately half of the PCa risk has been attributed to genetic factors. Africa is the most genetically diverse region of the world, and even within the continent, populations show important differences in allele frequencies and patterns of pathogenic variation. Despite this diversity, African men remain underrepresented in genomic studies, creating significant gaps in knowledge that limit precision medicine efforts. Methods: A total of 182 prostate cancer patients were recruited from teaching hospitals in Benin, Côte d’Ivoire, Ghana, Kenya and Nigeria. 50 cancer susceptibility genes using the Aviseq ONCO50 panel and the Illumina MiSeq platform. Variant calling was performed using an in-house Snakemake workflow, followed by additional bioinformatic steps to distinguish true PMS2 variants from PMS2CL-related artifacts. Pathogenicity assessment relied on annotations from ClinVar and LOVD databases. Results: Pathogenic and likely pathogenic variants were detected in 31.3% of the study group identified in 26 genes. The five most frequently altered genes were RAD50, PTCH1, MSH6, MUTYH, and NF1. Nigerian patients accounted for 52.6 percent of all pathogenic variants, with recurrent alterations observed in MSH6, MUTYH, NF1, and PTCH1. In contrast, pathogenic BRCA1 and BRCA2 variants were observed primarily in patients from Kenya, Benin, and Côte d’Ivoire. Several frameshift, nonsense, and splice-site variants identified in this study have not been previously reported in African populations.[SR1] Conclusion: This study provides one of the most detailed assessments of inherited cancer susceptibility gene variants in African PCa patients. The findings reveal substantial regional variation in the spectrum of pathogenic variants and highlight population-specific genomic signatures that may contribute to the unequal burden of PCa in men of African ancestry. These data emphasize the importance of expanding genomic research efforts within Africa to strengthen precision oncology and reduce global PCa disparities. Citation Format: Abimbola F. Onyia, Freeman Okwuchi, Opeyemi C. De Campos, Sylvester Divine, Olutola Olasehinde, Ayinde Yahaya, Ayo Salako, Aminu Zakari, Iya Bassey, Nicholas Titiloye, Bernard Petershie, Isidore GANDAHO, Luc Brun, Tore Sanni, Safiatou Coulibaly, Noel Coulibaly, Michael Fakayode, Coulibaly Issoufou, Valérie Gbonon, Kouame Benjamin, Yao Evrard, Peter Coleman, Ayun Cassell, Victor Ajumbo, Lilac Wattanga, Benson Ochieng Nyambega, Folakemi T. Odedina, Solomon Rotimi. Targeted sequencing of common cancer susceptibility genes reveals germline variants in African prostate cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6289.

Abstract Background: Accurate staging is essential for treatment selection, prognosis assessment, and trial eligibility. While prior studies attempted automating pathological (p) staging, few address clinical (c) staging and no studies have compared LLM-derived staging with clinician staging during clinical visit and retrospective cancer registry staging. Methods: We developed a multi-agent framework using Gemini-2.0-Flash-001 and GPT-5 to (1) identify reports (2) extract key data, and (3) apply AJCC 8th edition staging criteria. LLM staging was compared with clinician documentation and registry staging in breast cancer patients. Clinician-registry agreement served as the reference standard. Two independent breast oncologists reviewed discordant cases. Results: We analyzed 122 randomly selected breast cancer patients across all three Mayo Clinic sites from 2018 - 2023. LLM performance matched or exceeded human inter-rater agreement for pathological staging (95-99.2% vs. 95-98.4%). Clinical staging was more challenging, with LLM concordance of 73-77.9% for cT and 87-89.3% for cN versus 87.8% and 91.0% clinician-registry agreement. Among 89 patients with clinician-registry concordance, LLM concordance was 98.9% for pT/pN, 79.8% for cT, and 91.0% for cN. Experts favored LLM staging in 27.8% (5/18) of cT and 25.0% (2/8) of cN discordances. Error analysis revealed LLM challenges in handling non-mass enhancements (6 cases), selecting radiologic measurements (2 cases), identifying discrete masses (2 cases), and miscellaneous (3 cases). Conclusion: LLMs achieved human-level performance for pathological staging (98%), supporting human-in-the-loop deployment. For clinical staging (79.8% cT, 91.0% cN), future work must enhance multimodal reasoning and integrate physical examination data. Prospective validation is needed to assess real-world impact. With targeted refinements and oversight, automated staging can transform registry workflows while augmenting clinical decision-making. Citation Format: Arshad Mohammed, Umair Ayub, Pooja Advani, Shakeela W. Bahadur, Amye J. Tevaarwerk, Tufia C. Haddad, Elisabeth I. Heath, Brenda J. Ernst, Ben Zhou, Cui Tao, Sara J. Holton, Karthik V. Giridhar, Irbaz B. Riaz. Automating clinical and pathological staging for breast cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2744.

Abstract The CoMMpass study (NCT01454297) is a prospective, longitudinal observational study involving 1,141 newly diagnosed multiple myeloma (NDMM) patients. Bone marrow aspirates from the study participants were collected for comprehensive molecular characterization of tumor (using bulk RNA sequencing and whole genome sequencing) and tumor immune microenvironment using 3’ single-cell RNA sequencing (scRNA-seq). To support exploration of this rich multi-omic dataset, we developed CoMMpass Explorer (CE), an intuitive interactive platform that enables real-time analysis of clinical and genomic data from CoMMpass. A central feature of CE is cohort building, where users can filter and stratify patients by clinical, genomic, and survival data elements to create custom cohorts for analysis. CE provides five main views: Overall Summary for clinical feature distribution, Kaplan-Meier curves, and multivariate Cox proportional hazards models; Mutational Profile for visualizing and comparing somatic mutations; Tumor Profile for bulk differential expression and gene set enrichment; Immune Microenvironment for comparing cell type abundance and cell cycle dynamics between cohorts using scRNA-seq data; and Pseudo-Bulk, which aggregates single-cell expression by cell type to enable cohort-level comparisons of transcriptional programs using DEseq2. CE reproduces prior CoMMpass studies, including WEE1 expression being associated with poorer progression-free survival (Simhal, et al.) and different mutation frequencies between African American and European American patients (Manojlovic, et al.). We further demonstrate CE’s utility by interrogating the 2025 Consensus Genomic Staging (CGS) risk classification system (Avet-Loiseau, et al). We compared CGS high-risk (HR, n=249) vs. CGS standard-risk (SR, n=573) patients. HR patients have significantly worse progression-free survival, overall survival, and time to second-line therapy compared with SR patients. Univariate models recapitulated expected differences in the clinical features that define CGS risk. Bulk tumor RNA-seq and ssGSEA highlighted a more proliferative and genomically unstable transcriptional program in HR group, with upregulation of angiogenesis and cell-cycle-related pathways. In the immune microenvironment, monocytes were more abundant in the SR group. Pseudo-bulk RNA-seq of plasma cells showed overexpression of ANXA1, NSD2, IGF1R, MAF and related genes in HR. CE democratizes access to the CoMMpass multi-omic resource, allowing researchers to interrogate clinical and molecular heterogeneity. By enabling hypothesis generation and replication of published results, CE serves as a valuable tool for identifying prognostic biomarkers and meaningful patterns in gene expression, mutation profiles, and the immune microenvironment. Citation Format: Wanxing Zhang, Chaitanya R. Acharya, Steven M. Foltz, David E. Avigan, Samir Parekh, Ravi Vij, Shaji Kunnathu Kumar, Taxiarchis Kourelis, Sagar Lonial, Hearn Cho, Ioannis S. Vlachos, Sacha Gnjatic, Li Ding, Manoj Bhasin, George Mulligan. CoMMpass Explorer: An interactive platform to explore clinical and genomic data from newly diagnosed multiple myeloma patients from the landmark CoMMpass observational study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5504.

Abstract Background: The increasing volume and diversity of clinical genomic reports pose a significant challenge across healthcare institutions for the interpretation and proper implementation of precision oncology research. Reports from multiple different vendors (e.g., Invitae, Ambry Genetics, Foundation Medicine) are typically PDFs and exhibit substantial heterogeneity in panel design, gene coverage, and reporting standards, which hinders efficient retrospective data mining and patient cohort identification within the electronic medical records. We sought to develop a framework to interrogate all of these reports. Methods: We extracted genomic reports from patients with breast cancer treated with neoadjuvant chemotherapy and developed MolHarmonizer, a novel, scalable framework leveraging Python and Gemini LLMs, designed to process and harmonize genomic data from disparate multi-vendor reports. Gemini LLMs are employed explicitly for robust information extraction, normalization, and structuring of key genomic features, transforming unstructured data into a unified, queryable dataset. Results: Our MolHarmonizer framework successfully processed 1,147 genomic reports from 1703 breast cancer patients (2006-2023) from 23 different companies, demonstrating robust capability to extract and standardize critical actionable biomarkers. Data sources included Invitae (n=554), Ambry Genetics (n=189), Natera (n=95), Mayo Clinic (n=88), Tempus (n=63), Guardant Health (n=47), and Foundation Medicine (n=37), with others contributing less than 20 reports. Of the samples, 827/1147 (72.1%) were germline (blood/saliva). A majority of the patients were tested using the panels due to a personal/family history (n=925). Overall, 413/1147 (36.0%) reports identified at least one mutation. For breast cancer, 75 reports showed BRCA1/2 mutations (37 BRCA1, 37 BRCA2, and one patient with both BRCA1 and 2). Other mutations identified included: PIK3CA (n=40), TP53 (n=96), PTEN (n=21), ESR1 (n=13) and AKT1/2 (n=8). Conclusion: MolHarmonizer, a powerful framework leveraging Gemini LLMs, effectively addresses genomic data heterogeneity by automating biomarker extraction and harmonization. This enables rapid cohort identification and deep retrospective analyses for clinical insights, biomarker discovery, understanding disease history, facilitating novel pattern discovery, e.g., predicting BRCA1 mutations from WSI, and accelerating research within our neoadjuvant BC cohort. Future plans include expanding to include over 20,000 breast cancer patients, developing a user-friendly chatbot, and ensuring inter-institutional adaptability for a variety of complex diseases. Citation Format: Krishna Rani Kalari, Xiaojia Tang, Thanmayee Boyapati, Tanya L. Hoskin, Sumathilatha Myla, Sumedha G. Penheiter, Richard M. Weinshilboum, Liewei Wang, Hamid R. Tizhoosh, Karthik Vikram Giridhar, Matthew P. Goetz, Judy C. Boughey. Development of an LLM framework for analysis of heterogeneous breast cancer patients genomic reports [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2756.

Abstract Introduction: The National Cancer Institute estimated almost 317,000 new breast cancer and over 13,000 new cervical cancer cases in 2025. While the National Breast and Cervical Cancer Early Detection Program has served millions of women over the past two decades, inequities in cancer screening, subsequently delayed diagnosis, and timely and appropriate treatment remain a public health challenge in the United States. Despite the substantial impact of social determinants of health (SDOH) on cancer screening, few studies have accounted for SDOH at the individual level when assessing breast and cervical cancer screening adherence. The primary objective of this study is to examine whether the individual-level SDOH, measured using HOUsing-based SocioEconomic Status (HOUSES) index, is associated with breast and cervical cancer screening non-adherence (not current on respective USPSTF recommendations for age and frequency). Methods: In this retrospective study, patients were identified as those receiving primary care in the Mayo Clinic Health System and Mayo Clinic (Rochester, MN). The Midwest Quality Metrics panel was then used to assess patients due for screening for breast or cervical cancer in July 2023. The HOUSES, using home address and publicly available data on the residence which measures and categorizes housing status into quartiles, was obtained using the electronic health records (EHRs)-linkable patient-level information. Logistic regression analyses were conducted, controlling for Census block group-level adverse social exposome from the Area Deprivation Index, age, and comorbidities. Results are presented as odds ratios (OR) with corresponding 95% confidence intervals (CI). Results: For breast cancer, among 128,462 eligible patients, 20.1% (n= 25,857) were non-adherent. Compared to the highest HOUSES quartile (Q4), lower HOUSES groups showed significantly higher odds of non-adherence: Q3 OR=1.20 (95% CI=1.15, 1.25), Q2 OR=1.45; (95% CI=1.40, 1.53), and Q1 OR=1.90 (95% CI=1.81, 1.99). For cervical cancer, among 175,712 eligible patients, 29.9% (n=52,533) were non-adherent. Compared to the highest HOUSES quartile (Q4), lower HOUSES groups showed significantly higher odds of non-adherence: Q3 OR=1.07 (95% CI=1.03, 1.10), Q2 OR=1.16; (95% CI=1.12, 1.20), and Q1 OR=1.36 (95% CI=1.31, 1.41). Conclusions: A clinically meaningful association between the HOUSES index and cancer screening adherence was observed. A lower HOUSES index was associated with higher odds of non-adherence for both breast and cervical cancer screening, even after accounting for neighborhood-level risk, age, and comorbidities. Incorporating HOUSES into EHRs can be a practical “screening-for-screening” tool that enables close monitoring of higher-risk patients without additional burden of surveys. Citation Format: Eunice Y. Park, Madison Beenken, Dave Watson, Chung Il Wi, Tufia Haddad, Gladys Asiedu, Karla BALLMAN, James R. Cerhan, Carolyn Flock, Brian Lynch, Folakemi T. Odedina, Scott H. Okuno, Young J Juhn, . HOUSES as a screening tool for cancer screening: Patient-level housing-based socioeconomic status and breast and cervical cancer screening adherence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7599.

Abstract Objectives Microscopic colitis (MC) is an inflammatory disease of the large intestine characterized by chronic diarrhea, normal‐appearing colonic mucosa on endoscopy, and abnormal inflammatory histopathology. While it is a common cause of chronic diarrhea in adults, MC is infrequently reported in children, and data on its presentation, treatment, and outcomes remain limited. This study aimed to analyze single‐center experience and conduct a literature review on pediatric MC. Methods A retrospective review of the Mayo Clinic electronic health records from 2013 to 2024 was performed. Children (≤18 years) diagnosed with MC were included. Demographics, clinical presentation, treatment, and outcomes were collected. A systematic review of pediatric MC literature was completed. Results MC was diagnosed in 42 children (median age 12.5 years; Q1–Q3 7.25–14.75), with 28 (67%) females. Systematic review identified 29 studies with 258 children with MC (mean age 10 years, standard deviation [SD] 4.9). At Mayo Clinic, treatment varied among providers, and budesonide as monotherapy or in combination was most effective. In the literature, the most commonly used treatments included 5‐aminosalicylates (5‐ASA, 36%) and budesonide (31.5%). Combination therapy with budesonide plus a biologic or mesalamine appeared to be the most effective therapy, followed by budesonide monotherapy and corticosteroids. Mucosal remission rate was highest with corticosteroids, followed by budesonide. Mean recurrence rate across all treatments was 69%. Biologics (vedolizumab, infliximab) and bismuth showed the lowest recurrence rates. Conclusion Budesonide, either alone or in combination, appears to be most commonly used and effective in treating pediatric MC, but recurrence rates remain high after therapy discontinuation.