Citations

Abstract Introduction: Diffuse large B-cell lymphoma (DLBCL) is the most common type of malignant lymphoma. Previous studies have shown that DLBCL cells are susceptible to GPX4 (Glutathione peroxidase 4)-regulated ferroptosis, an iron-dependent type of programmed cell death characterized by increased reactive oxygen species and excessive lipid peroxidation. In addition to GPX4, FSP1 (Ferroptosis suppressor protein 1, previously known as AIFM2) is a glutathione-independent repressor of ferroptosis that has shown prognostic significance in solid tumors. In this study, we aimed to reveal the significance of GPX4 and FSP1 in DLBCL. Patients and Methods: We performed immunohistochemistry (IHC) for GPX4 and FSP1 in a large cohorts of patients with de novo DLBCL, and evaluated their cytoplasmic and nuclear expression. Prognostic analysis was performed for FSP1 and GPX4 expression in patients treated with rituximab (R)-CHOP or CHOP chemotherapy, respective of TP53 mutation status, as p53 regulates ferroptosis and TP53 mutation is associated with poorer prognosis in DLBCL. Results: FSP1 expression with a ≥10% cutoff was positive in 42.3% of DLBCL cases. Patients with TP53 mutations had a non-significant trend of higher mean FSP1 expression than those with wild-type (Wt) TP53 (P=0.11). Prognostic analysis revealed that cytoplasmic FSP1+ expression was associated with significantly poorer overall survival and progression-free survival in Wt-TP53 DLBCLs treated with R-CHOP (P=0.016 and P=0.003, respectively), and only showed non-significant unfavorable trends in TP53 mutated DLBCLs and patients treated with CHOP. In contrast, GPX4 expression did not show a significant unfavorable prognostic effect in DLBCL, and in fact, was associated with a non-significant trend of better survival. Previously we have quantified immune cell abundance and PD-1/PD-L1 expression in the tumor microenvironment of the study cohort using multiplex fluorescent IHC. Correlative analysis found that FSP1+ patients had significantly higher mean and median abundance of CD68+ cells (both M1 and M2 macrophages) and CD11c+ cells than FSP1- patients. Further analysis in Wt-TP53 and mutated TP53 subcohorts found that only in the TP53 mutated DLBCL subcohort, FSP1 expression was associated with significantly higher mean and median CD163-CD68+ (M1) and overall CD68+ macrophages, whereas in the Wt-TP53 DLBCL subcohort, FSP1 expression was associated with significantly higher median (but not mean) CD163+CD68+ (M2) macrophages and CD11c+ cells. Summary: Cytoplasmic FSP1 expression but not GPX4 had significantly adverse prognostic effect in patients with Wt-TP53 DLBCL treated with standard immunochemotherapy. Our results also suggest that in addition to ferroptosis regulation, macrophage abundance was relevant for the prognostic effects of FSP1 expression. Citation Format: Beibei Lyu, Zijun Xu-Monette, Xiaoxian X. Zhao, Eric D. Hsi, Ming Chen, Carlo Visco, Alexandar Tzankov, Karen Dybkaer, Mu-En Wang, Chang Wang, Qingyan Au, Harry Nunns, Zenggang Pan, Benjamin Parsons, Santiago Montes-Moreno, Fenghuang Zhan, Michael B. Møller, Leon Bernal-Mizrachi, Youli Zu, Shanxiang Zhang, Weina Chen, Govind Bhagat, Yong Li, KEN H. YOUNG. Expression of the ferroptosis suppressor FSP1 but not GPX4 shows significant adverse prognostic effect in diffuse large B-cell lymphoma with wild-type TP53 [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 4661.

Abstract Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with individual cancer risk, and polygenic risk scores (PRS) are typically derived from these cancer-specific variants. Although previous pan-cancer studies revealed shared genetic architectures across cancer types, latent factors contributing to cancer risk have not been explored. This may allow for improved prediction of cancer risk based on a latent cancer factor which leverages shared variants across cancers. Here, we conducted an integrative pan-cancer GWAS across seven solid tumors (breast, ovarian, endometrial, pancreatic, lung, colorectal, melanoma) to identify shared latent genetic factors and novel pleiotropic variants. We curated the most recent and large-scale GWAS summary statistics to maximize statistical power, comprising 398,917 cases and 1,501,715 controls of European ancestry. Shared genetic structures among 6,346,960 common variants were evaluated using Genomic Structural Equation Modeling (GenomicSEM). Three latent factors (Common Cancer Factor, Female-Specific Cancer Factor and Non-Sex Specific Cancer Factor) were constructed, and associations of individual variants with each latent factor were estimated. Genome-wide significant loci (p < 5x10-8) were functionally annotated and subjected to pathway enrichment analysis. Models capturing shared genetic risk across cancers fit the data well. A single “Common Cancer Factor” explained much of the shared risk (SRMR = 0.064 [lower is better], CFI = 0.938 [closer to 1 is better]), and a correlated two-factor model—distinguishing female-specific from other cancers—showed even stronger fit and biological relevance (SRMR = 0.055, CFI = 0.988). The one-factor (Common Cancer Factor; SRMR: 0.064, CFI: 0.938, AIC: 54.7, p_chisq: 0.021) and the two-factor (Female-Specific Cancer Factor and Non-Sex Specific Cancer Factor; SRMR: 0.055, CFI: 0.988, AIC: 45.4, p_chisq: 0.281) models demonstrated robust model fit and biological relevance. Factor-specific GWAS identified 233 genome-wide significant loci (p < 5x10-8) with 24 distinct loci showing shared susceptibility across cancers. More importantly, we identified eight novel variants that were not previously reported or related with any cancer risk, potentially regulating cancer-related genes such as PRC1, CEBPB, SMC2, KLF5 and ATXN2. Further analyses are needed to elucidate their roles in tumorigenesis. Our findings reveal a shared genetic architecture across major solid tumors and uncover novel pleiotropic variants with potential regulatory roles in oncogenesis. This study provides novel insights into the genetic basis of cancer susceptibility and supports the development of multi-cancer PRS to improve prediction in cancer prevention and prognosis. Citation Format: Xunxuan Chen, Gamaliel T. Taengwa, Brandon J. Coombes, Stacey J. Winham. Pan-cancer genome-wide study reveals shared genetic architecture and novel pleiotropic variants across seven solid cancers [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 3600.

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.