Mulligan, George J.

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: Multiple myeloma is the second most common adult blood cancer and remains incurable, despite recent advances. The IMWG/IMS recently published updated risk criteria, Consensus Genomic Staging (CGS), combining genomic events with clinical measures to identify high-risk patients (Avet-Loiseau, et al. JCO 2025). We applied CGS risk criteria to baseline samples from the Multiple Myeloma Research Foundation CoMMpass Study (NCT01454297), a prospective, longitudinal observational study that enrolled more than1100 participants between 2011-2017. Methods: We assessed patient risk following CGS criteria. Criteria 1: del(17p), with a cutoff of >20% clonal fraction, and/or TP53 mutation. Criteria 2: an IgH translocation including t(4;14), t(14;16), or t(14;20) along with 1q+ and/or del(1p32). Criteria 3: monoallelic del(1p32) along with 1q+ or biallelic del(1p32). Criteria 4: beta-2 microglobulin >= 5.5 mg/L with normal creatinine. Patients meeting one or more criteria were classified as High Risk. To test if risk showed association with genetic ancestry, we grouped patients into those with high African genetic ancestry and those with low African genetic ancestry. Genetic ancestry was measured using ADMIXTURE in comparison to 1000 Genomes. Results: We evaluated the CGS risk status of 877 CoMMpass patients, finding 69.2% (573/828) to be Standard Risk (SR) and 30.8% (255/828) to be High Risk (HR). HR patients showed worse progression-free survival (median PFS 26.3 months vs. 42.5 months; log rank test, p < 0.0001) and overall survival (median OS 63.9 months vs. median not reached; p < 0.0001). 10.6% (91/858) of patients met Criteria 1, 10.7% (93/873) met Criteria 2, 5.6% (49/877) met Criteria 3, and 8.7% (73/835) met Criteria 4. We found 14.2% (123/867) of patients to have high African-like genetic ancestry (AFR-high) and 85.8% (744/867) to have low African-like genetic ancestry (AFR-low). We observed significantly fewer HR patients within the AFR-high group (20%, 23/115) than in the AFR-low group (32.4%, 231/712) (Fisher’s exact test, p = 0.0065). The AFR-high group met HR criteria at a lower rate across all criteria, but only with Criteria 3 was the difference significant (p-value = 0.03). Higher levels of creatinine in AFR-high patients may have impacted meeting the normal creatinine requirement of Criteria 4. Conclusions: HR patients comprise 30.8% of CoMMpass subjects and show significantly worse PFS and OS than SR patients. AFR-high patients met HR criteria at a lower rate than AFR-low patients according to the CGS criteria. Clinical trials that utilize CGS criteria to determine patient eligibility may be challenged to enroll a representative patient population, including AFR-high patients. Screening and eligibility criteria should be carefully considered to mitigate potential enrollment disparities. Citation Format: Steven M. Foltz, Chaitanya R. Acharya, Alexander Gout, Yuxin Jin, David E. Avigan, Ravi Vij, Shaji Kunnathu Kumar, Sagar Lonial, Hearn Cho, Katie Wozniak, Jonathan J. Keats, Craig Cole, John D. Carpten, George J. Mulligan. Multiple myeloma risk classification of CoMMpass using Consensus Genomic Staging identifies differences between patients with high and low African genetic ancestry [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 3887.