Sato, Kazuhiro

Abstract Multiple Myeloma (MM) is a hematologic malignancy marked by uncontrolled clonal expansion of plasma cells. Previous research has examined single-cell transcriptome profiles of Monoclonal gammopathy of undetermined significance (MGUS) and MM tumor microenvironment (TME) and found that natural killer (NK) cell abundance is elevated in the early stages and correlated with altered chemokine receptor expression. This study suggested the critical role of immune cells on myeloma progression from asymptomatic MGUS to symptomatic MM. Up to date, however, there are no published studies comprehensively comparing tumor and immune populations differences between MM NON-progressors (NPs) and FAST-progressors (FPs) and investigating how clonal plasma cells affect disease progression in a large cohort. Therefore, understanding how tumor and immune cells influence disease progression within symptomatic MM is of great interest.Here, we subjected CD138-negative Bone Marrow Mononuclear cells (BMMC) samples from 418 MM patients to scRNA-seq. From MMRF CoMMpass study (NCT01454297), we also have whole exome sequencing (WES) and bulk RNA-seq from CD138-positive fraction of BMMC samples. Based on time to progressive disease (TTPD), we classified patients into 2 categories. Patients with TTPD less than 18 months were classified as FAST-progressors (FPs), whereas patients with TTPD more than 5 years were classified as NON-progressors (NPs). By analyzing patient genomic alterations and its association with progression, we found that there was a significant association of slow MM progression with t(11;14) (p = 0.048), consistent with previous study. In our preliminary analysis, we profiled 83 CD138-sorted MM bone marrow samples using scRNA-seq. Interestingly, we found plasma cells from samples with the same genetic alterations tend to cluster together, highlighting the important role of genetic drivers in transcriptome profiles of plasma cells. Moreover, integrated analysis of bone marrow samples from 83 MM patients and 4 healthy donors revealed an atypical naïve-B cell subset with enrichment of cells from fast-progressors and partial expression of MS4A1. Differentially expressed genes for this naïve-B cell subset includes KLF9, BCL2L11, JOSD1, and IRS2, etc. Overall, as part of MMRF immune profiling research, this study will help to interrogate how genetic alterations and disease progression interplay MM tumor and TME and provide a sufficiently broad and valuable dataset for systematically characterizing MM at single-cell resolution. Hopefully, this study could identify novel targets for MM immunotherapies, and ultimately identify patients with high risk of fast progression for early intervention in the clinic. Citation Format: Lijun Yao, Tianjiao Wang, Kazuhiro Sato, Reyka Jayasinghe, I-Ling Chiang, Darwin D'souza, William Pilcher, Edgar Gonzalez-Kozlova, Yered Pita-Juarez, Taxiarchis Kourelis, Deon Bryant Doxie, Beena Thomas, Brian Lee, Swati Sharma Bhasin, Upadhyaya Bhaskar, Mark Fiala, Julie Fortier, Travis Dawson, John Leech, Shaji Kumar, Hearn Cho, Seunghee Kim-Schulze, Bee Raj, Stephen Oh, the MMRF Immune Profiling Research Team, John Dipersio, Ravi Vij, Adeeb Rahman, Ionnis Vlachos, Shaadi Mehr, Mark Hamilton, Daniel Auclair, Surendra Dasari, David Avigan, Madhav Dhodapkar, Sacha Gnjatic, Manoj Bhasin, Li Ding. Single-cell transcriptome profiling of multiple myeloma bone marrow samples suggests that disease progression interplays with tumor and tumor microenvironment in The MMRF CoMMpass Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1729.

Abstract Multiple Myeloma (MM) is the second most common hematologic malignancy, marked by uncontrolled clonal expansion of plasma cells. MM genome is complex and heterogeneous, with a high frequency of structural variants (SVs) and copy-number abnormalities (CNAs). Single-cell sequencing technologies offer advantages over traditional bulk methods in cancer genomics research for evaluating cellular heterogeneity and investigating evolution of cellular subpopulations within the tumor. Thus, there is an impetus to translate the growing understanding of the genomic landscape of MM into dissecting the tumor heterogeneity using scRNA-seq. So far, there are no reported studies systematically comparing tumor and immune populations differences between MM NON-progressors (NPs) and RAPID-progressor (RPs) and investigating how clonal plasma cells contribute to progression in a large cohort. In addition, the bone marrow microenvironment plays an important role in the evolution of premalignant MM and MM progression. A previous study of single-cell transcriptomics analysis of Monoclonal gammopathy of undetermined significance (MGUS) and MM tumor microenvironment (TME) revealed that natural killer (NK) cell abundance is frequently increased in the early stages and associated with altered chemokine receptor expression. This study shed the light on the role of immune cells on disease progression from asymptomatic MGUS to symptomatic MM. However to date, how immune cells influence disease progression within symptomatic MM is still unclear. Here, we subjected 344 CD138-negative Bone Marrow Mononuclear cells (BMMC) samples to scRNA-seq. To control for the first line therapy, 272 patients were treated with RVD and Autologous stem cell transplant (ASCT) and were stratified into 3 groups based on progression: 200 NON-progressors (NPs) (PFS> 5 years), 7 Intermediate Progressors (IPs, PFS 2-4 years) and 38 RAPID-progressors (RPs) (PFS<=18 months). In addition, there are 72 subjects treated with RVD but without ASCT, including 34 NPs, 2 IPs and 36 RPs. From MMRF CoMMpass study (NCT01454297), we also have whole exome sequencing (WES) and bulk RNA-seq from CD138-positive fraction of BMMC samples. Our preliminary analysis of scRNA-seq of 6 samples treated by the same first-line therapies (RVD but without ASCT) revealed that plasma cells (PCs) from two patients (MMRF2550 and MMRF2562) with chromosome 13q deletion clustered together, whereas PCs from a patient (MMRF2187) with t(8;14) Myc translocation formed a distinct cluster. Interestingly, PCs from a patient (MMRF2271) with both chromosome 13q deletion and t(8;14) formed another independent cluster. These observations highlight the important role of genetic drivers in transcriptome profiles of plasma cells. In addition, we further investigated how progression features correlate with the immune microenvironment and identified differentially expressed genes between NK cells from RPs versus those from NPs, which could potentially serve as MM progression markers. Interestingly, several cytotoxicity genes are significantly upregulated in FPs, such as GZMB and KLRB1 (log Fold Change=1.44, and 8.41 respectively). Overall, our preliminary results provide a small glimpse of the interconnected nature of driver genetic alterations and progression features in MM tumor and TME. This study will provide a sufficiently broad, deep, and diverse vast dataset for accurately characterizing MM at single-cell resolution to help interrogate how genetic alterations and disease progression interplay MM tumor and TME. We hope this study could identify novel candidate targets for therapeutic approaches, and ultimately stratify patients by risk of progression for early intervention in the clinic. Disclosures Kumar: Roche-Genentech: Consultancy, Research Funding; Merck: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Novartis: Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Carsgen: Research Funding; Bluebird Bio: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Tenebio: Research Funding; BMS: Consultancy, Research Funding; Antengene: Consultancy, Honoraria; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Oh: Abbvie: Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Membership on an entity's Board of Directors or advisory committees; Celgene Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Constellation: Membership on an entity's Board of Directors or advisory committees; CTI Biopharma: Membership on an entity's Board of Directors or advisory committees; Disc Medicine: Membership on an entity's Board of Directors or advisory committees; Geron: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees; Kartos Therapeutics: Membership on an entity's Board of Directors or advisory committees; PharamaEssentia: Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Membership on an entity's Board of Directors or advisory committees. Vij: BMS: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; BMS: Honoraria; GSK: Honoraria; Oncopeptides: Honoraria; Karyopharm: Honoraria; CareDx: Honoraria; Legend: Honoraria; Biegene: Honoraria; Adaptive: Honoraria; Harpoon: Honoraria. Avigan: Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Kite Pharma: Consultancy, Research Funding; Juno: Membership on an entity's Board of Directors or advisory committees; Partner Tx: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Aviv MedTech Ltd: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Legend Biotech: Membership on an entity's Board of Directors or advisory committees; Chugai: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Parexcel: Consultancy; Takeda: Consultancy; Sanofi: Consultancy.