-Author name in bold denotes the presenting author
-Asterisk * with author name denotes a Non-ASH member
Clinically Relevant Abstract denotes an abstract that is clinically relevant.

PhD Trainee denotes that this is a recommended PHD Trainee Session.

Ticketed Session denotes that this is a ticketed session.

648 In-Depth Characterization of the High Risk-Associated Tumor Immune Landscape in Multiple Myeloma

Program: Oral and Poster Abstracts
Type: Oral
Session: 652. Multiple Myeloma: Clinical and Epidemiological: Novel Biomarkers for Treatment Guidance in Multiple Myeloma
Hematology Disease Topics & Pathways:
Research, clinical trials, adult, Translational Research, epidemiology, Clinical Research, health outcomes research, bioinformatics, Diseases, Adverse Events, computational biology, survivorship, Myeloid Malignancies, Technology and Procedures, profiling, Study Population, Human
Sunday, December 10, 2023: 5:45 PM

Yered Pita-Juarez, PhD1*, Dimitra Karagkouni2*, Edgar Gonzalez-Kozlova3*, Yuling Ma4*, Lijun Yao5*, William Pilcher6*, Beena Thomas, PhD7,8*, Alessandro Lagana, PhD9, Sarthak Satpathy10*, Swati Bhasin, PhD7,8, Yizhe Song11, Ravi Vij, MD, MBA12, Darwin D'Souza13*, Travis Dawson, PHD13*, Geoffrey Kelly13*, Jessica Wendy Schulman, BSc14*, Shaji Kunnathu Kumar, MD15, David Avigan, MD16, Seunghee Kim-Schulze, PhD17*, Li Ding, PhD18*, Hearn Jay Cho, MD19, Taxiarchis Kourelis, MD15, Eva Lepisto, MSc, MA14*, Manoj Bhasin, PhD6,10, April Cook14*, Mark Hamilton, PhD20*, George Mulligan, PhD14, Immune Network21*, Ioannis Vlachos, PhD4* and Sacha Gnjatic22*

1Pathology, Beth Israel Deaconess Medical Center, Boston, MA
2Broad Institute of MIT and Harvard, Cambridge, MA
3MSSM, New York
4Department of Pathology, Cancer Research Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
5WUSTL, Saint Louis
6Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA
7Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta, Atlanta, GA
8Department of Pediatrics, Emory University, Atlanta, GA
9Department of Medicine, Hematology and Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York
10Department of Biomedical Informatics, Emory University, Atlanta, GA
11WUSTL, St Louis, MO
12Division of Oncology, Washington University School of Medicine, Saint Louis, MO
13Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY
14MMRF, Norwalk, CT
15Division of Hematology, Mayo Clinic, Rochester, MN
16Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
17Department of Immunology & Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, NY
18WUSTL, St Louis
19Department of Medicine, Hematology and Medical Oncology, Tisch Cancer Institute, Tisch Cancer Institute, New York, NY
20Multiple Myeloma Research Foundation, Norwalk, CT
21MMRF, Norwalk
22Icahn School of Medicine at Mount Sinai, New York, NY


Newly-diagnosed multiple myeloma (MM) patients often share tumor genetic abnormalities associated with a high risk of progression and poor survival. We hypothesized that single-cell transcriptomic characterization of the tumor immune microenvironment (TIME) may be combined with tumor-based risk stratification to uncover novel disease biology mechanisms associated with clinical outcomes and improve risk stratification.


We performed single-cell RNA sequencing of 361 CD138 negative sorted bone marrow mononuclear cells (BMMCs) samples from 263 MM patients enrolled at time of diagnosis in the Multiple Myeloma Research Foundation CoMMpass study (NCT01454297). Specimens were analyzed at baseline (n=263) across a network of five collaborating academic research centers following assay harmonization. Genetic factors that determine risk were defined as one or more of the following gain- or loss-of-function events derived from baseline genomic sequencing data: del17p14, translocations of the Ig locus with the MAF/A/B or WHSC1/MMSET/NSD2 loci, and gain of chromosome 1q21. Statistical modeling strategies were used to assess single-cell populations or RNA signatures associations with known risk factors or disease progression (FDR<0.05).


The study generated high-quality single-cell profiles of 731,643 cells from 123 high-risk and 107 standard-risk MM patients based on genetics. Based on distinct transcriptome profiles, BMMCs formed 106 clusters corresponding to 5 major compartments: NK and T cells, B cells, erythrocytes, myeloid cells, and plasma cells. Our preliminary differential abundance analysis comparing high- vs standard-risk patients at baseline uncovered significant differences in the TIME associated with genetic risk. The high-risk group was identified as enriched in effector CD8+, and CD4+ T cells. In contrast, the high-risk group exhibited depletion of naive CD8+ and interferon-associated CD4+ and CD8+ T as compared to the standard-risk group. Within subclusters in the T and NK cells compartment, a higher cytotoxicity signature was observed in high-risk patients, characterized by the expression of granzymes and perforin. Finally, our preliminary survival and progression analysis associated a higher frequency of IDO1-expressing macrophages in worst progression patients, while better outcomes were associated with CD8+ T and B cells expressing androgen response and IL6/STAT3/EMT programs, respectively.


Current approaches for risk stratification are based on bulk measurements of tumor’s genetic or epigenetics features, which do not capture the diversity and dynamics of the TIME. Through single-cell transcriptomics, we were able to capture, in high granularity, the TIME and correlate specific immune cell populations and phenotypes with relapse risk and poor prognostic outcomes. These results suggest that immune subpopulations may be an essential novel aspect for improving current risk stratification models.

Disclosures: Bhasin: Anxomics LLC: Current Employment, Current equity holder in private company. Vij: Takeda: Honoraria, Research Funding; Janssen: Honoraria; Pfizer: Honoraria; Karyopharm: Honoraria; Harpoon: Honoraria; Legend: Honoraria; Sanofi: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria, Research Funding. Avigan: Paraxel: Current Employment; Celgene: Consultancy, Other: Advisory role, Research Funding; Kite/Gilead: Consultancy, Other: Advisory role, Research Funding; Chugai Pharma: Consultancy, Other: Advisory role; Karyopharm Therapeutics: Consultancy, Other: Advisory role; Juno Therapeutics: Consultancy, Other: Advisory role; Legend Biotech: Consultancy, Other: Advisory role; Takeda: Consultancy, Other: Advisory role; Bristol-Myers Squibb: Consultancy, Other: Advisory board; Aviv Med Tech: Consultancy, Other: Advisory board; Partner Therapeutics: Consultancy, Other: Advisory board; Janssen: Consultancy, Other: Advisory board; Sanofi: Consultancy, Other: Advisory board; Kowa Pharmaceutical: Consultancy, Other: Advisory board; Pharmacyclics: Research Funding; Kite, a Gilead Company: Research Funding. Cho: Bristol Myers-Squibb: Research Funding; Takeda, Inc.: Research Funding. Gnjatic: Boehringer-Ingelheim: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Research Funding; Regeneron: Research Funding; Takeda.: Research Funding; Genentech,: Research Funding.

<< Previous Abstract | Next Abstract
*signifies non-member of ASH