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D’souza, Darwin

https://orcid.org/0000-0002-1943-5173

Mayo Clinic

Icahn School of Medicine at Mount Sinai

Citations 5

Daratumumab-based quadruplet therapy in functional high-risk relapse/refractory multiple myeloma patients induces changes associated with CD8 T cell signaling, activation and expansion
D’souza, Darwin , Hamilton, Mark , Chen, Zhihong , Cho, Hearn, Kumar, Shaji , Mulligan, George, Acharya, Chaitanya R. , Jayasinghe, Reyka G. , Foltz, Steven , Kim-Schulze, Seunghee

Blood | December 4, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 3955-3955

10.1182/blood-2025-3955 Get It

Abstract Background: The Multiple Myeloma Research Foundation (MMRF) and its partners launched the MyDRUG platform clinical trial (NCT03732703) to evaluate the safety and efficacy of genomically-guided treatments for functional high-risk relapsed/refractory myeloma patients (fHRMM). fHRMM patients with no discernible activating mutations and who had received 1-3 prior therapies (exposed to at least one proteasome inhibitor and an IMiD) were given a combination of daratumumab (D), ixazomib (I), pomalidomide (P) and dexamethasone (d) (D-IPd) quadruplet therapy. The goal of this study is to evaluate the immunomodulatory effects of daratumumab-(anti-CD38)-based therapy on fHRMM patients enrolled in the MMRF-sponsored MyDRUG umbrella clinical trial over the duration of therapy and to correlate immune changes with patient response immediately following the first two cycles of therapy. Methods Bone marrow (BM) aspirates were collected at baseline (BL) prior to therapy, at the end of 2 cycles (EOC2), 4 cycles (EOC4) of the quadruplet therapy and at the end of treatment (EOT) or progressive disease (PD). CD138-negative bone marrow mononuclear cells were isolated for profiling the immune microenvironment using scRNAseq, scTCRseq and CyTOF. Results Single-cell RNA and TCR profiles were generated from ~90,000 cells across 41 samples from 16 subjects. scRNAseq identified CD3+ T cells, NK cells, classical and non-classical monocytes and B cells. CD8+ T cells were further resolved into their subsets including precursor (TPEX) and terminally exhausted T cells (TEX) within the bone marrow microenvironment. Within the CD8+ T cell compartment, an expansion of the effector memory (TEM) cell population was observed following 2-cycles of therapy (EOC2). However, this TEM expansion was not sustained at timepoint EOC4. Towards the end of therapy, enrichment of precursors to putative exhausted and terminal dysfunctional effector memory cells (TEMRA) was observed. Subjects with partial (PR), very good partial (VGPR) and complete (CR) best overall responses showed an initial increase in TEM cells followed by a slow expansion of TEX and TEMRAcells over time. One patient with progressive disease (PD) maintained the highest LAG3 expression across the cohort among CD8 T cell subsets (TEMRA, EM) and CD4 Tregs at baseline while observing a significant upregulation of PDCD1 in CD4 Tregs and CD8 Naive cells by EOC2. Cell-cell communication network analysis identified secreted ligands between responders (CR/VGPR) and partial responders (PR) at EOC2. Samples with PR exhibited upregulation of signaling of TNF from the CD8 Naïve compartment (p=0.048, Wilcoxon), IFNG from the CD8 EM (p=0.073, Wilcoxon) and TEMRA (p=0.048, Wilcoxon) populations along with IFNG (p=0.073, Wilcoxon) from NK cells. CD14+ and CD14+16+ Monocytes on the other hand showed enrichment of LGALS9 (p=0.03 (CD14+), p=0.048 (CD14+CD16), Wilcoxon) in the PR group at EOC2 relative to responders. Finally, longitudinal tracking of T cell clonality showed preferential progressive expansion of TEMRA cells after the therapy. We mapped hyperexpanded (more than 16 copies) clonotypes, presumed to be tumor-reactive, to various CD8+ T cell subsets. These hyperexpanded clonotypes are mapped to the TEMRA, TEX and TEM CD8+ T cells. Analysis of TCR repertoires clonality and diversity also demonstrated a reduced richness and increased clonality of CD8+ TCRs in responders. Summary/Conclusion These preliminary analyses of D-IPd quadruplet therapy of RRMM indicate that paired single cell RNA and TCR sequencing of BM T cells suggests a selective expansion of clonotypic CD8+ T cells. When considering patient response, the only PD patient profiled in this study maintained an exhaustive signature (LAG3, PDCD1) in multiple T cell compartments at BL. The differential expression of the receptor ligand pairs after treatment between different clinical response groups suggests an altered TME response that may inform future therapeutic stratification. These results support further explorations of rational combinations of targeted and immune therapies for greater efficacy in this disease.
Abstract 5258: The immunomodulatory effects of daratumumab-based therapy on functional high-risk relapse/refractory multiple myeloma (fHRMM) patients enrolled in the MyDRUG trial
D’souza, Darwin , Hamilton, Mark , Zhihong, Zhihong, Kumar, Shaji, Mulligan, George, Acharya, Chaitanya R. , Jayasinghe, Reyka G. , Kim-Schulze, Seunghee , Cho, Hearn Jay , Kumar, Shaji

Cancer Research | April 21, 2025 | Volume: 85 | Issue: 8_Supplement_1 | Pages: 5258-5258

10.1158/1538-7445.am2025-5258 Get It

Abstract Background: The goal of this study is to evaluate the immunomodulatory effects of daratumumab-(anti-CD38)-based therapy on fHRMM patients enrolled in the MMRF sponsored MyDRUG umbrella clinical trial (NCT03732703) over the duration of therapy and to correlate immune changes with patient response. Methods: fHRMM who had received 1-3 prior therapies (exposed to at least one proteasome inhibitor and an IMiD) were given a combination of daratumumab (D), ixazomib (I), pomalidomide (P) and dexamethasone (d) (D-IPd) quadruplet therapy. Bone marrow (BM) aspirates were then collected from patients prior to therapy (BL), after 2 cycles (EOC2), after 4 cycles (EOC4) of the quadruplet therapy and at the end of treatment or disease progression (EOT). Immune and tumor fractions were enriched by CD138 selection. Here, CD138- bone marrow mononuclear cells were isolated and transcriptionally profiled by scRNAseq and scTCRseq. Results: Single-cell RNA and TCR profiles were generated from ∼90,000 cells across 41 samples from 16 subjects. scRNAseq identified CD3+ T cells, NK cells, classical and non-classical monocytes and B cells. CD8+ T cells were further resolved into their subsets including precursor (TPEX) and terminally exhausted T cells (TEX) within the bone marrow microenvironment. Within the CD8+ T cell compartment, an expansion of the effector memory (TEM) cell population was observed following 2-cycles of therapy (EOC2). However, this TEM expansion was not sustained at timepoint EOC4. Towards the end of therapy, enrichment of precursors to exhausted and terminal dysfunctional effector memory cells (TEMRA) was observed. Subjects with partial (PR), very good partial (VGPR) and complete (CR) best overall responses showed an initial increase in TEM cells followed by a slow expansion of TEX and TEMRA cells over time. Longitudinal tracking of T cell clonality showed preferential progressive expansion of TEMRA cells after the therapy. We mapped hyperexpanded (more than 16 copies) clonotypes, presumed to be tumor-reactive, to various CD8+ T cell subsets. These hyperexpanded clonotypes mapped to the TEMRA, TEX and TEM CD8+ T cells. Analysis of TCR repertoires clonality and diversity also demonstrated a reduced richness and increased clonality of CD8+ TCRs in responders. Conclusions: Paired single cell RNA and TCR sequencing of BM T cells from RRMM patients receiving D-IPd quadruplet therapy revealed a selective expansion of clonotypic CD8+ T cells with a clonal replacement of BM exhausted clonotypes by dysfunctional circulating CD8+ T cells in responders over time. Citation Format: Chaitanya R. Acharya, Darwin D'souza, Reyka Jayasinghe, Mark Hamilton, Zhihong Zhihong, Seunghee Kim-Schulze, Hearn J. Cho, Shaji Kumar, George Mulligan. The immunomodulatory effects of daratumumab-based therapy on functional high-risk relapse/refractory multiple myeloma (fHRMM) patients enrolled in the MyDRUG trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5258.
In-Depth Characterization of the High Risk-Associated Tumor Immune Landscape in Multiple Myeloma
Karagkouni, Dimitra , Thomas, Beena , Song, Yizhe , Vij, Ravi , D’souza, Darwin , Dawson, Travis , Kelly, Geoffrey , Kumar, Shaji , Avigan, David , Ding, Li , Kourelis, Taxiarchis , Lepisto, Eva M. , Cook, April , Hamilton, Mark , Mulligan, George, Network, Immune, Vlachos, Ioannis S. , Gnjatic, Sacha , Gnjatic, Sacha , Song, Yizhe , Vlachos, Ioannis S , Pita-Juárez, Yered , Gonzalez‐Kozlova, Edgar , Ma, Yuling , Yao, Lijun , Pilcher, William , Thomas, Beena, Lagana, Alessandro , Satpathy, Sarthak , Bhasin, Swati S. , Schulman, Jessica , Kim-Schulze, Seunghee , Cho, Hearn Jay , Bhasin, Manoj K , Cook, April

Blood | December 1, 2023 | Volume: 142 | Issue: Supplement 1 | Pages: 648-648

10.1182/blood-2023-189940 Get It

Introduction 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. Methods 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). Results 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. Conclusions 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.
Comprehensive Characterization of the Multiple Myeloma Immune Microenvironment Using Integrated scRNA-seq, CyTOF, and CITE-seq Analysis
Jayasinghe, Reyka G. , Lee, Brian , Bhasin, Swati S. , Pilcher, William , Dasari, Surendra , Fiala, Mark A. , Pita-Juárez, Yered , Strausbauch, Michael, Kelly, Geoffrey , Thomas, Beena , Kumar, Shaji , Anderson, Emilie, Wendl, Michael C. , Dawson, Travis , D’souza, Darwin , Cheloni, Giulia , Li, Ying , Dhodapkar, Kavita M. , Vij, Ravi , Vlachos, Ioannis S. , Mehr, Shaadi , Hamilton, Mark , Auclair, Daniel , Kourelis, Taxiarchis , Avigan, David , Dhodapkar, Madhav V. , Gnjatic, Sacha , Ding, Li , Jayasinghe, Reyka G , Bhasin, Swati S , Pilcher, William , Dasari, Surendra , Fiala, Mark A , Pita-Juarez, Yered , Kumar, Shaji K , Dawson, Travis , Oh, Stephen T , Li, Ying , Rahman, Adeeb H , Dhodapkar, Kavita M , Hamilton, Mark , Auclair, Daniel , Dhodapkar, Madhav V , Gnjatic, Sacha , Bhasin, Manoj K , Ding, Li , Vlachos, Ioannis S , Yao, Lijun , Doxie, Deon Bryant , Gonzalez‐Kozlova, Edgar , Thomas, Beena E., Cho, Hearn Jay , Oh, Stephen T. , DiPersio, John F. , Kim-Schulze, Seunghee

Cancer Research Communications | August 31, 2022 | Volume: 2 | Issue: 10 | Pages: 1255-1265

10.1158/2767-9764.crc-22-0022 Get It

As part of the Multiple Myeloma Research Foundation (MMRF) immune atlas pilot project, we compared immune cells of multiple myeloma bone marrow samples from 18 patients assessed by single-cell RNA sequencing (scRNA-seq), mass cytometry (CyTOF), and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to understand the concordance of measurements among single-cell techniques. Cell type abundances are relatively consistent across the three approaches, while variations are observed in T cells, macrophages, and monocytes. Concordance and correlation analysis of cell type marker gene expression across different modalities highlighted the importance of choosing cell type marker genes best suited to particular modalities. By integrating data from these three assays, we found International Staging System stage 3 patients exhibited decreased CD4+ T/CD8+ T cells ratio. Moreover, we observed upregulation of RAC2 and PSMB9, in natural killer cells of fast progressors compared with those of nonprogressors, as revealed by both scRNA-seq and CITE-seq RNA measurement. This detailed examination of the immune microenvironment in multiple myeloma using multiple single-cell technologies revealed markers associated with multiple myeloma rapid progression which will be further characterized by the full-scale immune atlas project. Significance: scRNA-seq, CyTOF, and CITE-seq are increasingly used for evaluating cellular heterogeneity. Understanding their concordances is of great interest. To date, this study is the most comprehensive examination of the measurement of the immune microenvironment in multiple myeloma using the three techniques. Moreover, we identified markers predicted to be significantly associated with multiple myeloma rapid progression.
Abstract 1729: 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
Sato, Kazuhiro , Chiang, I-Ling, D’souza, Darwin , Kourelis, Taxiarchis , Thomas, Beena , Lee, Brian , Upadhyaya, Bhaskar , Fortier, Julie M. , Dawson, Travis , Kumar, Shaji , Cho, Hearn, Raj, Bee, Vij, Ravi , Vlachos, Ionnis, Mehr, Shaadi , Hamilton, Mark , Auclair, Daniel , Dasari, Surendra , Avigan, David , Dhodapkar, Madhav V. , Ding, Li , Yao, Lijun , Wang, Tianjiao , Jayasinghe, Reyka G. , Pilcher, William , Gonzalez‐Kozlova, Edgar , Pita-Juárez, Yered , Doxie, Deon Bryant , Thomas, Beena, Bhasin, Swati S. , Fiala, Mark A. , Leech, John M. , Kim-Schulze, Seunghee , Oh, Stephen T. , DiPersio, John F. , Rahman, Adeeb H , Gnjatic, Sacha , Bhasin, Manoj K

Cancer Research | June 15, 2022 | Volume: 82 | Issue: 12_Supplement | Pages: 1729-1729

10.1158/1538-7445.am2022-1729 Get It

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.