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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.

In this article, we present a flexible model for microbiome count data. We consider a quasi‐likelihood framework, in which we do not make any assumptions on the distribution of the microbiome count except that its variance is an unknown but smooth function of the mean. By comparing our model to the negative binomial generalized linear model (GLM) and Poisson GLM in simulation studies, we show that our flexible quasi‐likelihood method yields valid inferential results. Using a real microbiome study, we demonstrate the utility of our method by examining the relationship between adenomas and microbiota. We also provide an R package “fql” for the application of our method.

7501 Background: In patients (pts) with R/R CLL/SLL that progressed on BTKi and failed venetoclax (ven)-based regimens, achieving CR with current treatment is uncommon. New therapies that achieve deep and durable responses are needed. We report the primary analysis of the phase 1/2, single-arm, multicenter TRANSCEND CLL 004 (NCT03331198) study evaluating liso-cel in pts with R/R CLL/SLL. Methods: Pts must have received at least 2 prior lines of therapy, including a BTKi. Eligible pts received liso-cel at a target dose of either 50 (DL1) or 100 (DL2) × 106 CAR+ T cells. The primary endpoint was rate of CR and CR with incomplete marrow recovery (CRi) by IRC per 2018 iwCLL criteria in the prespecified subset of efficacy-evaluable pts with disease progression on BTKi and ven failure (primary efficacy analysis set [PEAS]) at DL2 (null hypothesis [H0]: ≤ 5%). Key secondary endpoints were ORR (H0: ≤ 40%) and rate of undetectable minimal residual disease (uMRD; 10−4) in blood (H0: ≤ 5%). Results: Of 137 leukapheresed pts, 117 received liso-cel (safety set), 96 (DL1 = 9; DL2 = 87) were efficacy evaluable, and 53 (DL1 = 4; DL2 = 49) were in the PEAS. In the safety set, median (range) age was 65 y (49–82), 83% had high-risk features, median (range) lines of prior therapy was 5 (2–12), and all pts had prior BTKi. Median (range) on-study follow-up was 21.1 mo (0.4–55.6) for the safety set. In the PEAS at DL2, the primary endpoint of CR/CRi rate was met at 18.4% (95% CI, 8.8–32.0; 1-sided P = 0.0006; Table). ORR was 42.9% and was not statistically significant (95% CI, 28.8–57.8; 1-sided P = 0.3931). The uMRD rate was 63.3% in blood and 59.2% in marrow. Median (95% CI) DOR was 35.3 mo (11.01–not reached [NR]) with a median follow-up of 19.7 mo. Median duration of CR/CRi was NR. In the safety set, rate of any-grade CRS was 84.6% (gr 3, 8.5%; no gr 4/5) and neurological events (NE) was 45.3% (gr 3, 17.9%; gr 4, 0.9%; no gr 5); 69.2% received tocilizumab and/or corticosteroids for CRS/NEs. Rate of gr ≥ 3 infections, hypogammaglobulinemia, and prolonged cytopenia was 17.1%, 15.4%, and 53.8%, respectively. One death related to liso-cel was due to hemophagocytic lymphohistiocytosis. Liso-cel exhibited rapid in vivo expansion and was detected by qPCR in blood up to 36 mo after infusion. Conclusions: Liso-cel demonstrated durable CR/CRi, high uMRD rates, and a manageable safety profile in pts with heavily pretreated, high-risk R/R CLL/SLL and high unmet need. Clinical trial information: NCT03331198 . [Table: see text]