Cho, Hearn Jay

Compared with traditional bulk sequencing technologies, single-cell technologies have advantages to evaluate cellular heterogeneity and investigate the evolution of cellular subpopulations from the tumor and microenvironment. Application of single-cell sequencing in Multiple Myeloma (MM) is especially beneficial given MM is a highly heterogeneous disease with uncontrolled clonal expansion of plasma cells. Single-cell RNA sequencing (scRNA-seq) has been previously utilized to understand this hematopoietic malignancy in both tumor and immune populations in MM (Ledergor G. et al., 2018, Zavidij, O. et al., 2020). Mass cytometry (CyTOF) has also been used to identify the expansion of novel memory B cells in MM. (Hansmann, L. et al., 2015). Among the various single cell techniques, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) is a multimodal approach with simultaneous quantification of single-cell transcriptomes and surface proteins. Since these three single-cell approaches enable the identification of cell types, cell states and characterization of cellular heterogeneity at transcriptomic and/or protein levels, understanding the concordance of the measurements among these three modalities is of great interest. We applied scRNA-seq, CyTOF and CITE-seq on four baseline samples of CD138-negative 'immune cell' fractions from patients enrolled in the MMRF CoMMpass study (NCT01454297). Two subjects were fast progressors (PFS < 18 months) and two subjects were non-progressors (PFS not reached). With multi-center collaboration coordinated by Multiple Myeloma Research Foundation (MMRF), each sample was subject to scRNA-seq and CyTOF by 3 independent centers. All sites received aliquots of the same sample. On average, 1,060 immune cells were detected in each sample using scRNA-seq and >64K CD45+ cells were detected using CyTOF. CITE-seq was performed in one center and 4,805 CD138-negative immune cells were identified on average. To compare cell type abundance between scRNA-seq, CyTOF and CITE-seq, we calculated the cell subset frequency of each immune population relative to the CD45+ populations. Overall, all three approaches were concordant while there is a stronger concordance between scRNA-seq and CyTOF. Cell type abundance is especially consistent for B cells, monocytes/macrophages, and plasmacytoid dendritic cells (pDC) among the 3 methods. For the same patient of interest, natural killer (NK) cell frequency was detected at the lowest level in CyTOF relative to scRNA and CITE-seq. The T cell population showed the highest discrepancy among techniques, with highest abundance in scRNA-seq followed by CyTOF and lowest abundance in CITE-seq. Interestingly, CITE-seq detected far less CD4 T cells compared to the other two techniques while CD8 T cell frequency did not show drastic differences. In addition to cell type abundance, we further examined the concordance of expression of cell type signature genes between scRNA-seq and CyTOF. Overall, expression between RNA-level and protein-level is positively correlated with typical cell type markers highly expressed in both techniques, especially in the following cell populations: CD8+ T cells (CD3, CD8), NK cells (CD56, GranzymeB/GZMB, NKG2A/KLRC1), B cells (CD19, CD38), Monocytes (CD14, CD11c/ITGAX, CD33). To note, although the concordance in CD4+ T cells is generally good, we found the expression of CD4 is higher in CyTOF compared to scRNA-seq whereas CD127/IL7R tends to be overexpressed in scRNA-seq. This could explain why IL7R is often identified as a differentially expressed gene (DEG) in CD4+ T cell population while CD4 is barely seen in DEG list in scRNA-seq analysis. It is also interesting to notice that the expression of most NK cell markers has strong concordance between scRNA-seq and CyTOF except NKG2D/KLRK1, which has much higher expression in CyTOF relative to scRNA-seq. Our preliminary results suggested good concordance of immune cell type abundance identified in CyTOF, scRNA-seq and CITE-seq as well as concordant expression of some canonical cell type markers between RNA level and protein level. This work provides the field with reference data sets and shows more detailed examination of NK and T cell subsets is needed when handling single cell sequencing with different modalities. Disclosures Dhodapkar: Roche/Genentech: Membership on an entity's Board of Directors or advisory committees, Other; Lava Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other; Kite: Membership on an entity's Board of Directors or advisory committees, Other; Janssen: Membership on an entity's Board of Directors or advisory committees, Other; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Other; Amgen: Membership on an entity's Board of Directors or advisory committees, Other. Kumar:MedImmune: Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Tenebio: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Genecentrix: Consultancy; Cellectar: Other; Dr. Reddy's Laboratories: Honoraria. Gnjatic:Neon Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; OncoMed: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Genentech: Research Funding; Immune Design: Research Funding; Agenus: Research Funding; Janssen R&D: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees. Bhasin:Canomiiks Inc: Current equity holder in private company, Other: Co-Founder.

TPS8057 Background: Multiple myeloma (MM) is the second most prevalent blood cancer, representing approximately 1% of all cancers. Although overall survival has improved in recent years due to new approved agents, the vast majority of MM patients (pts) ultimately stop responding to treatment. Moreover, about a quarter of MM pts characterized as “high risk” experience limited benefit from existing treatments. Seminal genomic sequencing research efforts, such as the MMRF CoMMpass study, have highlighted that a large number of MM cases harbor potentially actionable oncogenic molecular alterations and published reports on small numbers of cases suggest that Precision Medicine (PM) interventions clinically targeting such actionable drivers may benefit MM pts. These results suggest that PM approaches in MM are possible and should be further studied clinically. To that end, we have launched MyDRUG, a master protocol aimed at developing new myeloma regimens based on individual pt’s genomics. Methods: This study is a Phase I-II, multicenter master protocol in functional high risk MM patients (i.e patients having progressed from baseline treatment within 18 months without maintenance or 3 years on maintenance) with 1-3 prior lines of therapy. Patients are screened for actionable genomic alterations on the CLIA-grade MI-ONCOSEQ platform. Patients with actionable alterations are assigned to the appropriate targeted agent used in combination with a backbone regimen ixazomib, pomalidomide and dexamethasone (IPd), whereas patients without such alterations go on an immune arm (see Table). Inclusion criteria include measurable disease (as measured by M-protein and FLC) and acceptable hematologic and metabolic functions. A maximum of 12 evaluable pts will be accrued onto the phase I portion of each arm and an additional 21 evaluable phase II pts will be accrued onto each arm for a total of 27 evaluable pts at the MTD combination dose. The primary objective of the study is to evaluate ORR per IMWG consensus criteria. Secondary objectives are to assess adverse events (AEs), progression-free survival, and overall survival (OS). Experimental correlative aims include assessing molecular or clonal response, molecular and immune signatures of resistance/response, MRD. Clinical trial information: NCT03732703. [Table: see text]

TPS8053 Background: The advent of proteasome inhibitors and immunomodulatory drugs (IMiDs) have significantly improved outcomes in MM, and the first monoclonal antibodies for MM have been recently approved (daratumumab, elotuzumab). Despite novel therapies and improved disease management, MM is still considered incurable and most pts relapse, confirming the need for additional treatment options. MM cells express PD-L1, with higher levels observed after relapse and with advanced disease. Additionally, PD-L1–expressing immune cells in the microenvironment promote MM cell survival and potential immune escape. However, anti–PD-1 monotherapy did not result in objective responses in the MM cohort of a Ph I study, suggesting that MM pts need combination therapy. Daratumumab has activity as a single agent, as well as in combination with IMiDs plus dexamethasone and bortezomib plus dexamethasone in R/R MM. Immunomodulatory activity for daratumumab has also been reported. Thus, disruption of the PD-L1/PD-1 pathway may be additive or synergistic. The safety and efficacy of atezo (anti–PD-L1) alone or with lenalidomide or pomalidomide and/or daratumumab will be evaluated in a Ph Ib study of MM pts. NCT02431208. Methods: R/R MM pts with ≤ 3 prior therapies will be enrolled in Cohorts A (atezo), B (atezo + lenalidomide), D (atezo + daratumumab) and E (atezo + daratumumab + lenalidomide); MM pts with measurable disease after ASCT (Cohort C: atezo) or ≥ 3 prior therapies (Cohort F: atezo + daratumumab + pomalidomide) will also be enrolled. Cohorts B, D, E and F include a safety run-in (D) or dose escalation phase (B, E, F) and an expansion. Lenalidomide and pomalidomide will be dose escalated and the MTD evaluated in expansion phases. Atezo will be given at 1200 mg IV (A, B, C) or 840 mg IV (D, E, F); pts will get daratumumab at 16 mg/kg IV (D, E, F). All pts will be ECOG PS ≤ 2. Primary endpoints are ORR and the RP2D of lenalidomide and pomalidomide with atezo and daratumumab and the RP2D of lenalidomide with atezo. DOR and PFS are secondary endpoints; safety, PK and the relationship between biomarkers and other endpoints, including efficacy, will be assessed. Pts will be enrolled at 19 US sites. Clinical trial information: NCT02431208.