Abstract
Background: The success of allogeneic stem cell transplantation mediated by the graft versus leukemia effect of engrafted T-cells strongly supports the premise to investigate T cell biology in acute myeloid leukemia (AML). Of particular interest are CD8 cells, which are key players in eliciting anti-cancer cytotoxic activities but are understudied in AML. In this study, we conducted single cell RNA profiling in bone marrows from healthy donors, treatment naïve (RxNaive) and relapsed/refractory (R/R) AML patients to investigate the CD8 landscape in AML.
Methods: We conducted paired single cell gene expression (scRNA) and T-cell repertoire (scTCR) profiling of bone marrow mononuclear cells from 3 healthy donors and 23 RxNaive adult AML patients (median age 71.81 years; range 51-86 years) and leveraged our previously published data of 8 relapsed/refractory AML patients (median age 73 years; range 64-88 years). After doublet removal and quality assessment, a total of 51,219 T cells passed the filtering criteria, of which 23,320 (45.5%) were CD8 cells. A total of 17,782/23,320 (74.1%) CD8 cells had paired scTCR. We applied principal component analysis to identify sources of variability across CD8 cells, then used Harmony-based linear correction integrated with K-nearest neighbors for cluster identification. We then applied non-linear dimensionality reduction (UMAP) to project cells into 2 dimensions.
Results: In total, 6 CD8 T cell subtypes were defined including naïve, memory, effector memory, cytotoxic and exhausted T cell subtypes. Panel 1 shows the UMAP projection of CD8 cells overlaid with neighborhoods demonstrating differential abundance of cells by patient type (healthy, RxNaive or R/R). Naïve, memory, MAIT and exhausted clusters were shared across healthy, RxNaive and R/R patients (Panel 1, left). Remarkably, the effector clusters (effector memory and cytotoxic) demonstrated distinct patterns of disease states. Specifically, the Top effector clusters (Panel 1, top right) were largely contributed by R/R AML patients. However, the Bottom effector clusters (Panel 1, bottom right) were enriched by cells from healthy and RxNaive. Only 2.5% of R/R effector cells were part of the bottom effector clusters. This indicated that naïve and memory cells of RxNaive and R/R AML patients are biologically similar, however, effector cells took diverging paths in RxNaive versus R/R AML patients.
We next explored the biological programs that govern the Top clusters and thus associate with R/R state as compared to the Bottom clusters, associated with RxNaive AML patients. We conducted consensus non-negative matrix factorization coupled with gene expression profiling and pathway analysis. This revealed positive enrichment for IFNa and IFNg signaling and significant negative enrichment for TNFa and TGFb signaling in the Top clusters, suggesting a cytokine dependent remodeling of CD8 effector function in R/R cells. We next explored whether the top 25 differential genes (herein referred to as CD8 Dysfunctional Signature) in the Top clusters (enriched for R/R CD8 cells) can predict outcomes in two cohorts of newly diagnosed AML patients (Abbas et al 2021 and TCGA AML cohorts). Interestingly, the CD8 Dysfunctional Signature was indeed predictive of outcomes, with patients harboring higher CD8 Dysfunctional Signature scores having worse outcomes (p=0.0054, Panel 2).
We next explored whether the TCR repertoires are also different in AML of RxNaive and R/R patients. Indeed, TCR profiling revealed lower clonotype diversity and significant clonotype expansion in R/R patients, with 34% of R/R cells with TCR data exhibiting hyperexpansion (clone size >100). However, these hyperexpanded clonotypes were largely derived from dysfunctional CD8 cells.
Conclusion: We characterized the CD8 landscape in RxNaive and R/R AML patients and defined distinct states of effector CD8 cells predictive of outcomes. CD8+ T-cells in R/R patients are markedly different from healthy/RxNaive patients, and characterized by a dysfunctional state, skewed distribution, lower clonal diversity, and significant clonal hyperexpansion. This dysfunctional state may be due to the AML microenvironment actively shaping the T-cell repertoires or the chemotherapy received by the patient, which may narrow the repertoire by eliminating active T-cells.
Disclosures
Green:Kite/Gilead: Research Funding; Tessa Therapeutics: Honoraria; KDAc Therapeutics: Current holder of stock options in a privately-held company; Allogene: Research Funding; Monte Rosa Therapeutics: Honoraria; Sanofi: Research Funding; Daiichi Sankyo: Consultancy, Honoraria; Abbvie: Research Funding. Daver:Kartos and Jazz Pharmaceuticals: Other: Data monitoring committee member; Agios, Celgene, SOBI and STAR Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopham Therapeutics and Newave Pharmaceutical: Research Funding; Astellas, AbbVie, Genentech, Daiichi-Sankyo, Novartis, Jazz, Amgen, Servier, Karyopharm, Trovagene, Trillium, Syndax, Gilead, Pfizer, Bristol Myers Squibb, Kite, Actinium, Arog, Immunogen, Arcellx, and Shattuck: Consultancy, Other: Advisory Role; Astellas, AbbVie, Genentech, Daiichi-Sankyo, Gilead, Immunogen, Pfizer, Bristol Myers Squibb, Trovagene, Servier, Novimmune, Incyte, Hanmi, Fate, Amgen, Kite, Novartis, Astex, KAHR, Shattuck, Sobi, Glycomimetics, Trillium: Research Funding. Konopleva:Reata Pharmaceuticals, Novartis and Eli Lilly: Patents & Royalties; AbbVie, Genentech, F. Hoffman La-Roche, Eli Lilly, Cellectis, Calithera, Ablynx, Stemline Therapeutics, Agios, Ascentage, Astra Zeneca; Rafael Pharmaceutical; Sanofi, Forty-Seven: Research Funding; Forty-Seven; F. Hoffman LaRoche: Honoraria; AbbVie, Genentech, F. Hoffman La-Roche, Stemline Therapeutics, Amgen, Forty-Seven, Kisoji; Janssen: Consultancy; Stocks, Reata Pharmaceuticals: Current equity holder in publicly-traded company; Stemline Therapeutics, F. Hoffman La-Roche; Janssen: Membership on an entity's Board of Directors or advisory committees.
