No abstract

Leukemic relapse remains a major barrier to successful allogeneic hematopoietic stem cell transplantation (allo-HSCT) for aggressive hematologic malignancies. The basis for relapse of advanced lymphoid malignancies remains incompletely understood and may involve escape from the graft-versus-leukemia (GvL) effect. We hypothesized that for patients with chronic lymphocytic leukemia (CLL) treated with allo-HSCT, leukemic cell–intrinsic features influence transplant outcomes by directing the evolutionary trajectories of CLL cells. Integrated genetic, transcriptomic, and epigenetic analyses of CLL cells from 10 patients revealed that the clinical kinetics of post-HSCT relapse are shaped by distinct molecular dynamics. Early relapses after allo-HSCT exhibited notable genetic stability; single CLL cell transcriptional analysis demonstrated a cellular heterogeneity that was static over time. In contrast, CLL cells relapsing late after allo-HSCT displayed notable genetic evolution and evidence of neoantigen depletion, consistent with marked single-cell transcriptional shifts that were unique to each patient. We observed a greater rate of epigenetic change for late relapses not seen in early relapses or relapses after chemotherapy alone, suggesting that the selection pressures of the GvL bottleneck are unlike those imposed by chemotherapy. No selective advantage for human leukocyte antigen (HLA) loss was observed, even when present in pretransplant subpopulations. Gain of stem cell modules was a common signature associated with leukemia relapse regardless of posttransplant relapse kinetics. These data elucidate the biological pathways that underlie GvL resistance and posttransplant relapse.

The factors mediating GvL resistance following allogeneic stem cell transplant (SCT) in lymphoid malignancies remain incompletely characterized. Because cell-intrinsic features shape chemotherapeutic relapse, we hypothesized that they also shape GvL outcomes by influencing evolutionary trajectories of CLL relapse after reduced intensity conditioning SCT (RIC). We identified 9 heavily pre-treated patients (pts) (range: 1-5 therapies, median: 3) with various times to CLL relapse after RIC (range: 83-1825 days), of which 8 had at least partial responses before relapse. To define evolutionary trajectories, we generated paired whole-exome and RNA sequencing data from purified CLL cells pre/post-RIC, using MuTect2 and ABSOLUTE algorithms to identify somatic alterations (SAs) and corresponding cancer cell fractions (CCFs). 5 pts had clonal SAs in TP53 and/or SF3B1 pre-SCT, and no single SA was specific to post-RIC. Furthermore, we found no SAs nor altered expression of HLA class I/II or b2M in either baseline or post-RIC samples. However, we found 6 relapse pairs to exhibit complex branched evolution involving CCF shifts of at least 0.2 in subclonal and clonal SAs whereas 3 pairs showed genomic stability. Clonal evolution was associated with longer time to relapse (Wilcoxon, p=0.02; median 798 versus 304 days) as well as complete response (p=0.05), suggesting that GvL immune escape may be facilitated by clonal evolution. To determine the phenotypic consequences of clonal evolution, we examined single cell transcriptomes using scRNAseq from paired pre/post-RIC CLL cells from 2 pts with early (304, 442 days; "ERs") and 2 pts with late (1801, 1825 days; "LRs") relapses after RIC. Using the inDrop platform, we profiled a median of 3560 CLL cells/pt (range: 2254-5278). Clustering using Seurat revealed marked transcriptional stability after RIC in ERs whereas dramatic shifts in gene expression programs were observed in LRs. Single cell trajectory analysis using Monocle identified ordered biological processes through which LRs, but not ERs, progressed. Branched expression analysis revealed multiple patient specific pathways defining LRs, including within chromatin regulators (EBF1, BANK1), oncogenic pathways (AFF3, DENND4A) and ribosomal biosynthesis (EEF1G, NACA). Thus, genetic evolution in LRs results in distinct phenotypic consequences. To directly link SAs with transcriptional outcomes, we interrogated scRNAseq data for known SAs identified by WES. In one LR, loss of a CLL cancer driver (RPS15mut) was observed in two of three post-RIC transcriptional clusters, either through deletion of chr.19p (where RPS15 resides) or reversion to the wildtype allele (implying loss of heterozygosity). In addition, genomic and transcriptional loss of HLA genes were detectable in pre-RIC clusters that failed to expand at relapse in both LRs, suggesting that pre-existing HLA loss does not provide a selective advantage for CLL relapse after RIC, consistent with our bulk analyses. These data highlight how scRNAseq can delineate genetic selection pressures within subpopulations of a single patient. To investigate whether epigenetic dysregulation underlies these genetic changes, we measured locally disordered methylation (LDM), a known epigenetic mechanism of CLL genetic variability. Genome-wide methylome profiles revealed increases in LDM in LRs compared to ERs for various genomic regions (Kruskal-Wallis (KW), p<0.05 for promoters, genes, distal regulatory modules); no increases in LDM were observed in an independent cohort of late CLL relapse after chemotherapy alone (n=7; time between samples: 496-1511 days). Moreover, we controlled for time between samples by calculating the rate of change in LDM and still found significant differences only during LR after RIC (versus ER or late relapse after chemotherapy; KW, p<10-13). Finally, genes with increased LDM were enriched for multiple stem cell gene sets (q<0.01), implicating a common stem-like state in LRs. Altogether, these data highlight important features of GvL resistance in CLL: 1) GvL selective pressure, shown by LRs, can shape evolutionary trajectories through genotypic alterations that directly exert phenotypic consequences; 2) alterations in HLA genes have less influence in CLL than in myeloid malignancies; and 3) GvL immune editing may select for epigenetic variability that facilitates evasion through stem-like states. Disclosures Brown: Octapharma: Consultancy; Novartis: Consultancy; Loxo: Consultancy, Research Funding; Kite: Consultancy, Research Funding; Janssen: Honoraria; Invectys: Other: other; Gilead: Consultancy, Research Funding; Genentech/Roche: Consultancy; Dynamo Therapeutics: Consultancy; Catapult Therapeutics: Consultancy; BeiGene: Consultancy; AstraZeneca: Consultancy; Acerta Pharma: Consultancy; Morphosys: Other: Data safety monitoring boards ; Sun Pharmaceuticals, Inc: Research Funding; Sun: Research Funding; Verastem: Consultancy, Research Funding; TG Therapeutics: Consultancy; Teva: Honoraria; Sunesis: Consultancy; Pharmacyclics: Consultancy; Pfizer: Consultancy. Getz:MuTect, ABSOLTUE, MutSig and POLYSOLVER: Patents & Royalties: MuTect, ABSOLTUE, MutSig and POLYSOLVER; IBM: Research Funding; Pharmacyclics: Research Funding. Ho:Jazz Pharmaceuticals: Consultancy; Jazz Pharmaceuticals: Research Funding; Omeros Corporation: Membership on an entity's Board of Directors or advisory committees. Neuberg:Celgene: Research Funding; Pharmacyclics: Research Funding; Madrigal Pharmaceuticals: Equity Ownership. Soiffer:Gilead, Mana therapeutic, Cugene, Jazz: Consultancy; Jazz: Consultancy; Kiadis: Other: supervisory board; Mana therapeutic: Consultancy; Cugene: Consultancy; Juno, kiadis: Membership on an entity's Board of Directors or advisory committees, Other: DSMB. Ritz:TScan Therapeutics: Consultancy; Equillium: Research Funding; Merck: Research Funding; Kite Pharma: Research Funding; Aleta Biotherapeutics: Consultancy; Celgene: Consultancy; Avrobio: Consultancy; LifeVault Bio: Consultancy; Draper Labs: Consultancy; Talaris Therapeutics: Consultancy. Wu:Neon Therapeutics: Other: Member, Advisory Board; Pharmacyclics: Research Funding.

One Sentence Summary:We find that the clinical kinetics of chronic lymphocytic leukemia relapse after stem cell transplant are underwritten by distinct genetic and epigenetic evolutionary trajectories and suggest that the selection pressures of the post-transplant, immunologic bottleneck are unlike those imposed by chemotherapy.Abstract: Resistance to the graft-versus-leukemia (GvL) effect remains the major barrier to successful allogeneic hematopoietic stem cell transplantation (allo-HSCT) for aggressive hematologic malignancies. The basis of GvL resistance for advanced lymphoid malignancies remains incompletely understood. We hypothesized that for patients with chronic lymphocytic leukemia (CLL) treated with allo-HSCT, leukemic cell-intrinsic features shape GvL outcomes by directing the evolutionary trajectories of CLL cells. Integrated genetic, transcriptomic and epigenetic analyses of CLL cells from 10 patients revealed that the clinical kinetics of post-HSCT relapse are shaped by distinct molecular dynamics and suggest that the selection pressures of the GvL bottleneck are unlike those imposed by chemotherapy. No selective advantage for HLA loss was observed, even when present in pre-transplant subpopulations. Regardless of posttransplant relapse kinetics, gain of stem cell modules was a common signature associated with leukemia relapse. These data elucidate the biological pathways that underlie GvL resistance and post-transplant relapse. IntroductionAllogeneic hematopoietic stem cell transplantation (allo-HSCT) is one of the earliest forms of successful cancer immunotherapy whose study has elucidated critical insights into tumorimmune interactions (1, 2). As the only curative option for aggressive and advanced hematologic malignancies, allo-HSCT derives its potency from the underlying, donor-derived graft-versusleukemia (GvL) effect wherein donor immune cells recognize and eradicate recipient leukemic cells. Reduced-intensity conditioning regimens (RIC) for allo-HSCT are increasingly used to reduce treatment-related morbidity and preserve the curative GvL effect (3, 4), but posttransplant disease recurrence limits their efficacy. Therefore, elucidating the mechanisms underpinning GvL resistance is vital to improve transplant outcomes.Multiple studies have identified various pathways of GvL resistance associated with relapse of myeloid malignancies, including loss of HLA class I and II genes, upregulation of inhibitory immune checkpoint molecules, and oncogene-driven immune evasion (5-9). For lymphoid malignancies however, less is known about potential mechanisms of GvL evasion. In particular, how underlying genetic and epigenetic features inform the clinical kinetics of post-transplant relapse or whether dysregulation of HLA class I and II genes influences GvL resistance remains unclear.To address these questions, we assembled a cohort of 10 patients with chronic lymphocytic leukemia (CLL), the majority of whom were treated with RIC allo-HSCT. We hypothesized that leukemic-intrinsic features primarily shape...