Baseline Immune State and T-cell Clonal Kinetics are Associated with Durable Response to CAR-T Therapy in Large B-cell Lymphoma.

Engineered cellular therapy with CD19-targeting chimeric antigen receptor T-cells (CAR-T) has revolutionized outcomes for patients with relapsed/refractory Large B-Cell Lymphoma (LBCL), but the cellular and molecular features associated with response remain largely unresolved. We analyzed serial peripheral blood samples ranging from day of apheresis (day -28/baseline) to 28 days after CAR-T infusion from 50 patients with LBCL treated with axicabtagene ciloleucel (axi-cel) by integrating single cell RNA and TCR sequencing (scRNA-seq/scTCR-seq), flow cytometry, and mass cytometry (CyTOF) to characterize features associated with response to CAR-T. Pretreatment patient characteristics associated with response included presence of B cells and increased lymphocyte-to-monocyte ratio (ALC/AMC). Infusion products from responders were enriched for clonally expanded, highly activated CD8+ T cells. We expanded these observations to 99 patients from the ZUMA-1 cohort and identified a subset of patients with elevated baseline B cells, 80% of whom were complete responders. We integrated B cell proportion 0.5% and ALC/AMC 1.2 into a two-factor predictive model and applied this model to the ZUMA-1 cohort. Estimated progression free survival (PFS) at 1 year in patients meeting one or both criteria was 65% versus 31% for patients meeting neither criterion. Our results suggest that patients' immunologic state at baseline affects likelihood of response to CAR-T through both modulation of the T cell apheresis product composition and promoting a more favorable circulating immune compartment prior to therapy. These baseline immunologic features, measured readily in the clinical setting prior to CAR-T, can be applied to predict response to therapy.

Integrative genotyping of cancer and immune phenotypes by long-read sequencing.

Single-cell transcriptomics has become the definitive method for classifying cell types and states, and can be augmented with genotype information to improve cell lineage identification. Due to constraints of short-read sequencing, current methods to detect natural genetic barcodes often require cumbersome primer panels and early commitment to targets. Here we devise a flexible long-read sequencing workflow and analysis pipeline, termed nanoranger, that starts from intermediate single-cell cDNA libraries to detect cell lineage-defining features, including single-nucleotide variants, fusion genes, isoforms, sequences of chimeric antigen and TCRs. Through systematic analysis of these classes of natural 'barcodes', we define the optimal targets for nanoranger, namely those loci close to the 5' end of highly expressed genes with transcript lengths shorter than 4 kB. As proof-of-concept, we apply nanoranger to longitudinal tracking of subclones of acute myeloid leukemia (AML) and describe the heterogeneous isoform landscape of thousands of marrow-infiltrating immune cells. We propose that enhanced cellular genotyping using nanoranger can improve the tracking of single-cell tumor and immune cell co-evolution.

Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy.

Understanding how intra-tumoral immune populations coordinate to generate anti-tumor responses following therapy can guide precise treatment prioritization. We performed systematic dissection of an established adoptive cellular therapy, donor lymphocyte infusion (DLI), by analyzing 348,905 single-cell transcriptomes from 74 longitudinal bone-marrow samples of 25 patients with relapsed myeloid leukemia; a subset was evaluated by protein-based spatial analysis. In acute myelogenous leukemia (AML) responders, diverse immune cell types within the bone-marrow microenvironment (BME) were predicted to interact with a clonally expanded population of ZNF683 + GZMB + CD8+ cytotoxic T lymphocytes (CTLs) which demonstrated in vitro specificity for autologous leukemia. This population, originating predominantly from the DLI product, expanded concurrently with NK and B cells. AML nonresponder BME revealed a paucity of crosstalk and elevated TIGIT expression in CD8+ CTLs. Our study highlights recipient BME differences as a key determinant of effective anti-leukemia response and opens new opportunities to modulate cell-based leukemia-directed therapy.

Tracking rare single donor and recipient immune and leukemia cells after allogeneic hematopoietic cell transplantation using mitochondrial DNA mutations.

Combined tracking of clonal evolution and chimeric cell phenotypes could enable detection of the key cellular populations associated with response following therapy, including after allogeneic hematopoietic stem cell transplantation (HSCT). We demonstrate that mitochondrial DNA (mtDNA) mutations co-evolve with somatic nuclear DNA mutations at relapse post-HSCT and provide a sensitive means to monitor these cellular populations. Further, detection of mtDNA mutations via single-cell ATAC with select antigen profiling by sequencing (ASAP-seq) simultaneously determines not only donor and recipient cells, but also their phenotype, at frequencies of 0.1-1%. Finally, integration of mtDNA mutations, surface markers, and chromatin accessibility profiles enables the phenotypic resolution of leukemic populations from normal immune cells, thereby providing fresh insights into residual donor-derived engraftment and short-term clonal evolution following therapy for post-transplant leukemia relapse. As throughput evolves, we envision future development of single-cell sequencing-based post-transplant monitoring as a powerful approach for guiding clinical decision making.