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Autologous chimeric antigen receptor (CAR) T-cell therapies targeting CD19 have high efficacy in large B-cell lymphomas (LBCL), but long-term remissions are observed in less than half the patients and treatment-associated adverse events such as immune effector cell-associated neurotoxicity syndrome (ICANS) are a clinical challenge. We performed single-cell RNA sequencing with capture-based cell identification on autologous axicabtagene ciloleucel (axi-cel) anti-CD19 CAR T-cell infusion products to identify transcriptomic features associated with efficacy and toxicity in 24 patients with LBCL. Patients that achieved a complete response by PET/CT at their 3-month follow-up had 3-fold higher frequencies of CD8 T-cells expressing memory signatures compared to patients with partial response or progressive disease. Molecular response measured by cell-free DNA (cfDNA) sequencing at day 7 post-infusion was significantly associated with clinical response (p=0.008), and a signature of CD8 T-cell exhaustion was associated (q=2.8×10 −149 ) with a poor molecular response. Furthermore, a rare cell population *

Crosstalk between tumor cells and other cells within the tumor microenvironment (TME) plays a crucial role in tumor progression, metastases, and therapy resistance. We present iTALK, a computational approach to characterize and illustrate intercellular communication signals in the multicellular tumor ecosystem using single-cell RNA sequencing data. iTALK can in principle be used to dissect the complexity, diversity, and dynamics of cell-cell communication from a wide range of cellular processes.The TME has emerged as a key modulator of tumor progression, immune evasion, and emergence of the anti-tumor therapy resistance mechanisms 1, 2 . The TME includes a diversity of cell types such as tumor cells, a heterogeneous group of immune cells, and the nonimmune stromal components. Tumor cells orchestrate and interact dynamically with these non-tumor components, and the crosstalk between them is thought to provide key signals that can direct and promote tumor cell growth and migration. Through this intercellular communication, tumor cells can elicit profound phenotypic changes in other TME cells such as tumor-associated fibroblasts, macrophages and T cells, and reprogram the TME, in order to escape from immune surveillance to facilitate survival. Therefore, a better understanding of the cell-cell communication signals may help identify novel modulating therapeutic strategies for better patient advantage. However, this has been hampered by the lack of bioinformatics tools for efficient data analysis and visualization.Here, we present iTALK (identifying and illustrating alterations in intercellular signaling network; https://github.com/Coolgenome/iTALK), an open source R package designed to profile and visualize the ligand-receptor mediated intercellular cross-talk signals from singlecell RNA sequencing data (scRNA-seq) ( Fig. 1 and Online Methods). We demonstrated that iTALK can be successfully applied to scRNA-seq data to capture highly abundant ligandreceptor gene (or transcript) pairs, identify gains or losses of cellular interactions by comparative analysis, and track the dynamic changes of intercellular communication signals in longitudinal samples. Notably, functional annotation of ligand-receptor genes is automatically added with our curated iTALK ligand-receptor database, and the output can be visualized in different formats with our efficient data visualization tool, which is implemented as part of iTALK. This approach can be applied to data sets ranging from hundreds to hundreds of thousands of cells and is not limited by sequencing platforms. It is also noteworthy that, in addition to studying the TME, iTALK can also be applied to a wide range of biomedical research fields that involve cell-cell communication.

Metabolic reprogramming is linked to cancer cell growth and proliferation, metastasis, and therapeutic resistance in a multitude of cancers. Targeting dysregulated metabolic pathways to overcome resistance, an urgent clinical need in all relapsed/refractory cancers, remains difficult. Through genomic analyses of clinical specimens, we show that metabolic reprogramming toward oxidative phosphorylation (OXPHOS) and glutaminolysis is associated with therapeutic resistance to the Bruton’s tyrosine kinase inhibitor ibrutinib in mantle cell lymphoma (MCL), a B cell lymphoma subtype with poor clinical outcomes. Inhibition of OXPHOS with a clinically applicable small molecule, IACS-010759, which targets complex I of the mitochondrial electron transport chain, results in marked growth inhibition in vitro and in vivo in ibrutinib-resistant patient-derived cancer models. This work suggests that targeting metabolic pathways to subvert therapeutic resistance is a clinically viable approach to treat highly refractory malignancies.

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ObjectivePeritoneal carcinomatosis (PC) occurs frequently in patients with gastric adenocarcinoma (GAC) and confers a poor prognosis. Multiplex profiling of primary GACs has been insightful but the underpinnings of PC’s development/progression remain largely unknown. We characterised exome/transcriptome/immune landscapes of PC cells from patients with GAC aiming to identify novel therapeutic targets.DesignWe performed whole-exome sequencing (WES) and whole transcriptome sequencing (RNA-seq) on 44 PC specimens (43 patients with PC) including an integrative analysis of WES, RNA-seq, immune profile, clinical and pathological phenotypes to dissect the molecular pathogenesis, identifying actionable targets and/or biomarkers and comparison with TCGA primary GACs.ResultsWe identified distinct alterations in PC versus primary GACs, such as more frequent CDH1 and TAF1 mutations, 6q loss and chr19 gain. Alterations associated with aggressive PC phenotypes emerged with increased mutations in TP53, CDH1, TAF1 and KMT2C, higher level of ‘clock-like’ mutational signature, increase in whole-genome doublings, chromosomal instability (particularly, copy number losses), reprogrammed microenvironment, enriched cell cycle pathways, MYC activation and impaired immune response. Integrated analysis identified two main molecular subtypes: ‘mesenchymal-like’ and ‘epithelial-like’ with discriminating response to chemotherapy (31% vs 71%). Patients with the less responsive ‘mesenchymal-like’ subtype had high expression of immune checkpoint T-Cell Immunoglobulin And Mucin Domain-Containing Protein 3 (TIM-3), its ligand galectin-9, V-domain Ig suppressor of T cell activation (VISTA) and transforming growth factor-β as potential therapeutic immune targets.ConclusionsWe have uncovered the unique mutational landscape, copy number alteration and gene expression profile of PC cells and defined PC molecular subtypes, which correlated with PC therapy resistance/response. Novel targets and immune checkpoint proteins have been identified with a potential to be translated into clinics.

Little is known of the geospatial architecture of individual cell populations in lung adenocarcinoma (LUAD) evolution. Here, we perform single-cell RNA sequencing of 186,916 cells from five early-stage LUADs and 14 multiregion normal lung tissues of defined spatial proximities from the tumors. We show that cellular lineages, states, and transcriptomic features geospatially evolve across normal regions to LUADs. LUADs also exhibit pronounced intratumor cell heterogeneity within single sites and transcriptional lineage-plasticity programs. T regulatory cell phenotypes are increased in normal tissues with proximity to LUAD, in contrast to diminished signatures and fractions of cytotoxic CD8+ T cells, antigen-presenting macrophages, and inflammatory dendritic cells. We further find that the LUAD ligand–receptor interactome harbors increased expression of epithelial CD24, which mediates protumor phenotypes. These data provide a spatial atlas of LUAD evolution, and a resource for identification of targets for its treatment. Significance: The geospatial ecosystem of the peripheral lung and early-stage LUAD is not known. Our multiregion single-cell sequencing analyses unravel cell populations, states, and phenotypes in the spatial and ecologic evolution of LUAD from the lung that comprise high-potential targets for early interception. This article is highlighted in the In This Issue feature, p. 2355

Although anti-CD19 chimeric antigen receptor (CAR) T-cell therapy produces high response rates and durable remissions in patients with large B-cell lymphoma (LBCL), relapses can still occur by mechanisms that are incompletely elucidated. We examined the CD19 antigen characteristics of pretreatment (n=100) and post-relapse (n=20) tumor biopsies from patients treated with axicabtagene ciloleucel (axi-cel) in the multicenter phase 1/2 ZUMA-1 study (NCT02899052). CD19 target antigen expression was variable at baseline and a subset of evaluable patients who relapsed after axi-cel CAR T-cell therapy (~30%) had CD19-low or negative tumors. By comparison CD20, CD22, and CD79a were mostly present at relapse, including in tumors with low CD19 levels. Transcriptomic analysis revealed that the observed impact to antigen levels in a subset of tumor biopsies at relapse was primarily attributed to low or absent CD19 protein expression that was unrelated to alternative splicing events and mutations in CD19, which were also observed. The emergence of tumor cells with low or no CD19 antigen expression are thought to drive the relapse process in some patients, in the context of targeted removal of antigen-positive tumor cells by the therapy. These findings support multi-antigen targeting CAR approaches to improve clinical outcomes in patients with LBCL.