Cancer vaccines: Building a bridge over troubled waters.

Cancer vaccines aim to direct the immune system to eradicate cancer cells. Here we review the essential immunologic concepts underpinning natural immunity and highlight the multiple unique challenges faced by vaccines targeting cancer. Recent technological advances in mass spectrometry, neoantigen prediction, genetically and pharmacologically engineered mouse models, and single-cell omics have revealed new biology, which can help to bridge this divide. We particularly focus on translationally relevant aspects, such as antigen selection and delivery and the monitoring of human post-vaccination responses, and encourage more aggressive exploration of novel approaches.

Cancer-Germline Antigen Expression Discriminates Clinical Outcome to CTLA-4 Blockade.

CTLA-4 immune checkpoint blockade is clinically effective in a subset of patients with metastatic melanoma. We identify a subcluster of MAGE-A cancer-germline antigens, located within a narrow 75 kb region of chromosome Xq28, that predicts resistance uniquely to blockade of CTLA-4, but not PD-1. We validate this gene expression signature in an independent anti-CTLA-4-treated cohort and show its specificity to the CTLA-4 pathway with two independent anti-PD-1-treated cohorts. Autophagy, a process critical for optimal anti-cancer immunity, has previously been shown to be suppressed by the MAGE-TRIM28 ubiquitin ligase in vitro. We now show that the expression of the key autophagosome component LC3B and other activators of autophagy are negatively associated with MAGE-A protein levels in human melanomas, including samples from patients with resistance to CTLA-4 blockade. Our findings implicate autophagy suppression in resistance to CTLA-4 blockade in melanoma, suggesting exploitation of autophagy induction for potential therapeutic synergy with CTLA-4 inhibitors.

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer.

We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments.

Spatial maps of T cell receptors and transcriptomes reveal distinct immune niches and interactions in the adaptive immune response.

T cells mediate antigen-specific immune responses to disease through the specificity and diversity of their clonotypic T cell receptors (TCRs). Determining the spatial distributions of T cell clonotypes in tissues is essential to understanding T cell behavior, but spatial sequencing methods remain unable to profile the TCR repertoire. Here, we developed Slide-TCR-seq, a 10-µm-resolution method, to sequence whole transcriptomes and TCRs within intact tissues. We confirmed the ability of Slide-TCR-seq to map the characteristic locations of T cells and their receptors in mouse spleen. In human lymphoid germinal centers, we identified spatially distinct TCR repertoires. Profiling T cells in renal cell carcinoma and melanoma specimens revealed heterogeneous immune responses: T cell states and infiltration differed intra- and inter-clonally, and adjacent tumor and immune cells exhibited distinct gene expression. Altogether, our method yields insights into the spatial relationships between clonality, neighboring cell types, and gene expression that drive T cell responses.

Splice it up: Atypical transcripts to boost leukemia immunotherapy.

Neoantigens are prime targets for cancer immunotherapy, but their identification in low mutational burden malignancies remains challenging. In this issue of Immunity, Ehx et al. show that atypical transcripts, and particularly retained introns, expand the spectrum of leukemia immunotherapy targets.

Molecular and genetic properties of tumors associated with local immune cytolytic activity.

How the genomic landscape of a tumor shapes and is shaped by anti-tumor immunity has not been systematically explored. Using large-scale genomic data sets of solid tissue tumor biopsies, we quantified the cytolytic activity of the local immune infiltrate and identified associated properties across 18 tumor types. The number of predicted MHC Class I-associated neoantigens was correlated with cytolytic activity and was lower than expected in colorectal and other tumors, suggesting immune-mediated elimination. We identified recurrently mutated genes that showed positive association with cytolytic activity, including beta-2-microglobulin (B2M), HLA-A, -B and -C and Caspase 8 (CASP8), highlighting loss of antigen presentation and blockade of extrinsic apoptosis as key strategies of resistance to cytolytic activity. Genetic amplifications were also associated with high cytolytic activity, including immunosuppressive factors such as PDL1/2 and ALOX12B/15B. Our genetic findings thus provide evidence for immunoediting in tumors and uncover mechanisms of tumor-intrinsic resistance to cytolytic activity.

Dictionary of immune responses to cytokines at single-cell resolution.

Cytokines mediate cell-cell communication in the immune system and represent important therapeutic targets1-3. A myriad of studies have highlighted their central role in immune function4-13, yet we lack a global view of the cellular responses of each immune cell type to each cytokine. To address this gap, we created the Immune Dictionary, a compendium of single-cell transcriptomic profiles of more than 17 immune cell types in response to each of 86 cytokines (>1,400 cytokine-cell type combinations) in mouse lymph nodes in vivo. A cytokine-centric view of the dictionary revealed that most cytokines induce highly cell-type-specific responses. For example, the inflammatory cytokine interleukin-1ß induces distinct gene programmes in almost every cell type. A cell-type-centric view of the dictionary identified more than 66 cytokine-driven cellular polarization states across immune cell types, including previously uncharacterized states such as an interleukin-18-induced polyfunctional natural killer cell state. Based on this dictionary, we developed companion software, Immune Response Enrichment Analysis, for assessing cytokine activities and immune cell polarization from gene expression data, and applied it to reveal cytokine networks in tumours following immune checkpoint blockade therapy. Our dictionary generates new hypotheses for cytokine functions, illuminates pleiotropic effects of cytokines, expands our knowledge of activation states of each immune cell type, and provides a framework to deduce the roles of specific cytokines and cell-cell communication networks in any immune response.

Slide-tags enables single-nucleus barcoding for multimodal spatial genomics.

Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed1-6. However, missing from these measurements is the ability to routinely and easily spatially localize these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are tagged with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as an input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 µm spatial resolution and delivered whole-transcriptome data that are indistinguishable in quality from ordinary single-nucleus RNA-sequencing data. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualized receptor-ligand interactions driving B cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to almost any single-cell measurement technology. As a proof of principle, we performed multiomic measurements of open chromatin, RNA and T cell receptor (TCR) sequences in the same cells from metastatic melanoma, identifying transcription factor motifs driving cancer cell state transitions in spatially distinct microenvironments. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.

Latent human herpesvirus 6 is reactivated in CAR T cells.

Cell therapies have yielded durable clinical benefits for patients with cancer, but the risks associated with the development of therapies from manipulated human cells are understudied. For example, we lack a comprehensive understanding of the mechanisms of toxicities observed in patients receiving T cell therapies, including recent reports of encephalitis caused by reactivation of human herpesvirus 6 (HHV-6)1. Here, through petabase-scale viral genomics mining, we examine the landscape of human latent viral reactivation and demonstrate that HHV-6B can become reactivated in cultures of human CD4+ T cells. Using single-cell sequencing, we identify a rare population of HHV-6 'super-expressors' (about 1 in 300-10,000 cells) that possess high viral transcriptional activity, among research-grade allogeneic chimeric antigen receptor (CAR) T cells. By analysing single-cell sequencing data from patients receiving cell therapy products that are approved by the US Food and Drug Administration2 or are in clinical studies3-5, we identify the presence of HHV-6-super-expressor CAR T cells in patients in vivo. Together, the findings of our study demonstrate the utility of comprehensive genomics analyses in implicating cell therapy products as a potential source contributing to the lytic HHV-6 infection that has been reported in clinical trials1,6-8 and may influence the design and production of autologous and allogeneic cell therapies.

Evolution and impact of subclonal mutations in chronic lymphocytic leukemia.

Clonal evolution is a key feature of cancer progression and relapse. We studied intratumoral heterogeneity in 149 chronic lymphocytic leukemia (CLL) cases by integrating whole-exome sequence and copy number to measure the fraction of cancer cells harboring each somatic mutation. We identified driver mutations as predominantly clonal (e.g., MYD88, trisomy 12, and del(13q)) or subclonal (e.g., SF3B1 and TP53), corresponding to earlier and later events in CLL evolution. We sampled leukemia cells from 18 patients at two time points. Ten of twelve CLL cases treated with chemotherapy (but only one of six without treatment) underwent clonal evolution, predominantly involving subclones with driver mutations (e.g., SF3B1 and TP53) that expanded over time. Furthermore, presence of a subclonal driver mutation was an independent risk factor for rapid disease progression. Our study thus uncovers patterns of clonal evolution in CLL, providing insights into its stepwise transformation, and links the presence of subclones with adverse clinical outcomes.

Landscape of helper and regulatory antitumour CD4+ T cells in melanoma.

Within the tumour microenvironment, CD4+ T cells can promote or suppress antitumour responses through the recognition of antigens presented by human leukocyte antigen (HLA) class II molecules1,2, but how cancers co-opt these physiologic processes to achieve immune evasion remains incompletely understood. Here we performed in-depth analysis of the phenotype and tumour specificity of CD4+ T cells infiltrating human melanoma specimens, finding that exhausted cytotoxic CD4+ T cells could be directly induced by melanoma cells through recognition of HLA class II-restricted neoantigens, and also HLA class I-restricted tumour-associated antigens. CD4+ T regulatory (TReg) cells could be indirectly elicited through presentation of tumour antigens via antigen-presenting cells. Notably, numerous tumour-reactive CD4+ TReg clones were stimulated directly by HLA class II-positive melanoma and demonstrated specificity for melanoma neoantigens. This phenomenon was observed in the presence of an extremely high tumour neoantigen load, which we confirmed to be associated with HLA class II positivity through the analysis of 116 melanoma specimens. Our data reveal the landscape of infiltrating CD4+ T cells in melanoma and point to the presentation of HLA class II-restricted neoantigens and direct engagement of immunosuppressive CD4+ TReg cells as a mechanism of immune evasion that is favoured in HLA class II-positive melanoma.

A Bayesian framework for inferring dynamic intercellular interactions from time-series single-cell data.

Characterizing cell-cell communication and tracking its variability over time are crucial for understanding the coordination of biological processes mediating normal development, disease progression, and responses to perturbations such as therapies. Existing tools fail to capture time-dependent intercellular interactions, and primarily rely on existing databases compiled from limited contexts. We introduce DIISCO, a Bayesian framework designed to characterize the temporal dynamics of cellular interactions using single-cell RNA sequencing data from multiple time points. Our method utilizes structured Gaussian process regression to unveil time-resolved interactions among diverse cell types according to their coevolution and incorporates prior knowledge of receptor-ligand complexes. We show the interpretability of DIISCO in simulated data and new data collected from T cells co-cultured with lymphoma cells, demonstrating its potential to uncover dynamic cell-cell crosstalk.

Phenotype, specificity and avidity of antitumour CD8+ T cells in melanoma.

Interactions between T cell receptors (TCRs) and their cognate tumour antigens are central to antitumour immune responses1-3; however, the relationship between phenotypic characteristics and TCR properties is not well elucidated. Here we show, by linking the antigenic specificity of TCRs and the cellular phenotype of melanoma-infiltrating lymphocytes at single-cell resolution, that tumour specificity shapes the expression state of intratumoural CD8+ T cells. Non-tumour-reactive T cells were enriched for viral specificities and exhibited a non-exhausted memory phenotype, whereas melanoma-reactive lymphocytes predominantly displayed an exhausted state that encompassed diverse levels of differentiation but rarely acquired memory properties. These exhausted phenotypes were observed both among clonotypes specific for public overexpressed melanoma antigens (shared across different tumours) or personal neoantigens (specific for each tumour). The recognition of such tumour antigens was provided by TCRs with avidities inversely related to the abundance of cognate targets in melanoma cells and proportional to the binding affinity of peptide-human leukocyte antigen (HLA) complexes. The persistence of TCR clonotypes in peripheral blood was negatively affected by the level of intratumoural exhaustion, and increased in patients with a poor response to immune checkpoint blockade, consistent with chronic stimulation mediated by residual tumour antigens. By revealing how the quality and quantity of tumour antigens drive the features of T cell responses within the tumour microenvironment, we gain insights into the properties of the anti-melanoma TCR repertoire.

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.

Loss of PTEN Is Associated with Resistance to Anti-PD-1 Checkpoint Blockade Therapy in Metastatic Uterine Leiomyosarcoma.

Response to immune checkpoint blockade in mesenchymal tumors is poorly characterized, but immunogenomic dissection of these cancers could inform immunotherapy mediators. We identified a treatment-naive patient who has metastatic uterine leiomyosarcoma and has experienced complete tumor remission for >2 years on anti-PD-1 (pembrolizumab) monotherapy. We analyzed the primary tumor, the sole treatment-resistant metastasis, and germline tissue to explore mechanisms of immunotherapy sensitivity and resistance. Both tumors stained diffusely for PD-L2 and showed sparse PD-L1 staining. PD-1+ cell infiltration significantly decreased in the resistant tumor (p = 0.039). Genomically, the treatment-resistant tumor uniquely harbored biallelic PTEN loss and had reduced expression of two neoantigens that demonstrated strong immunoreactivity with patient T cells in vitro, suggesting long-lasting immunological memory. In this near-complete response to PD-1 blockade in a mesenchymal tumor, we identified PTEN mutations and reduced expression of genes encoding neoantigens as potential mediators of resistance to immune checkpoint therapy.

Mass Spectrometry Profiling of HLA-Associated Peptidomes in Mono-allelic Cells Enables More Accurate Epitope Prediction.

Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on datasets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation.

The end of the beginning: application of single-cell sequencing to chronic lymphocytic leukemia.

Single-cell analysis has emerged over the past decade as a transformative technology informative for the systematic analysis of complex cell populations such as in cancers and the tumor immune microenvironment. The methodologic and analytical advancements in this realm have evolved rapidly, scaling from but a few cells at its outset to the current capabilities of processing and analyzing hundreds of thousands of individual cells at a time. The types of profiling attainable at individual cell resolution now range from genetic and transcriptomic characterization and extend to epigenomic and spatial analysis. Additionally, the increasing ability to achieve multiomic integration of these data layers now yields ever richer insights into diverse molecular disease subtypes and the patterns of cellular circuitry on a per-cancer basis. Over the years, chronic lymphocytic leukemia (CLL) consistently has been at the forefront of genomic investigation, given the ready accessibility of pure leukemia cells and immune cells from circulating blood of patients with this disease. Herein, we review the recent forays into the application of single-cell analysis to CLL, which are already revealing a new understanding of the natural progression of CLL, the impact of novel therapies, and the interactions with coevolving nonmalignant immune cell populations. As we emerge from the end of the beginning of this technologic revolution, CLL stands poised to reap the benefits of single-cell analysis from the standpoints of uncovering fresh fundamental biological knowledge and of providing a path to devising regimens of personalized diagnosis, treatment, and monitoring.

Richter syndrome: novel insights into the biology of transformation.

Although the genetic landscape of chronic lymphocytic leukemia (CLL) has been broadly profiled by large-scale sequencing studies performed over the past decade, the molecular basis of the transformation of CLL into aggressive lymphoma, or Richter syndrome (RS), has remained incompletely characterized. Recent advances in computational methods of clonal deconvolution, as well as extensive sample collection efforts in this rapidly progressive malignancy, have now enabled comprehensive analysis of paired CLL and RS samples and have led to multiple new studies investigating the genetic, transcriptomic, and epigenetic origins of RS. In parallel, new genetically engineered and xenograft mouse models have provided the opportunity for gleaning fresh biological and mechanistic insights into RS development and stepwise evolution from antecedent CLL. Altogether, these studies have defined RS driver lesions and CLL risk lesions and identified pathways dysregulated in transformation. Moreover, unique molecular subtypes of RS have been revealed, including a disease marked by profound genomic instability with chromothripsis/chromoplexy and whole genome duplication. Novel profiling approaches, including single-cell DNA and transcriptome sequencing of RS biopsy specimens and cell-free DNA profiling of patient plasma, demonstrate promise for the timely identification of RS clones and may translate to noninvasive identification and early diagnosis of RS. This review summarizes the recent scientific advances in RS and supports the integrated study of human genomics with mouse modeling to provide an advanced understanding of the biological underpinnings of transformation. These recent studies have major implications for much-needed novel therapeutic strategies for this still largely incurable malignancy.

Mechanisms of response and resistance to combined decitabine and ipilimumab for advanced myeloid disease.

The challenge of eradicating leukemia in patients with acute myelogenous leukemia (AML) after initial cytoreduction has motivated modern efforts to combine synergistic active modalities including immunotherapy. Recently, the ETCTN/CTEP 10026 study tested the combination of the DNA methyltransferase inhibitor decitabine together with the immune checkpoint inhibitor ipilimumab for AML/myelodysplastic syndrome (MDS) either after allogeneic hematopoietic stem cell transplantation (HSCT) or in the HSCT-naïve setting. Integrative transcriptome-based analysis of 304 961 individual marrow-infiltrating cells for 18 of 48 subjects treated on study revealed the strong association of response with a high baseline ratio of T to AML cells. Clinical responses were predominantly driven by decitabine-induced cytoreduction. Evidence of immune activation was only apparent after ipilimumab exposure, which altered CD4+ T-cell gene expression, in line with ongoing T-cell differentiation and increased frequency of marrow-infiltrating regulatory T cells. For post-HSCT samples, relapse could be attributed to insufficient clearing of malignant clones in progenitor cell populations. In contrast to AML/MDS bone marrow, the transcriptomes of leukemia cutis samples from patients with durable remission after ipilimumab monotherapy showed evidence of increased infiltration with antigen-experienced resident memory T cells and higher expression of CTLA-4 and FOXP3. Altogether, activity of combined decitabine and ipilimumab is impacted by cellular expression states within the microenvironmental niche of leukemic cells. The inadequate elimination of leukemic progenitors mandates urgent development of novel approaches for targeting these cell populations to generate long-lasting responses. This trial was registered at www.clinicaltrials.gov as #NCT02890329.