IGSF8 is an innate immune checkpoint and cancer immunotherapy target.

Antigen presentation defects in tumors are prevalent mechanisms of adaptive immune evasion and resistance to cancer immunotherapy, whereas how tumors evade innate immunity is less clear. Using CRISPR screens, we discovered that IGSF8 expressed on tumors suppresses NK cell function by interacting with human KIR3DL2 and mouse Klra9 receptors on NK cells. IGSF8 is normally expressed in neuronal tissues and is not required for cell survival in vitro or in vivo. It is overexpressed and associated with low antigen presentation, low immune infiltration, and worse clinical outcomes in many tumors. An antibody that blocks IGSF8-NK receptor interaction enhances NK cell killing of malignant cells in vitro and upregulates antigen presentation, NK cell-mediated cytotoxicity, and T cell signaling in vivo. In syngeneic tumor models, anti-IGSF8 alone, or in combination with anti-PD1, inhibits tumor growth. Our results indicate that IGSF8 is an innate immune checkpoint that could be exploited as a therapeutic target.

Topical therapy for regression and melanoma prevention of congenital giant nevi.

Giant congenital melanocytic nevi are NRAS-driven proliferations that may cover up to 80% of the body surface. Their most dangerous consequence is progression to melanoma. This risk often triggers preemptive extensive surgical excisions in childhood, producing severe lifelong challenges. We have presented preclinical models, including multiple genetically engineered mice and xenografted human lesions, which enabled testing locally applied pharmacologic agents to avoid surgery. The murine models permitted the identification of proliferative versus senescent nevus phases and treatments targeting both. These nevi recapitulated the histologic and molecular features of human giant congenital nevi, including the risk of melanoma transformation. Cutaneously delivered MEK, PI3K, and c-KIT inhibitors or proinflammatory squaric acid dibutylester (SADBE) achieved major regressions. SADBE triggered innate immunity that ablated detectable nevocytes, fully prevented melanoma, and regressed human giant nevus xenografts. These findings reveal nevus mechanistic vulnerabilities and suggest opportunities for topical interventions that may alter the therapeutic options for children with congenital giant nevi.

In vivo CRISPR screens identify the E3 ligase Cop1 as a modulator of macrophage infiltration and cancer immunotherapy target.

Despite remarkable clinical efficacy of immune checkpoint blockade (ICB) in cancer treatment, ICB benefits for triple-negative breast cancer (TNBC) remain limited. Through pooled in vivo CRISPR knockout (KO) screens in syngeneic TNBC mouse models, we found that deletion of the E3 ubiquitin ligase Cop1 in cancer cells decreases secretion of macrophage-associated chemokines, reduces tumor macrophage infiltration, enhances anti-tumor immunity, and strengthens ICB response. Transcriptomics, epigenomics, and proteomics analyses revealed that Cop1 functions through proteasomal degradation of the C/ebpδ protein. The Cop1 substrate Trib2 functions as a scaffold linking Cop1 and C/ebpδ, which leads to polyubiquitination of C/ebpδ. In addition, deletion of the E3 ubiquitin ligase Cop1 in cancer cells stabilizes C/ebpδ to suppress expression of macrophage chemoattractant genes. Our integrated approach implicates Cop1 as a target for improving cancer immunotherapy efficacy in TNBC by regulating chemokine secretion and macrophage infiltration in the tumor microenvironment.

Inhibitory CD161 receptor identified in glioma-infiltrating T cells by single-cell analysis.

T cells are critical effectors of cancer immunotherapies, but little is known about their gene expression programs in diffuse gliomas. Here, we leverage single-cell RNA sequencing (RNA-seq) to chart the gene expression and clonal landscape of tumor-infiltrating T cells across 31 patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma and IDH mutant glioma. We identify potential effectors of anti-tumor immunity in subsets of T cells that co-express cytotoxic programs and several natural killer (NK) cell genes. Analysis of clonally expanded tumor-infiltrating T cells further identifies the NK gene KLRB1 (encoding CD161) as a candidate inhibitory receptor. Accordingly, genetic inactivation of KLRB1 or antibody-mediated CD161 blockade enhances T cell-mediated killing of glioma cells in vitro and their anti-tumor function in vivo. KLRB1 and its associated transcriptional program are also expressed by substantial T cell populations in other human cancers. Our work provides an atlas of T cells in gliomas and highlights CD161 and other NK cell receptors as immunotherapy targets.

Applications of Immunogenomics to Cancer.

Cancer immunogenomics originally was framed by research supporting the hypothesis that cancer mutations generated novel peptides seen as "non-self" by the immune system. The search for these "neoantigens" has been facilitated by the combination of new sequencing technologies, specialized computational analyses, and HLA binding predictions that evaluate somatic alterations in a cancer genome and interpret their ability to produce an immune-stimulatory peptide. The resulting information can characterize a tumor's neoantigen load, its cadre of infiltrating immune cell types, the T or B cell receptor repertoire, and direct the design of a personalized therapeutic.

A high-resolution view of intra-tumoral B cell immunity.

In this issue of Immunity, Meylan et al. (2022) uses spatial transcriptomics to examine B cell immunity within intratumoral tertiary lymphoid structures (TLSs). They find that B cells expand and mature into plasma cells (PCs) within the TLS, migrate along fibroblastic tracks to tumor beds, and produce IgG antibodies that target cancer cells.

Convergent transcription at intragenic super-enhancers targets AID-initiated genomic instability.

Activation-induced cytidine deaminase (AID) initiates both somatic hypermutation (SHM) for antibody affinity maturation and DNA breakage for antibody class switch recombination (CSR) via transcription-dependent cytidine deamination of single-stranded DNA targets. Though largely specific for immunoglobulin genes, AID also acts on a limited set of off-targets, generating oncogenic translocations and mutations that contribute to B cell lymphoma. How AID is recruited to off-targets has been a long-standing mystery. Based on deep GRO-seq studies of mouse and human B lineage cells activated for CSR or SHM, we report that most robust AID off-target translocations occur within highly focal regions of target genes in which sense and antisense transcription converge. Moreover, we found that such AID-targeting "convergent" transcription arises from antisense transcription that emanates from super-enhancers within sense transcribed gene bodies. Our findings provide an explanation for AID off-targeting to a small subset of mostly lineage-specific genes in activated B cells.

Transfer learning enables predictions in network biology.

Mapping gene networks requires large amounts of transcriptomic data to learn the connections between genes, which impedes discoveries in settings with limited data, including rare diseases and diseases affecting clinically inaccessible tissues. Recently, transfer learning has revolutionized fields such as natural language understanding1,2 and computer vision3 by leveraging deep learning models pretrained on large-scale general datasets that can then be fine-tuned towards a vast array of downstream tasks with limited task-specific data. Here, we developed a context-aware, attention-based deep learning model, Geneformer, pretrained on a large-scale corpus of about 30 million single-cell transcriptomes to enable context-specific predictions in settings with limited data in network biology. During pretraining, Geneformer gained a fundamental understanding of network dynamics, encoding network hierarchy in the attention weights of the model in a completely self-supervised manner. Fine-tuning towards a diverse panel of downstream tasks relevant to chromatin and network dynamics using limited task-specific data demonstrated that Geneformer consistently boosted predictive accuracy. Applied to disease modelling with limited patient data, Geneformer identified candidate therapeutic targets for cardiomyopathy. Overall, Geneformer represents a pretrained deep learning model from which fine-tuning towards a broad range of downstream applications can be pursued to accelerate discovery of key network regulators and candidate therapeutic targets.

Systematic characterization of mutations altering protein degradation in human cancers.

The ubiquitin-proteasome system (UPS) is the primary route for selective protein degradation in human cells. The UPS is an attractive target for novel cancer therapies, but the precise UPS genes and substrates important for cancer growth are incompletely understood. Leveraging multi-omics data across more than 9,000 human tumors and 33 cancer types, we found that over 19% of all cancer driver genes affect UPS function. We implicate transcription factors as important substrates and show that c-Myc stability is modulated by CUL3. Moreover, we developed a deep learning model (deepDegron) to identify mutations that result in degron loss and experimentally validated the prediction that gain-of-function truncating mutations in GATA3 and PPM1D result in increased protein stability. Last, we identified UPS driver genes associated with prognosis and the tumor microenvironment. This study demonstrates the important role of UPS dysregulation in human cancer and underscores the potential therapeutic utility of targeting the UPS.

Genome-wide map of nuclear protein degradation shows NCoR1 turnover as a key to mitochondrial gene regulation.

Transcription factor activity and turnover are functionally linked, but the global patterns by which DNA-bound regulators are eliminated remain poorly understood. We established an assay to define the chromosomal location of DNA-associated proteins that are slated for degradation by the ubiquitin-proteasome system. The genome-wide map described here ties proteolysis in mammalian cells to active enhancers and to promoters of specific gene families. Nuclear-encoded mitochondrial genes in particular correlate with protein elimination, which positively affects their transcription. We show that the nuclear receptor corepressor NCoR1 is a key target of proteolysis and physically interacts with the transcription factor CREB. Proteasome inhibition stabilizes NCoR1 in a site-specific manner and restrains mitochondrial activity by repressing CREB-sensitive genes. In conclusion, this functional map of nuclear proteolysis links chromatin architecture with local protein stability and identifies proteolytic derepression as highly dynamic in regulating the transcription of genes involved in energy metabolism.

Synthetic Lethal and Resistance Interactions with BET Bromodomain Inhibitors in Triple-Negative Breast Cancer.

BET bromodomain inhibitors (BBDIs) are candidate therapeutic agents for triple-negative breast cancer (TNBC) and other cancer types, but inherent and acquired resistance to BBDIs limits their potential clinical use. Using CRISPR and small-molecule inhibitor screens combined with comprehensive molecular profiling of BBDI response and resistance, we identified synthetic lethal interactions with BBDIs and genes that, when deleted, confer resistance. We observed synergy with regulators of cell cycle progression, YAP, AXL, and SRC signaling, and chemotherapeutic agents. We also uncovered functional similarities and differences among BRD2, BRD4, and BRD7. Although deletion of BRD2 enhances sensitivity to BBDIs, BRD7 loss leads to gain of TEAD-YAP chromatin binding and luminal features associated with BBDI resistance. Single-cell RNA-seq, ATAC-seq, and cellular barcoding analysis of BBDI responses in sensitive and resistant cell lines highlight significant heterogeneity among samples and demonstrate that BBDI resistance can be pre-existing or acquired.

Tet3 CXXC domain and dioxygenase activity cooperatively regulate key genes for Xenopus eye and neural development.

Ten-Eleven Translocation (Tet) family of dioxygenases dynamically regulates DNA methylation and has been implicated in cell lineage differentiation and oncogenesis. Yet their functions and mechanisms of action in gene regulation and embryonic development are largely unknown. Here, we report that Xenopus Tet3 plays an essential role in early eye and neural development by directly regulating a set of key developmental genes. Tet3 is an active 5mC hydroxylase regulating the 5mC/5hmC status at target gene promoters. Biochemical and structural studies further demonstrate that the Tet3 CXXC domain is critical for specific Tet3 targeting. Finally, we show that the enzymatic activity and CXXC domain are both crucial for Tet3's biological function. Together, these findings define Tet3 as a transcription regulator and reveal a molecular mechanism by which the 5mC hydroxylase and DNA binding activities of Tet3 cooperate to control target gene expression and embryonic development.

Efficient and accurate KIR and HLA genotyping with massively parallel sequencing data.

Killer cell immunoglobulin like receptor (KIR) genes and human leukocyte antigen (HLA) genes play important roles in innate and adaptive immunity. They are highly polymorphic and cannot be genotyped with standard variant calling pipelines. Compared with HLA genes, many KIR genes are similar to each other in sequences and may be absent in the chromosomes. Therefore, although many tools have been developed to genotype HLA genes using common sequencing data, none of them work for KIR genes. Even specialized KIR genotypers could not resolve all the KIR genes. Here we describe T1K, a novel computational method for the efficient and accurate inference of KIR or HLA alleles from RNA-seq, whole-genome sequencing, or whole-exome sequencing data. T1K jointly considers alleles across all genotyped genes, so it can reliably identify present genes and distinguish homologous genes, including the challenging KIR2DL5A/KIR2DL5B genes. This model also benefits HLA genotyping, where T1K achieves high accuracy in benchmarks. Moreover, T1K can call novel single-nucleotide variants and process single-cell data. Applying T1K to tumor single-cell RNA-seq data, we found that KIR2DL4 expression was enriched in tumor-specific CD8+ T cells. T1K may open the opportunity for HLA and KIR genotyping across various sequencing applications.

MIRA: joint regulatory modeling of multimodal expression and chromatin accessibility in single cells.

Rigorously comparing gene expression and chromatin accessibility in the same single cells could illuminate the logic of how coupling or decoupling of these mechanisms regulates fate commitment. Here we present MIRA, probabilistic multimodal models for integrated regulatory analysis, a comprehensive methodology that systematically contrasts transcription and accessibility to infer the regulatory circuitry driving cells along cell state trajectories. MIRA leverages topic modeling of cell states and regulatory potential modeling of individual gene loci. MIRA thereby represents cell states in an efficient and interpretable latent space, infers high-fidelity cell state trees, determines key regulators of fate decisions at branch points and exposes the variable influence of local accessibility on transcription at distinct loci. Applied to epidermal differentiation and embryonic brain development from two different multimodal platforms, MIRA revealed that early developmental genes were tightly regulated by local chromatin landscape whereas terminal fate genes were titrated without requiring extensive chromatin remodeling.

Inhibition of EZH2 transactivation function sensitizes solid tumors to genotoxic stress.

Drugs that block the activity of the methyltransferase EZH2 are in clinical development for the treatment of non-Hodgkin lymphomas harboring EZH2 gain-of-function mutations that enhance its polycomb repressive function. We have previously reported that EZH2 can act as a transcriptional activator in castration-resistant prostate cancer (CRPC). Now we show that EZH2 inhibitors can also block the transactivation activity of EZH2 and inhibit the growth of CRPC cells. Gene expression and epigenomics profiling of cells treated with EZH2 inhibitors demonstrated that in addition to derepressing gene expression, these compounds also robustly down-regulate a set of DNA damage repair (DDR) genes, especially those involved in the base excision repair (BER) pathway. Methylation of the pioneer factor FOXA1 by EZH2 contributes to the activation of these genes, and interaction with the transcriptional coactivator P300 via the transactivation domain on EZH2 directly turns on the transcription. In addition, CRISPR-Cas9-mediated knockout screens in the presence of EZH2 inhibitors identified these BER genes as the determinants that underlie the growth-inhibitory effect of EZH2 inhibitors. Interrogation of public data from diverse types of solid tumors expressing wild-type EZH2 demonstrated that expression of DDR genes is significantly correlated with EZH2 dependency and cellular sensitivity to EZH2 inhibitors. Consistent with these findings, treatment of CRPC cells with EZH2 inhibitors dramatically enhances their sensitivity to genotoxic stress. These studies reveal a previously unappreciated mechanism of action of EZH2 inhibitors and provide a mechanistic basis for potential combination cancer therapies.

Stromal cell diversity associated with immune evasion in human triple-negative breast cancer.

The tumour stroma regulates nearly all stages of carcinogenesis. Stromal heterogeneity in human triple-negative breast cancers (TNBCs) remains poorly understood, limiting the development of stromal-targeted therapies. Single-cell RNA sequencing of five TNBCs revealed two cancer-associated fibroblast (CAF) and two perivascular-like (PVL) subpopulations. CAFs clustered into two states: the first with features of myofibroblasts and the second characterised by high expression of growth factors and immunomodulatory molecules. PVL cells clustered into two states consistent with a differentiated and immature phenotype. We showed that these stromal states have distinct morphologies, spatial relationships and functional properties in regulating the extracellular matrix. Using cell signalling predictions, we provide evidence that stromal-immune crosstalk acts via a diverse array of immunoregulatory molecules. Importantly, the investigation of gene signatures from inflammatory-CAFs and differentiated-PVL cells in independent TNBC patient cohorts revealed strong associations with cytotoxic T-cell dysfunction and exclusion, respectively. Such insights present promising candidates to further investigate for new therapeutic strategies in the treatment of TNBCs.

TRUST4: immune repertoire reconstruction from bulk and single-cell RNA-seq data.

We introduce the TRUST4 open-source algorithm for reconstruction of immune receptor repertoires in αß/γδ T cells and B cells from RNA-sequencing (RNA-seq) data. Compared with competing methods, TRUST4 supports both FASTQ and BAM format and is faster and more sensitive in assembling longer-even full-length-receptor repertoires. TRUST4 can also call repertoire sequences from single-cell RNA-seq (scRNA-seq) data without V(D)J enrichment, and is compatible with both SMART-seq and 5' 10x Genomics platforms.

Androgen receptor regulates a distinct transcription program in androgen-independent prostate cancer.

The evolution of prostate cancer from an androgen-dependent state to one that is androgen-independent marks its lethal progression. The androgen receptor (AR) is essential in both, though its function in androgen-independent cancers is poorly understood. We have defined the direct AR-dependent target genes in both androgen-dependent and -independent cancer cells by generating AR-dependent gene expression profiles and AR cistromes. In contrast to what is found in androgen-dependent cells, AR selectively upregulates M-phase cell-cycle genes in androgen-independent cells, including UBE2C, a gene that inactivates the M-phase checkpoint. We find that epigenetic marks at the UBE2C enhancer, notably histone H3K4 methylation and FoxA1 transcription factor binding, are present in androgen-independent cells and direct AR-enhancer binding and UBE2C activation. Thus, the role of AR in androgen-independent cancer cells is not to direct the androgen-dependent gene expression program without androgen, but rather to execute a distinct program resulting in androgen-independent growth.

TISMO: syngeneic mouse tumor database to model tumor immunity and immunotherapy response.

Syngeneic mouse models are tumors derived from murine cancer cells engrafted on genetically identical mouse strains. They are widely used tools for studying tumor immunity and immunotherapy response in the context of a fully functional murine immune system. Large volumes of syngeneic mouse tumor expression profiles under different immunotherapy treatments have been generated, although a lack of systematic collection and analysis makes data reuse challenging. We present Tumor Immune Syngeneic MOuse (TISMO), a database with an extensive collection of syngeneic mouse model profiles with interactive visualization features. TISMO contains 605 in vitro RNA-seq samples from 49 syngeneic cancer cell lines across 23 cancer types, of which 195 underwent cytokine treatment. TISMO also includes 1518 in vivo RNA-seq samples from 68 syngeneic mouse tumor models across 19 cancer types, of which 832 were from immune checkpoint blockade (ICB) studies. We manually annotated the sample metadata, such as cell line, mouse strain, transplantation site, treatment, and response status, and uniformly processed and quality-controlled the RNA-seq data. Besides data download, TISMO provides interactive web interfaces to investigate whether specific gene expression, pathway enrichment, or immune infiltration level is associated with differential immunotherapy response. TISMO is available at http://tismo.cistrome.org.

Molecular and cellular features of CTLA-4 blockade for relapsed myeloid malignancies after transplantation.

Relapsed myeloid disease after allogeneic stem cell transplantation (HSCT) remains largely incurable. We previously demonstrated the potent activity of immune checkpoint blockade in this clinical setting with ipilimumab or nivolumab. To define the molecular and cellular pathways by which CTLA-4 blockade with ipilimumab can reinvigorate an effective graft-versus-leukemia (GVL) response, we integrated transcriptomic analysis of leukemic biopsies with immunophenotypic profiling of matched peripheral blood samples collected from patients treated with ipilimumab following HSCT on the Experimental Therapeutics Clinical Trials Network 9204 trial. Response to ipilimumab was associated with transcriptomic evidence of increased local CD8+ T-cell infiltration and activation. Systemically, ipilimumab decreased naïve and increased memory T-cell populations and increased expression of markers of T-cell activation and costimulation such as PD-1, HLA-DR, and ICOS, irrespective of response. However, responding patients were characterized by higher turnover of T-cell receptor sequences in peripheral blood and showed increased expression of proinflammatory chemokines in plasma that was further amplified by ipilimumab. Altogether, these data highlight the compositional T-cell shifts and inflammatory pathways induced by ipilimumab both locally and systemically that associate with successful GVL outcomes. This trial was registered at www.clinicaltrials.gov as #NCT01822509.