Demo Faculty

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 …

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 …

Immune checkpoint blockade (ICB) therapy revolutionized cancer treatment, but many patients with impaired MHC-I expression remain refractory. Here, we combined FACS-based genome-wide CRISPR screens with a data-mining approach to identify drugs that can upregulate MHC-I without inducing PD-L1. CRISPR screening identified TRAF3, a suppressor of the NFκB pathway, as a negative regulator of MHC-I but not PD-L1. The Traf3-knockout gene expression signature is associated with better survival in ICB-naïve patients with cancer and better ICB response. We then screened for drugs with similar transcriptional effects as this signature and identified Second Mitochondria-derived Activator of Caspase (SMAC) mimetics. We experimentally validated that the SMAC mimetic birinapant upregulates MHC-I, sensitizes cancer cells to T cell–dependent killing, and adds to ICB efficacy. Our findings provide …

A number of cancer drugs activate innate immune pathways in tumor cells but unfortunately also compromise antitumor immune function. We discovered that inhibition of CARM1, an epigenetic enzyme and cotranscriptional activator, elicited beneficial antitumor activity in both cytotoxic T cells and tumor cells. In T cells, Carm1 inactivation substantially enhanced their antitumor function and preserved memory-like populations required for sustained antitumor immunity. In tumor cells, Carm1 inactivation induced a potent type 1 interferon response that sensitized resistant tumors to cytotoxic T cells. Substantially increased numbers of dendritic cells, CD8 T cells, and natural killer cells were present in Carm1-deficient tumors, and infiltrating CD8 T cells expressed low levels of exhaustion markers. Targeting of CARM1 with a small molecule elicited potent antitumor immunity and sensitized resistant tumors …

c-MYC (MYC) is a major driver of prostate cancer tumorigenesis and progression. Although MYC is overexpressed in both early and metastatic disease and associated with poor survival, its impact on prostate transcriptional reprogramming remains elusive. We demonstrate that MYC overexpression significantly diminishes the androgen receptor (AR) transcriptional program (the set of genes directly targeted by the AR protein) in luminal prostate cells without altering AR expression. Importantly, analyses of clinical specimens revealed that concurrent low AR and high MYC transcriptional programs accelerate prostate cancer progression toward a metastatic, castration-resistant disease. Data integration of single-cell transcriptomics together with ChIP-seq revealed an increased RNA polymerase II (Pol II) promoter-proximal pausing at AR-dependent genes following MYC overexpression without an accompanying deactivation of AR-bound enhancers. Altogether, our findings suggest that MYC overexpression antagonizes the canonical AR transcriptional program and contributes to prostate tumor initiation and progression by disrupting transcriptional pause release at AR-regulated genes.

A number of cancer drugs activate innate immune pathways in tumor cells but unfortunately also compromise anti-tumor immune function. We discovered that inhibition of Carm1, an epigenetic enzyme and co-transcriptional activator, elicited beneficial anti-tumor activity in both cytotoxic T cells and tumor cells. In T cells, Carm1 inactivation substantially enhanced their anti-tumor function and preserved memory-like populations required for sustained anti-tumor immunity. In tumor cells, Carm1 inactivation induced a potent type 1 interferon response that sensitized resistant tumors to cytotoxic T cells. Substantially increased numbers of dendritic cells, CD8 T cells and NK cells were present in Carm1-deficient tumors, and infiltrating CD8 T cells expressed low levels of exhaustion markers. Targeting of Carm1 with a small molecule elicited potent anti-tumor immunity and sensitized resistant tumors to checkpoint blockade …

Cancer immunotherapy shows limited efficacy against many solid tumors that originate from epithelial tissues, including triple-negative breast cancer (TNBC). We identify the SOX4 transcription factor as an important resistance mechanism to T cell-mediated cytotoxicity for TNBC cells. Mechanistic studies demonstrate that inactivation of SOX4 in tumor cells increases the expression of genes in a number of innate and adaptive immune pathways important for protective tumor immunity. Expression of SOX4 is regulated by the integrin αvβ6 receptor on the surface of tumor cells, which activates TGFβ from a latent precursor. An integrin αvβ6/8-blocking monoclonal antibody (mAb) inhibits SOX4 expression and sensitizes TNBC cells to cytotoxic T cells. This integrin mAb induces a substantial survival benefit in highly metastatic murine TNBC models poorly responsive to PD-1 blockade. Targeting of the integrin αvβ6-TGFβ …

A number of cancer drugs activate innate immune pathways in tumor cells but unfortunately also compromise anti-tumor immune function. We discovered that inhibition of Carm1, an epigenetic enzyme and co-transcriptional activator, elicited beneficial anti-tumor activity in both cytotoxic T cells and tumor cells. In T cells, Carm1 inactivation substantially enhanced their anti-tumor function and preserved memory-like populations required for sustained anti-tumor immunity. In tumor cells, Carm1 inactivation induced a potent type 1 interferon response that sensitized resistant tumors to cytotoxic T cells. Substantially increased numbers of dendritic cells, CD8 T cells and NK cells were present in Carm1-deficient tumors, and infiltrating CD8 T cells expressed low levels of exhaustion markers. Targeting of Carm1 with a small molecule elicited potent anti-tumor immunity and sensitized resistant tumors to checkpoint blockade …

Targeted protein degradation (TPD) has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cell9s endogenous protein degradation machinery. However, the susceptibility of proteins for targeting by TPD approaches, termed "degradability", is largely unknown. Recent systematic studies to map the degradable kinome have shown differences in degradation between kinases with similar drug-target engagement, suggesting yet unknown factors influencing degradability. We therefore developed a machine learning model, MAPD (Model-based Analysis of Protein Degradability), to predict degradability from protein features that encompass post-translational modifications, protein stability, protein expression and protein-protein interactions. MAPD shows accurate performance in predicting kinases that are degradable by TPD compounds (auPRC=0.759) and is likely generalizable to independent non-kinase proteins. We found five features with statistical significance to achieve optimal prediction, with ubiquitination potential being the most predictive. By structural modeling, we found that E2-accessible ubiquitination sites, but not lysine residues in general, are particularly associated with kinase degradability. Finally, we extended MAPD predictions to the entire proteome to find 964 disease-causing proteins, including 278 cancer genes, that may be tractable to TPD drug development.

Understanding the impact of regulatory variants on complex phenotypes is a significant challenge because the genes and pathways that are targeted by such variants are typically unknown. Furthermore, a regulatory variant might influence a particular gene9s expression in a cell type or tissue-specific manner. Cell-type specific long-range regulatory interactions that occur between a distal regulatory sequence and a gene offers a powerful framework for understanding the impact of regulatory variants on complex phenotypes. However, high-resolution maps of such long-range interactions are available only for a handful of model cell lines. To address this challenge, we have developed L-HiC-Reg, a Random Forests based regression method to predict high-resolution contact counts in new cell lines, and a network-based framework to identify candidate cell line-specific gene networks targeted by a set of variants from a Genome-wide association study (GWAS). We applied our approach to predict interactions in 55 Roadmap Epigenome Consortium cell lines, which we used to interpret regulatory SNPs in the NHGRI GWAS catalogue. Using our approach, we performed an in-depth characterization of fifteen different phenotypes including Schizophrenia, Coronary Artery Disease (CAD) and Crohn9s disease. In CAD, we found differentially wired subnetworks consisting of known as well as novel gene targets of regulatory SNPs. Taken together, our compendium of interactions and associated network-based analysis pipeline offers a powerful resource to leverage long-range regulatory interactions to examine the context-specific impact of regulatory …

Targeted protein degradation (TPD) has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cell9s endogenous protein degradation machinery. However, the susceptibility of proteins for targeting by TPD approaches, termed "degradability", is largely unknown. Recent systematic studies to map the degradable kinome have shown differences in degradation between kinases with similar drug-target engagement, suggesting yet unknown factors influencing degradability. We therefore developed a machine learning model, MAPD (Model-based Analysis of Protein Degradability), to predict degradability from protein features that encompass post-translational modifications, protein stability, protein expression and protein-protein interactions. MAPD shows accurate performance in predicting kinases that are degradable by TPD compounds (auPRC=0.759) and is likely generalizable to independent non-kinase proteins. We found five features with statistical significance to achieve optimal prediction, with ubiquitination potential being the most predictive. By structural modeling, we found that E2-accessible ubiquitination sites, but not lysine residues in general, are particularly associated with kinase degradability. Finally, we extended MAPD predictions to the entire proteome to find 964 disease-causing proteins, including 278 cancer genes, that may be tractable to TPD drug development.

Understanding the impact of regulatory variants on complex phenotypes is a significant challenge because the genes and pathways that are targeted by such variants are typically unknown. Furthermore, a regulatory variant might influence a particular gene9s expression in a cell type or tissue-specific manner. Cell-type specific long-range regulatory interactions that occur between a distal regulatory sequence and a gene offers a powerful framework for understanding the impact of regulatory variants on complex phenotypes. However, high-resolution maps of such long-range interactions are available only for a handful of model cell lines. To address this challenge, we have developed L-HiC-Reg, a Random Forests based regression method to predict high-resolution contact counts in new cell lines, and a network-based framework to identify candidate cell line-specific gene networks targeted by a set of variants from a Genome-wide association study (GWAS). We applied our approach to predict interactions in 55 Roadmap Epigenome Consortium cell lines, which we used to interpret regulatory SNPs in the NHGRI GWAS catalogue. Using our approach, we performed an in-depth characterization of fifteen different phenotypes including Schizophrenia, Coronary Artery Disease (CAD) and Crohn9s disease. In CAD, we found differentially wired subnetworks consisting of known as well as novel gene targets of regulatory SNPs. Taken together, our compendium of interactions and associated network-based analysis pipeline offers a powerful resource to leverage long-range regulatory interactions to examine the context-specific impact of regulatory …

Blood malignancies provide unique opportunities for longitudinal tracking of disease evolution following therapeutic bottlenecks and for the monitoring of changes in anti-tumor immunity. The expanding development of multi-modal single-cell sequencing technologies affords newer platforms to elucidate the mechanisms underlying these processes at unprecedented resolution. Furthermore, the identification of molecular events that can serve as in-vivo barcodes now facilitate the tracking of the trajectories of malignant and of immune cell populations over time within primary human samples, as these permit unambiguous identification of the clonal lineage of cell populations within heterogeneous phenotypes. Here, we provide an overview of the potential for chromosomal copy number changes, somatic nuclear and mitochondrial DNA mutations, single nucleotide polymorphisms, and T and B cell receptor sequences …

While cancers evolve during disease progression and in response to therapy, temporal dynamics remain difficult to study in humans due to the lack of consistent barcodes marking individual clones in vivo. We employ mitochondrial single-cell assay for transposase-accessible chromatin with sequencing to profile 163,279 cells from 9 patients with chronic lymphocytic leukemia (CLL) collected across disease course and utilize mitochondrial DNA (mtDNA) mutations as natural genetic markers of cancer clones. We observe stable propagation of mtDNA mutations over years in the absence of strong selective pressure indicating clonal persistence, but dramatic changes following tight bottlenecks including disease transformation and relapse post-therapy, paralleled by acquisition of copy number variants, changes in chromatin accessibility and gene expression. Furthermore, we link CLL subclones to distinct chromatin …

Understanding the impact of regulatory variants on complex phenotypes is a significant challenge because the genes and pathways that are targeted by such variants and the cell type context in which regulatory variants operate are typically unknown. Cell-type-specific long-range regulatory interactions that occur between a distal regulatory sequence and a gene offer a powerful framework for examining the impact of regulatory variants on complex phenotypes. However, high-resolution maps of such long-range interactions are available only for a handful of cell types. Furthermore, identifying specific gene subnetworks or pathways that are targeted by a set of variants is a significant challenge. We have developed L-HiC-Reg, a Random Forests regression method to predict high-resolution contact counts in new cell types, and a network-based framework to identify candidate cell-type-specific gene networks targeted by a set of variants from a genome-wide association study (GWAS). We applied our approach to predict interactions in 55 Roadmap Epigenomics Mapping Consortium cell types, which we used to interpret regulatory single nucleotide polymorphisms (SNPs) in the NHGRI-EBI GWAS catalogue. Using our approach, we performed an in-depth characterization of fifteen different phenotypes including schizophrenia, coronary artery disease (CAD) and Crohn’s disease. We found differentially wired subnetworks consisting of known as well as novel gene targets of regulatory SNPs. Taken together, our compendium of interactions and the associated network-based analysis pipeline leverages long-range regulatory interactions to examine the …

While cancers evolve during disease progression and in response to therapy, temporal dynamics remain difficult to study in humans due to the lack of consistent barcodes marking individual clones in vivo. We employ mitochondrial single-cell assay for transposase-accessible chromatin with sequencing to profile 163,279 cells from 9 patients with chronic lymphocytic leukemia (CLL) collected across disease course and utilize mitochondrial DNA (mtDNA) mutations as natural genetic markers of cancer clones. We observe stable propagation of mtDNA mutations over years in the absence of strong selective pressure indicating clonal persistence, but dramatic changes following tight bottlenecks including disease transformation and relapse post-therapy, paralleled by acquisition of copy number variants, changes in chromatin accessibility and gene expression. Furthermore, we link CLL subclones to distinct chromatin …

Immunoprofiling to identify biomarkers and integration with clinical trials outcome are critical to improve immunotherapy approaches for cancer patients. However, the translational potential of individual studies is often limited by small sample size of trials and the complexity of immuno-oncology biomarkers. Variability in assays further limits comparison and interpretation of data across studies and laboratories. To enable a systematic approach to biomarker identification and correlation with clinical outcome across trials, the Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC) Network was established through support of the Cancer MoonshotSM Initiative of the National Cancer Institute and the Partnership for Accelerating Cancer Therapies (PACT) with industry partners via the Foundation for the National Institutes of Health. The CIMAC-CIDC Network is composed …

In near-eye display systems that support three-dimensional (3D) augmented and virtual reality, a central factor in determining the user experience is the size of the eyebox. The eyebox refers to a volume where the eye receives an acceptable view of the image with respect to a set of criteria and thresholds. The size and location of this volume are primarily driven by optical architecture choices in which designers trade-off a number of constraints, such as field of view, image quality, and product design. It is thus important to clearly quantify how design decisions affect the properties of the eyebox. Recent work has started evaluating the eyebox in 3D based purely on optical criteria. However, such analyses do not incorporate perceptual criteria that determine visual quality, which are particularly important for binocular 3D systems. To address this limitation, we introduce the framework of a perceptual eyebox. The …

We developed Lisa (http://lisa.cistrome.org/) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the input gene sets, Lisa first uses histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the regulation of these genes. Using TR ChIP-seq peaks or imputed TR binding sites, Lisa probes the chromatin models using in silico deletion to find the most relevant TRs. Applied to gene sets derived from targeted TF perturbation experiments, Lisa boosted the performance of imputed TR cistromes and outperformed alternative methods in identifying the perturbed TRs.

Immune checkpoint blockade (ICB) therapy has improved patient survival in a variety of cancers, but only a minority of cancer patients respond. Multiple studies have sought to identify general biomarkers of ICB response, but elucidating the molecular and cellular drivers of resistance for individual tumors remains challenging. We sought to determine whether a tumor with defined genetic background exhibits a stereotypic or heterogeneous response to ICB treatment. We establish a unique mouse system that utilizes clonal tracing and mathematical modeling to monitor the growth of each cancer clone, as well as the bulk tumor, in response to ICB. We find that tumors derived from the same clonal populations showed heterogeneous ICB response and diverse response patterns. Primary response is associated with higher immune infiltration and leads to enrichment of pre-existing ICB-resistant cancer clones. We further …