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Immunotherapy has had a tremendous impact on cancer treatment in the past decade, with hitherto unseen responses at advanced and metastatic stages of the disease. However, the aggressive brain tumor glioblastoma (GBM) is highly immunosuppressive and remains largely refractory to current immunotherapeutic approaches. The stimulator of interferon genes (STING) DNA sensing pathway has emerged as a next-generation immunotherapy target with potent local immune stimulatory properties. Here, we investigated the status of the STING pathway in GBM and the modulation of the brain tumor microenvironment (TME) with the STING agonist ADU-S100. Our data reveal the presence of STING in human GBM specimens, where it stains strongly in the tumor vasculature. We show that human GBM explants can respond to STING agonist treatment by secretion of inflammatory cytokines. In murine GBM models, we show a profound shift in the tumor immune landscape after STING agonist treatment, with massive infiltration of the tumor-bearing hemisphere with innate immune cells including inflammatory macrophages, neutrophils, and natural killer (NK) populations. Treatment of established murine intracranial GL261 and CT-2A tumors by biodegradable ADU-S100–loaded intracranial implants demonstrated a significant increase in survival in both models and long-term survival with immune memory in GL261. Responses to treatment were abolished by NK cell depletion. This study reveals therapeutic potential and deep remodeling of the TME by STING activation in GBM and warrants further examination of STING agonists alone or in combination with other immunotherapies such as cancer vaccines, chimeric antigen receptor T cells, NK therapies, and immune checkpoint blockade.

A comprehensive understanding of the molecular vulnerabilities of every type of cancer will provide a powerful roadmap to guide therapeutic approaches. Efforts such as The Cancer Genome Atlas Project will identify genes with aberrant copy number, sequence, or expression in various cancer types, providing a survey of the genes that may have a causal role in cancer. A complementary approach is to perform systematic loss-of-function studies to identify essential genes in particular cancer cell types. We have begun a systematic effort, termed Project Achilles, aimed at identifying genetic vulnerabilities across large numbers of cancer cell lines. Here, we report the assessment of the essentiality of 11,194 genes in 102 human cancer cell lines. We show that the integration of these functional data with information derived from surveying cancer genomes pinpoints known and previously undescribed lineage-specific dependencies across a wide spectrum of cancers. In particular, we found 54 genes that are specifically essential for the proliferation and viability of ovarian cancer cells and also amplified in primary tumors or differentially overexpressed in ovarian cancer cell lines. One such gene, PAX8, is focally amplified in 16% of high-grade serous ovarian cancers and expressed at higher levels in ovarian tumors. Suppression of PAX8 selectively induces apoptotic cell death of ovarian cancer cells. These results identify PAX8 as an ovarian lineage-specific dependency. More generally, these observations demonstrate that the integration of genome-scale functional and structural studies provides an efficient path to identify dependencies of specific cancer types on particular genes and pathways.

BackgroundImmune checkpoint inhibitors have revolutionized cancer treatment, but the benefits in refractory patients with esophageal cancer have been modest. Predictors of response as well as new targets for novel therapeutic combinations are needed. In this phase 2 clinical trial, we tested single-agent pembrolizumab in patients with advanced esophageal cancer, who received at least one prior line of therapy.MethodsPembrolizumab 200 mg every 3 weeks was tested in 49 patients with refractory esophageal cancer: 39 with adenocarcinoma and 10 with esophageal squamous cell carcinoma. Major endpoints were radiological response by Immune-related Response Evaluation Criteria In Solid Tumors and survival. Tumor samples were evaluated for programmed cell death ligand 1 (PD-L1) expression, tumor mutational burden (TMB), and immune contexture by both NanoString mRNA expression analysis and flow cytometry. Peripheral blood mononuclear cells and a panel of circulating chemokines were also analyzed.ResultsThe overall response rate (ORR) was 8% (4 of 49 patients; 95% CI 2.3% to 19.6%). Median overall survival (OS) was 5.8 months (95% CI 4.0 to 9.5). ORR and OS were not associated with histology. For PD-L1-positive patients, ORR was 13.3% (95% CI 1.7% to 40.5%) and median OS was 7.9 months (95% CI 4.7 to 15.5). A trend toward improved OS was observed in seven patients with a TMB ≥10 mut/Mb (p=0.086). Tumors with a PD-L1 Combined Positive Score ≥1 showed enrichment of LAG3 (p=0.005) and IDO1 (p=0.04) gene expression. Baseline levels of circulating CXCL10, interleukin 2 (IL2) receptor α (IL2RA) and IL6 were associated with survival: CXCL10 favorably, (HR 0.37, p=0.002 (progression-free survival); HR 0.55, p=0.018 (OS)); IL2RA and IL6 unfavorably (HR 1.57, p=0.020 for IL6 (OS); HR 2.36, p=0.025 for IL2RA (OS)).ConclusionsPembrolizumab monotherapy was modestly effective in refractory esophageal cancer. Circulating CXCL10 at baseline appeared to be a robust predictor of response. Other T cell exhaustion markers are upregulated in PD-L1-positive patients, suggesting that immunotherapy combinations such as anti-LAG3/programmed cell death protein 1 (PD-1) or anti-IDO1/PD-1 may be of promise in refractory esophageal cancer.

Liquid biopsy is a promising non-invasive technology that is capable of diagnosing cancer. However, current ctDNA-based approaches detect only a minority of early-stage disease. We set out to improve the sensitivity of liquid biopsy by harnessing tumor recognition by T cells through the sequencing of the circulating T-cell receptor repertoire. We studied a cohort of 463 patients with lung cancer (86% stage I) and 587 subjects without cancer using gDNA extracted from blood buffy coats. We performed TCR β chain sequencing to yield a median of 113,571 TCR clonotypes per sample and built a TCR sequence similarity graph to cluster clonotypes into TCR repertoire functional units (RFUs). The TCR frequencies of RFUs were tested for association with cancer status and RFUs with a statistically significant association were combined into a cancer score using a support vector machine model. The model was evaluated by 10-fold cross-validation and compared with a ctDNA panel of 237 mutation hotspots in 154 lung cancer driver genes and 17 cancer related protein biomarkers in 85 subjects. We identified 327 cancer-associated TCR RFUs with a false discovery rate (FDR) ≤ 0.1, including 157 enriched in cancer samples and 170 enriched in controls. Levels of 247/327 (76%) RFUs were correlated with the presence of an HLA allele at FDR ≤ 0.1 and tumor-infiltrating lymphocyte TCRs from multiple RFUs bound HLA presented tumor antigen peptides, suggesting antigen recognition as a driver of the cancer-RFU associations found. The RFU cancer score detected nearly 50% of stage I lung cancers at a specificity of 80% and boosted the sensitivity by up to 20 percentage points when added to ctDNA and circulating proteins in a multi-analyte cancer screening test. Overall, we show that circulating TCR repertoire functional unit analysis can complement established analytes to improve liquid biopsy sensitivity for early-stage cancer.

The zinc-finger transcription factor Helios is critical for maintaining the identity, anergic phenotype and suppressive activity of regulatory T (T reg ) cells. While it is an attractive target to enhance the efficacy of currently approved immunotherapies, no existing approaches can directly modulate Helios activity or abundance. Here, we report the structure-guided development of small molecules that recruit the E3 ubiquitin ligase substrate receptor cereblon to Helios, thereby promoting its degradation. Pharmacological Helios degradation destabilized the anergic phenotype and reduced the suppressive activity of T reg cells, establishing a route towards Helios-targeting therapeutics. More generally, this study provides a framework for the development of small-molecule degraders for previously unligandable targets by reprogramming E3 ligase substrate specificity. Two degraders targeting zinc finger transcription factor IKZF2 (Helios) were developed by reprogramming CRL4 CRBN E3 ligase, and the pharmacologic degradation of Helios results in T reg destabilization.

Programming T cells to distinguish self from non-self is a vital, multi-step process that occurs in the thymus 1 – 4 . Signalling through the pre-T cell receptor (preTCR), a CD3-associated heterodimer comprising an invariant pTα chain and a clone-specific β chain, is a critical early checkpoint in thymocyte development within the αβ T cell lineage 5 , 6 . PreTCRs arrayed on CD4 − CD8 − double-negative thymocytes ligate peptides bound to major histocompatibility complex molecules (pMHC) on thymic stroma, similar to αβ T cell receptors that appear on CD4 + CD8 + double-positive thymocytes, but via a different molecular docking strategy 7 – 10 . Here we show the consequences of these distinct interactions for thymocyte progression using synchronized fetal thymic progenitor cultures that differ in the presence or absence of pMHC on support stroma, and single-cell transcriptomes at key thymocyte developmental transitions. Although major histocompatibility complex (MHC)-negative stroma fosters αβ T cell differentiation, the absence of preTCR–pMHC interactions leads to deviant thymocyte transcriptional programming associated with dedifferentiation. Highly proliferative double-negative and double-positive thymocyte subsets emerge, with antecedent characteristics of T cell lymphoblastic and myeloid malignancies. Compensatory upregulation of diverse MHC class Ib proteins in B2m / H2-Ab1 MHC-knockout mice partially safeguards in vivo thymocyte progression, although disseminated double-positive thymic tumours may develop with ageing. Thus, as well as promoting β chain repertoire broadening for subsequent αβ T cell receptor utilization, preTCR–pMHC interactions limit cellular plasticity to facilitate normal thymocyte differentiation and proliferation that, if absent, introduce developmental vulnerabilities. Aberrant thymocyte developmental programming results when interactions between thymic stroma and pre-T cell receptors occur in the absence of major histocompatibility complex bound to antigen peptide.

Resistance to oncogene-targeted therapies involves discrete drug-tolerant persister cells, originally discovered through in vitro assays. Whether a similar phenomenon limits efficacy of programmed cell death 1 (PD-1) blockade is poorly understood. Here, we performed dynamic single-cell RNA-Seq of murine organotypic tumor spheroids undergoing PD-1 blockade, identifying a discrete subpopulation of immunotherapy persister cells (IPCs) that resisted CD8+ T cell-mediated killing. These cells expressed Snai1 and stem cell antigen 1 (Sca-1) and exhibited hybrid epithelial-mesenchymal features characteristic of a stem cell-like state. IPCs were expanded by IL-6 but were vulnerable to TNF-α-induced cytotoxicity, relying on baculoviral IAP repeat-containing protein 2 (Birc2) and Birc3 as survival factors. Combining PD-1 blockade with Birc2/3 antagonism in mice reduced IPCs and enhanced tumor cell killing in vivo, resulting in durable responsiveness that matched TNF cytotoxicity thresholds in vitro. Together, these data demonstrate the power of high-resolution functional ex vivo profiling to uncover fundamental mechanisms of immune escape from durable anti-PD-1 responses, while identifying IPCs as a cancer cell subpopulation targetable by specific therapeutic combinations.

Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,000 shRNAs after 16 population doublings using Next Generation Sequencing. All the cell lines were screened using standardized conditions to best assess differential genetic dependencies across cell lines. When combined with genomic characterization of these cell lines, this dataset facilitates the linkage of genetic dependencies with specific cellular contexts (e.g., gene mutations or cell lineage). To enable such comparisons, we developed and provided a bioinformatics tool to identify linear and nonlinear correlations between these features. Design Type(s) genotyping design • cell type comparison design • RNAi screening • loss-of-function screening by pooled shRNA Measurement Type(s) SNP interrogation genotyping • cell viability assay Technology Type(s) microfluidics platform • next generation sequencing Factor Type(s) Tumor Subtype • Growth Medium • Doubling Time • Study Personnel Sample Characteristic(s) Homo sapiens • A2780 cell • BJHTERT • C2BBe1 cell • COLO-783 • EFO-21 cell • GP2D cell • IGROV-1 cell • JHESOAD1 • KM12 • LN215 • LN319 • LN382 • NCI-H1792 cell • OAW42 cell • RMGI • SK-CO-1 cell • SLR24 • TCCSUP cell • THP-1 cell • TOV-21G cell • TT cell • 22RV1 cell • 697 cell • 786-O cell • A1207 • A172 cell • A-204 cell • A2058 cell • A549 cell • A673 cell • ACHN cell • AGS cell • AM38 • AML-193 cell • AsPC-1 cell • BT-20 cell • BT-474 cell • BT-549 cell • BxPC-3 cell • C32 cell • CADO-ES1 cell • CAKI-1 cell • CAL-120 cell • CAL-51 cell • CALU-1 cell • CAOV-3 cell • CAOV-4 cell • CAS-1 cell • CFPAC-1 • CH157MN • COLO205 • COLO-704 • COLO741 • COR-L23 cell • COV318 • COV362 • COV434 • COV504 • COV644 • DBTRG-05MG cell • DK-MG cell • DLD-1 cell • DU4475 cell • EFE-184 cell • EFM-19 cell • EFO-27 cell • EJM • EW8 • EWS502 • F36P • F5 cell • FU-OV-1 cell • GB1 • GCIY • GMS-10 cell • HCC1187 cell • HCC1395 cell • HCC1954 cell • HCC2218 cell • HCC2814 • HCC364 • HCC44 • HCC70 cell • HCC827 cell • HCC827GR5 • HCT116 • HCT116G9B • HEC-1-A cell • HEYA8 • HL-60 cell • HLF • HNT34 • HPAC cell • HPAF-II cell • HS683 • HS766T • HS944T • HT-1197 cell • HT-29 cell • HT55 cell • HUG1N • HUTU80 • IGR-39 cell • IOMMLEE • JHOC5 • JHOM1 • JHOS4 • JJN3 • K-562 cell • KALS1 • KASUMI-1 cell • KMS11 • KMS12BM • KMS20 • KMS26 • KMS34 • KNS60 • KNS81 • KP1NL • KP2 • KP4 • KURAMOCHI • KYSE-150 cell • KYSE-30 cell • KYSE-450 cell • KYSE-510 cell • L33 • L-363 cell • LAMA-84 cell • LK2 • LN-229 cell • LN235 • LN340 • LN428 • LN443 • LN464 • LNZ308 • LOVO cell • LP-1 cell • LS411N cell • LS513 cell • MCF7 cell • MDA-MB-453 cell • MIAPACA2 • MKN7 • MM1S • MOLM13 • MONO-MAC-1 cell • MONO-MAC-6 cell • MV-4-11 cell • NALM-6 cell • NB-4 cell • NCI-H1299 cell • NCI-H1437 cell • NCI-H1650 cell • NCI-H196 cell • NCI-H1975 cell • NCI-H2052 cell • NCI-H2122 cell • NCI-H2171 cell • NCI-H23 cell • NCI-H2452 cell • NCI-H441 cell • NCI-H508 cell • NCI-H524 cell • NCI-H660 cell • NCI-H661 cell • NCI-H716 cell • NCI-H82 cell • NCI-H838 cell • NCI-N87 cell • NIHOVCAR3 • NOMO1 • OCI-AML2 cell • OCIAML3 • OCI-AML5 cell • OE33 cell • OELE • OPM-2 cell • OV7 • OV-90 cell • OVCAR4 • OVCAR8 • OVISE • OVMANA • PANC0327 • PANC0813 • PANC1005 • PLB-985 cell • PSN1 cell • QGP1 • REH cell • RKN • RKO cell • RMUGS • RPE101 • RPE1A4D • RPE74 • RPMI8226 • RS411 • RT112 cell • SEM • SF126 • SF172 • SF295 • SF767 • SJSA-1 cell • SK-MEL-5 cell • SK-MM-2 cell • SKNO1 • SK-OV-3 cell • SKRC20 • SKRC31 • SLR20 • SLR21 • SLR23 • SLR25 • SLR26 • SNU1105 • SNU201 • SNU840 • SNU-C1 cell • SNU-C2A cell • SU8686 • SW 1417 cell • SW1783 • SW1990 • SW48 cell • SW480 cell • T98G cell • TC32 • TC71 • TE10 • TE15 cell • TE9 • TOV-112D cell • TYKNU • U178 • U251MG • U-343 Mga cell • U87MG • UOK101 • VCAP • YKG1 • ZR-75-30 cell Machine-accessible metadata file describing the reported data (ISA-Tab format)

With the emergence of checkpoint blockade and other immunotherapeutic drugs, and the growing adoption of smaller, more flexible adaptive clinical trial designs, there is an unmet need to develop diagnostics that can rapidly immunophenotype patient tumors. The ability to longitudinally profile the tumor immune infiltrate in response to immunotherapy also presents a window of opportunity to illuminate mechanisms of resistance. We have developed a fine needle aspirate biopsy (FNA) platform to perform immune profiling on thoracic malignancies. Matching peripheral blood, bulk resected tumor, and FNA were analyzed from 13 mesothelioma patients. FNA samples yielded greater numbers of viable cells when compared to core needle biopsies. Cell numbers were adequate to perform flow cytometric analyses on T cell lineage, T cell activation and inhibitory receptor expression, and myeloid immunosuppressive checkpoint markers. FNA samples were representative of the tumor as a whole as assessed by head-to-head comparison to single cell suspensions of dissociated whole tumor. Parallel analysis of matched patient blood enabled us to establish quality assurance criteria to determine the accuracy of FNA procedures to sample tumor tissue. FNA biopsies provide a diagnostic to rapidly phenotype the tumor immune microenvironment that may be of great relevance to clinical trials.

BackgroundIdentification of genes modulating the intrinsic immunogenicity of tumor cells may reveal biology underlying resistance to immunotherapy. Targeting these genes pharmacologically may potentiate durable anti-tumor immunity when combined with immune checkpoint blockade. Utilizing high throughput CRISPR-Cas9 screening assays, our group and others have identified Setdb1 as a negative regulator of antigen processing and presentation. While Setdb1 as a target has been validated, a structural understanding of the protein is necessary for rational drug design. Here we present the results of a CRISPR base editor screen tiling across the protein-coding sequence of Setdb1 to identify domains regulating antigen processing and presentation in tumor cells.MethodsWe transduced B16F10-ova cells with two base editor libraries (pRDA_478 BE3.9 C>T; pRDA_479 ABE8e A>G) encompassing ~2600 sgRNAs targeting the protein coding regions of the Setdb1 gene, and including appropriate positive and negative controls. Stably BE-expressing cells were cultured +/- IFN-β for 48hr and then positively selected for surface expression of SIINFEKL peptide presented on H2-kb. sgRNA abundance in positive- and negative-sorted fractions was deconvoluted by NGS and predicted missense mutations were mapped onto a 3D projection of the Setdb1 protein.ResultsOur initial screen identified multiple missense mutations, splice site alterations, and introduction of premature termination codons that phenocopied the full Setdb1 knockout. We validated 14 hits from the initial screen through standard CRISPR-Cas9 follow-up: single sgRNA cloning, transduction, establishment of cell lines, functional validation by FACS assay of modulation of H2-Kb-SIINFEKL surface staining +/- IFN-β, and confirmation by Sanger sequencing of correct edit. Top hit inducing a missense Cys759Arg mutation reproduced from initial screen, phenocopied the immunogenicity of full Setdb1 knockout in response to IFN-β exposure, and maps to a region of Setdb1 homologous between mouse and human.ConclusionsWe performed a CRISPR base editor screen tiling across the Setdb1 gene to identify function domains of the protein that, when mutated, would enhance susceptibility to immune-mediated killing. When overlaid onto 3D structure, hits provide target domains for medicinal chemistry efforts.