Chromosome 7 gain compensates for chromosome 10 loss in glioma.

The co-occurrence of chromosome 10 loss and chromosome 7 gain in gliomas is the most frequent loss-gain co-aneuploidy pair in human cancers. This phenomenon has been investigated since the late 1980s without resolution. Expanding beyond previous gene-centric studies, we investigated the co-occurrence in a genome-wide manner taking an evolutionary perspective. Mining of large-scale tumor aneuploidy data confirmed the previous finding of a small-scale longitudinal study that the most likely order is chromosome 10 loss followed by chromosome 7 gain. Extensive analysis of genomic and transcriptomic data from both patients and cell lines revealed that this co-occurrence can be explained by functional rescue interactions that are highly enriched on chromosome 7, which could potentially compensate for any detrimental consequences arising from the loss of chromosome 10. Transcriptomic data from various normal, non-cancerous human brain tissues were analyzed to assess which tissues may be most predisposed to tolerate compensation of chromosome 10 loss by chromosome 7 gain. The analysis indicated that the pre-existing transcriptomic states in the cortex and frontal cortex, where gliomas arise, are more favorable than other brain regions for compensation by rescuer genes that are active on chromosome 7. Collectively, these findings suggest that the phenomenon of chromosome 10 loss and chromosome 7 gain in gliomas is orchestrated by a complex interaction of many genes residing within these two chromosomes and provide a plausible reason why this co-occurrence happens preferentially in cancers originating in certain regions of the brain.

A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. METHODS: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. RESULTS: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. CONCLUSIONS: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy. TRIAL REGISTRATION: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.

Chromosome 7 to the rescue: overcoming chromosome 10 loss in gliomas.

The co-occurrence of chromosome 10 loss and chromosome 7 gain in gliomas is the most frequent loss-gain co-aneuploidy pair in human cancers, a phenomenon that has been investigated without resolution since the late 1980s. Expanding beyond previous gene-centric studies, we investigate the co-occurrence in a genome-wide manner taking an evolutionary perspective. First, by mining large tumor aneuploidy data, we predict that the more likely order is 10 loss followed by 7 gain. Second, by analyzing extensive genomic and transcriptomic data from both patients and cell lines, we find that this co-occurrence can be explained by functional rescue interactions that are highly enriched on 7, which can possibly compensate for any detrimental consequences arising from the loss of 10. Finally, by analyzing transcriptomic data from normal, non-cancerous, human brain tissues, we provide a plausible reason why this co-occurrence happens preferentially in cancers originating in certain regions of the brain.

CRISPR screens decode cancer cell pathways that trigger γδ T cell detection.

γδ T cells are potent anticancer effectors with the potential to target tumours broadly, independent of patient-specific neoantigens or human leukocyte antigen background1-5. γδ T cells can sense conserved cell stress signals prevalent in transformed cells2,3, although the mechanisms behind the targeting of stressed target cells remain poorly characterized. Vγ9Vδ2 T cells-the most abundant subset of human γδ T cells4-recognize a protein complex containing butyrophilin 2A1 (BTN2A1) and BTN3A1 (refs. 6-8), a widely expressed cell surface protein that is activated by phosphoantigens abundantly produced by tumour cells. Here we combined genome-wide CRISPR screens in target cancer cells to identify pathways that regulate γδ T cell killing and BTN3A cell surface expression. The screens showed previously unappreciated multilayered regulation of BTN3A abundance on the cell surface and triggering of γδ T cells through transcription, post-translational modifications and membrane trafficking. In addition, diverse genetic perturbations and inhibitors disrupting metabolic pathways in the cancer cells, particularly ATP-producing processes, were found to alter BTN3A levels. This induction of both BTN3A and BTN2A1 during metabolic crises is dependent on AMP-activated protein kinase (AMPK). Finally, small-molecule activation of AMPK in a cell line model and in patient-derived tumour organoids led to increased expression of the BTN2A1-BTN3A complex and increased Vγ9Vδ2 T cell receptor-mediated killing. This AMPK-dependent mechanism of metabolic stress-induced ligand upregulation deepens our understanding of γδ T cell stress surveillance and suggests new avenues available to enhance γδ T cell anticancer activity.

A landscape of response to drug combinations in non-small cell lung cancer.

Combination of anti-cancer drugs is broadly seen as way to overcome the often-limited efficacy of single agents. The design and testing of combinations are however very challenging. Here we present a uniquely large dataset screening over 5000 targeted agent combinations across 81 non-small cell lung cancer cell lines. Our analysis reveals a profound heterogeneity of response across the tumor models. Notably, combinations very rarely result in a strong gain in efficacy over the range of response observable with single agents. Importantly, gain of activity over single agents is more often seen when co-targeting functionally proximal genes, offering a strategy for designing more efficient combinations. Because combinatorial effect is strongly context specific, tumor specificity should be achievable. The resource provided, together with an additional validation screen sheds light on major challenges and opportunities in building efficacious combinations against cancer and provides an opportunity for training computational models for synergy prediction.

Tutorial: integrative computational analysis of bulk RNA-sequencing data to characterize tumor immunity using RIMA.

RNA-sequencing (RNA-seq) has become an increasingly cost-effective technique for molecular profiling and immune characterization of tumors. In the past decade, many computational tools have been developed to characterize tumor immunity from gene expression data. However, the analysis of large-scale RNA-seq data requires bioinformatics proficiency, large computational resources and cancer genomics and immunology knowledge. In this tutorial, we provide an overview of computational analysis of bulk RNA-seq data for immune characterization of tumors and introduce commonly used computational tools with relevance to cancer immunology and immunotherapy. These tools have diverse functions such as evaluation of expression signatures, estimation of immune infiltration, inference of the immune repertoire, prediction of immunotherapy response, neoantigen detection and microbiome quantification. We describe the RNA-seq IMmune Analysis (RIMA) pipeline integrating many of these tools to streamline RNA-seq analysis. We also developed a comprehensive and user-friendly guide in the form of a GitBook with text and video demos to assist users in analyzing bulk RNA-seq data for immune characterization at both individual sample and cohort levels by using RIMA.

Discovery of Targets for Immune-Metabolic Antitumor Drugs Identifies Estrogen-Related Receptor Alpha.

Drugs that kill tumors through multiple mechanisms have the potential for broad clinical benefits. Here, we first developed an in silico multiomics approach (BipotentR) to find cancer cell-specific regulators that simultaneously modulate tumor immunity and another oncogenic pathway and then used it to identify 38 candidate immune-metabolic regulators. We show the tumor activities of these regulators stratify patients with melanoma by their response to anti-PD-1 using machine learning and deep neural approaches, which improve the predictive power of current biomarkers. The topmost identified regulator, ESRRA, is activated in immunotherapy-resistant tumors. Its inhibition killed tumors by suppressing energy metabolism and activating two immune mechanisms: (i) cytokine induction, causing proinflammatory macrophage polarization, and (ii) antigen-presentation stimulation, recruiting CD8+ T cells into tumors. We also demonstrate a wide utility of BipotentR by applying it to angiogenesis and growth suppressor evasion pathways. BipotentR (http://bipotentr.dfci.harvard.edu/) provides a resource for evaluating patient response and discovering drug targets that act simultaneously through multiple mechanisms. SIGNIFICANCE: BipotentR presents resources for evaluating patient response and identifying targets for drugs that can kill tumors through multiple mechanisms concurrently. Inhibition of the topmost candidate target killed tumors by suppressing energy metabolism and effects on two immune mechanisms. This article is highlighted in the In This Issue feature, p. 517.

INCISOR: An Algorithm to Identify Synthetic Rescue Mediators of Resistance to Targeted and Immunotherapy.

Despite the success of targeted therapies including immunotherapies in cancer treatments, tumor resistance to targeted therapies remains a fundamental challenge. Tumors can evolve resistance to a therapy that targets one gene by acquiring compensatory alterations in another gene, such compensatory interaction between two genes is referred to as synthetic rescue (SR) interactions. To identify SRs, here we describe an algorithm, INCISOR, that leverages tumor transcriptomics and clinical information from 10,000 patients as well as data from experimental screens. INCISOR can identify SRs that are common across several cancer-types in genome-wide fashion by sifting through half a billion possible gene-gene combinations and provide a framework to design therapies to tackle resistance.

Supporting the Next Generation of Scientists to Lead Cancer Immunology Research.

Recent success in the use of immunotherapy for a broad range of cancers has propelled the field of cancer immunology to the forefront of cancer research. As more and more young investigators join the community of cancer immunologists, the Arthur L. Irving Family Foundation Cancer Immunology Symposium provided a platform to bring this expanding and vibrant community together and support the development of the future leaders in the field. This commentary outlines the lessons that emerged from the inaugural symposium highlighting the areas of scientific and career development that are essential for professional growth in the field of cancer immunology and beyond. Leading scientists and clinicians in the field provided their experience on the topics of scientific trajectory, career trajectory, publishing, fundraising, leadership, mentoring, and collaboration. Herein, we provide a conceptual and practical framework for career development to the broader scientific community.

Evolution of delayed resistance to immunotherapy in a melanoma responder.

Despite initial responses1-3, most melanoma patients develop resistance4 to immune checkpoint blockade (ICB). To understand the evolution of resistance, we studied 37 tumor samples over 9 years from a patient with metastatic melanoma with complete clinical response to ICB followed by delayed recurrence and death. Phylogenetic analysis revealed co-evolution of seven lineages with multiple convergent, but independent resistance-associated alterations. All recurrent tumors emerged from a lineage characterized by loss of chromosome 15q, with post-treatment clones acquiring additional genomic driver events. Deconvolution of bulk RNA sequencing and highly multiplexed immunofluorescence (t-CyCIF) revealed differences in immune composition among different lineages. Imaging revealed a vasculogenic mimicry phenotype in NGFRhi tumor cells with high PD-L1 expression in close proximity to immune cells. Rapid autopsy demonstrated two distinct NGFR spatial patterns with high polarity and proximity to immune cells in subcutaneous tumors versus a diffuse spatial pattern in lung tumors, suggesting different roles of this neural-crest-like program in different tumor microenvironments. Broadly, this study establishes a high-resolution map of the evolutionary dynamics of resistance to ICB, characterizes a de-differentiated neural-crest tumor population in melanoma immunotherapy resistance and describes site-specific differences in tumor-immune interactions via longitudinal analysis of a patient with melanoma with an unusual clinical course.

Cell-free DNA captures tumor heterogeneity and driver alterations in rapid autopsies with pre-treated metastatic cancer.

In patients with metastatic cancer, spatial heterogeneity of somatic alterations may lead to incomplete assessment of a cancer's mutational profile when analyzing a single tumor biopsy. In this study, we perform sequencing of cell-free DNA (cfDNA) and distinct metastatic tissue samples from ten rapid autopsy cases with pre-treated metastatic cancer. We show that levels of heterogeneity in genetic biomarkers vary between patients but that gene expression signatures representative of the tumor microenvironment are more consistent. Across nine patients with plasma samples available, we are able to detect 62/62 truncal and 47/121 non-truncal point mutations in cfDNA. We observe that mutation clonality in cfDNA is correlated with the number of metastatic lesions in which the mutation is detected and use this result to derive a clonality threshold to classify truncal and non-truncal driver alterations with reasonable specificity. In contrast, mutation truncality is more often incorrectly assigned when studying single tissue samples. Our results demonstrate the utility of a single cfDNA sample relative to that of single tissue samples when treating patients with metastatic cancer.

Therapeutically Increasing MHC-I Expression Potentiates Immune Checkpoint Blockade.

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 preclinical rationale for treating tumors expressing low MHC-I expression with SMAC mimetics to enhance sensitivity to immunotherapy. The approach used in this study can be generalized to identify other drugs that enhance immunotherapy efficacy. SIGNIFICANCE: MHC-I loss or downregulation in cancer cells is a major mechanism of resistance to T cell-based immunotherapies. Our study reveals that birinapant may be used for patients with low baseline MHC-I to enhance ICB response. This represents promising immunotherapy opportunities given the biosafety profile of birinapant from multiple clinical trials.This article is highlighted in the In This Issue feature, p. 1307.

Cross-Site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms for the CIMAC-CIDC Network.

PURPOSE: Whole-exome (WES) and RNA sequencing (RNA-seq) are key components of cancer immunogenomic analyses. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the Cancer Immune Monitoring and Analysis Centers (CIMAC) and the Cancer Immunologic Data Commons (CIDC) conducted a systematic harmonization study. EXPERIMENTAL DESIGN: DNA and RNA were centrally extracted from fresh frozen and formalin-fixed paraffin-embedded non-small cell lung carcinoma tumors and distributed to three centers for WES and RNA-seq profiling. In addition, two 10-plex HapMap cell line pools with known mutations were used to evaluate the accuracy of the WES platforms. RESULTS: The WES platforms achieved high precision (> 0.98) and recall (> 0.87) on the HapMap pools when evaluated on loci using > 50× common coverage. Nonsynonymous mutations clustered by tumor sample, achieving an index of specific agreement above 0.67 among replicates, centers, and sample processing. A DV200 > 24% for RNA, as a putative presequencing RNA quality control (QC) metric, was found to be a reliable threshold for generating consistent expression readouts in RNA-seq and NanoString data. MedTIN > 30 was likewise assessed as a reliable RNA-seq QC metric, above which samples from the same tumor across replicates, centers, and sample processing runs could be robustly clustered and HLA typing, immune infiltration, and immune repertoire inference could be performed. CONCLUSIONS: The CIMAC collaborating laboratory platforms effectively generated consistent WES and RNA-seq data and enable robust cross-trial comparisons and meta-analyses of highly complex immuno-oncology biomarker data across the NCI CIMAC-CIDC Network.

Clonal tracing reveals diverse patterns of response to immune checkpoint blockade.

BACKGROUND: 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. RESULTS: 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 identify several cancer cell-intrinsic gene expression signatures associated with ICB resistance, including increased interferon response genes and glucocorticoid response genes. These findings are supported by clinical data from ICB treatment cohorts. CONCLUSIONS: Our study demonstrates diverse response patterns from the same ancestor cancer cells in response to ICB. This suggests the value of monitoring clonal constitution and tumor microenvironment over time to optimize ICB response and to design new combination therapies. Furthermore, as ICB response may enrich for cancer cell-intrinsic resistance signatures, this can affect interpretations of tumor RNA-seq data for response-signature association studies.

CRISPR Screens Identify Essential Cell Growth Mediators in BRAF Inhibitor-resistant Melanoma.

BRAF is a serine/threonine kinase that harbors activating mutations in ∼7% of human malignancies and ∼60% of melanomas. Despite initial clinical responses to BRAF inhibitors, patients frequently develop drug resistance. To identify candidate therapeutic targets for BRAF inhibitor resistant melanoma, we conduct CRISPR screens in melanoma cells harboring an activating BRAF mutation that had also acquired resistance to BRAF inhibitors. To investigate the mechanisms and pathways enabling resistance to BRAF inhibitors in melanomas, we integrate expression, ATAC-seq, and CRISPR screen data. We identify the JUN family transcription factors and the ETS family transcription factor ETV5 as key regulators of CDK6, which together enable resistance to BRAF inhibitors in melanoma cells. Our findings reveal genes contributing to resistance to a selective BRAF inhibitor PLX4720, providing new insights into gene regulation in BRAF inhibitor resistant melanoma cells.

Translational reprogramming marks adaptation to asparagine restriction in cancer.

While amino acid restriction remains an attractive strategy for cancer therapy, metabolic adaptations limit its effectiveness. Here we demonstrate a role of translational reprogramming in the survival of asparagine-restricted cancer cells. Asparagine limitation in melanoma and pancreatic cancer cells activates receptor tyrosine kinase-MAPK signalling as part of a feedforward mechanism involving mammalian target of rapamycin complex 1 (mTORC1)-dependent increase in MAPK-interacting kinase 1 (MNK1) and eukaryotic translation initiation factor 4E (eIF4E), resulting in enhanced translation of activating transcription factor 4 (ATF4) mRNA. MAPK inhibition attenuates translational induction of ATF4 and the expression of its target asparagine synthetase (ASNS), sensitizing melanoma and pancreatic tumours to asparagine restriction, reflected in inhibition of their growth. Correspondingly, low ASNS expression is among the top predictors of response to inhibitors of MAPK signalling in patients with melanoma and is associated with favourable prognosis when combined with low MAPK signalling activity. These studies reveal an axis of adaptation to asparagine deprivation and present a rationale for clinical evaluation of MAPK inhibitors in combination with asparagine restriction approaches.

Immune receptor repertoires in pediatric and adult acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML), caused by the abnormal proliferation of immature myeloid cells in the blood or bone marrow, is one of the most common hematologic malignancies. Currently, the interactions between malignant myeloid cells and the immune microenvironment, especially T cells and B cells, remain poorly characterized. METHODS: In this study, we systematically analyzed the T cell receptor and B cell receptor (TCR and BCR) repertoires from the RNA-seq data of 145 pediatric and 151 adult AML samples as well as 73 non-tumor peripheral blood samples. RESULTS: We inferred over 225,000 complementarity-determining region 3 (CDR3) sequences in TCR α, ß, γ, and δ chains and 1,210,000 CDR3 sequences in B cell immunoglobulin (Ig) heavy and light chains. We found higher clonal expansion of both T cells and B cells in the AML microenvironment and observed many differences between pediatric and adult AML. Most notably, adult AML samples have significantly higher level of B cell activation and more secondary Ig class switch events than pediatric AML or non-tumor samples. Furthermore, adult AML with highly expanded IgA2 B cells, which might represent an immunosuppressive microenvironment, are associated with regulatory T cells and worse overall survival. CONCLUSIONS: Our comprehensive characterization of the AML immune receptor repertoires improved our understanding of T cell and B cell immunity in AML, which may provide insights into immunotherapies in hematological malignancies.

Beyond Synthetic Lethality: Charting the Landscape of Pairwise Gene Expression States Associated with Survival in Cancer.

The phenotypic effect of perturbing a gene's activity depends on the activity level of other genes, reflecting the notion that phenotypes are emergent properties of a network of functionally interacting genes. In the context of cancer, contemporary investigations have primarily focused on just one type of functional relationship between two genes-synthetic lethality (SL). Here, we define the more general concept of "survival-associated pairwise gene expression states" (SPAGEs) as gene pairs whose joint expression levels are associated with survival. We describe a data-driven approach called SPAGE-finder that when applied to The Cancer Genome Atlas (TCGA) data identified 71,946 SPAGEs spanning 12 distinct types, only a minority of which are SLs. The detected SPAGEs explain cancer driver genes' tissue specificity and differences in patients' response to drugs and stratify breast cancer tumors into refined subtypes. These results expand the scope of cancer SPAGEs and lay a conceptual basis for future studies of SPAGEs and their translational applications.

Allele-specific enhancers mediate associations between LCAT and ABCA1 polymorphisms and HDL metabolism.

For most complex traits, the majority of SNPs identified through genome-wide association studies (GWAS) reside within noncoding regions that have no known function. However, these regions are enriched for the regulatory enhancers specific to the cells relevant to the specific trait. Indeed, many of the GWAS loci that have been functionally characterized lie within enhancers that regulate expression levels of key genes. In order to identify polymorphisms with potential allele-specific regulatory effects, we developed a bioinformatics pipeline that harnesses epigenetic signatures as well as transcription factor (TF) binding motifs to identify putative enhancers containing a SNP with potential allele-specific TF binding in linkage disequilibrium (LD) with a GWAS-identified SNP. We applied the approach to GWAS findings for blood lipids, revealing 7 putative enhancers harboring associated SNPs, 3 of which lie within the introns of LCAT and ABCA1, genes that play crucial roles in cholesterol biogenesis and lipoprotein metabolism. All 3 enhancers demonstrated allele-specific in vitro regulatory activity in liver-derived cell lines. We demonstrated that these putative enhancers are in close physical proximity to the promoters of their respective genes, in situ, likely through chromatin looping. In addition, the associated alleles altered the likelihood of transcription activator STAT3 binding. Our results demonstrate that through our approach, the LD blocks that contain GWAS signals, often hundreds of kilobases in size with multiple SNPs serving as statistical proxies to the true functional site, can provide an experimentally testable hypothesis for the underlying regulatory mechanism linking genetic variants to complex traits.

Gut microbiota dependent anti-tumor immunity restricts melanoma growth in Rnf5-/- mice.

Accumulating evidence points to an important role for the gut microbiome in anti-tumor immunity. Here, we show that altered intestinal microbiota contributes to anti-tumor immunity, limiting tumor expansion. Mice lacking the ubiquitin ligase RNF5 exhibit attenuated activation of the unfolded protein response (UPR) components, which coincides with increased expression of inflammasome components, recruitment and activation of dendritic cells and reduced expression of antimicrobial peptides in intestinal epithelial cells. Reduced UPR expression is also seen in murine and human melanoma tumor specimens that responded to immune checkpoint therapy. Co-housing of Rnf5-/- and WT mice abolishes the anti-tumor immunity and tumor inhibition phenotype, whereas transfer of 11 bacterial strains, including B. rodentium, enriched in Rnf5-/- mice, establishes anti-tumor immunity and restricts melanoma growth in germ-free WT mice. Altered UPR signaling, exemplified in Rnf5-/- mice, coincides with altered gut microbiota composition and anti-tumor immunity to control melanoma growth.