Co-localization of clusters of TCR-regulated genes with TAD rearrangements.

BACKGROUND: Gene expression has long been known to be influenced by the relative proximity of DNA regulatory elements. Topologically associating domains (TADs) are self-interacting genomic regions involved in regulating gene expression by controlling the proximity of these elements. Prior studies of TADs and their biological roles have revealed correlations between TAD changes and cellular differentiation. Here, we used Hi-C and RNA-seq data to correlate TCR-induced changes in TAD structure and gene expression in human CD4+ T cells. RESULTS: We developed a pipeline, Differentially Expressed Gene Enrichment Finder (DEGEF), that identifies regions of differentially expressed gene enrichment. Using DEGEF, we found that TCR-regulated genes cluster non-uniformly across the genome and that these clusters preferentially localized in regions of TAD rearrangement. Interestingly, clusters of upregulated genes preferentially formed new Hi-C contacts compared to downregulated clusters, suggesting that TCR-activated CD4+ T cells may regulate genes by changing stimulatory contacts rather than inhibitory contacts. CONCLUSIONS: Our observations support a significant relationship between TAD rearrangements and changes in local gene expression. These findings indicate potentially important roles for TAD rearrangements in shaping their local regulatory environments and thus driving differential expression of nearby genes during CD4+ T cell activation. Moreover, they provide new insights into global mechanisms that regulate gene expression.

Cancer aneuploidies are shaped primarily by effects on tumour fitness.

Aneuploidies-whole-chromosome or whole-arm imbalances-are the most prevalent alteration in cancer genomes1,2. However, it is still debated whether their prevalence is due to selection or ease of generation as passenger events1,2. Here we developed a method, BISCUT, that identifies loci subject to fitness advantages or disadvantages by interrogating length distributions of telomere- or centromere-bounded copy-number events. These loci were significantly enriched for known cancer driver genes, including genes not detected through analysis of focal copy-number events, and were often lineage specific. BISCUT identified the helicase-encoding gene WRN as a haploinsufficient tumour-suppressor gene on chromosome 8p, which is supported by several lines of evidence. We also formally quantified the role of selection and mechanical biases in driving aneuploidy, finding that rates of arm-level copy-number alterations are most highly correlated with their effects on cellular fitness1,2. These results provide insight into the driving forces behind aneuploidy and its contribution to tumorigenesis.

Tangent normalization for somatic copy-number inference in cancer genome analysis.

MOTIVATION: Somatic copy-number alterations (SCNAs) play an important role in cancer development. Systematic noise in sequencing and array data present a significant challenge to the inference of SCNAs for cancer genome analyses. As part of The Cancer Genome Atlas, the Broad Institute Genome Characterization Center developed the Tangent normalization method to generate copy-number profiles using data from single-nucleotide polymorphism (SNP) arrays and whole-exome sequencing (WES) technologies for over 10 000 pairs of tumors and matched normal samples. Here, we describe the Tangent method, which uses a unique linear combination of normal samples as a reference for each tumor sample, to subtract systematic errors that vary across samples. We also describe a modification of Tangent, called Pseudo-Tangent, which enables denoising through comparisons between tumor profiles when few normal samples are available. RESULTS: Tangent normalization substantially increases signal-to-noise ratios (SNRs) compared to conventional normalization methods in both SNP array and WES analyses. Tangent and Pseudo-Tangent normalizations improve the SNR by reducing noise with minimal effect on signal and exceed the contribution of other steps in the analysis such as choice of segmentation algorithm. Tangent and Pseudo-Tangent are broadly applicable and enable more accurate inference of SCNAs from DNA sequencing and array data. AVAILABILITY AND IMPLEMENTATION: Tangent is available at https://github.com/broadinstitute/tangent and as a Docker image (https://hub.docker.com/r/broadinstitute/tangent). Tangent is also the normalization method for the copy-number pipeline in Genome Analysis Toolkit 4 (GATK4). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Analysis of KIR gene variants in The Cancer Genome Atlas and UK Biobank using KIRCLE.

BACKGROUND: Natural killer (NK) cells represent a critical component of the innate immune system's response against cancer and viral infections, among other diseases. To distinguish healthy host cells from infected or tumor cells, killer immunoglobulin receptors (KIR) on NK cells bind and recognize Human Leukocyte Antigen (HLA) complexes on their target cells. However, NK cells exhibit great diversity in their mechanism of activation, and the outcomes of their activation are not yet understood fully. Just like the HLAs they bind, KIR receptors exhibit high allelic diversity in the human population. Here we provide a method to identify KIR allele variants from whole exome sequencing data and uncover novel associations between these variants and various molecular and clinical correlates. RESULTS: In order to better understand KIRs, we have developed KIRCLE, a novel method for genotyping individual KIR genes from whole exome sequencing data, and used it to analyze approximately sixty-thousand patient samples in The Cancer Genome Atlas (TCGA) and UK Biobank. We were able to assess population frequencies for different KIR alleles and demonstrate that, similar to HLA alleles, individuals' KIR alleles correlate strongly with their ethnicities. In addition, we observed associations between different KIR alleles and HLA alleles, including HLA-B*53 with KIR3DL2*013 (Fisher's exact FDR = 7.64e-51). Finally, we showcased statistically significant associations between KIR alleles and various clinical correlates, including peptic ulcer disease (Fisher's exact FDR = 0.0429) and age of onset of atopy (Mann-Whitney U FDR = 0.0751). CONCLUSIONS: We show that KIRCLE is able to infer KIR variants accurately and consistently, and we demonstrate its utility using data from approximately sixty-thousand individuals from TCGA and UK Biobank to discover novel molecular and clinical correlations with KIR germline variants. Peptic ulcer disease and atopy are just two diseases in which NK cells may play a role beyond their "classical" realm of anti-tumor and anti-viral responses. This tool may be used both as a benchmark for future KIR-variant-inference algorithms, and to better understand the immunogenomics of and disease processes involving KIRs.

Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway.

RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(-) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(-) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(-) cases are required to understand this important LUAD subset.

Loss of wild type KRAS in KRASMUT lung adenocarcinoma is associated with cancer mortality and confers sensitivity to FASN inhibitors.

OBJECTIVES: Wild type RAS (RASWT) suppresses the function of oncogenic RAS mutants (RASMUT) in laboratory models. Loss of RASWT, which we termed loss of heterozygosity (LOH) for any RAS (LAR) or LAKR in the context of KRAS (LOH at KRAS), is found in patients with RASMUT cancers. However, the incidence and prognostic significance of LAR has not been studied in modern patient cohorts. LAR or LAKR in RASMUT cancers is attractive as a potential biomarker for targeted therapy. MATERIALS AND METHODS: We evaluated for associations between LAKR and cancer mortality in patients with KRASMUT lung adenocarcinoma (LUAD). We also evaluated for associations between LAKR and the metabolic state of cancer cell lines, given that KRAS has been shown to regulate fatty acid synthesis. In line with this, we investigated fatty acid synthase (FASN) inhibitors as potential therapies for KRASMUT LAKR, including combination strategies involving clinical KRASG12C and FASN inhibitors. RESULTS: 24 % of patients with KRASMUT LUAD showed LAKR. KRASMUT LAKR cases had a median survival of 16 vs. 30 months in KRASMUT non-LAKR (p =  0.017) and LAKR was independently associated with death in this cohort (p =  0.011). We also found that KRASMUT LUAD cell lines with LAKR contained elevated levels of FASN and fatty acids relative to non-LAKR cell lines. KRASMUT LUAD cells with LAKR showed higher sensitivity to treatment with FASN inhibitors than those without. FASN inhibitors such as TVB-3664 showed synergistic effects with the KRASG12C inhibitor MRTX849 in LUAD cells with KRASG12C and LAKR, including an in vivo trial using a xenograft model. CONCLUSIONS: LAKR in KRASMUT cancers may represent an independent negative prognostic factor for patients with KRASMUT LUAD. It also predicts for response to treatment with FASN inhibitors. Prospective testing of combination therapies including KRASG12C and FASN inhibitors in patients with KRASG12C LAKR is warranted.

Loss of heterozygosity of essential genes represents a widespread class of potential cancer vulnerabilities.

Alterations in non-driver genes represent an emerging class of potential therapeutic targets in cancer. Hundreds to thousands of non-driver genes undergo loss of heterozygosity (LOH) events per tumor, generating discrete differences between tumor and normal cells. Here we interrogate LOH of polymorphisms in essential genes as a novel class of therapeutic targets. We hypothesized that monoallelic inactivation of the allele retained in tumors can selectively kill cancer cells but not somatic cells, which retain both alleles. We identified 5664 variants in 1278 essential genes that undergo LOH in cancer and evaluated the potential for each to be targeted using allele-specific gene-editing, RNAi, or small-molecule approaches. We further show that allele-specific inactivation of either of two essential genes (PRIM1 and EXOSC8) reduces growth of cells harboring that allele, while cells harboring the non-targeted allele remain intact. We conclude that LOH of essential genes represents a rich class of non-driver cancer vulnerabilities.

Mechanistic insights into cancer cell killing through interaction of phosphodiesterase 3A and schlafen family member 12.

Cytotoxic molecules can kill cancer cells by disrupting critical cellular processes or by inducing novel activities. 6-(4-(Diethylamino)-3-nitrophenyl)-5-methyl-4,5-dihydropyridazin-3(2H)-one (DNMDP) is a small molecule that kills cancer cells by generation of novel activity. DNMDP induces complex formation between phosphodiesterase 3A (PDE3A) and schlafen family member 12 (SLFN12) and specifically kills cancer cells expressing elevated levels of these two proteins. Here, we examined the characteristics and covariates of the cancer cell response to DNMDP. On average, the sensitivity of human cancer cell lines to DNMDP is correlated with PDE3A expression levels. However, DNMDP could also bind the related protein, PDE3B, and PDE3B supported DNMDP sensitivity in the absence of PDE3A expression. Although inhibition of PDE3A catalytic activity did not account for DNMDP sensitivity, we found that expression of the catalytic domain of PDE3A in cancer cells lacking PDE3A is sufficient to confer sensitivity to DNMDP, and substitutions in the PDE3A active site abolish compound binding. Moreover, a genome-wide CRISPR screen identified the aryl hydrocarbon receptor-interacting protein (AIP), a co-chaperone protein, as required for response to DNMDP. We determined that AIP is also required for PDE3A-SLFN12 complex formation. Our results provide mechanistic insights into how DNMDP induces PDE3A-SLFN12 complex formation, thereby killing cancer cells with high levels of PDE3A and SLFN12 expression.

Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons' Data.

We present a systematic analysis of the effects of synchronizing a large-scale, deeply characterized, multi-omic dataset to the current human reference genome, using updated software, pipelines, and annotations. For each of 5 molecular data platforms in The Cancer Genome Atlas (TCGA)-mRNA and miRNA expression, single nucleotide variants, DNA methylation and copy number alterations-comprehensive sample, gene, and probe-level studies were performed, towards quantifying the degree of similarity between the 'legacy' GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as 'harmonized' by the Genomic Data Commons. We offer gene lists to elucidate differences that remained after controlling for confounders, and strategies to mitigate their impact on biological interpretation. Our results demonstrate that the hg19 and hg38 TCGA datasets are very highly concordant, promote informed use of either legacy or harmonized omics data, and provide a rubric that encourages similar comparisons as new data emerge and reference data evolve.

Identification of ADAR1 adenosine deaminase dependency in a subset of cancer cells.

Systematic exploration of cancer cell vulnerabilities can inform the development of novel cancer therapeutics. Here, through analysis of genome-scale loss-of-function datasets, we identify adenosine deaminase acting on RNA (ADAR or ADAR1) as an essential gene for the survival of a subset of cancer cell lines. ADAR1-dependent cell lines display increased expression of interferon-stimulated genes. Activation of type I interferon signaling in the context of ADAR1 deficiency can induce cell lethality in non-ADAR1-dependent cell lines. ADAR deletion causes activation of the double-stranded RNA sensor, protein kinase R (PKR). Disruption of PKR signaling, through inactivation of PKR or overexpression of either a wildtype or catalytically inactive mutant version of the p150 isoform of ADAR1, partially rescues cell lethality after ADAR1 loss, suggesting that both catalytic and non-enzymatic functions of ADAR1 may contribute to preventing PKR-mediated cell lethality. Together, these data nominate ADAR1 as a potential therapeutic target in a subset of cancers.

The Immune Landscape of Cancer.

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-ß dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.

Genomic and Functional Approaches to Understanding Cancer Aneuploidy.

Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy.

Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas.

DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic response. We systematically analyzed somatic alterations to provide a comprehensive view of DDR deficiency across 33 cancer types. Mutations with accompanying loss of heterozygosity were observed in over 1/3 of DDR genes, including TP53 and BRCA1/2. Other prevalent alterations included epigenetic silencing of the direct repair genes EXO5, MGMT, and ALKBH3 in ∼20% of samples. Homologous recombination deficiency (HRD) was present at varying frequency in many cancer types, most notably ovarian cancer. However, in contrast to ovarian cancer, HRD was associated with worse outcomes in several other cancers. Protein structure-based analyses allowed us to predict functional consequences of rare, recurrent DDR mutations. A new machine-learning-based classifier developed from gene expression data allowed us to identify alterations that phenocopy deleterious TP53 mutations. These frequent DDR gene alterations in many human cancers have functional consequences that may determine cancer progression and guide therapy.

Somatic Superenhancer Duplications and Hotspot Mutations Lead to Oncogenic Activation of the KLF5 Transcription Factor.

The Krüppel-like family of transcription factors plays critical roles in human development and is associated with cancer pathogenesis. Krüppel-like factor 5 gene (KLF5) has been shown to promote cancer cell proliferation and tumorigenesis and to be genomically amplified in cancer cells. We recently reported that the KLF5 gene is also subject to other types of somatic coding and noncoding genomic alterations in diverse cancer types. Here, we show that these alterations activate KLF5 by three distinct mechanisms: (i) Focal amplification of superenhancers activates KLF5 expression in squamous cell carcinomas; (ii) Missense mutations disrupt KLF5-FBXW7 interactions to increase KLF5 protein stability in colorectal cancer; (iii) Cancer type-specific hotspot mutations within a zinc-finger DNA binding domain of KLF5 change its DNA binding specificity and reshape cellular transcription. Utilizing data from CRISPR/Cas9 gene knockout screening, we reveal that cancer cells with KLF5 overexpression are dependent on KLF5 for their proliferation, suggesting KLF5 as a putative therapeutic target.Significance: Our observations, together with previous studies that identified oncogenic properties of KLF5, establish the importance of KLF5 activation in human cancers, delineate the varied genomic mechanisms underlying this occurrence, and nominate KLF5 as a putative target for therapeutic intervention in cancer. Cancer Discov; 8(1); 108-25. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 1.