Dataset Information

A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples.

ABSTRACT: The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploidy, but not mutation load, suggesting a hypothesis centered on "chromatin-state" to explain their interplay. Integrating eQTL, mRNA co-expression, and Hi-C data analysis, we developed a computational method to infer causal enhancer-gene interactions, revealing enhancers of clinically actionable genes. Having identified an enhancer ?140 kb downstream of PD-L1, a major immunotherapy target, we validated it experimentally. This study provides a systematic view of enhancer activity in diverse tumor contexts and suggests the clinical implications of enhancers.

SUBMITTER: Chen H

PROVIDER: S-EPMC5890960 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples.

Chen Han H Li Chunyan C Peng Xinxin X Zhou Zhicheng Z Weinstein John N JN Liang Han H

Cell 20180401 2

The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploi ...[more]

PMID: 29625054

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Project description:Expression and differential expression analysis of breast cancer patient samples and normal samples from breast reduction operations. Fresh frozen tumor biopsies from early breast cancer cases were collected from 920 patients included in the Oslo Micrometastasis (MicMa) Study -- Oslo I from various hospitals between 1995 and 1998 (Naume et al. "Presence of bone marrow micrometastasis is associated with different recurrence risk within molecular subtypes of breast cancer." Mol Oncol 2007, 1: 160-171; Wiedswang et al. "Detection of isolated tumor cells in bone marrow is an independent prognostic factor in breast cancer." J Clin Oncol 2003, 21: 3469-3478.). Breast tissue samples from breast reduction operations were provided from the Colosseum Clinic, Oslo in co-operation with Akershus University Hospital, Lørenskog and are referred to as normal tissue. Expression and differential expression was assessed by using an Agilent custom microarray (244K, nONCOchip). The custom array contains probes for genomic regions that have been found to be differentially expressed (i) throughout cell cycle progression, (ii) in response to the anti-proliferative and pro-apoptotic p53 pathway, and (iii) the anti-apoptotic and pro-proliferative STAT-3 pathway by employing TAS (Kampa et al. "Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22". Genome Research, 14:331-42, 2004). In addition, the Agilent custom array (244K) interrogates probes for genomic regions predicted to contain a conserved secondary structure identified by RNAz (Washietl et al. "Fast and reliable prediction of noncoding RNAs." Proc Natl Acad Sci USA. 102:2454-9, 2005.) or Evofold (Pedersen et al. "Identification and classification of conserved RNA secondary structures in the human genome." PLoS Comput Biol. 2:e33, 2006.), as well as known non-coding RNAs from public databases, and the Agilent mRNA probe set 014850. We analyzed 5 to 6 arrays each for breast cancer patient samples and normal samples.

Project description:The effects of non-amplification short variant (SV) mutations in CD274 (programmed death-ligand 1 (PD-L1)) on PD-L1 protein expression and immune checkpoint inhibitors (ICPIs) therapy are unknown. Here, we present a retrospective analysis of CD274 mutations detected by comprehensive genomic profiling (CGP) and correlate these results with tumor-cell PD-L1 immunohistochemistry (IHC)-based expression assessment to better understand the relationship between mutations and protein expression of PD-L1. CGP was performed on hybridization-captured, adaptor ligation-based libraries using DNA and/or RNA extracted from 314,631 tumor samples that were sequenced for up to 406 cancer-related genes and select gene rearrangements. PD-L1 IHC was performed on a subset of cases (n=58,341) using the DAKO 22C3 PD-L1 IHC assay and scored with the tumor proportion score (TPS). Overall, the prevalence of CD274 SV mutations was low (0.3%, 1081/314,631) with 577 unique variants. The most common CD274 SV mutations were R260H (n=51), R260C (n=18), R125Q (n=12), C272fs*13 (n=11), R86W (n=10), and R113H (n=10). The prevalence of CD274 mutations varied depending on tumor type with diffuse large B-cell lymphoma (1.9%, 19/997), cutaneous squamous cell carcinoma (1.6%, 14/868), endometrial adenocarcinoma (1.0%, 36/3740), unknown primary melanoma (0.9%, 33/3679), and cutaneous melanoma (0.8%, 32/3874) having the highest frequency of mutations. Of the R260H cases concurrently tested with PD-L1 IHC, most (81.8%, 9/11) had no PD-L1 expression, which contrasts to the five E237K cases where most (80%, 4/5) had PD-L1 expression. In addition, we saw a significantly lower level of PD-L1 expression in samples with a clonal truncating variant (nonsense or frameshift indel) when compared with samples with a subclonal truncating variants (mean: TPS=1 vs TPS=38; p<0.001), and also in clonal versus subclonal missense mutations (mean: TPS=11 vs TPS=22, respectively; p=0.049) CONCLUSIONS: We defined the landscape of CD274 mutations in a large cohort of tumor types that can be used as a reference for examining CD274 mutations as potential resistance biomarkers for ICPI. Furthermore, we presented novel data on the correlation of CD274 mutations and PD-L1 protein expression, providing important new information on the potential functionality of these mutations and can serve as a basis for future research.

Dataset Information

A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples.

Publications

A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples.

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