Evidence map›Paper›PMID 27556922›Full record

ArticleBMC genomics2016

An integrative genomics approach for identifying novel functional consequences of PBRM1 truncated mutations in clear cell renal cell carcinoma (ccRCC).

Yuanyuan Wang, Xingyi Guo, Michael J Bray, Zhiyong Ding, Zhongming Zhao

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 32 citations in OpenAlex.

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  12. The Role of DNA Methylation in Renal Cell Carcinoma.Molecular diagnosis & therapy · 2018
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Yuanyuan WangDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, 37203, USA.
Xingyi GuoDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, 37203, USA.
Michael J BrayVanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA.
Zhiyong DingDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
Zhongming ZhaoDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, 37203, USA. zhongming.zhao@uth.tmc.edu.
Vanderbilt University · USThe University of Texas MD Anderson Cancer Center · US

Funding

Mapping the Genetic Architecture of Complex Disease via RNA-seq and GWAS DataR01LM011177 · NLM · VANDERBILT UNIVERSITY · PI WANG, LILY, ZHAO, ZHONGMING · 2012 to 2014
$1.0M
MicroRNA and Transcription Factor Co-regulation in CancerR21CA196508 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHAO, ZHONGMING · 2016 to 2017
$368k
NCI NIH HHS R21 CA196508NLM NIH HHS R01 LM011177
6 · The paper itself

Abstract

backgroundClear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. Recent large-scale next-generation sequencing analyses reveal that PBRM1 is the second most frequently mutated gene harboring many truncated mutations and has a suspected tumor suppressor role in ccRCC. However, the biological consequences of PBRM1 somatic mutations (e.g., truncated mutations) that drive tumor progression in ccRCC remain unclear.

methodsIn this study, we proposed an integrative genomics approach to explore the functional consequences of PBRM1 truncated mutations in ccRCC by incorporating somatic mutations, mRNA expression, DNA methylation, and microRNA (miRNA) expression profiles from The Cancer Genome Atlas (TCGA). We performed a systematic analysis to detect the differential molecular features in a total of 11 ccRCC samples harboring PBRM1 truncated mutations from the 33 "pan-negative" ccRCC samples. We excluded the samples that had any of the five high-confidence driver genes (VHL, BAP1, SETD2, PTEN and KDM5C) reported in ccRCC to avoid their possible influence in our results.

resultsWe identified 613 differentially expressed genes (128 up-regulated and 485 down-regulated genes using cutoff |log2FC| > 1 and p < 0.05) in PBRM1 mutated group versus "pan-negative" group. The gene function enrichment analysis revealed that down-regulated genes were significantly enriched in extracellular matrix organization (adjusted p = 2.05 × 10(-7)), cell adhesion (adjusted p = 2.85 × 10(-7)), and ion transport (adjusted p = 9.97 × 10(-6)). Surprisingly, 26 transcriptional factors (TFs) genes including HOXB9, PAX6 and FOXC1 were found to be significantly differentially expressed (23 over expressed TFs and three lower expressed TFs) in PBRM1 mutated group compared with "pan-negative" group. In addition, we identified 1405 differentially methylated CpG sites (targeting 1308 genes, ||log2FC| > 1, p < 0.01) and 185 significantly altered microRNAs (|log2FC| > 1, p < 0.05) associated with truncated PBRM1 mutations. Our integrative analysis suggested that methylation and miRNA alterations were likely the downstream events associated with PBRM1 truncation mutations.

conclusionsIn summary, this study provided some important insights into the understanding of tumorigenesis driven by PBRM1 truncated mutations in ccRCC. The approach may be applied to many driver genes in various cancers.

Indexed as

GenomicsCarcinoma, Renal CellCell Transformation, NeoplasticDNA-Binding ProteinsDNA MethylationGene Expression Regulation, NeoplasticHigh-Throughput Nucleotide SequencingHumansMicroRNAsMutationNuclear ProteinsRNA, MessengerTranscription FactorsDNA-Binding ProteinsMicroRNAsNuclear ProteinsPBRM1 protein, humanRNA, MessengerTranscription FactorsClear cell renal cell carcinoma (ccRCC)Driver geneExpressionMethylationmicroRNAPBRM1

Identifiers

PMID27556922
PMCPMC5001239
OpenAlexW2517294648

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.