Evidence map›Paper›PMID 37704602›Full record

ArticleNature communications2023

Global impact of somatic structural variation on the cancer proteome.

Fengju Chen, Yiqun Zhang, Darshan S Chandrashekar, Sooryanarayana Varambally, Chad J Creighton

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
9.6field-weighted citation impact, top 2% 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

33 citing papers in PubMed, 38 citations in OpenAlex.

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  20. An Overview of Analytical Approaches to Cancer Proteogenomics.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Fengju Chen *Dan L. Duncan Comprehensive Cancer Center Division of Biostatistics, Baylor College of Medicine, Houston, TX, USA.
Yiqun Zhang *Dan L. Duncan Comprehensive Cancer Center Division of Biostatistics, Baylor College of Medicine, Houston, TX, USA.ORCID http://orcid.org/0000-0001-5058-5623
Darshan S ChandrashekarMolecular and Cellular Pathology, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
Sooryanarayana VaramballyMolecular and Cellular Pathology, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
Chad J CreightonDan L. Duncan Comprehensive Cancer Center Division of Biostatistics, Baylor College of Medicine, Houston, TX, USA. creighto@bcm.edu.ORCID http://orcid.org/0000-0002-6090-703X
Baylor College of Medicine · USUniversity of Alabama at Birmingham · US

Funding

Tumor BiologyP30CA125123 · NCI · BAYLOR COLLEGE OF MEDICINE · PI Michael M Ittmann · 2007 to 2026
$73.9M
TRAINING AND CAREER DEVELOPMENTU54CA118948 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI UPENDER MANNE · 2005 to 2026
$26.6M
NCI NIH HHS P30 CA125123NCI NIH HHS U54 CA118948
6 · The paper itself

Abstract

Both proteome and transcriptome data can help assess the relevance of non-coding somatic mutations in cancer. Here, we combine mass spectrometry-based proteomics data with whole genome sequencing data across 1307 human tumors spanning various tissues to determine the extent somatic structural variant (SV) breakpoint patterns impact protein expression of nearby genes. We find that about 25% of the hundreds of genes with SV-associated cis-regulatory alterations at the mRNA level are similarly associated at the protein level. SVs associated with enhancer hijacking, retrotransposon translocation, altered DNA methylation, or fusion transcripts are implicated in protein over-expression. SVs combined with altered protein levels considerably extend the numbers of patients with tumors somatically altered for critical pathways. We catalog both SV breakpoint patterns involving patient survival and genes with nearby SV breakpoints associated with increased cell dependency in cancer cell lines. Pan-cancer proteogenomics identifies targetable non-coding alterations, by virtue of the associated deregulated genes.

Indexed as

NeoplasmsProteomeCell LineDNA MethylationHumansMass SpectrometryProteome

Identifiers

PMID37704602
PMCPMC10499989
OpenAlexW4386715615

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.