Evidence map›Paper›PMID 25592567›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2015

Integrative genome-wide analysis of the determinants of RNA splicing in kidney renal clear cell carcinoma.

Kjong-Van Lehmann, André Kahles, Cyriac Kandoth, William Lee, Nikolaus Schultz, Oliver Stegle, Gunnar Rätsch

Open access · greenAbstract read
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact, top 67% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

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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

7 authors at 2 institutions in 2 countries.

Kjong-Van LehmannComputational Biology Center, Memorial Kettering Cancer Center, New York, NY 10044, U.S.A.
André Kahles
Cyriac Kandoth
William Lee
Nikolaus Schultz
Oliver Stegle
Gunnar Rätsch
Memorial Sloan Kettering Cancer Center · USEuropean Bioinformatics Institute · GB

Funding

Identifying and validating novel susceptibility genes for breast cancerR01CA176785 · NCI · MAYO CLINIC ROCHESTER · PI COUCH, FERGUS JOSEPH, NATHANSON, KATHERINE L. · 2014 to 2018
$3.4M
NCI NIH HHS 1R01CA176785-01A1NCI NIH HHS R01 CA176785
6 · The paper itself

Abstract

We present a genome-wide analysis of splicing patterns of 282 kidney renal clear cell carcinoma patients in which we integrate data from whole-exome sequencing of tumor and normal samples, RNA-seq and copy number variation. We proposed a scoring mechanism to compare splicing patterns in tumor samples to normal samples in order to rank and detect tumor-specific isoforms that have a potential for new biomarkers. We identified a subset of genes that show introns only observable in tumor but not in normal samples, ENCODE and GEUVADIS samples. In order to improve our understanding of the underlying genetic mechanisms of splicing variation we performed a large-scale association analysis to find links between somatic or germline variants with alternative splicing events. We identified 915 cis- and trans-splicing quantitative trait loci (sQTL) associated with changes in splicing patterns. Some of these sQTL have previously been associated with being susceptibility loci for cancer and other diseases. Our analysis also allowed us to identify the function of several COSMIC variants showing significant association with changes in alternative splicing. This demonstrates the potential significance of variants affecting alternative splicing events and yields insights into the mechanisms related to an array of disease phenotypes.

Indexed as

RNA SplicingAlternative SplicingBiomarkers, TumorCarcinoma, Renal CellComputational BiologyExomeGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyHumansIntronsKidney NeoplasmsQuantitative Trait LociSequence Analysis, RNABiomarkers, Tumor

Identifiers

PMID25592567
PMCPMC4333684
OpenAlexW2950913899

What OpenQuestion holds

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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.