Evidence map›Paper›PMID 29805765›Full record

ArticleOncotarget2018

Global isoform-specific transcript alterations and deregulated networks in clear cell renal cell carcinoma.

Michael J Hamilton, Thomas Girke, Ernest Martinez

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
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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

3 authors at 1 institution in 1 country.

Michael J HamiltonDepartment of Biochemistry, University of California at Riverside, Riverside, CA, USA.
Thomas GirkeDepartment of Botany and Plant Sciences, University of California at Riverside, Riverside, CA, USA.
Ernest MartinezDepartment of Biochemistry, University of California at Riverside, Riverside, CA, USA.
University of California, Riverside · US

Funding

Functional characterization of the long non-coding RNA Scirocco in development anR01CA158540 · NCI · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI MARTINEZ, ERNEST · 2012 to 2017
$1.5M
Acquisition of a Scalable Storage Cluster for Data Intensive NIH ResearchS10OD016290 · OD · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI GIRKE, THOMAS · 2014 to 2014
$593k
NCI NIH HHS R01 CA158540
6 · The paper itself

Abstract

Extensive genome-wide analyses of deregulated gene expression have now been performed for many types of cancer. However, most studies have focused on deregulation at the gene-level, which may overlook the alterations of specific transcripts for a given gene. Clear cell renal cell carcinoma (ccRCC) is one of the best-characterized and most pervasive renal cancers, and ccRCCs are well-documented to have aberrant RNA processing. In the present study, we examine the extent of aberrant isoform-specific RNA expression by reporting a comprehensive transcript-level analysis, using the new kallisto-sleuth-RATs pipeline, investigating coding and non-coding differential transcript expression in ccRCC. We analyzed 50 ccRCC tumors and their matched normal samples from The Cancer Genome Altas datasets. We identified 7,339 differentially expressed transcripts and 94 genes exhibiting differential transcript isoform usage in ccRCC. Additionally, transcript-level coexpression network analyses identified vasculature development and the tricarboxylic acid cycle as the most significantly deregulated networks correlating with ccRCC progression. These analyses uncovered several uncharacterized transcripts, including lncRNAs

Indexed as

cancerccRCCkallistosleuthtranscript

Identifiers

PMID29805765
PMCPMC5955119
OpenAlexW2799657582

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.