Evidence map›Paper›PMID 25116943›Full record

ArticleGenome biology2014

Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer.

Nicole M White, Christopher R Cabanski, Jessica M Silva-Fisher, Ha X Dang, Ramaswamy Govindan, Christopher A Maher

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 142 papers.

0numbers the graph read from it
0cells of the map it votes in
142citing papers in PubMed
9.4field-weighted citation impact, top 1% 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

142 citing papers in PubMed, 219 citations in OpenAlex.

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  15. bioRxiv : the preprint server for biology · 2024
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82 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 1 country.

Nicole M White
Christopher R Cabanski
Jessica M Silva-Fisher
Ha X Dang
Ramaswamy Govindan
Christopher A Maher
Washington University in St. Louis · USAlvin J. Siteman Cancer Center

Funding

Large Scale Genome SequencingU54HG003079 · NHGRI · WASHINGTON UNIVERSITY · PI DUTCHER, SUSAN K · 2004 to 2016
$445.7M
MOLECULAR ONCOLOGY TRAINING GRANTT32CA113275 · NCI · WASHINGTON UNIVERSITY · PI Matthew J Walter · 2006 to 2026
$5.7M
NCI NIH HHS T32 CA113275NHGRI NIH HHS U54 HG003079
6 · The paper itself

Abstract

backgroundLong intergenic non-coding RNAs (lncRNAs) represent an emerging and under-studied class of transcripts that play a significant role in human cancers. Due to the tissue- and cancer-specific expression patterns observed for many lncRNAs it is believed that they could serve as ideal diagnostic biomarkers. However, until each tumor type is examined more closely, many of these lncRNAs will remain elusive.

resultsHere we characterize the lncRNA landscape in lung cancer using publicly available transcriptome sequencing data from a cohort of 567 adenocarcinoma and squamous cell carcinoma tumors. Through this compendium we identify over 3,000 unannotated intergenic transcripts representing novel lncRNAs. Through comparison of both adenocarcinoma and squamous cell carcinomas with matched controls we discover 111 differentially expressed lncRNAs, which we term lung cancer-associated lncRNAs (LCALs). A pan-cancer analysis of 324 additional tumor and adjacent normal pairs enable us to identify a subset of lncRNAs that display enriched expression specific to lung cancer as well as a subset that appear to be broadly deregulated across human cancers. Integration of exome sequencing data reveals that expression levels of many LCALs have significant associations with the mutational status of key oncogenes in lung cancer. Functional validation, using both knockdown and overexpression, shows that the most differentially expressed lncRNA, LCAL1, plays a role in cellular proliferation.

conclusionsOur systematic characterization of publicly available transcriptome data provides the foundation for future efforts to understand the role of LCALs, develop novel biomarkers, and improve knowledge of lung tumor biology.

Indexed as

TranscriptomeAdenocarcinomaCarcinoma, Squamous CellDatabases, GeneticExomeHumansLung NeoplasmsMolecular Sequence DataOncogene ProteinsRNA, Long NoncodingSequence Analysis, DNASequence Analysis, RNAOncogene ProteinsRNA, Long Noncoding

Identifiers

PMID25116943
PMCPMC4156652
OpenAlexW2100441605

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LicenceCC BY
Read underepoch 390

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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.