Evidence map›Paper›PMID 28036280›Full record

ArticleOncotarget2017

Pan-organ transcriptome variation across 21 cancer types.

Wangxiong Hu, Yanmei Yang, Xiaofen Li, Shu Zheng

Open access · diamondAbstract readComparative Study
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 10 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

4 authors at 2 institutions in 1 country.

Wangxiong HuCancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
Yanmei YangKey Laboratory of Reproductive and Genetics, Ministry of Education, Women's Hospital, Zhejiang University, Hangzhou, Zhejiang 310006, China.
Xiaofen LiCancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
Shu ZhengCancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
Zhejiang University · CNWomen's Hospital, School of Medicine, Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is widely accepted that some messenger RNAs are evolutionarily conserved across species, both in sequence and tissue-expression specificity. To date, however, little effort has been made to exploit the transcriptome divergence between cancer and adjacent normal tissue at the pan-organ level. In this work, a transcriptome sequencing dataset from 675 normal-tumor pairs, representing 21 solid organs in The Cancer Genome Atlas, is used to evaluate expression evolution. The results show that in most cancer types, gene expression divergence and organ-specificity are reduced in cancer tissue compared to adjacent normal tissue. Furthermore, we observe that all cancers share cell cycle dysregulation through interrogating differentially expressed protein coding genes. Meanwhile, weighted correlation network analysis is used to detect of the gene module structure variation between cancer and adjacent normal tissue. And modules consisting of tightly co-regulated genes in cancer change substantially compared with those in adjacent normal tissue. We thus assume that the destruction of a coordinated regulatory network might result in tumorigenesis and tumor progression. Our results provide new insights into the complex cancer biology and shed light on the mysterious regulation mode for cancer.

Indexed as

TranscriptomeBiomarkers, TumorCell Cycle CheckpointsCell Transformation, NeoplasticComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksGenetic Predisposition to DiseaseHumansNeoplasmsOrgan SpecificityPhenotypeRNA, MessengerSignal TransductionBiomarkers, TumorRNA, Messengergene expressionorgan-specific genespan-cancerweighted correlation network analysis

Identifiers

PMID28036280
PMCPMC5351671
OpenAlexW2560884962

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.