Evidence map›Paper›PMID 29534679›Full record

ArticleBMC cancer2018

Integrated genomic analysis identifies clinically relevant subtypes of renal clear cell carcinoma.

Peng Wu, Jia-Li Liu, Shi-Mei Pei, Chang-Peng Wu, Kai Yang, Shu-Peng Wang, Song Wu

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

23 citing papers in PubMed, 31 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 4 institutions in 1 country.

Peng WuThe Affiliated Luohu Hospital of Shenzhen University, Department of Urological Surgery, Shenzhen University, Shenzhen, 518000, China.
Jia-Li LiuShenzhen Second People'Hospital, 1st affiliated hospital of ShenZhen University, Shenzhen, 518037, China.
Shi-Mei PeiShenzhen Following Precision Medical Institute, Shenzhen Luohu Hospital Group, Shenzhen, 518000, China.
Chang-Peng WuShenzhen Second People'Hospital, 1st affiliated hospital of ShenZhen University, Shenzhen, 518037, China.
Kai YangThe Affiliated Luohu Hospital of Shenzhen University, Department of Urological Surgery, Shenzhen University, Shenzhen, 518000, China.
Shu-Peng WangThe Affiliated Luohu Hospital of Shenzhen University, Department of Urological Surgery, Shenzhen University, Shenzhen, 518000, China.
Song WuThe Affiliated Luohu Hospital of Shenzhen University, Department of Urological Surgery, Shenzhen University, Shenzhen, 518000, China. wusong@szu.edu.cn.
Shenzhen Luohu People's Hospital · CNShenzhen Second People's Hospital · CNShenzhen University · CNDalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRenal cell carcinoma (RCC) account for over 80% of renal malignancies. The most common type of RCC can be classified into three subtypes including clear cell, papillary and chromophobe. ccRCC (the Clear Cell Renal Cell Carcinoma) is the most frequent form and shows variations in genetics and behavior. To improve accuracy and personalized care and increase the cure rate of cancer, molecular typing for individuals is necessary.

methodsWe adopted the genome, transcriptome and methylation HMK450 data of ccRCC in The Cancer Genome Atlas Network in this research. Consensus Clustering algorithm was used to cluster the expression data and three subtypes were found. To further validate our results, we analyzed an independent data set and arrived at a consistent conclusion. Next, we characterized the subtype by unifying genomic and clinical dimensions of ccRCC molecular stratification. We also implemented GSEA between the malignant subtype and the other subtypes to explore latent pathway varieties and WGCNA to discover intratumoral gene interaction network. Moreover, the epigenetic state changes between subgroups on methylation data are discovered and Kaplan-Meier survival analysis was performed to delve the relation between specific genes and prognosis.

resultsWe found a subtype of poor prognosis in clear cell renal cell carcinoma, which is abnormally upregulated in focal adhesions and cytoskeleton related pathways, and the expression of core genes in the pathways are negatively correlated with patient outcomes.

conclusionsOur work of classification schema could provide an applicable framework of molecular typing to ccRCC patients which has implications to influence treatment decisions, judge biological mechanisms involved in ccRCC tumor progression, and potential future drug discovery.

Indexed as

Gene Expression Regulation, NeoplasticTranscriptomeBiomarkers, TumorCarcinoma, Renal CellFemaleFollow-Up StudiesGene Expression ProfilingGene Regulatory NetworksGenomicsHumansKidney NeoplasmsMaleMiddle AgedPrognosisSurvival RateSystems IntegrationBiomarkers, TumorccRCCGene expressionMolecular classificationPathway

Identifiers

PMID29534679
PMCPMC5851245
OpenAlexW2802381203

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Registered trials

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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.