Evidence map›Paper›PMID 29208006›Full record

ArticleJournal of experimental & clinical cancer research : CR2017

Identification and validation of a 44-gene expression signature for the classification of renal cell carcinomas.

Qifeng Wang, Hualei Gan, Chengshu Chen, Yifeng Sun, Jinying Chen, Midie Xu, Weiwei Weng, Liyu Cao, Qinghua Xu, Jian Wang

Open access · goldAbstract read
In one paragraph

Article in Journal of experimental & clinical cancer research : CR, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

10 citing papers in PubMed, 26 citations in OpenAlex.

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  6. POLE2 Serves as a Prognostic Biomarker and Is Associated with Immune Infiltration in Squamous Cell Lung Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2020
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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

10 authors at 3 institutions in 2 countries.

Qifeng WangDepartment of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
Hualei GanDepartment of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
Chengshu ChenCanhelp Genomics, Hangzhou, Zhejiang, China.
Yifeng SunCanhelp Genomics, Hangzhou, Zhejiang, China.
Jinying ChenCanhelp Genomics, Hangzhou, Zhejiang, China.
Midie XuDepartment of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
Weiwei WengDepartment of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
Liyu CaoDepartment of Biomedical Engineering, University of California, Irvine, USA.
Qinghua XuCanhelp Genomics, Hangzhou, Zhejiang, China. qinghua.xu@cancerhelp.cn.
Jian WangDepartment of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China. softtissuetumor@163.com.
Shanghai Medical College of Fudan University · CNFudan University Shanghai Cancer Center · CNUniversity of California, Irvine · US

Funding

National Natural Science Foundation of China 81401963National Natural Science Foundation of China 81602078
6 · The paper itself

Abstract

backgroundRenal cancers account for more than 3% of all adult malignancies and cause more than 23,400 deaths per year in China alone. The four most common types of kidney tumours include clear cell, papillary, chromophobe and benign oncocytoma. These histological subtypes vary in their clinical course and prognosis, and different clinical strategies have been developed for their management. Some kidney tumours can be very difficult to distinguish based on the pathological assessment of morphology and immunohistochemistry.

methodsSix renal cell carcinoma microarray data sets, including 106 clear cell, 66 papillary, 42 chromophobe, 46 oncocytoma and 35 adjacent normal tissue samples, were subjected to integrative analysis. These data were combined and used as a training set for candidate gene expression signature identification. In addition, two independent cohorts of 1020 RNA-Seq samples from The Cancer Genome Atlas database and 129 qRT-PCR samples from Fudan University Shanghai Cancer Center (FUSCC) were analysed to validate the selected gene expression signature.

resultsA 44-gene expression signature derived from microarray analysis was strongly associated with the histological differentiation of renal tumours and could be used for tumour subtype classification. The signature performance was further validated in 1020 RNA-Seq samples and 129 qRT-PCR samples with overall accuracies of 93.4 and 93.0%, respectively.

conclusionsA 44-gene expression signature that could accurately discriminate renal tumour subtypes was identified in this study. Our results may prompt further development of this gene expression signature into a molecular assay amenable to routine clinical practice.

Indexed as

Carcinoma, Renal CellFemaleGene Expression ProfilingHumansMaleOligonucleotide Array Sequence AnalysisReal-Time Polymerase Chain ReactionTissue Array AnalysisGene expression profilingMicroarrayNext-generation sequencingQuantitative real-time PCRRenal cell carcinomas

Identifiers

PMID29208006
PMCPMC5717815
OpenAlexW2773775200

What OpenQuestion holds

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LicenceCC BY
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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.