Evidence map›Paper›PMID 31672930›Full record

ArticleAging2019

Identifying hub genes of clear cell renal cell carcinoma associated with the proportion of regulatory T cells by weighted gene co-expression network analysis.

Ye-Hui Chen, Shao-Hao Chen, Jian Hou, Zhi-Bin Ke, Yu-Peng Wu, Ting-Ting Lin, Yong Wei, Xue-Yi Xue, Qing-Shui Zheng, Jin-Bei Huang and 1 more

Abstract readValidation Study
In one paragraph

Article in Aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

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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

13 citing papers in PubMed.

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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

11 authors.

Ye-Hui ChenDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Shao-Hao ChenDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Jian HouDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Zhi-Bin KeDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Yu-Peng WuDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Ting-Ting LinDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Yong WeiDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Xue-Yi XueDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Qing-Shui ZhengDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Jin-Bei HuangDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Ning XuDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNumerous patients with clear cell renal cell carcinoma (ccRCC) experience drug resistance after immunotherapy. Regulatory T (Treg) cells may work as a suppressor for anti-tumor immune response. PURPOSE: We performed bioinformatics analysis to better understand the role of Treg cells in ccRCC.

resultsModule 10 revealed the most relevance with Treg cells. Functional annotation showed that biological processes and pathways were mainly related to activation of the immune system and the processes of immunoreaction. Four hub genes were selected: LCK, MAP4K1, SLAMF6, and RHOH. Further validation showed that the four hub genes well-distinguished tumor and normal tissues and were good prognostic biomarkers for ccRCC.

conclusionThe identified hub genes facilitate our knowledge of the underlying molecular mechanism of how Treg cells affect ccRCC in anti-tumor immune therapy.

methodsThe CIBERSORT algorithm was performed to evaluate tumor-infiltrating immune cells based on the Cancer Genome Atlas cohort. Weighted gene co-expression network analysis was conducted to explore the modules related to Treg cells. Gene Ontology analysis and pathway enrichment analysis were performed for functional annotation and a protein-protein interaction network was built. Samples from the International Cancer Genomics Consortium database was used as a validation set.

Indexed as

T-Lymphocytes, RegulatoryAdultAgedAged, 80 and overAlgorithmsBiomarkers, TumorCarcinoma, Renal CellFemaleGene Regulatory NetworksHumansKidney NeoplasmsLymphocyte Specific Protein Tyrosine Kinase p56(lck)MaleMiddle AgedProtein Interaction MapsProtein Serine-Threonine KinasesBiomarkers, Tumorhematopoietic progenitor kinase 1LCK protein, humanLymphocyte Specific Protein Tyrosine Kinase p56(lck)Protein Serine-Threonine Kinasesrho GTP-Binding ProteinsRhoH protein, humanSignaling Lymphocytic Activation Molecule FamilySLAMF6 protein, humanTranscription Factorsanti-tumor immuneccRCChub genesTreg cellsweighted gene co-expression network analysis

Identifiers

PMID31672930
PMCPMC6874443

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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.