Evidence map›Paper›PMID 32655621›Full record

ArticleFrontiers in genetics2020

Bioinformatics Analysis Finds Immune Gene Markers Related to the Prognosis of Bladder Cancer.

Xingyu Chen, Yi Jin, Lian Gong, Dong He, YaXing Cheng, Mengqing Xiao, Yuxing Zhu, Zhanwang Wang, Ke Cao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
6.5field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 38 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

9 authors at 3 institutions in 1 country.

Xingyu ChenDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Yi JinHunan Cancer Hospital, Xiangya School of Medicine, Central South University, Changsha, China.
Lian GongDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Dong HeDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
YaXing ChengDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Mengqing XiaoDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Yuxing ZhuDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Zhanwang WangDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Ke CaoDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Third Xiangya Hospital · CNCentral South University · CNHunan Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bladder cancer is one of the most common malignant tumors of the urinary system that seriously threatens the health of a population. In recent years, the application of immunotherapy has significantly changed the treatment of bladder cancer, but only some patients can benefit from the treatment with immune-checkpoint inhibitors. Many problems are unsolved in the field of bladder cancer immunotherapy, especially in the search for genes that are critical to the level of immune cell infiltration and new effective therapeutic targets. We attempted to use bioinformatics analysis to identify immune gene markers related to the prognosis of bladder cancer and to establish a prognostic signature for bladder cancer patients based on their immune gene expression profiles. We used univariate Cox proportional hazards regression analysis, the least absolute shrinkage and selection operator (LASSO) Cox regression, and multivariate Cox proportional hazards regression analysis from The Cancer Genome Atlas bladder cancer cohort (TCGA-BLCA). Fifteen genes related to prognosis were screened using the survival analysis, correlation analysis, cancer and adjacent cancer differential expression analysis, and mutation analysis. The potential biological role of these genes was determined using survival analysis and principal component analysis (PCA). The receiver operating characteristic (ROC) curve assesses the prognostic value of the predictive signature. The gene ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG), Gene set enrichment analysis (GSEA), and other methods were used to reveal the differential gene enrichment in the signaling pathways and cellular processes of high- and low-risk groups. The single-sample GSEA (ssGSEA) method was used to quantify the infiltration levels of 24 immune cells in the tumor immune microenvironment and these immune genes were found to be closely related to the tumor immune microenvironment. In summary, we screened 15 immune genes that were closely related to bladder cancer overall survival (OS) and may be potential prognostic indicators of bladder cancer. They may have research and clinical application value in bladder cancer immunotherapy. We used 15 immune genes to construct a new immune-related gene signature that was verified and could be helpful in improving individualized prognosis of patients with bladder cancer.

Indexed as

biomarkerbladder cancerimmune geneprognosistumor immune microenvironment

Identifiers

PMID32655621
PMCPMC7324668
OpenAlexW3037394188

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.