Evidence map›Paper›PMID 32218698›Full record

ArticleInternational journal of medical sciences2020

Profiles of Immune Infiltration in Bladder Cancer and its Clinical Significance: an Integrative Genomic Analysis.

Zonglong Wu, Kejia Zhu, Qinggang Liu, Yaxiao Liu, Lipeng Chen, Jianfeng Cui, Hongda Guo, Nan Zhou, Yaofeng Zhu, Yan Li and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of medical sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 25 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

11 authors at 1 institution in 1 country.

Zonglong WuDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Kejia ZhuDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Qinggang LiuDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Yaxiao LiuDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Lipeng ChenDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Jianfeng CuiDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Hongda GuoDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Nan ZhouDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Yaofeng ZhuDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Yan LiDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Benkang ShiDepartment of Urology, Qilu Hospital of Shandong University, Jinan, P.R. China.
Qilu Hospital of Shandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor-infiltrating immune cells are closely related to the prognosis of bladder cancer. Analysis of tumor infiltrating immune cells is usually based on immunohistochemical analysis. Since many immune cell marker proteins are not specific for different immune cells, which may induce misleading or incomplete. CIBERSORT is an algorithm to estimate specific cell types in a mixed cell population using gene expression data. In this study, the CIBERSORT algorithm was used to identify the immune cell infiltration signatures. The gene expression profiles, mutation data, and clinical data were collected from The Cancer Genome Atlas (TCGA) database. Unsupervised consensus clustering was used to acquire the immune cell infiltration subtypes of bladder cancer based on the fractions of 22 immune cell types. Four immune cell clusters with different immune infiltrate and mutation characteristics were identified. In addition, this stratification has a prognostic relevance, with cluster 2 having the best outcome, cluster 1 the worst. These clusters showed distinct mRNA expression patterns. The characteristic genes in subtype cluster 1 were mainly involved in cell division, those in subtype cluster 2 were mainly related in antigen processing and presentation, those in subtype cluster 3 were mainly involved in epidermal cell differentiation, and those in subtype cluster 4 were mainly related in the humoral immune response. These differences may affect the development of the bladder cancer, the sensitivity to treatment as well as the prognosis. Through further validation, this study may contribute to the development of personalized therapy and precision medical treatments.

Indexed as

GenomicsBiomarkers, TumorB-LymphocytesCell LineageGene Expression Regulation, NeoplasticGenome, HumanHumansMutationNeoplasm ProteinsPrecision MedicinePrognosisT-LymphocytesUrinary Bladder NeoplasmsBiomarkers, TumorNeoplasm Proteinsbladder cancerCIBERSORT algorithmgene expressionimmune infiltration subtypespersonalized therapyThe Cancer Genome Atlas

Identifiers

PMID32218698
PMCPMC7085262
OpenAlexW3012751230

What OpenQuestion holds

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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.