Evidence map›Paper›PMID 37691944›Full record

ArticleFrontiers in immunology2023

A novel signature constructed by differential genes of muscle-invasive and non-muscle-invasive bladder cancer for the prediction of prognosis in bladder cancer.

Weizhuo Wang, Xi Zhang, Silin Jiang, Peng Xu, Kang Chen, Kai Li, Fei Wang, Xiang Le, Ke Zhang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.3field-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

11 citing papers in PubMed, 9 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 5 institutions in 1 country.

Weizhuo WangDepartment of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China.
Xi ZhangDepartment of Urology, Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Silin JiangDepartment of Urology, Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Peng XuDepartment of Urology, Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Kang ChenDepartment of Urology, North China University of Science and Technology, Tangshan, China.
Kai LiDepartment of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China.
Fei WangDepartment of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China.
Xiang LeDepartment of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China.
Ke ZhangDepartment of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China.
Nanjing Medical University · CNSuzhou Municipal Hospital · CNJiangsu Province Hospital · CNNorth China University of Science and Technology · CNSecond Affiliated Hospital of Nanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bladder cancer (BCa) is a malignant tumor that usually forms cancer cells in the inner lining of the bladder. Hundreds of thousands of people worldwide have BCa diagnosed each year. The purpose of this study was to construct a prognostic model by differential expression of genes between muscular and non-muscular invasive BCa, and to investigate the prognosis of BCa patients. Methods: The data of BCa patients was sourced from the GEO and TCGA database. Single-cell sequencing data was obtained from three patients in the GSE135337 database, and microarray data for verification was obtained from GSE32894. Univariate, Lasso and multivariate cox regression analyses were performed to construct the prognostic model. The prognostic features, immune features and drug sensitivity of the model were further evaluated. Single-cell data and microarray data were used to validate the differential expression of model genes between muscle-invasive and non-muscle-invasive BCa. The invasion and migration of BCa cells were evaluated using the transwell assay and wound-healing assay. The cell proliferation capacity was simultaneously evaluated using Colony formation experiments. The protein expression of the specific gene was detected by western blot analysis. Results: We identified 183 differentially expressed muscle-invasive-related differential genes (MIRDGs), among which four were selected to establish a prognostic model. Based on our signature, patients in different groups displayed varying levels of immune infiltration and immunotherapy profiles. Single-cell sequencing data and microarray data confirmed that four invasion-related genes were expressed at higher levels in muscle-invasive BCa. Given the critical role of S100A9 in the progression of BCa, we performed further analysis. The results showed that protein expression of S100A9 was high in muscle-invasive BCa, and S100A9 knockdown could inhibit the proliferation, migration and invasion of BCa. Conclusion: These findings demonstrated that the prognostic model for BCa patients was reasonably accurate and valid, and it may prove to be of considerable value for the treatment and prognosis of BCa patients in the future. S100A9 may become a better prognostic marker and potential therapeutic target to further guide clinical treatment decisions.

Indexed as

Non-Muscle Invasive Bladder NeoplasmsUrinary Bladder NeoplasmsCalgranulin BHumansMusclesPrognosisUrinary BladderCalgranulin Bbiomarkerbladder cancerimmune microenvironmentmuscle-invasiveprognostic signature

Identifiers

PMID37691944
PMCPMC10483405
OpenAlexW4386135857

What OpenQuestion holds

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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.