Evidence map›Paper›PMID 38714855›Full record

ArticleScientific reports2024

Predicting bladder cancer survival with high accuracy: insights from MAPK pathway-related genes.

Guangyang Cheng, Zhaokai Zhou, Shiqi Li, Shuai Yang, Yan Wang, Zhuo Ye, Chuanchuan Ren

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

7 authors.

Guangyang Cheng *Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Zhaokai Zhou *Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Shiqi Li *Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Shuai YangDepartment of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Yan WangDepartment of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Zhuo YeDepartment of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Chuanchuan RenDepartment of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China. cc_ren@zzu.edu.cn.

Funding

National Natural Science Foundation of China 82000724
6 · The paper itself

Abstract

The mitogen-activated protein kinase (MAPK) pathway plays a critical role in tumor development and immunotherapy. Nevertheless, additional research is necessary to comprehend the relationship between the MAPK pathway and the prognosis of bladder cancer (BLCA), as well as its influence on the tumor immune microenvironment. To create prognostic models, we screened ten genes associated with the MAPK pathway using COX and least absolute shrinkage and selection operator (LASSO) regression analysis. These models were validated in the Genomic Data Commons (GEO) cohort and further examined for immune infiltration, somatic mutation, and drug sensitivity characteristics. Finally, the findings were validated using The Human Protein Atlas (HPA) database and through Quantitative Real-time PCR (qRT-PCR). Patients were classified into high-risk and low-risk groups based on the prognosis-related genes of the MAPK pathway. The high-risk group had poorer overall survival than the low-risk group and showed increased immune infiltration compared to the low-risk group. Additionally, the nomograms built using the risk scores and clinical factors exhibited high accuracy in predicting the survival of BLCA patients. The prognostic profiling of MAPK pathway-associated genes represents a potent clinical prediction tool, serving as the foundation for precise clinical treatment of BLCA.

Indexed as

MAP Kinase Signaling SystemUrinary Bladder NeoplasmsAgedBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedNomogramsPrognosisTumor MicroenvironmentBiomarkers, Tumor

Identifiers

PMID38714855
PMCPMC11076554

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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.