Evidence map›Paper›PMID 35044630›Full record

ArticleHuman cell2022

Development of a CAFs-related gene signature to predict survival and drug response in bladder cancer.

Zhao Zhang, Zhijuan Liang, Dan Li, Liping Wang, Yuanbin Chen, Ye Liang, Wei Jiao, Haitao Niu

Abstract read
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In one paragraph

Article in Human cell, 2022. 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
–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

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.

  1. Review
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  6. Stabilization of OLFML1 via mInternational journal of biological sciences · 2025
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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

8 authors.

Zhao ZhangDepartment of Urology, The Affiliated Hospital of Qingdao University, No.16 Jiangsu Road, Qingdao, 266000, China.
Zhijuan LiangKey Laboratory, Department of Urology and Andrology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Dan LiKey Laboratory, Department of Urology and Andrology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Liping WangKey Laboratory, Department of Urology and Andrology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Yuanbin ChenKey Laboratory, Department of Urology and Andrology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Ye LiangKey Laboratory, Department of Urology and Andrology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Wei JiaoDepartment of Urology, The Affiliated Hospital of Qingdao University, No.16 Jiangsu Road, Qingdao, 266000, China. jiaowei3929@163.com.
Haitao NiuDepartment of Urology, The Affiliated Hospital of Qingdao University, No.16 Jiangsu Road, Qingdao, 266000, China. niuht0532@126.com.ORCID http://orcid.org/0000-0001-6035-3500

Funding

Key projects of Qingdao Science and Technology Program 18-6-1-64-nshMajor Science and technology innovation project of Shandong Province 2019JZZY021002National Natural Science Foundation of China 81472411National Natural Science Foundation of China 81772713National Natural Science Foundation of China 82071750Research and Development Program of Shandong Province 2018GSF118197Taishan Scholar Foundation of Shandong Province tsqn20161077
6 · The paper itself

Abstract

As one of important components of tumor microenvironment, CAFs (cancer-associated fibroblasts) play a vital role in the development and metastasis of bladder cancer. The present study aimed to develop a CAFs-related gene signature to predict the prognosis of patients and the response to chemotherapy and immunotherapy based on research of multidatabase. Expression data and clinical information were obtained from TCGA and GEO databases. Different bioinformatic and statistical methods were combined to construct the robust CAFs-related gene signature for prognosis. The model was explored from four aspects: single-cell source, immune infiltration, correlation with cancer-related genes and pathways, and prediction of drug response. After screening, five genes (BNC2, LAMA2, MFAP5, NID1, and OLFML1) related to CAFs were used for constructing the signature to divide patients into high- and low-risk groups. Patients in low-risk group had better prognosis and multidatabase analysis confirmed the predictive value. The five genes were mainly expressed by fibroblasts and involved in regulation of pathways related with glycolysis, hypoxia, and epithelial-mesenchymal transition (EMT). BNC2, LAMA2, and NID1 were strongly associated with drug sensitivity. Moreover, the immunological status was different between high- and low-risk groups. High-risk patients had poor response to chemotherapy or immunotherapy. The CAFs-related gene signature might help to optimize risk stratification and provide a new insight in individual treatment for bladder cancer.

Indexed as

Cancer-Associated FibroblastsPharmaceutical PreparationsUrinary Bladder NeoplasmsEpithelial-Mesenchymal TransitionHumansOncogenesTumor MicroenvironmentPharmaceutical PreparationsBladder cancerCancer-associated fibroblastGene signatureImmune responsePrognosis

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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.