Evidence map›Paper›PMID 42295562›Full record

ArticleImmunologic research2026

Machine learning-based identification of basement membrane-related signature to predict recurrence and immunotherapy benefit in bladder cancer.

Min Weng, Xiaojun Wang, Yating Zhan, Yangyang Guo, Zejun Yan, Liangchen Qu, Yadong Liu, Chaoyue Chen

Abstract read
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In one paragraph

Article in Immunologic research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Min Weng *Department of Urology, The First Affiliated Hospital of Ningbo University, Ningbo, 315000, China.
Xiaojun Wang *Department of Emergency, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, 318000, China.
Yating Zhan *Department of Blood Transfusion, The First Affiliated Hospital of Ningbo University, Ningbo, 315000, China.
Yangyang GuoDepartment of Thyroid and Breast Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, 315000, China.
Zejun YanDepartment of Urology, The First Affiliated Hospital of Ningbo University, Ningbo, 315000, China.
Liangchen QuDepartment of Emergency, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, 318000, China. qulc5682@enzemed.com.
Yadong LiuDepartment of Urology, The First Affiliated Hospital of Ningbo University, Ningbo, 315000, China. fyyliuyadong@nbu.edu.cn.
Chaoyue ChenDepartment of Blood Transfusion, Wenzhou Central Hospital Affiliated to Wenzhou Medical University, Wenzhou, 325000, China. 617987146@qq.com.

Funding

Ningbo Clinical Research Center for Urological Disease No.2019A21001Ningbo Top Medical and Health Research Program No.2022020203Zhejiang Natural Science Foundation No.LTGY24H160005
6 · The paper itself

Abstract

The basement membrane (BM) plays a critical role in regulating bladder cancer (BC) progression. However, a BM-related signature for predicting BC recurrence has yet to be established. In this study, we developed a basement membrane-related signature (BRS) with 7 mRNAs using multiple machine learning algorithms based on data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The predictive performance of BRS for BC recurrence was evaluated via Kaplan-Meier survival and receiver operating characteristic (ROC) curves. A nomogram integrating BRS with clinical characteristics was developed and demonstrated superior clinical utility compared to individual parameters. Notably, immune infiltration analysis revealed distinct microenvironmental phenotypes between the two BRS groups: the low-BRS group was characterized by higher CD8

Indexed as

Basement MembraneImmunotherapyMachine LearningNeoplasm Recurrence, LocalUrinary Bladder NeoplasmsBiomarkers, TumorCD8-Positive T-LymphocytesGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisTumor MicroenvironmentBiomarkers, TumorBasement membraneBladder cancerImmunotherapy benefitMachine learningRecurrence riskTumor microenvironment

Identifiers

PMID42295562

What Socratic holds

Textmetadata
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 Socratic graph.