Evidence map›Paper›PMID 41715136›Full record

ArticleJournal of translational medicine2026

Single-cell transcriptomic analysis and machine learning identify ATAD3A as a key gene that stabilizes mitochondrial-endoplasmic reticulum membranes, promoting bladder cancer progression.

Henghui Zhang, Sisi Han, Zhengming Su, Zaosong Zheng, Dejun Ru, Bihong Xu, Xianhan Jiang, Fengjin Zhao

Abstract read
In one paragraph

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

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Henghui Zhang *Department of Urology, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, 510515, China.
Sisi Han *Department of Cardiovascular Medicine, The Affiliated Qingyuan Hospital, Guangzhou Medical University, Qingyuan People's Hospital, Guangdong, 511500, China.
Zhengming Su *Department of Urology, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, 510515, China.
Zaosong ZhengDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P.R. China.
Dejun RuDepartment of Urology, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, 510515, China.
Bihong XuDepartment of Pathology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P.R. China. xushuyong2012@163.com.
Xianhan JiangDepartment of Urology, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, 510515, China. jiangxianhanz@126.com.
Fengjin ZhaoDepartment of Urology, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, 510515, China. zhfj621@163.com.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2023A03J0422Guangzhou Major Medical Discipline Project 2005-2007Major technical projects of Guangzhou 2026C-ZD013the Characteristic Innovation Project of Department of Education of Guangdong Province 2023KTSCX107The National Natural Science Fund of China 82072808
6 · The paper itself

Abstract

backgroundMitochondria-associated endoplasmic reticulum membranes (MAM) play a critical regulatory role in cancer, yet their function in bladder cancer (BCa) remains unclear.

methodsThis study conducted a comprehensive analysis of extensive RNA sequencing and single-cell transcriptomic data. A MAM risk feature model was constructed and evaluated using LASSO-Cox regression, Kaplan-Meier survival curves, and receiver operating characteristic (ROC) analysis. Cell communication networks were decoded using CellChat, and tumor-infiltrating immune cells were quantified through CIBERSORT. Machine learning, OncoPredict, Scissor algorithm, and spatial transcriptomics were employed to analyze chemical reactions. The tumor-promoting functions and molecular mechanisms of ATAD3A were validated through cell and animal models, as well as transmission electron microscopy and fluorescence confocal microscopy.

resultsThis study systematically delineates the gene expression profile of MAM in BCa and constructs a robust MAM prognostic signature that effectively predicts poor patient outcomes. A high MAM score is significantly associated with an immunosuppressive microenvironment and chemotherapy resistance. Using machine learning, we developed a random forest model that successfully identified ATAD3A as a key gene predicting cisplatin resistance, which is significantly correlated with platinum resistance at both single-cell and spatial transcriptomic levels. Further validation shows that ATAD3A is highly expressed in BCa tissue, and its knockdown significantly suppresses tumor growth. Mechanistically, ATAD3A maintains MAM structural integrity, regulates mitochondrial calcium homeostasis and membrane potential, thereby promoting cellular homeostasis and enhancing chemotherapy resistance.

conclusionThis study connects MAM to BCa chemotherapy resistance through machine learning and multi-omics analysis, establishing ATAD3A as a prognostic biomarker and potential therapeutic target in BCa.

Indexed as

ATPases Associated with Diverse Cellular ActivitiesDisease ProgressionEndoplasmic ReticulumGene Expression ProfilingMachine LearningMembrane ProteinsMitochondriaMitochondrial ProteinsSingle-Cell AnalysisUrinary Bladder NeoplasmsAnimalsCell Line, TumorGene Expression Regulation, NeoplasticHumansMitochondria Associated MembranesPrognosisATAD3A protein, humanATPases Associated with Diverse Cellular ActivitiesMembrane ProteinsMitochondrial ProteinsATAD3ABladder cancerMachine learningMitochondria-associated endoplasmic reticulum membranesSingle cell

Identifiers

PMID41715136
PMCPMC13032607

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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.