Evidence map›Paper›PMID 41898571›Full record

ArticleInternational journal of molecular sciences2026

Integrating Multi-Omics Atlas to Uncover Genetic and Epigenetic Mechanisms and Reveal Cell State Evolution Across Ecotypes in Male Urological Cancers.

Jing Bai, He Yu, Congxue Hu, Yining Ma, Mingjie Dong, Liyuan Li, Kaiyue Yang, Zhenzhen Wang, Yunpeng Zhang, Xia Li and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 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

11 authors.

Jing BaiCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.
He YuCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.
Congxue HuCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.
Yining MaCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.
Mingjie DongCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.
Liyuan LiCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.
Kaiyue YangCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.
Zhenzhen WangSchool of Intelligent Medicine and Technology (Big Data Research Center), Hainan Medical University, Haikou 571199, China.
Yunpeng ZhangCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.ORCID 0000-0002-3709-3656
Xia LiCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.
Yan CaoCollege of Bioinformatics Science and Technology, Department of Urology, Harbin Medical University, Harbin 150081, China.

Funding

China Postdoctoral Science Foundation 2024M760709Haiyan Foundation of Harbin Medical University Cancer Hospital JJZD2021-06Heilongjiang Chunyan Youth Science and Technology Talent team project CYQN24009Heilongjiang Postdoctoral Fund LBH-Z24210Key Research and Development Program of Heilongjiang Province 2024ZX12C27National Natural Science Foundation of China 62172131National Natural Science Foundation of China 62472131National Natural Science Foundation of China U23A20166National Science and Technology Major Program 2024ZD0530500
6 · The paper itself

Abstract

Male urological cancers, including clear cell renal cell carcinoma (ccRCC), bladder cancer (BC), and prostate cancer (PCa), are characterized by extensive heterogeneity and complex ecosystems, yet the underlying mechanisms remain incompletely understood. In this study, scRNA-seq, scATAC-seq and spatial transcriptomics data are integrated to systematically characterize the features of the tumor microenvironment (TME). We identify tumor cell subclones and elucidate the impact of chromosomal abnormalities on their characteristic functions. We further identify transcription factor regulatory networks by analyzing tumor cell differentiation trajectories. Importantly, we integrate DNA methylation and SNP information to deeply dissect the tumor cell differentiation process, revealing the multilayer regulatory mechanisms of tumor-related genes. Additionally, we reveal the evolution of cellular states across ecotypes to provide a more comprehensive characterization of TME. Finally, we screened potential therapeutic agents targeting the molecular mechanisms underlying tumor cell differentiation (Amivantamab in ccRCC, Levothyroxine in BC, Ouabain in PCa) and signature genes of ecotype. In conclusion, our work establishes a comprehensive framework for tumor assessment and informs the development of precision therapeutic strategies.

Indexed as

Epigenesis, GeneticUrologic NeoplasmsCarcinoma, Renal CellCell DifferentiationDNA MethylationEcotypeGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansKidney NeoplasmsMaleMultiomicsProstatic NeoplasmsSingle-Cell Gene Expression AnalysisSpatial TranscriptomicsTranscriptomecancer ecotypeepigeneticsmale urological cancerssingle-cell RNA sequencingspatial transcriptomics

Identifiers

PMID41898571
PMCPMC13026699

What Socratic holds

Textmetadata
LicenceCC BY
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.