Evidence map›Paper›PMID 40165961›Full record

ArticleFrontiers in immunology2025

New insights into markers for distinguishing neuroendocrine prostate cancer: evidence from single-cell analysis.

Hailang Luo, Boyang Li, Meng Zhang, Hongqun Wang, Zongyao Hao, Qintao Ge, Chaozhao Liang

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. 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

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Hailang Luo *Department of Urology, the First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.
Boyang LiDepartment of Urology, the First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.
Meng ZhangDepartment of Urology, the First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.
Hongqun WangDepartment of Pathology, the Third People's Hospital of Bengbu City, Bengbu, China.
Zongyao HaoDepartment of Urology, the First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.
Qintao GeDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, China.
Chaozhao LiangDepartment of Urology, the First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Neuroendocrine prostate cancer (NEPC) is a highly aggressive malignancy with few effective treatment options. The identification of reliable biomarkers for NEPC is essential for early detection and intervention. Methods: We combined single-cell and bulk transcriptome analysis to identify novel markers of NEPC. InferCNV to assess copy number variations and leveraging consensus non-negative matrix factorization (cNMF) to characterize transcriptional programs. Pseudotime analysis was used to decipher prostate cancer (PCa) progression differentiation trajectory. BayesPrism integrates single-cell results and TCGA-PRAD sequencing information to further study prognostic features. Immunohistochemistry (IHC) was performed to validate the elevated expression of ASCL1 and WDFY4 in NEPC. Results: We identified five distinct expression programs of PCa malignant epithelial cells, where Module 3 presented NEPC expression patterns, with activation of DNA replication and cell cycle pathways and classical NEPC marker expression. Patients with high Module 3 proportion correlated to poor clinical outcomes, advanced Gleason scores, and higher T stages. Pseudotime analysis highlighted key trajectory-dependent genes involved in the transition to NEPC, where expression of ASCL1 and WDFY4 elevated with progressing to NEPC cell fate, which were further confirmed by IHC analysis, indicating that WDFY4 and ASCL1 might be novel potential markers for distinguishing NEPC. Conclusions: Combined single-cell and bulk analysis, we highlight the cellular heterogeneity and transcriptional programs, validated novel biomarkers of NEPC. Providing a foundation for early prediction of NEPC and management.

Indexed as

Biomarkers, TumorCarcinoma, NeuroendocrineNeuroendocrine TumorsProstatic NeoplasmsSingle-Cell AnalysisBasic Helix-Loop-Helix ProteinsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMalePrognosisASCL1 protein, humanBasic Helix-Loop-Helix ProteinsBiomarkers, TumorASCL1biomarkerneuroendocrine prostate cancer (NEPC)single cell analysisWDFY4

Identifiers

PMID40165961
PMCPMC11955813

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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.