A diagnostic signature derived from NK cell related genes in prostate cancer: insights from integrated scRNA-seq and bulk RNA-seq analyses with functional validation of KIT.

Zhengjun Chen, Fang Zhou, Jingzhi Tian, Qian Lv, Dong Wang, Shida Fan

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Article in Frontiers in immunology, 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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5 · Who and what money

Authors and funding

6 authors.

Zhengjun Chen *Robotic Minimally Invasive Surgery Center, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Fang Zhou *Robotic Minimally Invasive Surgery Center, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Jingzhi TianRobotic Minimally Invasive Surgery Center, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Qian LvRobotic Minimally Invasive Surgery Center, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Dong WangRobotic Minimally Invasive Surgery Center, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Shida FanRobotic Minimally Invasive Surgery Center, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Prostate cancer is one of the most common malignant tumors of the male genitourinary system. The impaired activity of natural killer (NK) cells observed in prostate cancer may contribute to immune evasion. This study aimed to develop robust NK cell-related diagnostic signatures. Methods: Based on NK related genes identified by scRNA-seq analysis, weighted gene co-expression network analysis, least absolute shrinkage and selection operator regression analysis, and machine learning algorithms were used to develop a novel diagnostic model. The expression of diagnostic genes was validated using tumor and adjacent normal tissues collected from prostate cancer patients. The biological functions of KIT as an NK cell related gene were further evaluated in prostate cancer cells. Results: A nine-gene NK cell-related diagnostic signature was developed, including Conclusion: This study provides a new understanding of NK cell related gene signatures in prostate cancer diagnosis and highlights KIT as a promising candidate for future therapeutic investigation. Further research is needed to explore the mechanisms underlying the expression of these genes and their roles in the tumor microenvironment.

Indexed as

Biomarkers, TumorKiller Cells, NaturalProstatic NeoplasmsCell Line, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleRNA-SeqSingle-Cell Gene Expression AnalysisTranscriptomeBiomarkers, Tumordiagnostic modelimmunotherapyNK cell marker genesprostate cancersingle-cell and bulk RNA-sequencing

Identifiers

PMID42317356

DOI10.3389/fimmu.2026.1692792

PMCPMC13272176

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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 Socratic graph.