ArticleJournal of translational medicine2025
Construction of a prostate adenocarcinoma molecular classification: integrating spatial transcriptomics with retrospective cohort validation.
Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- SRRT promotes prostate cancer progression and serves as a prognostic biomarker through STAT3 pathway activation.Oncology reports · 2026Article
- Identification of KIF14 as a ferroptosis biomarker for predicting the prognosis and immunotherapy efficacy of bladder cancer.Discover oncology · 2025Article
- A systems biology approach to unveil shared therapeutic targets and pathological pathways across major human cancers.Computational and structural biotechnology journal · 2025Article
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16 authors.
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Abstract
backgroundProstate adenocarcinoma (PRAD) is a biologically heterogeneous disease threatening the health of elderly males worldwide, and some PRAD subtypes with certain molecular landscape are always associated with poor prognosis. A more precise molecular classification system for PRAD is urgently needed.
methodsThrough spatial transcriptome analysis, we identified different malignant cell/spot types in PRAD. Then, Monocle 2 analysis was applied to identify malignant cell fates and differentiation-related genes. Together with the prognosis-related genes identified through Kaplan-Meier analysis and univariate Cox regression in TCGA-PRAD cohort, we defined malignant cell differentiation-related prognostic genes (MDPGs). Based on MDPGs, we constructed a malignant cell differentiation-based PRAD classification (MDPC) using the ConsensusClusterPlus algorithm. Then, we explored multi-omics correlations of MDPC, and constructed the regulation networks of MDPC as well as the prognostic prediction model. Finally, we validated the prognostic prediction value of MDPC through immunohistochemical staining and follow-up of a retrospective cohort.
resultsThree malignant spot types were identified through spatial transcriptome analysis. Then, we defined 33 MDPGs and successfully constructed MDPC with three different subtypes (DPP4
conclusionWe successfully constructed MDPC with validated prognostic prediction value. This classification system provided clinicians with an effective tool to stratify PRAD patients, identifying high-risk individuals, recognizing patients prone to develop bone metastasis, and offering opportunities for early intervention to improve patients' prognosis.
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