ArticleNPJ digital medicine2025
Integrative machine learning models predict prostate cancer diagnosis and biochemical recurrence risk: Advancing precision oncology.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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.
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.
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Who cites it
28 citing papers in PubMed.
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- Machine learning-guided multi-omics suggests iron-dependent hormonal signaling drives root morphological plasticity in wheat under temperature stress.The New phytologist · 2026Article
- An externally validated lactylation-associated prognostic signature for overall survival prediction in lung adenocarcinoma identifiesTranslational cancer research · 2026Article
- Molecular landscape and clinical translation of DNA damage response alterations in solid tumors: A pan-cancer perspective on precision oncology.Neoplasia (New York, N.Y.) · 2026Review
- Development and validation of a novel T cell exhaustion-related signature to predict prognosis in patients with breast cancer.Discover oncology · 2026Article
- Machine learning-based identification of basement membrane-related signature to predict recurrence and immunotherapy benefit in bladder cancer.Immunologic research · 2026Article
- Identification of MYC co-expression gene: POLR3G is associated with cell senescence, immunotherapy, chemotherapy responses, and clinical prognosis in bladder cancer patients.Translational oncology · 2026Article
- Anoctamin 5 as a protective factor in prostate cancer: Insights from WGCNA, machine learning, and experimental analysis, with a focus on the anoctamin family.Translational oncology · 2026Article
- Machine learning-based prognostic model integrating preoperative HALP score and lactate dehydrogenase for predicting postoperative recurrence of prostate cancer.World journal of surgical oncology · 2026Article
- A Metabolic-Related Gene Signature for Predicting Biochemical Recurrence After Radical Prostatectomy: An Integrative Analysis and Targeted Therapeutic Validation.International journal of molecular sciences · 2026Article
- Identification of Mitochondrial Signature Biomarkers and Molecular Mechanisms in Atherosclerotic Tissues and Blood: Combined Single-Cell and Bulk RNA Sequencing Analysis.Molecular neurobiology · 2026Article
- Review
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- Talin1 is downregulated in testicular germ cell tumors according to combined bioinformatics and experimental approaches.Scientific reports · 2026Article
- Molecular Subtyping Based on EGFR Mutation-Associated Genes and the Prognostic Role of TRAF2 in Lung Adenocarcinoma.Human mutation · 2026Article
- Article
- Unraveling Signaling Pathways in Immune Microenvironment Crosstalk to Overcome Immunotherapy Resistance in Colorectal Cancer.Human mutation · 2026Review
- From Germline Susceptibility to Therapeutic Vulnerability: DNA Damage Response Gene Mutations Driving Multiple Myeloma Evolution and Precision Therapy.Human mutation · 2026Review
- Downregulation of ankyrin 3 (ANK3) promotes malignant behaviors associated with altered adhesion dynamics and actin cytoskeleton remodeling in renal cell carcinoma.Cell and tissue research · 2025Article
- Integrating WGCNA, TCN, and Alternative Splicing to Map Early Caste Programs in Day-2 Honeybee Larvae.Genes · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Prostate cancer (PCa) ranks among the most prevalent cancers in men worldwide. Biochemical recurrence (BCR) presents a major clinical challenge in PCa management, with significant prognostic heterogeneity observed among patients post-recurrence. This study aimed to develop machine learning models for predicting both the diagnosis and prognosis of PCa patients. Using WGCNA, we initially identified 16 BCR-related target genes. Cluster analysis revealed these genes were significantly associated with PCa prognosis, drug sensitivity, and immune infiltration. We constructed a robust diagnostic model integrating multiple machine learning algorithms, demonstrating strong predictive capability for PCa. Furthermore, a BCR-related prognostic model built using the LASSO algorithm also yielded satisfactory performance. Among the differentially expressed BCR-associated prognostic genes, COMP emerged as a critical regulatory factor. Both in vitro and in vivo experiments confirmed COMP's role in influencing PCa progression. Additionally, COMP demonstrates significant potential as a dual biomarker for both the diagnosis and recurrence prediction of PCa.
Identifiers
What Socratic holds
Registered trials
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.