ArticleProstate cancer and prostatic diseases2021
A comparative study of PCS and PAM50 prostate cancer classification schemes.
Article in Prostate cancer and prostatic diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Genomic classifiers and prognosis of localized prostate cancer: a systematic review.Prostate cancer and prostatic diseases · 2025Pooled it
- Increasing Cancer Stemness Drives Prostate Cancer Progression, Plasticity, Therapy Resistance and Poor Patient Survival.bioRxiv : the preprint server for biology · 2026Article
- Impact of Genomic Mutations on the Transcriptional Pathways and Tumor Microenvironment Landscape of Localized Early Prostate Cancer.The Prostate · 2026Article
- Prediction Analysis of Microarray of 50 genes (PAM50) classifier validated for predicting prostate cancer progression in active surveillance: Miami Active Surveillance Trial (MAST).BJU international · 2026Article
- From Data to Decision: Integrating Bioinformatics into Glioma Patient Stratification and Immunotherapy Selection.International journal of molecular sciences · 2026Review
- From pathways to prediction: a comparative machine learning framework for prostate cancer survival.Bioinformatics advances · 2026Article
- Development and Validation of a Cuproptosis-Based Risk Score Model for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer: A Transcriptomic Analysis.The breast journal · 2026Article
- Luminal and Basal Subtypes Across Carcinomas: Molecular Programs Beyond Tissue of Origin.Cancers · 2025Review
- Extracellular vesicle heterogeneity through the lens of multiomics.Cell reports. Medicine · 2025Article
- The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy.Military Medical Research · 2024Review
- Bioinformatics in urology - molecular characterization of pathophysiology and response to treatment.Nature reviews. Urology · 2024Review
- Updates on Management of Biochemical Recurrent Prostate Cancer.Current treatment options in oncology · 2024Review
- Article
- Molecular classifications of prostate cancer: basis for individualized risk stratification and precision therapy.Annals of medicine · 2023Review
- Implementation of ensemble machine learning algorithms on exome datasets for predicting early diagnosis of cancers.BMC bioinformatics · 2022Article
- SR9009 inhibits lethal prostate cancer subtype 1 by regulating the LXRα/FOXM1 pathway independently of REV-ERBs.Cell death & disease · 2022Article
- Translation of the 27-gene immuno-oncology test (IO score) to predict outcomes in immune checkpoint inhibitor treated metastatic urothelial cancer patients.Journal of translational medicine · 2022Article
- Understanding and targeting prostate cancer cell heterogeneity and plasticity.Seminars in cancer biology · 2022Review
- From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer.International journal of molecular sciences · 2022Review
- A Deep Learning-Based Framework for Supporting Clinical Diagnosis of Glioblastoma Subtypes.Frontiers in genetics · 2022Article
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Authors and funding
12 authors at 6 institutions in 1 country.
Funding
Abstract
backgroundTwo prostate cancer (PC) classification methods based on transcriptome profiles, a de novo method referred to as the "Prostate Cancer Classification System" (PCS) and a variation of the established PAM50 breast cancer algorithm, were recently proposed. Both studies concluded that most human PC can be assigned to one of three tumor subtypes, two categorized as luminal and one as basal, suggesting the two methods reflect consistency in underlying biology. Despite the similarity, differences and commonalities between the two classification methods have not yet been reported.
methodsHere, we describe a comparison of the PCS and PAM50 classification systems. PCS and PAM50 signatures consisting of 37 (PCS37) and 50 genes, respectively, were used to categorize 9,947 PC patients into PCS and PAM50 classes. Enrichment of hallmark gene sets and luminal and basal marker gene expression were assessed in the same datasets. Finally, survival analysis was performed to compare PCS and PAM50 subtypes in terms of clinical outcomes.
resultsPCS and PAM50 subtypes show clear differential expression of PCS37 and PAM50 genes. While only three genes are shared in common between the two systems, there is some consensus between three subtype pairs (PCS1 versus Luminal B, PCS2 versus Luminal A, and PCS3 versus Basal) with respect to gene expression, cellular processes, and clinical outcomes. PCS categories displayed better separation of cellular processes and luminal and basal marker gene expression compared to PAM50. Although both PCS1 and Luminal B tumors exhibited the worst clinical outcomes, outcomes between aggressive and less aggressive subtypes were better defined in the PCS system, based on larger hazard ratios observed.
conclusionThe PCS and PAM50 classification systems are similar in terms of molecular profiles and clinical outcomes. However, the PCS system exhibits greater separation in multiple clinical outcomes and provides better separation of prostate luminal and basal characteristics.
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