Unmasking Neuroendocrine Prostate Cancer with a Machine Learning-Driven Seven-Gene Stemness Signature That Predicts Progression

Authors

Agustina Sabater
Pablo Sanchis
Rocio Seniuk
Gaston Pascual
Nicolas Anselmino
Daniel F Alonso
Federico Cayol
Elba Vazquez
Marcelo Marti
Javier Cotignola
Ayelen Toro
Estefania Labanca
Juan Bizzotto
Geraldine Gueron

Publication Date

10-22-2024

Journal

International Journal of Molecular Sciences

Abstract

Prostate cancer (PCa) poses a significant global health challenge, particularly due to its progression into aggressive forms like neuroendocrine prostate cancer (NEPC). This study developed and validated a stemness-associated gene signature using advanced machine learning techniques, including Random Forest and Lasso regression, applied to large-scale transcriptomic datasets. The resulting seven-gene signature (KMT5C, DPP4, TYMS, CDC25B, IRF5, MEN1, and DNMT3B) was validated across independent cohorts and patient-derived xenograft (PDX) models. This signature demonstrated strong prognostic value for progression-free, disease-free, relapse-free, metastasis-free, and overall survival. Importantly, the signature not only identified specific NEPC subtypes, such as large-cell neuroendocrine carcinoma, which is associated with very poor outcomes, but also predicted a poor prognosis for PCa cases that exhibit this molecular signature, even when they were not histopathologically classified as NEPC. This dual prognostic and classifier capability makes the seven-gene signature a robust tool for personalized medicine, providing a valuable resource for predicting disease progression and guiding treatment strategies in PCa management.

Keywords

Humans, Machine Learning, Male, Prostatic Neoplasms, Disease Progression, Prognosis, Gene Expression Regulation, Neoplastic, Animals, Transcriptome, Biomarkers, Tumor, Mice, Carcinoma, Neuroendocrine, Gene Expression Profiling, Neoplastic Stem Cells, prostate cancer, stemness, gene signature, prognosis, machine learning, neuroendocrine transdifferentiation, large cell neuroendocrine carcinoma

DOI

10.3390/ijms252111356

PMID

39518911

PMCID

PMC11545501

PubMedCentral® Posted Date

10-22-2024

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes