Optimized graph neural network-multilayer perceptron fusion classifier for metastatic prostate cancer detection in Western and Asian populations.

ABSTRACT:

Objective

Prostate cancer (PCa) exhibits significant genomic differences between Western and Asian populations. This study aimed to design a predictive model applicable across diverse populations while selecting a limited set of genes suitable for clinical implementation.

Methods

We utilized an integrated dataset of 1360 whole-exome and whole-genome sequences from Chinese and Western PCa cohorts to develop and evaluate the model. External validation was conducted using an independent cohort of patients. A graph neural network architecture, termed the pathway-aware multi-layered hierarchical network-Western and Asian (P-NETwa), was developed and trained on combined genomic profiles from Chinese and Western cohorts. The model employed a multilayer perceptron (MLP) to identify

SUBMITTER: Han F 

PROVIDER: S-EPMC12490683 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature