Artificial Intelligence and Multiomics Beyond PSA Screening in African and Middle Eastern Prostate Cancer Patients

Abstract

Prostate cancer (PCa) remains a major global health burden, with incidence rising as populations age. The molecular, histological, and patient-specific heterogeneity of PCa underscores the urgent need for advanced strategies to improve detection and risk stratification. This review highlights how multiomics integration, including transcriptomics, DNA methylation, proteomics, and metabolomics, combined with artificial intelligence (AI), can validate biological mechanisms across molecular layers, thereby enhancing diagnostic reliability and biological relevance. While prostate-specific antigen (PSA) testing has significantly shaped PCa epidemiology, its limited specificity and sensitivity have led to widespread overdiagnosis and overtreatment, particularly of indolent tumors. These limitations are especially pronounced in underrepresented populations, notably men of African descent and those in the Middle East and North Africa (MENA) region, where PSA-based screening demonstrates reduced effectiveness. Despite advances in biomarker discovery, current datasets lack sufficient ethnic and regional diversity, raising concerns about the clinical validity and equity of AI-driven models. We argue that equitable precision oncology requires not only technological innovation but also the development of inclusive, demographically representative datasets. This review offers a forward-looking perspective on advancing PCa screening and stratification beyond PSA, with a particular emphasis on addressing the unmet clinical needs of African and Middle Eastern patients.

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