Liqin  Guo , Jiayi  Wu

Biotechnology Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China
Author    Correspondence author
Cancer Genetics and Epigenetics, 2024, Vol. 12, No. 2   
Received: 01 Feb., 2024    Accepted: 05 Mar., 2024    Published: 21 Mar., 2024

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Prostate cancer remains a significant clinical challenge due to its complex genetic landscape and the difficulty in predicting disease progression and treatment response. Recent advances in whole-genome sequencing (WGS) have provided deeper insights into the genetic alterations driving prostate cancer, offering new avenues for personalized treatment strategies. This study synthesizes findings from multiple studies that have employed WGS to identify novel driver mutations, potential therapeutic targets, and biomarkers for treatment response in prostate cancer. Key discoveries include the identification of new putative driver genes, such as NEAT1 and FOXA1, and the elucidation of the role of noncoding mutations in disease progression. Integrative high-throughput sequencing has demonstrated the feasibility of identifying clinically actionable mutations within a clinically relevant timeframe, facilitating biomarker-driven clinical trials. Studies have also highlighted the genomic heterogeneity of prostate cancer, with frequent alterations in genes such as AR, TP53, and PTEN, and the presence of actionable mutations in a significant proportion of cases. Additionally, the use of liquid biopsies for WGS has emerged as a promising non-invasive approach to monitor metastatic castration-resistant prostate cancer (mCRPC) and guide personalized treatment. This study underscores the potential of WGS to transform the clinical management of prostate cancer by enabling precision medicine approaches tailored to the genetic profile of individual tumors.

Whole-genome sequencing; Prostate cancer; Driver mutations; Biomarkers; Personalized treatment