Genomic Alterations to Guide Treatment Selection in Metastatic Prostate Cancer

Amy Davies1, Arun A Azad2, Edmond M Kwan3

  • 1Department of Medical Oncology, Monash Health, Melbourne, Australia; Department of Medicine, School of Clinical Sciences, Monash University, Melbourne, Australia.

Insights

Genomic analysis aids treatment selection for metastatic prostate cancer. Understanding genetic alterations in plasma DNA can guide therapy choices and improve patient outcomes.

Area of Science:

  • Oncology
  • Genetics
  • Precision Medicine

Background:

  • Treatment options for metastatic castration-resistant prostate cancer (mCRPC) have expanded, including androgen receptor pathway inhibitors, taxanes, PARP inhibitors, and PSMA-targeted radionuclide theranostics.
  • Optimal selection and sequencing of therapies in mCRPC remain challenging due to the crowded treatment landscape.

Purpose of the Study:

  • To review the evidence of genomic alterations as clinical biomarkers in mCRPC.
  • To focus on correlative studies analyzing outcomes based on plasma cell-free DNA findings.
  • To guide treatment decisions in metastatic prostate cancer through tumor genotyping.

Main Methods:

  • Evaluation of current evidence on genomic alterations in oncogenic signaling pathways in mCRPC.
  • Focus on correlative studies using plasma cell-free DNA (cfDNA) for outcome analysis.
  • Discussion of challenges in interpreting genomic findings from samples with low tumor content.

Main Results:

  • Genomic alterations in key prostate cancer driver genes show associations with clinical outcomes.
  • Plasma cfDNA analysis shows promise in guiding precision medicine targeted therapies.
  • Pathologic and disease factors are crucial for interpreting tumor genotyping results.

Conclusions:

  • Genomic biomarkers are essential for guiding treatment decisions in metastatic prostate cancer.
  • Overcoming barriers to cost-effective genotyping and data interpretation will integrate biomarkers into routine care.
  • Predictive and prognostic biomarkers will inform on disease biology, drug sensitivity, and resistance in mCRPC.