Assessing the Detection Power of Genome-Wide Copy Number Variation Profiles in Prostate Cancer Using Simulated...

Area of Science:

• Genomics
• Oncology
• Bioinformatics

Background:

• Shallow whole-genome sequencing (sWGS) is a cost-effective method for analyzing tumor DNA.
• Identifying homologous recombination deficiency (HRD) and tandem duplication (TD) profiles in metastatic castration-resistant prostate cancer (mCRPC) can inform treatment strategies, including the use of poly (ADP-ribose) polymerase inhibitors.

Purpose of the Study:

• To determine the minimum sequencing depth and tumor content (TC) necessary for accurate detection of clinically significant genomic profiles using sWGS.
• To evaluate the utility of sWGS for identifying HRD and TD profiles in mCRPC.

Main Methods:

• In silico simulation of 3,360 whole-genome sequencing (WGS) data mixtures from 168 mCRPC tumor and matched normal biopsies.
• Varied tumor content (3%–20%) and sequencing depths (0.1×–5×) were generated.
• Copy number variations (CNVs) were analyzed using ichorCNA and WisecondorX with varying window sizes.

Main Results:

• An average sequencing depth of 1× with 20% TC was sufficient for high-sensitivity (>0.85) and high-specificity (>0.95) CNV detection.
• ichorCNA with a 50 Kb window size optimally detected HRD (R=0.88) and TD (R=0.72) profiles.
• TC estimation using ichorCNA correlated strongly with full-depth WGS data.

Conclusions:

• sWGS can reliably detect HRD and TD genomic profiles in mCRPC at ≥1× average sequencing depth and ≥20% TC.
• These findings suggest sWGS is a viable approach for identifying actionable genomic alterations in mCRPC.
• Further studies are needed to correlate these sWGS-detected markers with treatment outcomes.