A new method to accurately identify single nucleotide variants using small FFPE breast samples.

Area of Science:

• Genomics
• Cancer Biology
• Bioinformatics

Background:

• Formalin-fixed, paraffin-embedded (FFPE) samples are crucial for cancer diagnostics and research.
• Accurate DNA sequencing from FFPE tissues is challenging due to sample degradation.
• Existing methods struggle with reliable variant calling from limited FFPE-derived DNA.

Purpose of the Study:

• To develop and validate a novel bioinformatics pipeline for robustly identifying somatic single nucleotide variants (SNVs) from whole exome sequencing of FFPE breast cancer samples.
• To optimize variant-calling strategies for small amounts of DNA extracted from archival FFPE tissues.
• To assess the performance of the new pipeline compared to existing tools.

Main Methods:

• Development of a new bioinformatics pipeline integrating existing variant-calling strategies.
• Optimization using 28 pairs of technical replicates from FFPE breast cancer samples.
• Whole exome sequencing (WES) was performed on DNA extracted from FFPE samples.

Main Results:

• The optimized pipeline achieved a 5-fold increase in mean similarity between technical replicates, reaching 88%.
• The method reliably identified a mean of 21.4 SNVs per sample, outperforming existing tools.
• SNV identification accuracy decreased with less than 40 ng of DNA; insertion-deletion variants were less reliable than SNVs.
• Application to matched ductal carcinoma in situ and invasive ductal carcinoma samples revealed increased mutations and genetic divergence in invasive tumors.

Conclusions:

• The developed bioinformatics pipeline significantly improves the detection of SNVs in FFPE samples.
• This method offers a robust solution for analyzing degraded DNA from archival FFPE tissues for cancer research.
• The findings highlight the utility of the pipeline for comparative genomic studies of tumor progression.