Mutational profiling of micro-dissected pre-malignant lesions from archived specimens

Abstract

Background: Systematic cancer screening has led to the increased detection of pre-malignant lesions (PMLs). The absence of reliable prognostic markers can lead to inadequate treatment resulting in unnecessary stress or avoidable progression. Importantly, most mutational profiling studies have relied on PML synchronous to invasive cancer, or performed in patients without outcome information, hence limiting their utility for biomarker discovery. The limitations in comprehensive mutational profiling of PMLs are in large part due to the significant technical and methodological challenges: most PML specimens are small, fixed in formalin and paraffin embedded (FFPE) and lack matching normal DNA. Methods:Using test DNA from a highly degraded FFPE specimen, multiple targeted sequencing approaches were evaluated, varying DNA input amount (3-200 ng), library preparation strategy (BE: Blunt-End, SS: Single-Strand, AT: A-Tailing) and target size (whole exome vs cancer gene panel). Variants in high-input DNA from FFPE and mirrored frozen specimens were used for PML-specific variant calling training and testing, respectively. The resulting approach was applied to profile and compare multiple regions micro-dissected (mean area 5 mm 2 ) from 3 breast ductal carcinoma in situ (DCIS). Results:Using low-input FFPE DNA, BE and SS libraries resulted in 4.9 and 3.7 increase over AT libraries in the fraction of whole exome covered at 20x (BE:87%, SS:63%, AT:17%).Compared to high-confidence somatic mutations from frozen specimens, PML-specific variant filtering increased recall (BE:79%, SS:74%, AT:62%) and precision (BE:87%, SS:88%, AT:80%) to levels expected from sampling variation. Copy number alterations were consistent across all tested approaches and only impacted by the design of the capture probe-set. Applied to DNA extracted from 9 micro-dissected regions (8 PML, 1 normal epithelium), the approach achieved comparable performance, identified candidate driver events (gains of ERBB2 or FGFR1, loss of TP53) and illustrated the adequacy of the data to identify candidate driver mutations and measure intra-lesion genetic heterogeneity. Conclusion:The approach presented enables mutational profiling from archived microdissected PML regions, supporting the identification of pre-malignant drivers, and the characterization of PML molecular heterogeneity and evolution, all critical milestones the development of biology-informed prognostic markers and precision chemo-prevention strategies.