Pre-Analytical and Analytical Challenges in Whole-Exome Sequencing of Formalin-Fixed Paraffin-Embedded Breast and Prostate Cancer Tissue: A Real-World Multicenter Study.

Background/

Objectives

Formalin-fixed paraffin-embedded tissue is widely used in pathology and molecular diagnostics, yet its variable quality can critically influence the accuracy of sequencing-based analyses. This study investigated pre-analytical and analytical factors that can affect exome sequencing performance in a Brazilian multicenter cohort of patients with breast cancer and prostate adenocarcinoma.

Methods

Tumor samples were reviewed for diagnostic confirmation, and those with a minimum cellularity of 20% underwent DNA extraction, fluorometric quantification, fragmentation analysis, and exome sequencing. Pre-analytical parameters, including tumor content, DNA yield, and fragmentation profile, were recorded and correlated with sequencing results.

Results

Only 36.7% of all analyzed samples (163/444) generated valid whole-exome sequencing data, corresponding to 55.6% of those that proceeded to sequencing (163/293). Although 94.5% of specimens met the minimum ≥20% cellularity threshold and 66.0% advanced to sequencing, a substantial proportion failed to yield usable exome data. Successful sequencing was associated with shorter storage durations (p < 0.001) and superior analytical parameters (higher autosomal coverage, longer read lengths, lower duplication rates, and higher target coverage at ≥500× and ≥100×; p < 0.001). Detailed fixation-related variables (e.g., formalin type, fixation time, ischemia time) were not consistently available across centers, representing a major limitation for causal interpretation of pre-analytical effects.

Conclusions

Our study identified a high failure rate in sequencing archival tissue, highlighting the need to prioritize more recently collected specimens and refine standardized sample handling protocols to maintain DNA integrity. These improvements are essential for optimizing sequencing workflow performance and feasibility in real-world settings.