Comprehensive tumor mutational burden assessment using target-enhanced whole genome sequencing: A comparison with targeted panel testing.

Abstract

e15090 Background: Tumor Mutational Burden (TMB) is a critical biomarker for predicting immunotherapy response in oncology. However, targeted panels, limited by narrow genomic coverage, often yield inconsistent TMB estimates, either underestimating or overestimating due to design variability and extrapolation challenges. Whole Genome Sequencing (WGS) offers a more comprehensive and accurate approach, providing genome-wide mutation detection and reliable TMB assessment. Methods: We analyzed 202 tumor samples from lung, breast, colorectal, ovarian, and fallopian tube cancer patients. TMB was evaluated using the validated large targeted panel tests (TP), such as TruSight Oncology (TSO500) and GeneseeqPrime Pan-Solid Tumor, and CancerVision’s target-enhanced WGS (TE-WGS). TP define TMB as non-synonymous somatic mutations per megabase (mut/Mb) of the panel’s genomic regions, with high TMB classified as ≥10 mut/Mb. In contrast, TE-WGS calculates TMB across the effective genome size (2.9Gb) without limiting to coding regions. TE-WGS was analytically validated, demonstrating 99.8% sensitivity for single nucleotide variants (SNVs), 99.2% for indels, and high positive predictive values (SNVs: 99.3%, indels: 98.7%). Results: TMB values were compared between TE-WGS and TP. The TE-WGS assay showed strong concordance with TP for high (≥10 mut/Mb) and low ( < 10 mut/Mb) TMB classification: Sensitivity 79.3% (95% CI: 61.6–90.2%) and Specificity 95.4% (95% CI: 91.1–97.6%). Of the 202 samples, 23 (11.4%) were concordantly classified as high TMB, and 165 (81.7%) as low TMB. Discordance was observed in 14 cases (6.9%): 8 high TMB by TE-WGS but low by TP, and 6 low TMB by TE-WGS but high by TP. Analytical evaluation revealed that TE-WGS quantification was robust across varying tumor cellularity levels, demonstrating consistent performance independent of tumor purity. Discordant cases highlighted the advantage of TE-WGS in capturing mutations outside the genomic regions covered by TP, underscoring the importance of genome-wide assessment for accurate TMB quantification. Conclusions: TE-WGS offers a more comprehensive and reliable approach to TMB assessment compared to targeted panels, minimizing limitations of narrow genomic coverage and enhancing clinical utility.