Off-Target-Based Tumor Fraction Estimation from Targeted Sequencing Shows Concordance with Orthogonal Methods Across Advanced Solid Tumors

Circulating tumor DNA fraction (ctFraction) has emerged as an important biomarker for assessing tumor burden and monitoring treatment response in patients with cancer. In this study, we compared ctFraction estimates generated by ichorCNA, Fragle low-pass whole-genome sequencing (Fragle LP-WGS), Fragle off-target, and OTTER, a proprietary algorithm from Tempus AI. Plasma samples from 33 patients with advanced solid tumors were analyzed using a ctDNA assay targeting 150 cancer-associated genes, and ctFraction estimates generated by the different methods were compared. Fragle off-target demonstrated the highest concordance with Fragle LP-WGS (rho = 0.903), followed by OTTER (rho = 0.698) and ichorCNA (rho = 0.696), while OTTER and ichorCNA showed strong agreement (rho = 0.826). Mean VAF (mVAF) significantly correlated with all ctFraction estimates, with the strongest association observed for ichorCNA (rho = 0.910), followed by OTTER (rho = 0.865), Fragle LP-WGS (rho = 0.680), and Fragle off-target (rho = 0.658). Longitudinal analysis of 20 patients at baseline and after two cycles of treatment demonstrated strong correlations between changes in ctFraction (ΔctFraction) and mean ΔVAF for both ichorCNA and Fragle off-target (r = 0.955 and r = 0.906, respectively). Overall, these findings demonstrate that ctFraction estimates derived from copy-number- and fragmentomic-based approaches show strong concordance across advanced solid tumors and significantly correlate with mVAF, a commonly used measure of ctDNA abundance. Fragle off-target, in particular, provides an efficient strategy for ctFraction estimation directly from existing targeted sequencing data, eliminating the need for additional sequencing. Larger prospective studies are warranted to further evaluate Fragle off-target clinical utility for treatment monitoring and outcome prediction.