Abstract 6562: Comparative analysis of blood-based tumor fraction estimation in 300 cancer patients
Authors: Dai Chao , Zheng Tiantian , Dong Xiaoxi , Mo Wei , Wang Xiaohong , Luo Shujun , Zhou Kemin , Jia Shidong , Du Pan 
Published: April 2023

Abstract
Introduction Tumor fraction (TF) in cell-free DNA is an important known biomarker for monitoring treatment response and disease progression. cfDNA TF is usually estimated by variant allele frequency (VAF) of somatic mutations or copy number variation (CNV). cfDNA assays provide high VAF detection sensitivity by using deep sequencing depth based on target panels, which often makes TF underestimated due to limited panel gene coverage. Also because the interference of copy number changes and lack of matched normal, the VAF estimation is often inaccurate. On the other hand, although CNV based TF estimation does not require matched normal samples, it has lower detection sensitivity and underestimates cfDNA TF for patients without copy number changes. Importantly, tumor heterogeneity exists in many clinical cancer patient samples, where tumor DNA has complex subclone structures, which makes accurate TF estimation even more challenging.
Methods Here we performed comprehensive concordance study of cfDNA TF estimation, by applying both PredicineWES+ (20,000x sequencing depth in boosted cancer-related genes and 2,500x depth in rest exome regions) and PredicineCNB (LP-WGS with 3 × sequencing depth) on more than 300 plasma samples from cancer patients. Using a proprietary algorithm, we calculated TF by integrating PredicineWES+ derived VAFs and PredicineCNB derived CNVs for each sample, where tumor subcloning was taken into the consideration. We implemented proprietary EM algorithm to infer subclone populations, where CNV has high concordance with TF in each subclone.
Results Our study showed that CNV-based TF estimation is highly concordance with VAF-based TF from PredicineWES+ (correlation coefficient &gt; 0.8) when TF is &gt;5%. For clinical samples with &lt; 5% TF inferred from PredicineCNB, we used VAF-based TF. We developed an integrated TF estimation methodology by leveraging molecular insights derived from PredicineWES+ and PredicineCNB, and further performed clinical evaluation study using 50 longitudinal plasma samples from prostate cancer patients that are under different cancer stages or therapies. Our results demonstrated that the integrated TF estimation shows a positive correlation with therapy response and disease stage revealed by CT scan. Finally, serial analysis of plasma cfDNA demonstrated an increase in ctDNA TF and cancer variants, preceding evidence of radiographic and clinical disease progression in many patients.
Conclusion We conducted a comprehensive concordance study to infer cfDNA TF using PredicineWES+ and PredicineCNB in more than 300 patient samples. Our study demonstrated its clinical utility where the integrated TF analysis may provide a more robust and accurate estimation of disease burden in cancer patients.
Citation Format: Chao Dai, Tiantian Zheng, Xiaoxi Dong, Wei Mo, Xiaohong Wang, Shujun Luo, Kemin Zhou, Shidong Jia, Pan Du. Comparative analysis of blood-based tumor fraction estimation in 300 cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6562.