Abstract 2289: Predicting tumor somatic versus clonal hematopoiesis origin for short variants in liquid assay
Authors: Sun Daokun , Kuang Zheng , Fine Alexander D. , Polisecki Eliana , Gettler Holley , Al-Rekabi Hawra , Pavlick Dean , Huang Yanmei , Albacker Lee A. , Decker Brennan , Xu Chang 
Published: June 2023

Introduction A common challenge presented by emerging liquid biopsy technology is to distinguish somatic variants originated in CH from those in tumor. While sequencing of genomic DNA from matched peripheral blood mononuclear cells (PBMC) can effectively identify CH variants, its wide application still remains prohibitively expensive. Computational-only solutions are challenging due to shared bioinformatic presentations in both CH and somatic variants such as low allele frequency. Development of such algorithm with clinically meaningful accuracy will have extensive utility in cancer care.

Method We sequenced paired plasma-buffy coat samples from 754 pan-cancer patients using the FoundationOne® Liquid CDx (F1LCDx) assay. The samples were randomized into a training and a test set. Ground truth (tumor somatic vs. CH) for SV, including base substitutions and short indels, was determined by comparing variant calls in plasma vs in PBMC. A deep learning prediction model was developed in the training set. The model incorporates genomic and clinical features as input and returns a CH prediction score, which was dichotomized by a learned threshold. After the threshold and model parameters were finalized, we applied the model to the test set to evaluate performance.

Results In the test set of 222 paired samples (523 CH and 904 tumor somatic variants), the model achieved 91% sensitivity (probability of predicting true CH variants as CH) and 88% specificity (probability of predicting true tumor somatic variants as tumor somatic). The model accurately identified CH variants in challenging genes such as TP53 (sensitivity = 94%, specificity = 90%, n = 144) and ATM (sensitivity = 93%, specificity = 95%, n = 49), which that are known to harbor both tumor somatic and CH variants. Performance was further evaluated by cancer types and variant allele frequency. CH variants were identified with 90% sensitivity and 89% specificity in non-small cell lung carcinoma (n = 384), and with 87% sensitivity and 100% specificity in pancreas cancer (n = 53). CH variants were identified with 92% sensitivity and 87% specificity in 1%-5% variant allele frequency (n = 645), and with 94% sensitivity and 94% specificity in 5%-10% variant allele frequency (n = 189). Of note, a well-known oncogenic mutation in ATM was predicted as CH in a prostate cancer patient, which would prevent ineffective administration of PARP inhibitors. Multiple plasma specimens also gained more accurate bTMB and tumor fraction estimation by filtering out CH variants.

Conclusion For F1LCDx, we developed a computational method that distinguishes tumor somatic from CH variants from plasma cfDNA sequencing alone. The classifier exhibited high sensitivity and specificity in a pan-cancer cohort. Additional analytical validations are required in an external dataset. Clinical utility of this classifier will likely be further demonstrated in CH-corrected bTMB and tumor fraction.

Citation Format: Daokun Sun, Zheng Kuang, Alexander D. Fine, Eliana Polisecki, Holley Gettler, Hawra Al-Rekabi, Dean Pavlick, Yanmei Huang, Lee A. Albacker, Brennan Decker, Chang Xu. Predicting tumor somatic versus clonal hematopoiesis origin for short variants in liquid assay [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 2289.