Cell-free DNA methylation profile–based fusion epigenotyping to enhance <i>ALK</i> fusion detection in NSCLC patients.

Abstract

3070 Background: Short read lengths in next-generation sequencing and targeted panel probe design pose challenges to fusion detection by impairing the resolution of complex genomic rearrangements and the accurate mapping of intronic breakpoints. To address these limitations, we developed a cell-free DNA (cfDNA) methylation-based fusion epigenotyping method that leverages fusion-associated tumor epigenetic signatures to complement genomic-based methods and increase the fusion detection sensitivity of our liquid biopsy. We validated EML4 - ALK fusion detection by this algorithm in non-small cell lung cancer (NSCLC) using paired clinical tumor tissue and cfDNA samples. Methods: We trained a binary classifier to discriminate EML4-ALK fusion-positive from fusion-negative NSCLC using cfDNA methylation signal and genomic molecule support. To validate the epigenotyping classifier, an independent cohort of 577 clinical NSCLC samples was selected with paired tumor tissue and Guardant360 Liquid (Guardant Health, Palo Alto, CA) cfDNA for each patient (with epigenomic tumor fraction &gt; 0.03%). The cohort included 94 tissue-confirmed fusion-positive samples (78 cfDNA genomic positives and 16 cfDNA genomic false negatives) with EML4-ALK detected in tumor tissue, and 483 tissue-confirmed fusion-negative samples ( ALK fusion negative in both tissue and paired cfDNA). The epigenotyping classifier predictions in cfDNA were evaluated against tissue-based orthogonal truth. Results: Among tissue-confirmed fusion-positive samples, tissue-liquid assessment showed a high positive percent agreement (PPA) / sensitivity of 89.36% (84/94), as well as 100% concordance with genomic caller positives (78/78). The rate of rescued fusions by the epigenotyping classifier from genomic false negative liquid cases was 38% (6/16). Among tissue-confirmed fusion-negative samples, tissue-liquid assessment showed a high negative percent agreement (NPA) / specificity of 99.38% (480/483). The false positive rate (FPR) of high confidence calls (probability exceeding a 99.7% specificity threshold or with partial genomic evidence) was 0.0% (0/483). Conclusions: cfDNA methylation-based fusion epigenotyping substantially increased detection of actionable ALK fusions while maintaining high specificity, as demonstrated by tissue-liquid concordance. The results of this approach showed the clinical value of giving NSCLC patients an increased likelihood to receive more effective, less toxic ALK inhibitor therapy, while the minimized FPR helps ensure appropriately matched treatment decisions.