Abstract 3695: Monitoring response to immunotherapy using cell free DNA fragmentomes
Authors: Bahar Alipanahi, Lavanya Sivapalan, Jamie Medina, Zachary L. Skidmore, Paola Ghanem, Erica Peters, Gavin Pereira, Nisha Rao, Kavya Velliangiri, Alissa Konicki, Stephen Cristiano, Laurel Millberg, Jacob Carey, Keith Lumbard, Noushin Niknafs, Bryan Chesnick, Jennifer Tom, Alessandro Leal, Benjamin Levy, Patrick Forde, Peter Bach, Nicholas C. Dracopoli, Robert B. Scharpf, Victor Velculescu, Lorenzo Rinaldi, Valsamo Anagnostou
Journal: Cancer Research (2024)

Abstract BACKGROUND: The rapid detection of disease progression in patients receiving immune checkpoint inhibitors (ICIs) is challenging since there are no reliable biomarkers of clinical response. Liquid biopsy assays may address this unmet need by using cell-free DNA (cfDNA) to monitor treatment responses. Current targeted next-generation sequencing cfDNA assays are costly and have limited assay sensitivity for detection of cancer-specific mutations at low mutant allele frequency (MAF). Here, we demonstrate the utility of DELFI Tumor Fraction (DELFI-TF), a tumor- and mutation-independent cfDNA fragmentome approach to monitor treatment response in patients with metastatic non-small cell lung cancer (mNSCLC). METHODS: Overall, 422 longitudinal blood samples were collected from 141 mNSCLC patients of which 109 were treated with immunotherapy and 32 with targeted therapy (TT). Plasma-derived cfDNA was processed with whole genome sequencing at low coverage (~4x). Circulating tumor burden was quantified as the maximum MAF (maxMAF) of tumor-derived variants detected using a 500+gene panel. Matched white blood cells were used to filter out germline and clonal hematopoietic variants. A random forest regression model was trained with maxMAF as the response using fragmentation-derived features. The accuracy of DELFI-TF was assessed using leave one patient out cross-validation in the ICI cohort and holdout validation in the cohort of patients receiving TT. For survival analyses, we used the median baseline scores to define low/high DELFI-TF and maxMAF. RESULTS: In the ICI cohort, DELFI-TF scores were strongly correlated with the maxMAF (r=0.94, p&amp;lt;0.001, Pearson). At baseline, DELFI-TF and maxMAF both differentiate responding from non-responding tumors (p = 0.01 and p = 0.001 for DELFI-TF and maxMAF respectively; Wilcoxon). Patients with high DELFI-TF or maxMAF had significantly shorter progression-free survival (PFS) compared to low DELFI-TF or maxMAF (17.0 vs 4.7 months, p &amp;lt; 0.001; 17.0 vs 4.6 months, p &amp;lt; 0.001; Log-Rank respectively) and similar overall survival (OS) (DELFI-TF high 11.4 vs low 34.1 months, p&amp;lt;0.001; maxMAF high 10.9 vs low 34.1 months, p &amp;lt; 0.001, Log-Rank). Changes in DELFI-TF and maxMAF at the earliest timepoint were highly correlated (n=109; r=0.90; Pearson). In the validation cohort of TT patients, DELFI-TF at baseline outperformed maxMAF in distinguishing patients with PFS and OS benefits (DELFI-TF PFS 36.4 vs 11.5 months, p = 0.03; maxMAF PFS 21.9 vs 15.9 months, p=0.6; Log-Rank) (DELFI-TF OS high 37 months vs low not reached (NR), p &amp;lt; 0.05; Max MAF OS high 37 vs NR, p = 0.1, Log-Rank). The majority of TT patients (81%) had consistent changes with DELFI-TF and maxMAF from baseline to the earliest timepoint. CONCLUSIONS: DELFI-TF is a tumor and mutation independent approach that is cost-efficient with high performance comparable to current ctDNA assays for estimating tumor burden and monitoring response in cancer patients. Citation Format: Bahar Alipanahi, Lavanya Sivapalan, Jamie Medina, Zachary L. Skidmore, Paola Ghanem, Erica Peters, Gavin Pereira, Nisha Rao, Kavya Velliangiri, Alissa Konicki, Stephen Cristiano, Laurel Millberg, Jacob Carey, Keith Lumbard, Noushin Niknafs, Bryan Chesnick, Jennifer Tom, Alessandro Leal, Benjamin Levy, Patrick Forde, Peter Bach, Nicholas C. Dracopoli, Robert B. Scharpf, Victor Velculescu, Lorenzo Rinaldi, Valsamo Anagnostou. Monitoring response to immunotherapy using cell free DNA fragmentomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3695.