# Leveraging the cfDNA fragmentome to predict immunotherapy response Valsamo (Elsa) Anagnostou, MD, PhD Associate Professor Co-director, Upper Aerodigestive Malignancies Program Leader, Precision Oncology Analytics, Molecular Tumor Board & Lung Cancer Precision Medicine Center of Excellence Director, Thoracic Oncology Biorepository Johns Hopkins School of Medicine, Baltimore, MD --- # Disclosure Information ## Valsamo Anagnostou I have the following relevant financial relationships to disclose: Consultant for: Astra Zeneca, Neogenomics Grant/Research support (active, to institution): Astra Zeneca, Personal Genome Diagnostics/Labcorp Honoraria from: Foundation Medicine, Personal Genome Diagnostics/Labcorp, Guardant Health And-My additional financial relationship disclosures are: I am an inventor on patent applications (63/276,525, 17/779,936, 16/312,152, 16/341,862, 17/047,006 and 17/598,690) submitted by Johns Hopkins University related to cancer genomic analyses, ctDNA therapeutic response monitoring and immunogenomic features of response to immunotherapy that have been licensed to one or more entities. Under the terms of these license agreements, the University and inventors are entitled to fees and royalty distributions. --- # Opportunities and challenges with ctDNA response as an early endpoint for immunotherapy Aredo et al., ASCO Educational Book, 2025, in press --- # Mutation-based ctDNA molecular response predicts immunotherapy outcomes Anagnostou et al., Cancer Res, 2019, Sivapalan et al., Clin Can Res, 2023, Murray et al., Clin Can Res, 2024, Anagnostou et al., Nat Med, 2023 --- # Clinical sensitivity of mutation-based ctDNA molecular response by magnitude Sivapalan et al., under review --- # Inherent challenges with tumor-agnostic WBC DNA-informed liquid biopsy approaches Sivapalan et al., submitted --- # Johns Hopkins Thoracic Oncology prospective minimally invasive biomarker clinical protocol --- # Overview of the experimental approach and bioinformatic analyses --- # Concordance between cfDNA fragmentome- and mutation-derived tumor fraction estimates --- # Detectable rate by plasma-only, WBC-informed, tumor-informed and fragmentome approach --- # Differential cfDNA fragmentation patterns by timepoint and molecular response groups --- # Concordance between fragmentome-TF and mutation-based ctDNA response --- # Fragmentome-TF more accurately predicts outcomes in mutation-based molecular progressors --- # Landmark fragmentome-TF molecular response predicts progression-free survival --- # Landmark fragmentome-TF molecular response independently predicts overall survival --- # Acknowledgements Molecular Oncology Lab @Hopkins Thoracic Qiong Meng Noushin Niknafs Paul Lee Blair Landon Ilias Ziakas Archana Balan Jaime Wehr Danny Rabizadeh Chris Cherry Mimi Najjar Justin Huang Cancer Immunology Drew Pardoll Kellie Smith Pathology Peter Illei Janis Taube Kay Li CCTG and BR.36 investigators Janet Dancey Cheryl Ho Penelope Bradbury Pierre-Olivier Gaudreau Keyue Ding Egor Avrutin Liting Zhu ECOG-ACRIN, PRECOG Thoracic Surgery Richard Battafarano Stephen Yang Jinny Ha Stephen Broderick All Ireland NCI Cancer Consortium Hopkins Biomedical Engineering Rachel Karchin Cancer Genetics Cancer Research Institute Cancer Genetics & Epigenetics Victor Velculescu Bioinformatics Rob Scharpf Netherlands Cancer Institute DELFI Diagnostics Lorenzo Rinaldi Bryan Chesnick Zack Skidmore Bahar Alipanahi Funding Sources: NIH, FDA OCE, Department of Defense, Maryland Department of Health and Mental Hygiene, EA Thoracic ITSC, Johns Hopkins ICTR, Johns Hopkins Catalyst Award, Cancer Research Institute, LUNGevity, V Foundation, Swim Across America, Emerson Collective, The Mark Foundation, The Elsa U. Pardee Foundation, BMS, Astra Zeneca, Delfi Diagnostics, Labcorp