Leveraging the cfDNA fragmentome to predict immunotherapy response
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
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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
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Detectable rate by plasma-only, WBC-informed, tumor-informed and fragmentome approach
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Differential cfDNA fragmentation patterns by timepoint and molecular response groups
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Concordance between fragmentome-TF and mutation-based ctDNA response
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Fragmentome-TF more accurately predicts outcomes in mutation-based molecular progressors
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Landmark fragmentome-TF molecular response predicts progression-free survival
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Landmark fragmentome-TF molecular response independently predicts overall survival
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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 https://anagnostoulab.org
Gavin Pereira https://anagnostoulab.org
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