Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previ...

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Vydáno v:	Nature medicine Ročník 30; číslo 6; s. 1655 - 1666
Hlavní autoři:	Widman, Adam J., Shah, Minita, Frydendahl, Amanda, Halmos, Daniel, Khamnei, Cole C., Øgaard, Nadia, Rajagopalan, Srinivas, Arora, Anushri, Deshpande, Aditya, Hooper, William F., Quentin, Jean, Bass, Jake, Zhang, Mingxuan, Langanay, Theophile, Andersen, Laura, Steinsnyder, Zoe, Liao, Will, Rasmussen, Mads Heilskov, Henriksen, Tenna Vesterman, Jensen, Sarah Østrup, Nors, Jesper, Therkildsen, Christina, Sotelo, Jesus, Brand, Ryan, Schiffman, Joshua S., Shah, Ronak H., Cheng, Alexandre Pellan, Maher, Colleen, Spain, Lavinia, Krause, Kate, Frederick, Dennie T., den Brok, Wendie, Lohrisch, Caroline, Shenkier, Tamara, Simmons, Christine, Villa, Diego, Mungall, Andrew J., Moore, Richard, Zaikova, Elena, Cerda, Viviana, Kong, Esther, Lai, Daniel, Malbari, Murtaza S., Marton, Melissa, Manaa, Dina, Winterkorn, Lara, Gelmon, Karen, Callahan, Margaret K., Boland, Genevieve, Potenski, Catherine, Wolchok, Jedd D., Saxena, Ashish, Turajlic, Samra, Imielinski, Marcin, Berger, Michael F., Aparicio, Sam, Altorki, Nasser K., Postow, Michael A., Robine, Nicolas, Andersen, Claus Lindbjerg, Landau, Dan A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Nature Publishing Group US 01.06.2024 Nature Publishing Group
Témata:	631/208/69 692/699/67 Aneuploidy Biomarkers, Tumor - blood Biomarkers, Tumor - genetics Biomedical and Life Sciences Biomedicine Cancer Research Circulating Tumor DNA - blood Circulating Tumor DNA - genetics Colorectal cancer Colorectal Neoplasms - blood Colorectal Neoplasms - genetics Colorectal Neoplasms - pathology Deep learning Deoxyribonucleic acid DNA DNA Copy Number Variations Enrichment Gene sequencing Genomes Humans Immunotherapy Infectious Diseases Learning algorithms Lung cancer Lung Neoplasms - blood Lung Neoplasms - genetics Lung Neoplasms - pathology Machine Learning Melanoma Metabolic Diseases Minimal residual disease Molecular Medicine Monitoring Neoplasm, Residual - genetics Neoplasms - blood Neoplasms - genetics Neoplasms - pathology Neoplasms - therapy Neurosciences Nucleotides Polymorphism, Single Nucleotide Solid tumors Telemedicine Tumor Burden Tumors Whole Genome Sequencing
ISSN:	1078-8956, 1546-170X, 1546-170X
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Shrnutí:	In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGE SNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGE CNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGE SNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition. Detection of circulating tumor DNA using MRD-EDGE, a machine-learning-guided single-nucleotide variant and copy-number variant detection platform for signal enrichment, enables monitoring of minimal residual disease and immunotherapy response in settings of low tumor burden.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 These authors co-supervised These authors contributed equally
ISSN:	1078-8956 1546-170X 1546-170X
DOI:	10.1038/s41591-024-03040-4