Bridging biological cfDNA features and machine learning approaches.
Trends Genet
; 39(4): 285-307, 2023 04.
Article
em En
| MEDLINE
| ID: mdl-36792446
ABSTRACT
Liquid biopsies (LBs), particularly using circulating tumor DNA (ctDNA), are expected to revolutionize precision oncology and blood-based cancer screening. Recent technological improvements, in combination with the ever-growing understanding of cell-free DNA (cfDNA) biology, are enabling the detection of tumor-specific changes with extremely high resolution and new analysis concepts beyond genetic alterations, including methylomics, fragmentomics, and nucleosomics. The interrogation of a large number of markers and the high complexity of data render traditional correlation methods insufficient. In this regard, machine learning (ML) algorithms are increasingly being used to decipher disease- and tissue-specific signals from cfDNA. Here, we review recent insights into biological ctDNA features and how these are incorporated into sophisticated ML applications.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Hematológicas
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Ácidos Nucleicos Livres
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DNA Tumoral Circulante
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Neoplasias
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article