Early detection and stratification of colorectal cancer using plasma cell-free DNA fragmentomic profiling.
Genomics
; 116(4): 110876, 2024 07.
Article
en En
| MEDLINE
| ID: mdl-38849019
ABSTRACT
Timely accurate and cost-efficient detection of colorectal cancer (CRC) is of great clinical importance. This study aims to establish prediction models for detecting CRC using plasma cell-free DNA (cfDNA) fragmentomic features. Whole-genome sequencing (WGS) was performed on cfDNA from 620 participants, including healthy individuals, patients with benign colorectal diseases and CRC patients. Using WGS data, three machine learning methods were compared to build prediction models for the stratification of CRC patients. The optimal model to discriminate CRC patients of all stages from healthy individuals achieved a sensitivity of 92.31% and a specificity of 91.14%, while the model to separate early-stage CRC patients (stage 0-II) from healthy individuals achieved a sensitivity of 88.8% and a specificity of 96.2%. Additionally, the cfDNA fragmentation profiles reflected disease-specific genomic alterations in CRC. Overall, this study suggests that cfDNA fragmentation profiles may potentially become a noninvasive approach for the detection and stratification of CRC.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Neoplasias Colorrectales
/
Detección Precoz del Cáncer
Límite:
Adult
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Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Genomics
Asunto de la revista:
GENETICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
China