Exploring the potential of multiomics liquid biopsy testing in the clinical setting of lung cancer.
Cytopathology
; 35(6): 664-670, 2024 Nov.
Article
en En
| MEDLINE
| ID: mdl-38822635
ABSTRACT
The transformative role of artificial intelligence (AI) and multiomics could enhance the diagnostic and prognostic capabilities of liquid biopsy (LB) for lung cancer (LC). Despite advances, the transition from tissue biopsies to more sophisticated, non-invasive methods like LB has been impeded by challenges such as the heterogeneity of biomarkers and the low concentration of tumour-related analytes. The advent of multiomics - enabled by deep learning algorithms - offers a solution by allowing the simultaneous analysis of various analytes across multiple biological fluids, presenting a paradigm shift in cancer diagnostics. Through multi-marker, multi-analyte and multi-source approaches, this review showcases how AI and multiomics are identifying clinically valuable biomarker combinations that correlate with patients' health statuses. However, the path towards clinical implementation is fraught with challenges, including study reproducibility and lack of methodological standardization, thus necessitating urgent solutions to solve these common issues.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Biomarcadores de Tumor
/
Neoplasias Pulmonares
Límite:
Humans
Idioma:
En
Revista:
Cytopathology
Asunto de la revista:
PATOLOGIA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Italia