複数の生体マトリックスを用いた肺がんの臨床管理のための包括的なリキッドバイオプシーアプローチ

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related mortality in both men and women. It is broadly classified into two main histological subtypes, with non-small cell lung cancer (NSCLC) being the most prevalent, accounting for approximately 85-90% of all cases. Liquid biopsy refers to the analysis of tumor-derived material circulating in body fluids. This minimally invasive technique can be performed repeatedly over time and enables the detection of a tumor's genomic profile without tissue samples. Liquid biopsies have the potential to identify biomarkers across different lung cancer subtypes that may be associated with early detection, prognosis, and prediction of response to targeted therapies. In this context, bioinformatics tools play a critical role in analyzing large-scale, high-dimensional omics datasets, which can be transformed into clinically meaningful insights. This article emphasizes the significance of prognostic, predictive, and diagnostic biomarkers in lung cancer, which can be detected in various biological fluids. Furthermore, it highlights how integrating bioinformatics approaches can facilitate the development of a personalized molecular profile, ultimately supporting individualized treatment strategies for each patient.