Ultrasensitive Detection of Biomarkers for Guiding Immunotherapy in Lung Cancer: A Liquid Biopsy Approach
Liquid biopsy (LB) represents a promising strategy for the early diagnosis and treatment of lung cancer. However, relying solely on single-biomarker immunohistochemistry for predictive purposes has shown limited efficacy, often leading to suboptimal responses in certain patients. LB provides a complementary or alternative approach to immunohistochemistry by aiding in the identification of patients better suited for immunotherapy, thereby improving treatment precision. This review highlights key LB targets, including circulating tumor cells, exosomes, and small protein molecules, and explores the predictive and prognostic value of LB in immunotherapy for lung cancer and other tumors. These biomarkers play complex and multifaceted roles in liquid biopsies. Consequently, researchers have developed numerous targeted detection methods to study and identify key factors among multiple biomarkers in lung cancer and other tumor diseases. In addition, the limitations and future directions of LB are examined, aiming to advance its clinical application and support the development of personalized and precise immunotherapy. The integration of LB with artificial intelligence holds significant clinical potential for guiding immunotherapy and advancing precision medicine in lung cancer and other tumors.
Authors
- Yongfeng Lu (ORCID: https://orcid.org/0000-0002-5942-1999)
- Chuan Xu (ORCID: https://orcid.org/0000-0002-5320-2277)
- Caihong Liu (ORCID: https://orcid.org/0000-0002-2557-8090)
- Cheng Jiang (ORCID: https://orcid.org/0000-0003-4386-0740)
Publication Details
- Journal
- Oncology Advances
- Published
- 2024-12-25
- DOI
- https://doi.org/10.14218/ona.2024.00030
- Primary Topic
- Advanced Biosensing Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Basic and Applied Basic Research Foundation of Guangdong Province