Exploring histological predictive biomarkers for immune checkpoint inhibitor therapy response in non–small cell lung cancer
Treatment challenges persist in advanced lung cancer despite the development of therapies beyond the traditional platinum-based chemotherapy. The early 2000s marked a shift to tyrosine kinase inhibitors targeting epidermal growth factor receptor, ushering in personalized genetic-based treatment. A f...
Saved in:
Published in | Journal of pathology and translational medicine Vol. 58; no. 2; pp. 49 - 58 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Korea (South)
Korean Society of Pathologists, Korean Society for Cytopathology
01.03.2024
The Korean Society of Pathologists and the Korean Society for Cytopathology Korean Society of Pathologists & the Korean Society for Cytopathology 대한병리학회 |
Subjects | |
Online Access | Get full text |
ISSN | 2383-7837 2383-7845 |
DOI | 10.4132/jptm.2024.01.31 |
Cover
Summary: | Treatment challenges persist in advanced lung cancer despite the development of therapies beyond the traditional platinum-based chemotherapy. The early 2000s marked a shift to tyrosine kinase inhibitors targeting epidermal growth factor receptor, ushering in personalized genetic-based treatment. A further significant advance was the development of immune checkpoint inhibitors (ICIs), especially for non–small cell lung cancer. These target programmed death-ligand 1 (PD-L1) and cytotoxic T lymphocyte antigen 4, which enhanced the immune response against tumor cells. However, not all patients respond, and immune-related toxicities arise. This review emphasizes identifying biomarkers for ICI response prediction. While PD-L1 is a widely used, validated biomarker, its predictive accuracy is imperfect. Investigating tumor-infiltrating lymphocytes, tertiary lymphoid structure, and emerging biomarkers such as high endothelial venule, Human leukocyte antigen class I, T-cell immunoreceptors with Ig and ITIM domains, and lymphocyte activation gene-3 counts is promising. Understanding and exploring additional predictive biomarkers for ICI response are crucial for enhancing patient stratification and overall care in lung cancer treatment. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Review-3 content type line 23 |
ISSN: | 2383-7837 2383-7845 |
DOI: | 10.4132/jptm.2024.01.31 |