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Predictive biomarkers for response to immune checkpoint inhibitors in lung cancer: PD-L1 and beyond
Hironori Uruga1, Mari Mino-Kenudson2
1Department of Pathology, Toranomon Hospital, Tokyo, Japan.
Abstract:
Immune checkpoint inhibitor (ICI) therapies, including the programmed cell death protein 1 (PD-1) axis blockade, are considered a major oncological breakthrough of the early twenty-first century and have led to remarkable response rates and survival in a subset of patients with non-small cell lung cancer (NSCLC). However, the available therapies work only for one in five unselected, advanced NSCLC patients; thus, patient selection needs to be performed with the use of efficient biomarkers. Although imperfect, programmed death-ligand 1 (PD-L1) expression by immunohistochemistry (IHC) on tumor cells and/or immune cells has been established as a predictive biomarker for response to the PD-1 axis blockade. There remain several pre-analytical, analytical, and post-analytical issues, however, before implementing a PD-L1 IHC assay(s) in the pathology laboratory. In addition, given the lack of robust sensitivity and specificity of PD-L1 IHC for predicting response to ICIs, other biomarkers including tumor mutation burden (TMB) are under investigation. In this review, issues associated with PD-L1 IHC and TMB estimations will be discussed, and other promising biomarkers for predicting response to ICIs will be briefly introduced.
Insights
Immune checkpoint inhibitors (ICIs) show promise for non-small cell lung cancer (NSCLC), but patient selection is key. This review discusses programmed death-ligand 1 (PD-L1) testing challenges and explores alternative biomarkers like tumor mutation burden (TMB) for better treatment prediction.
Area of Science:
- Oncology
- Immunotherapy
- Pathology
Background:
- Immune checkpoint inhibitor (ICI) therapies, particularly programmed cell death protein 1 (PD-1) axis blockade, represent a significant advancement in cancer treatment.
- These therapies have demonstrated remarkable efficacy in a subset of patients with advanced non-small cell lung cancer (NSCLC), improving response rates and survival.
- However, current ICI treatments benefit only a fraction of unselected NSCLC patients, highlighting the critical need for effective patient selection biomarkers.
Purpose of the Study:
- To review the challenges and limitations associated with using programmed death-ligand 1 (PD-L1) expression by immunohistochemistry (IHC) as a predictive biomarker for ICI response in NSCLC.
- To discuss the issues related to pre-analytical, analytical, and post-analytical phases of PD-L1 IHC assays in pathology laboratories.
- To introduce and briefly discuss other promising biomarkers, such as tumor mutation burden (TMB), for predicting patient response to ICIs.
Main Methods:
- Literature review focusing on PD-L1 IHC assays and their implementation in clinical practice.
- Discussion of the analytical and clinical validation of PD-L1 IHC assays.
- Exploration of emerging biomarkers, including tumor mutation burden (TMB), for predicting ICI efficacy.
Main Results:
- Programmed death-ligand 1 (PD-L1) expression via IHC is an established, albeit imperfect, biomarker for predicting response to PD-1 axis blockade in NSCLC.
- Significant pre-analytical, analytical, and post-analytical challenges exist in the standardization and implementation of PD-L1 IHC assays.
- The sensitivity and specificity of PD-L1 IHC for predicting ICI response are suboptimal, necessitating the investigation of alternative biomarkers.
Conclusions:
- Accurate patient selection is crucial for optimizing the benefits of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC).
- Standardization and overcoming technical challenges in PD-L1 IHC assays are necessary for reliable biomarker implementation.
- Further research into alternative and complementary biomarkers, such as tumor mutation burden (TMB), is essential for improving the prediction of ICI response in NSCLC patients.
