Biomarkers of response to checkpoint inhibitors beyond PD-L1 in lung cancer
1Department of Pathology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA. lmsholl@bwh.harvard.edu.
Abstract:
Immunotherapy, including use of checkpoint inhibitors against PD-1, PD-L1, and CTLA-4, forms the backbone of oncologic management for the majority of non-small cell lung carcinoma patients. However, response to these therapies varies widely, from patients who have complete resolution of metastatic disease and long-term remission, to those who rapidly progress and succumb to their cancer despite use of the newest checkpoint inhibitors. While PD-L1 protein expression by immunohistochemistry serves as the principle predictive biomarker for immunotherapy response, neither the sensitivity nor the specificity of this approach is optimal, and clinical PD-L1 testing is plagued by concerns around result reproducibility and confusion born from the proliferation of different companion diagnostic assays. At the same time, insights into tumor and host immune-specific factors that inform both prognosis and response prediction are beginning to define better immunotherapy biomarkers. Beyond immune checkpoint expression status, common themes in analyses of immunotherapy response prediction include cancer neoantigen production, the state of the antigen presentation pathway in both tumor and antigen presenting cells, the admixture of effector and suppressor immune cells in the tumor microenvironment, and the genomic drivers and comutations that can influence the all of these variables. This review will address the state of PD-L1 testing in lung cancer, the role for tumor mutation burden as a predictive biomarker, the evolving status of human leukocyte antigen/major histocompatibility complex expression as a marker of antigen presentation, approaches to tumor immune cell quantitation including by multiplex immunofluorescence, and the importance of tumor genomic profiling to ascertain oncogenic driver (EGFR, ALK, KRAS, MET, etc.) and co-mutation (STK11, KEAP1, SMARCA4) status.
Insights
Immunotherapy response in lung cancer varies greatly. New biomarkers beyond PD-L1 expression, including tumor mutation burden and genomic profiling, are crucial for predicting treatment success.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Immunotherapy, particularly checkpoint inhibitors targeting PD-1, PD-L1, and CTLA-4, is a cornerstone in treating non-small cell lung carcinoma.
- Patient responses to immunotherapy are highly variable, ranging from complete remission to rapid progression, highlighting the need for better predictive biomarkers.
- Current PD-L1 expression testing as a biomarker has limitations in sensitivity, specificity, and reproducibility, compounded by diverse companion diagnostic assays.
Purpose of the Study:
- To review the current landscape of PD-L1 testing in lung cancer.
- To explore emerging biomarkers for predicting immunotherapy response, including tumor mutation burden, human leukocyte antigen (HLA) expression, and tumor immune cell infiltration.
- To emphasize the role of comprehensive genomic profiling in identifying oncogenic drivers and co-mutations that influence immunotherapy outcomes.
Main Methods:
- Review of current literature on immunotherapy biomarkers in non-small cell lung carcinoma.
- Analysis of the utility of PD-L1 expression testing and its limitations.
- Discussion of novel predictive markers such as tumor mutation burden, HLA/MHC expression, tumor microenvironment immune cell composition (e.g., via multiplex immunofluorescence), and tumor genomic profiling.
Main Results:
- PD-L1 expression testing, while standard, has suboptimal predictive accuracy and faces reproducibility challenges.
- Tumor mutation burden, HLA/MHC expression, and immune cell profiling show promise as complementary or alternative biomarkers.
- Genomic profiling reveals key oncogenic drivers (e.g., EGFR, ALK, KRAS) and co-mutations (e.g., STK11, KEAP1) that significantly impact immunotherapy efficacy.
Conclusions:
- Optimizing immunotherapy for lung cancer requires moving beyond PD-L1 expression to incorporate a multi-faceted biomarker approach.
- Integrating tumor mutation burden, immune cell analysis, and comprehensive genomic profiling can enhance prediction of treatment response and patient outcomes.
- Further research and standardization of these advanced biomarkers are essential for clinical implementation in non-small cell lung carcinoma management.
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