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Biomarkers of immunotherapy in non-small cell lung cancer
Lingling Wang1, Yue Hu2, Shengchao Wang3
1Department of Surgical Oncology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, P.R. China.
Abstract:
Immunotherapy has markedly improved the survival rate of patients with non-small cell lung cancer (NSCLC) and has introduced a new era in lung cancer treatment. However, not all patients with lung cancer benefit from checkpoint blockade, and some suffer from notable immunotoxicities. Thus, it is crucial to identify potential biomarkers suitable for screening the population that may benefit from immunotherapy. Based on the current clinical trials, the aim of the present study was to review the biomarkers for immune checkpoint inhibition, as well as other effective, invalid and hyperprogression markers that may have the potential to better predict responders to immunotherapy among patients with NSCLC. All these biomarkers may be incorporated into the predictive utility of bio-score systems and decision-making algorithms, to better guide the application of immunotherapy in the clinical setting.
Insights
Identifying biomarkers is crucial for predicting which non-small cell lung cancer (NSCLC) patients benefit from immunotherapy. This review explores markers to guide treatment selection and improve patient outcomes.
Area of Science:
- Oncology
- Immunology
- Biomarker Discovery
Background:
- Immunotherapy has transformed non-small cell lung cancer (NSCLC) treatment, improving survival rates.
- However, not all NSCLC patients respond to immune checkpoint inhibitors, and some experience severe side effects.
- Predictive biomarkers are needed to identify patients likely to benefit from immunotherapy.
Purpose of the Study:
- To review biomarkers for immune checkpoint inhibition in NSCLC.
- To identify markers predicting response, non-response, and hyperprogression to immunotherapy.
- To guide the clinical application of immunotherapy in NSCLC through bio-score systems and algorithms.
Main Methods:
- Systematic review of current clinical trials.
- Analysis of biomarkers for immune checkpoint inhibition.
- Evaluation of markers for treatment response and hyperprogression.
Main Results:
- Several biomarkers show potential for predicting immunotherapy response in NSCLC.
- Markers for identifying non-responders and hyperprogressors are also under investigation.
- Integration of biomarkers into clinical decision-making tools is proposed.
Conclusions:
- Biomarker identification is essential for optimizing immunotherapy in NSCLC.
- Predictive markers can help personalize treatment strategies and minimize adverse events.
- Further research and validation are needed to incorporate these biomarkers into clinical practice.
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