{"title":"非小细胞肺癌围手术期免疫检查点抑制剂免疫生物标志物的机制研究","authors":"Yanting Long, Runsen Jin, Hecheng Li","doi":"10.21037/tlcr-2025-162","DOIUrl":null,"url":null,"abstract":"<p><p>Immune checkpoint inhibitors (ICIs) targeting the programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) axis have revolutionized the treatment of non-small cell lung cancer (NSCLC), demonstrating remarkable efficacy in advanced-stage patients. These therapies have demonstrated durable responses and improved survival outcomes. Recently, perioperative ICIs have emerged as a promising approach for early-stage resectable NSCLC to address high postoperative recurrence rates and improve long-term survival. Clinical trials on adjuvant, neoadjuvant, and a combination of both perioperative ICIs therapies, such as CheckMate 816 and KEYNOTE-671, have demonstrated improvements in pathological complete response (pCR), event-free survival (EFS), and overall survival (OS). However, challenges remain, including low response rates in NSCLC patients and the occurrence of immune-related adverse events (irAEs). These factors highlight the urgent need for robust predictive biomarkers to better stratify patients and guide clinical decision-making. While numerous studies have explored the predictive and guiding value of various biomarkers, few have reached clinical application, leaving significant gaps. Moreover, the complexity and heterogeneity of tumor-immune interactions underscore the need for integrated, multimodal predictive models. This review highlights the current state and unresolved challenges in perioperative ICIs treatment for early-stage resectable NSCLC, emphasizing the critical role of biomarkers in advancing these therapies. It provides a comprehensive summary of potential biomarkers identified in recent research, elucidating their predictive mechanisms and interrelationships. The goal is to inspire the discovery of novel biomarkers and support the integration of multiple biomarkers for combined predictive models, ultimately optimizing patient selection and therapeutic outcomes.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 7","pages":"2821-2841"},"PeriodicalIF":3.5000,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12337034/pdf/","citationCount":"0","resultStr":"{\"title\":\"Mechanistic insights into the immune biomarker of perioperative immune checkpoint inhibitors for non-small cell lung cancer.\",\"authors\":\"Yanting Long, Runsen Jin, Hecheng Li\",\"doi\":\"10.21037/tlcr-2025-162\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Immune checkpoint inhibitors (ICIs) targeting the programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) axis have revolutionized the treatment of non-small cell lung cancer (NSCLC), demonstrating remarkable efficacy in advanced-stage patients. These therapies have demonstrated durable responses and improved survival outcomes. Recently, perioperative ICIs have emerged as a promising approach for early-stage resectable NSCLC to address high postoperative recurrence rates and improve long-term survival. Clinical trials on adjuvant, neoadjuvant, and a combination of both perioperative ICIs therapies, such as CheckMate 816 and KEYNOTE-671, have demonstrated improvements in pathological complete response (pCR), event-free survival (EFS), and overall survival (OS). However, challenges remain, including low response rates in NSCLC patients and the occurrence of immune-related adverse events (irAEs). These factors highlight the urgent need for robust predictive biomarkers to better stratify patients and guide clinical decision-making. While numerous studies have explored the predictive and guiding value of various biomarkers, few have reached clinical application, leaving significant gaps. Moreover, the complexity and heterogeneity of tumor-immune interactions underscore the need for integrated, multimodal predictive models. This review highlights the current state and unresolved challenges in perioperative ICIs treatment for early-stage resectable NSCLC, emphasizing the critical role of biomarkers in advancing these therapies. It provides a comprehensive summary of potential biomarkers identified in recent research, elucidating their predictive mechanisms and interrelationships. The goal is to inspire the discovery of novel biomarkers and support the integration of multiple biomarkers for combined predictive models, ultimately optimizing patient selection and therapeutic outcomes.</p>\",\"PeriodicalId\":23271,\"journal\":{\"name\":\"Translational lung cancer research\",\"volume\":\"14 7\",\"pages\":\"2821-2841\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12337034/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Translational lung cancer research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.21037/tlcr-2025-162\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/16 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational lung cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/tlcr-2025-162","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/16 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
Mechanistic insights into the immune biomarker of perioperative immune checkpoint inhibitors for non-small cell lung cancer.
Immune checkpoint inhibitors (ICIs) targeting the programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) axis have revolutionized the treatment of non-small cell lung cancer (NSCLC), demonstrating remarkable efficacy in advanced-stage patients. These therapies have demonstrated durable responses and improved survival outcomes. Recently, perioperative ICIs have emerged as a promising approach for early-stage resectable NSCLC to address high postoperative recurrence rates and improve long-term survival. Clinical trials on adjuvant, neoadjuvant, and a combination of both perioperative ICIs therapies, such as CheckMate 816 and KEYNOTE-671, have demonstrated improvements in pathological complete response (pCR), event-free survival (EFS), and overall survival (OS). However, challenges remain, including low response rates in NSCLC patients and the occurrence of immune-related adverse events (irAEs). These factors highlight the urgent need for robust predictive biomarkers to better stratify patients and guide clinical decision-making. While numerous studies have explored the predictive and guiding value of various biomarkers, few have reached clinical application, leaving significant gaps. Moreover, the complexity and heterogeneity of tumor-immune interactions underscore the need for integrated, multimodal predictive models. This review highlights the current state and unresolved challenges in perioperative ICIs treatment for early-stage resectable NSCLC, emphasizing the critical role of biomarkers in advancing these therapies. It provides a comprehensive summary of potential biomarkers identified in recent research, elucidating their predictive mechanisms and interrelationships. The goal is to inspire the discovery of novel biomarkers and support the integration of multiple biomarkers for combined predictive models, ultimately optimizing patient selection and therapeutic outcomes.
期刊介绍:
Translational Lung Cancer Research(TLCR, Transl Lung Cancer Res, Print ISSN 2218-6751; Online ISSN 2226-4477) is an international, peer-reviewed, open-access journal, which was founded in March 2012. TLCR is indexed by PubMed/PubMed Central and the Chemical Abstracts Service (CAS) Databases. It is published quarterly the first year, and published bimonthly since February 2013. It provides practical up-to-date information on prevention, early detection, diagnosis, and treatment of lung cancer. Specific areas of its interest include, but not limited to, multimodality therapy, markers, imaging, tumor biology, pathology, chemoprevention, and technical advances related to lung cancer.