Immune checkpoint inhibitors (ICIs) have made great progress in the field of tumors and have become a promising direction of tumor treatment. With advancements in genomics and bioinformatics technology, it is possible to individually analyze the neoantigens produced by somatic mutations of each patient. Neoantigen load (NAL), a promising biomarker for predicting the efficacy of ICIs, has been extensively studied. This article reviews the research progress on NAL as a biomarker for predicting the anti-tumor effects of ICI. First, we provide a definition of NAL, and summarize the detection methods, and their relationship with tumor mutation burden. In addition, we describe the common genomic sources of NAL. Finally, we review the predictive value of NAL as a tumor prediction marker based on various clinical studies. This review focuses on the predictive ability of NAL’s ICI efficacy against tumors. In melanoma, lung cancer, and gynecological tumors, NAL can be considered a predictor of treatment efficacy. In contrast, the use of NAL for urinary system and liver tumors requires further research. When NAL alone is insufficient to predict efficacy, its combination with other indicators can improve prediction efficiency. Evaluating the response of predictive biomarkers before the treatment initiation is essential for guiding the clinical treatment of cancer. The predictive power of NAL has great potential; however, it needs to be based on more accurate sequencing platforms and technologies.
In recent years, immune checkpoint inhibitors (ICIs) have become the standard treatment option for tumors. With the widespread application of ICIs, immune-related adverse events (irAEs) have gradually attracted the attention of researchers. Owing to the characteristics of ICIs, irAEs can affect each organ of the human body. Thromboembolism is uncommon in cancer patients receiving ICIs, but it may affect their survival. Most thromboembolic events do not cause serious effects after early prediction and treatment, but life-threatening toxic reactions are also observed. This condition should not be ignored because of vague and atypical symptoms, which make early diagnosis more challenging. This article focuses on the high-risk factors, underlying mechanisms, incidence, and prognosis of thromboembolism in patients using ICIs and briefly describes the intervention and treatment measures. This information would allow patients to effectively manage the side effects of thromboembolism during Immune checkpoint inhibitors treatment, ensuring the efficacy of ICIs and reducing mortality.
Background For treatment of advanced lung cancer, immune checkpoint inhibitors (ICIs) + chemotherapy or the combination of dual ICIs has become the standard first-line treatment in recent years. Considering the differences among patients’ immune systems, the response to ICIs may vary. Therefore, we aimed to evaluate the predictive implications of patient age and Eastern Cooperative Oncology Group (ECOG) performance status (PS) for the efficacy of ICIs for the treatment of lung cancer. Methods We searched the PubMed, Cochrane Library, Web of Science, and EMBASE databases for articles published between January 2010 and September 2020 that compared overall (OS) and progression-free survival (PFS) rates between patients with lung carcinoma who were administered ICIs and control treatments. Results Twenty-four trials including 15,584 patients were selected. ICIs significantly improved the OS rates in patients aged < 65 (hazard ratio [HR], 0.73; 95% confidence interval [CI], 0.65–0.82) and ≥ 65 (0.75 [0.70–0.82]) years, with an age cut-off of 65 years; patients aged < 65 (0.83 [0.72–0.95]) years, when age was classified as < 65, 65–74, and ≥ 75 years; and patients with an ECOG PS score of 0 (0.77 [0.69–0.86]) and 1 (0.78 [0.72–0.85]). However, the differences between the two age groups (p = 0.69), the three age groups (p = 0.43), and the ECOG PS groups (p = 0.82) were not insignificant. Significant advantages of ICIs in terms of PFS rates were found in patients aged < 65 (0.64 [0.52–0.79]) and ≥ 65 (0.73 [0.64–0.84]) years and in those with an ECOG PS score of 0 (0.63 [0.49–0.82]) and 1 (0.66 [0.59–0.75]). No significant difference was observed between the age (p = 0.35) and ECOG PS groups (p = 0.89). Conclusions Younger patients benefited more from ICI administration; however, lung cancer treatment cannot be decided based on age. Patients with different ECOG PS could benefit from ICIs, but data on patients with an ECOG PS score of ≥ 2 are lacking. In future studies, more patients with poor ECOG PS scores should be included.
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