Over the past decade, immune checkpoint inhibitors (ICIs) have emerged as a revolutionary cancer treatment modality, offering long-lasting responses and survival benefits for a substantial number of cancer patients. However, the response rates to ICIs vary significantly among individuals and cancer types, with a notable proportion of patients exhibiting resistance or showing no response. Therefore, dual ICI combination therapy has been proposed as a potential strategy to address these challenges. One of the targets is TIGIT, an inhibitory receptor associated with T-cell exhaustion. TIGIT has diverse immunosuppressive effects on the cancer immunity cycle, including the inhibition of natural killer cell effector function, suppression of dendritic cell maturation, promotion of macrophage polarization to the M2 phenotype, and differentiation of T cells to regulatory T cells. Furthermore, TIGIT is linked with PD-1 expression, and it can synergize with PD-1/PD-L1 blockade to enhance tumor rejection. Preclinical studies have demonstrated the potential benefits of co-inhibition of TIGIT and PD-1/PD-L1 in enhancing anti-tumor immunity and improving treatment outcomes in several cancer types. Several clinical trials are underway to evaluate the safety and efficacy of TIGIT and PD-1/PD-L1 co-inhibition in various cancer types, and the results are awaited. This review provides an overview of the mechanisms of TIGIT and PD-1/PD-L1 co-inhibition in anti-tumor treatment, summarizes the latest clinical trials investigating this combination therapy, and discusses its prospects. Overall, co-inhibition of TIGIT and PD-1/PD-L1 represents a promising therapeutic approach for cancer treatment that has the potential to improve the outcomes of cancer patients treated with ICIs.

BackgroundAlthough immunotherapy has been widely used, there is currently no research comparing immunotherapy for non-small cell lung cancer (NSCLC) patients with brain metastases (BMs). This meta-analysis addresses a gap in the comparison of immunotherapy efficacy, including immune checkpoint inhibitors (ICIs), chemotherapy (CT), radiotherapy (RT), and ICI combined CT or RT.MethodsA search of Pubmed, Cochrane, EMBASE, and ClinicalTrial.gov was conducted to identify studies which enrolled NSCLC patients with BM treated with ICIs. The outcomes consisted of intracerebral overall response rate (iORR), intracerebral disease control rate (iDCR), extracranial overall response rate (EORR), distant brain failure (DBF), local control (LC), progression-free survival (PFS), and overall survival (OS).ResultsA total of 3160 participants from 46 trials were included in the final analysis. Patients treated with immunotherapy were associated with a longer PFS (0.48, 95%CI: 0.41-0.56), and a longer OS (0.64, 95%CI: 0.60-0.69) compared with immunotherapy-naive patients. In prospective studies, dual ICI combined CT and ICI combined CT achieved a better OS. The hazard ratio (HR) of dual ICI combined CT versus dual ICI was 0.61, and the HR of ICI combined CT versus ICI monotherapy was 0.58. Moreover, no statistical difference in PFS, OS, EORR, iORR, iDCR, and EDCR was found between patients with ICI monotherapy and ICI combined cranial radiotherapy. Concurrent ICI combined RT was shown to decrease the rate of DBF (OR = 0.15, 95% CI: 0.03-0.73) compared with RT after ICI. Patients treated with WBRT might have an inferior efficacy than those with SRS because the iORR of SRS was 0.75 (0.70, 0.80) and WBRT was 0. Furthermore, no obvious difference in PFS and OS was observed among the three different types of ICI, which targets PD-1, PD-L1, and CTLA-4, respectively.ConclusionsPatients treated with ICI got superior efficacy to those without ICI. Furthermore, dual ICI combined CT and ICI combined CT seemed to be optimal for NSCLC patients with BM. In terms of response and survival, concurrent administration of SRS and ICI led to better outcomes for patients with BMs than non-concurrent or non-SRS.Importance of the StudyIn the new era of immunotherapy, our meta-analysis validated the importance of immunotherapy for non-small cell lung cancer (NSCLC) patients with brain metastases (BMs). By comparing the long-term and short-term impacts of various regimens, all immunotherapy treatments had superior efficacy to immunotherapy-naive. At the same time, through pairwise comparison in immunotherapy, our findings can help clinicians to make treatment decisions for NSCLC patients with BMs.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=269621, identifier CRD42021269621.

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Background To predict the risk of radiation pneumonitis (RP), deep learning (DL) models were built to stratify lung cancer patients. Our study also investigated the impact of RP on survival. Methods This study retrospectively collected 100 RP and 99 matched non-RP lung cancer patients treated with radiotherapy from two independent centers. These patients were randomly divided into training (n = 175) and validation cohorts (n = 24). The radiomics and dosiomics features were extracted from radiation planning computed tomography (CT). Clinical information was retrospectively collected from the electronic medical record database. All features were screened by LASSO cox regression. A multi-omics prediction model was developed by the optimal algorithm and estimated the area under the receiver operating characteristic curve (AUC). Overall survival (OS) between RP, non-RP, mild-RP, and severe-RP groups was analyzed by the Kaplan-Meier method. Results There were eventually selected 16 radiomics features, 2 dosiomics features, and 1 clinical feature to build the best multi-omics model. GLRLM_Gray Level Non Uniformity Normalized and GLCM_MCC from PTV were essential dosiomics features, and T stage was a paramount clinical feature. The optimal performance for predicting RP was the AUC of testing set [0.94, 95% confidence interval (CI) (0.939-1.000)] and the AUC of external validation set [0.92, 95% CI (0.80-1.00)]. All RP patients were divided into mild-RP and severe-RP group according to RP grade (≤ 2 grade and > 2 grade). The median OS was 31 months (95% CI, 28–39) for non-RP group compared with 49 months (95% CI, 36-NA) for RP group (HR = 0.53, P = 0.0022). Among RP subgroup, the median OS was 57months (95% CI, 47-NA) for mild-RP and 25 months (95% CI, 29-NA) for severe-RP, and mild-RP group exhibited a longer OS (HR = 3.72, P < 0.0001). Conclusion The multi-omics model contributed to improvement in the accuracy of the RP prediction. Interestingly, this study also demonstrated that compared with non-RP patients, RP patients displayed longer OS, especially mild-RP.

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