BackgroundImmune checkpoint (IC) blockades (ICBs) significantly improve patients’ clinical outcomes with solid tumors. Because the objective response rate of single-agent ICB is limited, it is meaningful to explore the combination of ICs for immunotherapy.MethodsRNA sequencing data of 95 newly diagnosed patients with esophageal squamous cell carcinoma (ESCC) from The Cancer Genome Atlas (TCGA) database were used to explore the prognostic significance of ICs. The results were validated by immunohistochemistry of 58 ESCC tissue samples from our clinical center.ResultsThe results of both TCGA and validation data suggested that high expression of programmed cell death 1 ligand 1 (PD-L1), T-cell immunoglobulin and mucin-domain-containing-3 (TIM3), and T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) was associated with poor overall survival (OS) of patients with ESCC. Importantly, PD-L1/TIM3 or PD-L1/TIGIT was the optimal combination for predicting poor OS and short restricted mean survival time of patients with ESCC and was an independent prognostic factor. Moreover, a nomogram model constructed by PD-L1, TIM3, and TIGIT together with the primary tumor, regional lymph node, distant metastasis stage could provide a concise and precise prediction of 1-year and 2-year OS rates and median survival time. PD-L1/TIM3 or PD-L1/TIGIT had a positive correlation with CD8+ T cells. Notably, PD-1 and TIM3/TIGIT were primarily coexpressed on CD8+ tumor-infiltrating lymphocyte in patients with ESCC by multiplexed immunofluorescence.ConclusionHigh expression of ICs was associated with poor OS of patients with ESCC. PD-L1/TIM3 and PD-L1/TIGIT were the optimal combinations for predicting OS, which might be potential targets for future ICBs therapy of ESCC.

Background and Purpose Leptomeningeal metastases (LM) is the end-event of lung cancer and the prognosis is dismal. Few studies explored the prognostic performance of systematic immunological levels in lung cancer patients with LM. Our study aimed to explore the possible relationship between the prognosis of LM and systematic immunological level and other clinical characteristics. Methods This retrospective, multi-institutional, observational study was conducted in 4 tertiary centers in China. Patients were screened from January 2009 to May 2019. Patients with radiographically or histologically confirmed LM were enrolled. The data of systematic immunological level and other clinical characteristics of each patient were extracted and statistically analyzed to establish a prognostic model based on statistical analysis results. The predictive accuracy and discriminative capability of the model were evaluated by the calibration curve and concordance index (C-index). Results A total of 109 patients were enrolled in the study. Patients with adenocarcinoma, tumors harboring EGFR mutation, at their age of 50–59, with either bone, brain, or lung metastases, were enriched in this cohort. The median overall survival (OS) was 20.4 months (95% CI: 15.2–25.6). Cox univariate and multivariate analysis revealed better PS (0–1), no distant lymph nodes metastasis (DLNM), simultaneous diagnosis of lung cancer and leptomeningeal metastasis (SDLL), and lower neutrophil to lymphocyte ratio (NLR), were associated with better OS. Based on these independent prognostic variables, a prognostic nomogram model with a C-index for OS prediction of 0.71, was constructed. The actual probability of survival at 1-, 2- and 3-year showed good concordance with the prediction curve of our nomogram. Conclusion The systematic immunological level was an independent prognostic factor of lung cancer patients with LM. The prognostic model based on statistical analysis had a good ability to predict the OS of patients.

Background. Epithelial-mesenchymal transition (EMT) is significantly associated with the invasion and development of esophageal squamous cell carcinoma (ESCC). However, the importance of EMT-related long noncoding RNA (lncRNA) is little known in ESCC. Methods. GSE53624 ( N = 119 ) and GSE53622 ( N = 60 ) datasets retrieved from the Gene Expression Omnibus (GEO) database were used as training and external validation cohorts, respectively. GSE53624 and GSE53622 datasets were all sampled from China. Then, the prognostic value of EMT-related lncRNA was comprehensively investigated by weighted coexpression network analysis (WGCNA) and COX regression model. Results. High expression of PLA2G4E-AS1, AC063976.1, and LINC01592 significantly correlated with the favorable overall survival (OS) of ESCC patients, and LINC01592 had the greatest contribution to OS. Importantly, ESCC patients were divided into low- and high-risk groups based on the optimal cut-off value of risk score estimated by the multivariate COX regression model of these three lncRNA. Patients with high risk had a shorter OS rate and restricted mean survival time (RMST) than those with low risk. Moreover, univariate and multivariate COX regression revealed that risk stratification, age, and TNM were independent prognostic predictors, which were used to construct a nomogram model for individualized and visualized prognosis prediction of ESCC patients. The calibration curves and time-dependent ROC curves in the training and validation cohorts suggested that the nomogram model had a good performance. Interestingly, clear trends indicated that risk score positively correlated with tumor microenvironment (TME) scores and immune checkpoints TIGIT, CTLA4, and BTLA. In addition, the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that PLA2G4E-AS1, AC063976.1, and LINC01592 were primarily associated with TNF signaling pathway, NF-kappa B signaling pathway, and ECM-receptor interaction. Conclusion. We developed EMT-related lncRNA PLA2G4E-AS1, AC063976.1, and LINC01592 for prognostic prediction and risk stratification of Chinese ESCC patients, which might provide deep insight for personalized prognosis prediction in Chinese ESCC patients and be potential biomarkers for designing novel therapy.

At present, there are various treatment strategies for colorectal cancer, including surgery, chemotherapy, radiotherapy, and targeted therapy. In recent years, with the continuous development of immunotherapy, immune checkpoint inhibitors (ICIs) can significantly improve the treatment of advanced colorectal cancer patients with high levels of microsatellite instability. In addition to ICIs, neoantigens, as a class of tumor-specific antigens (TSA), are regarded as new immunotherapy targets for many cancer species and are being explored for antitumor therapy. Immunotherapy strategies based on neoantigens include tumor vaccines and adoptive cell therapy (ACT). These methods aim to eliminate tumor cells by enhancing the immune response of host T-cells to neoantigens. In addition, for MSS colorectal cancer, such “cold tumors” with low mutation rates and stable microsatellites are not sensitive to ICIs, whereas neoantigens could provide a promising immunotherapeutic avenue. In this review, we summarized the current status of colorectal cancer neoantigen prediction and current clinical trials of neoantigens and discussed the difficulties and limitations of neoantigens-based therapies for the treatment of CRC.

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