Background Lung adenocarcinomas (LUAD) is the most common histological subtype of lung cancers. Tumor immune microenvironment (TIME) is involved in tumorigeneses, progressions, and metastases. This study is aimed to develop a robust immune‐related signature of LUAD. Methods A total of 1774 LUAD cases sourced from public databases were included in this study. Immune scores were calculated through ESTIMATE algorithm and weighted gene co‐expression network analysis (WGCNA) was applied to identify immune‐related genes. Stability selections and Lasso COX regressions were implemented to construct prognostic signatures. Validations and comparisons with other immune‐related signatures were conducted in independent Gene Expression Omnibus (GEO) cohorts. Abundant infiltrated immune cells and pathway enrichment analyses were carried out, respectively, through ImmuCellAI and gene set enrichment analysis (GSEA). Results In Cancer Genome Atlas (TCGA) LUAD cohorts, immune scores of higher levels were significantly associated with better prognoses ( P < .05). Yellow (n = 270) and Blue (n = 764) colored genes were selected as immune‐related genes, and after univariate Cox regression analysis ( P < .005), a total of 133 genes were screened out for subsequent model constructions. A four‐gene signature (ARNTL2, ECT2, PPIA, and TUBA4A) named IPSLUAD was developed through stability selection and Lasso COX regression. It was suggested by multivariate and subgroup analyses that IPSLUAD was an independent prognostic factor. It was suggested by Kaplan‐Meier survival analysis that eight out of nine patients in high‐risk groups had significantly worse prognoses in validation data sets ( P < .05). IPSLUAD outperformed other signatures in two independent cohorts. Conclusions A robust immune‐related prognostic signature with great performances in multiple LUAD cohorts was developed in this study.

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Background : The systemic immune-inflammation index (SII) has been reported to be associated with patient survival in various kinds of solid tumors. However, just few studies have focused on its prognostic value in patients with surgically resected esophageal squamous cell carcinoma (ESCC). Materials and Methods : This study was a single-institution, retrospective analysis of 468 ESCC patients who underwent curative esophagectomy at the Department of Thoracic Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College between 2005 and 2008. The receiver operating curve (ROC) was plotted to compare the discrimination ability of the SII and other inflammatory factors for overall survival (OS) and disease-free survival (DFS). Univariate and multivariate analyses were performed based on the Cox proportional hazards regression model. Results : The SII, neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) were all associated with OS in ESCC patients. The SII, NLR, and PLR were independent prognostic factors for OS (hazard ratio (HR) = 1.604, 95% confidence interval (CI) 1.247-2.063, P < 0.001; HR = 1.396, 95% CI 1.074-1.815, P = 0.013; HR = 1.370, 95% CI 1.067-1.758, P = 0.013, respectively) and DFS (HR = 1.681, 95% CI 1.307-2.162, P < 0.001; HR = 1.376, 95% CI 1.059-1.788, P = 0.017; HR = 1.398, 95% CI 1.089-1.794, P = 0.009, respectively). The area under the curve (AUC) for SII was bigger than NLR, PLR, and MLR (0.553, 0.540, 0.532, and 0.521, respectively). Conclusion : The SII is a simple and promising prognostic predictor for patients with surgically resected ESCC. The prognostic value of SII is superior to those of the NLR, PLR and MLR. Moreover, the SII retained prognostic significance in stage I-II ESCC subgroup (OS, DFS) and stage III ESCC subgroup (DFS).

Background The systemic immune‐inflammation index (SII) is correlated with patient survival in various types of solid tumors. However, only a few studies have focused on the prognostic value of the SII in patients with surgically resected non‐small cell lung cancer (NSCLC). Methods This study was a single center retrospective analysis of 569 NSCLC patients who underwent curative lobectomy at the Department of Thoracic Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College between 2006 and 2012. A receiver operating characteristic curve was plotted to compare the discriminatory ability of the SII for overall survival (OS). A Cox proportional hazards regression model was used to perform univariate and multivariate analyses. Results The SII, neutrophil‐lymphocyte ratio (NLR), and platelet‐lymphocyte ratio (PLR) all correlated with OS in NSCLC patients, and the SII was an independent prognostic factor for OS (hazard ratio 1.256, 95% confidence interval 1.018–1.551; P = 0.034). The area under the receiver operating characteristic curve of the SII (0.547) was larger than the NLR (0.541) and PLR (0.531). Furthermore, the SII retained prognostic significance in the lung adenocarcinoma subgroup. Conclusion The SII is a promising prognostic predictor for patients with surgically resected NSCLC and retained prognostic significance in the lung adenocarcinoma subgroup. The prognostic value of the SII is superior to the NLR and PLR.

Background Tumour Necrosis Factor (TNF) family members play important roles in mounting anti-tumour immune responses, and clinical trials targeting these molecules are ongoing. However, the expression patterns and clinical significance of TNF members in lung adenocarcinoma (LUAD) remain unrevealed. This study aimed to explore the gene expression profiles of TNF family members in LUAD and constructed a TNF family-based prognosis signature. Methods In total, 1300 LUAD cases from seven different cohorts were collected. Samples from The Cancer Genome Atlas (TCGA) were used as the training set, and the RNA data from five Gene Expression Omnibus (GEO) datasets and qPCR data from 102 samples were used for validation. The immune profiles and potential immunotherapy response prediction value of the signature were also explored. Findings After univariate Cox proportional hazards regression and stepwise multivariable Cox analysis, a TNF family-based signature was constructed in the TCGA dataset that significantly stratified cases into high- and low-risk groups in terms of OS. This signature remained an independent prognostic factor in multivariate analyses. Moreover, the clinical significance of the signature was well validated in different clinical subgroups and independent validation cohorts. Further analysis revealed that signature high-risk patients were characterized by distinctive immune cell proportions and immune-suppressive states. Additionally, signature scores were positively related to multiple immunotherapy biomarkers. Interpretation This was the first TNF family-based model for predicting outcomes and immune landscapes for patients with LUAD. The capability of this signature for predicting immunotherapy response needs further validation.