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.

Primary small cell carcinoma of the esophagus (PSCCE) is a lethal neuroendocrine carcinoma. Previous studies proposed a genetic similarity between PSCCE and esophageal squamous cell carcinoma (ESCC) but provided little evidence for differences in clinical course and neuroendocrine differentiation. We perform whole-exome sequencing, RNA sequencing and immunohistochemistry profiling on 46 PSCCE cases. Integrated analyses enable the discovery of multiple mechanisms of RB1 disruption in 98% (45/46) of cases. The transcriptomic landscape of PSCCE closely resembles small cell lung cancer (SCLC) but differs from ESCC or esophageal adenocarcinoma (EAC). Distinct gene expression patterns regulated by ASCL1 and NEUROD1 define two molecular subtypes, PSCCE-A and PSCCE-N, which are highly similar to SCLC subtypes. A T cell excluded phenotype is widely observed in PSCCE. In conclusion, PSCCE has genomic alterations, transcriptome features and molecular subtyping highly similar to SCLC but distinct from ESCC or EAC. These observations are relevant to oncogenesis mechanisms and therapeutic vulnerability.

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Novel tumor antigens and their related autoantibodies have tremendous potential for early diagnosis of non-small cell lung cancer (NSCLC). In this study, we identify antigens from NSCLC tissue and autoantibodies in sera of patients with NSCLC using a modified proteomics-based approach. We seperated and identified four NSCLC-associated proteins extracted from the cytosol in tumor tissues by mini-two-dimensional gel electrophoresis, followed by Western blot and hybridization with individual sera for confirmation of antibody binding. Of the proteins we identified, we selected 58 kDa chaperonin containing TCP1(T-Complex Protein 1) subunit 5 (CCT5) for validation. Serum levels of carcinoembryonic antigen (CEA) and cytokeratin 19 fragments (CYFRA 21-1) were measured in all serum samples with an immunoluminometric assay and a receiver operating characteristic (ROC) curve was analyzed for autoantibodies against CCT5, CEA and CYFRA 21-1. The results show that CCT5 can induce an autoantibody response in NSCLC sera and show higher expression in NSCLC tissues by immunohistochemistry and Western blot. Anti-CCT5 autoantibody was found in 51% (23/45) of patients with NSCLC, but only 2.5% (1/40) in non-tumor individual controls. A receiver operating characteristic curve constructed with a panel of autoantibodies against CCT5 (AUC=0.749), CEA (AUC=0.6758), and CYFRA 21-1(AUC=0.760) show a sensitivity of 51.1% and 97.5% specificity in discriminating NSCLC from matched controls. These results indicate the potential utility of screening autoantibodies in sera, show that CCT5 could be used as a biomarker in cancer diagnosis.

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