Background: Lung cancer has the highest morbidity and mortality worldwide, and lung adenocarcinoma (LADC) is the most common pathological subtype. Accumulating evidence suggests the tumor microenvironment (TME) is correlated with the tumor progress and the patient’s outcome. As the major components of TME, the tumor-infiltrated immune cells and stromal cells have attracted more and more attention. In this study, differentially expressed immune and stromal signature genes were used to construct a TME-related prognostic model for predicting the outcomes of LADC patients. Methods: The expression profiles of LADC samples with clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) related to the TME of LADC were identified using TCGA dataset by Wilcoxon rank sum test. The prognostic effects of TME-related DEGs were analyzed using univariate Cox regression. Then, the least absolute shrinkage and selection operator (LASSO) regression was performed to reduce the overfit and the number of genes for further analysis. Next, the prognostic model was constructed by step multivariate Cox regression and risk score of each sample was calculated. Then, survival and Receiver Operating Characteristic (ROC) analyses were conducted to validate the model using TCGA and GEO datasets, respectively. The Kyoto Encyclopedia of Genes and Genomes analysis of gene signature was performed using Gene Set Enrichment Analysis (GSEA). Finally, the overall immune status, tumor purity and the expression profiles of HLA genes of high- and low-risk samples was further analyzed to reveal the potential mechanisms of prognostic effects of the model. Results: A total of 93 TME-related DEGs were identified, of which 23 DEGs were up-regulated and 70 DEGs were down-regulated. The univariate cox analysis indicated that 23 DEGs has the prognostic effects, the hazard ratio ranged from 0.65 to 1.25 (p < 0.05). Then, seven genes were screened out from the 23 DEGs by LASSO regression method and were further analyzed by step multivariate Cox regression. Finally, a three-gene (ADAM12, Bruton Tyrosine Kinase (BTK), ERG) signature was constructed, and ADAM12, BTK can be used as independent prognostic factors. The three-gene signature well stratified the LADC patients in both training (TCGA) and testing (GEO) datasets as high-risk and low-risk groups, the 3-year area under curve (AUC) of ROC curves of three GEO sets were 0.718 (GSE3141), 0.646 (GSE30219) and 0.643 (GSE50081). The GSEA analysis indicated that highly expressed ADAM12, BTK, ERG mainly correlated with the activation of pathways involving in focal adhesion, immune regulation. The immune analysis indicated that the low-risk group has more immune activities and higher expression of HLA genes than that of the high-risk group. In sum, we identified and constructed a three TME-related DEGs signature, which could be used to predict the prognosis of LADC patients.

Background: Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and the most lethal malignant disease worldwide. However, the molecular mechanisms underlying LUAD are not fully understood.Methods: Four datasets (GSE118370,GSE85841,GSE43458andGSE32863) were obtained from the gene expression omnibus (GEO). Identification of differentially expressed genes (DEGs) and functional enrichment analysis were performed using the limma and clusterProfiler packages, respectively. A protein–protein interaction (PPI) network was constructed via Search Tool for the Retrieval of Interacting Genes (STRING) database, and the module analysis was performed by Cytoscape. Then, overall survival analysis was performed using the Kaplan–Meier curve, and prognostic candidate biomarkers were further analyzed using the Oncomine database.Results: Totally, 349 DEGs were identified, including 275 downregulated and 74 upregulated genes which were significantly enriched in the biological process of extracellular structure organization, leukocyte migration and response to peptide. The mainly enriched pathways were complement and coagulation cascades, malaria and prion diseases. By extracting key modules from the PPI network, 11 hub genes were screened out. Survival analysis showed that except VSIG4, other hub genes may be involved in the development of LUAD, in which MYH10, METTL7A, FCER1G and TMOD1 have not been reported previously to correlated with LUAD. Briefly, novel hub genes identified in this study will help to deepen our understanding of the molecular mechanisms of LUAD carcinogenesis and progression, and to discover candidate targets for early detection and treatment of LUAD.

MicroRNAs are highly conserved non-coding RNAs that regulate gene expression at the post-transcriptional level, and play pivotal roles in cancer development and progression. miR-100 has been reported to be significantly downregulated in a variety of cancers, including esophageal cancer. However, the role of miR-100 in human esophageal cancer has not been fully elucidated. We demonstrated that overexpression of miR-100 in esophageal cancer cells markedly inhibited cell proliferation, migration and invasion as well as tumor growth. We subsequently showed that CXCR7 is a direct target gene of miR-100. Our results indicated that miR-100 plays a tumor-suppressor role in esophageal cancer and suggest its potential application for esophageal cancer treatment.

Immunotherapeutic strategies based on Epstein-Barr virus (EBV) latent membrane protein 2 (LMP2) antigen-specific cytotoxic T lymphocytes (CTLs) have been proven to boost LMP2-specific CTL responses in patients with nasopharyngeal carcinoma (NPC). Such strategies can produce clinical benefits in some patients with NPC. Currently, the major challenge limiting the use of immunotherapy for NPC is its low clinical response rate. The efficacy of immunotherapy based on EBV-LMP2 specific CTLs depends mainly on their cytotoxic activity, but no studies have been conducted to elucidate this activity. In this study, laser confocal scanning microscopy (LCSM) and real-time cell analysis (RTCA) were used to evaluate the killing function and its underlying mechanism of LMP2-specific CTLs. LCSM showed that LMP2-specific CTLs recognize and kill target cells expressing viral escape protein LMP2, and that the killing rate is related to the number of CTLs adhering to the target cells. LMP2-specific CTL-mediated cytotoxicity is rate limited by the time required for effective contact and recognition between CTLs and target cells. RTCA showed that the protective effect of LMP2-specific CTLs required an appropriate effector-to-target ratio, and that LMP2-specific CTLs could not eradicate residual target cells at a low effector-to-target ratio. Moreover, our results revealed that LMP2-specific CTL responses involve two independent but complementary mechanisms: the perforin/granzyme and Fas/FasL pathways. Therefore, we have elucidated, for the first time, the selective cytotoxicity and mechanism by which LMP2-specific CTLs induced by the rAd-LMP2 vaccine kill target cells and have explored the killing mode and several key parameters of killing mediated by LMP2-specific CTLs. Our study will contribute to the knowledge of vaccines targeting EBV-LMP2 and to the improvement of immunotherapeutic strategies.