BackgroundLung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. The main obstacle to early diagnosis or monitoring of patients at high risk of poor survival has been the lack of essential predictive biomarkers.MethodsRNA-sequencing was performed on LUAD affected tissue and paired adjacent to noncancerous tissue samples and Gene Expression Omnibus dataset GSE19188 and GSE33532 were used to obtain an intersection of differential expressed genes and construct a protein–protein interaction network to get hub genes. Then corresponding overall survival information of two cohorts of LUAD patients from our hospital and The Cancer Genome Atlas project-LUAD were included in the present study. An analysis of the Kyoto Encyclopedia of Genes and Genomes database and Gene Ontology were carried out to study the signature mechanism.ResultsIn our study, we identified eight candidate genes (DLGAP5, KIF11, RAD51AP1, CCNB1, AURKA, CDC6, OIP5 and NCAPG) closely related to survival in LUAD. A linear prognostic model of the eight genes was constructed and weighted by the regression coefficient (β) from the multivariate Cox regression analysis of The Cancer Genome Atlas-LUAD cohort to divide patients into low- and high-risk groups. The prognostic ability of the signature was validated in LUAD patients at our hospital. Patients assigned to the high-risk group exhibited poor overall survival compared to patients in the low-risk group. Finally, functional enrichment analysis showed that cell division played a vital role in the development of LUAD.ConclusionThe study identified an mRNA signature including eight genes, which may serve as a potential prognostic marker of LUAD.

Background Aberrant DNA methylations are significantly associated with esophageal squamous cell carcinoma (ESCC). In this study, we aimed to investigate the DNA methylation-driven genes in ESCC by integrative bioinformatics analysis. Methods Data of DNA methylation and transcriptome profiling were downloaded from TCGA database. DNA methylation-driven genes were obtained by methylmix R package. David database and ConsensusPathDB were used to perform gene ontology (GO) analysis and pathway analysis, respectively. Survival R package was used to analyze overall survival analysis of methylation-driven genes. Results Totally 26 DNA methylation-driven genes were identified by the methylmix, which were enriched in molecular function of DNA binding and transcription factor activity. Then, ABCD1, SLC5A10, SPIN3, ZNF69, and ZNF608 were recognized as significant independent prognostic biomarkers from 26 methylation-driven genes. Additionally, a further integrative survival analysis, which combined methylation and gene expression data, was identified that ABCD1, CCDC8, FBXO17 were significantly associated with patients’ survival. Also, multiple aberrant methylation sites were found to be correlated with gene expression. Conclusion In summary, we studied the DNA methylation-driven genes in ESCC by bioinformatics analysis, offering better understand of molecular mechanisms of ESCC and providing potential biomarkers precision treatment and prognosis detection. Electronic supplementary material The online version of this article (10.1186/s12935-019-0770-9) contains supplementary material, which is available to authorized users.

BackgroundIncreasing evidence has demonstrated that circular RNAs (circRNAs) may play an important role in oncogenesis and tumor development; however, their role in lung adenocarcinoma (LUAD) remains unclear. We identified the differentially expressed circRNAs in LUAD and investigated the potential mechanisms for cancer progression.MethodsWe examined differentially expressed circRNAs in LUAD and paired normal tissues using downloaded circRNA microarrays from the Gene Expression Omnibus. We constructed gene co‐expression networks based on the degree of Pearson correlation to predict the critical circRNA in LUAD. Gene Ontology analysis was performed on the genes in the network. We observed one novel circRNA upregulated in LUAD, hsa_circ_0000792, as well as its potential sponged microRNA, miR‐375. Subsequent real‐time quantitative PCR was used to verify the bioinformatics analysis.ResultsSeveral circRNAs showed significantly different expression levels in LUAD tissues. Real‐time quantitative PCR and further co‐expression network analysis of 42 matched tissue samples showed a significant difference in expression between LUAD and normal tissues in hsa_circ_0000792 (P < 0.001). We built a network of hsa_circ_0000792‐targeted miRNA gene interactions, including miR‐375 and the corresponding messenger RNAs. Gene Ontology analysis revealed that hsa_circ_0000792 could participate in signal transduction and cell communication during LUAD development. Larger area under the curve by receiver operating characteristic curve analysis of hsa_circ_0000792 and miR‐375 (0.815 and 0.772, respectively) in LUAD indicated greater potential as biomarkers.ConclusionsWe identified hsa_circ_0000792 as a potential LUAD biomarker; however, further studies are required to determine the mechanism of this circRNA in LUAD development.

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Background Segmentectomy is increasingly used to resect lung nodules. Robotic‐assisted thoracic surgery (RATS) is considered a safe and practical method for segmentectomy. Few studies have compared robotic surgery and video‐assisted thoracic surgery (VATS) for lung segmentectomy. Method We retrospectively examined 215 consecutive patients who underwent typical (88 patients) or atypical (128 patients) segmentectomy by either robotic surgery or VATS. The postoperative characteristics including operation time, blood loss, pneumonia, tumor size, lymph nodes harvested, chest tube duration, prolonged air leak, atrial fibrillation, and postoperative hospital stay were recorded. Results A total of 88 patients underwent typical segmentectomy, while 127 patients underwent atypical segmentectomy. A greater number of lymph nodes were resected via RATS than by VATS (13.24 ± 4.84 vs. 11.71 ± 3.89; P = 0.018). The operation time for typical segmentectomy was shorter than that for atypical segmentectomy (115.69 ± 22.32 vs. 131.68 ± 22.52; P = 0). No significant differences were found between RATS and VATS in terms of chest drainage duration and postoperative hospital stay. The incidence of postoperative complications including prolonged air leak and atrial fibrillation was not significantly different between typical segmentectomy and atypical segmentectomy. Conclusion Atypical segmentectomy is more complicated than typical segmentectomy, which may lead to increases in complications and operation time. Robotic surgery was safe and practical for segmentectomy compared to VATS and more lymph nodes could be dissected by RATS without increasing the risk of postoperative complications.