PAGE 6862:Lanes 5 and 6 of the U6 panel of Fig. 4C were missing in the original published figure. The revised figure shows these lanes. This correction does not affect the results or conclusions of this work.

Objective: In the present study, we tried to describe the role of miR-29c-3p in esophageal carcinoma (EC) and the relationship of miR-29c-3p with CCNA2 as well as cell cycle, accordingly revealing the potential molecular mechanism across cell proliferation, migration and invasion.Methods: Expression profiles of EC miRNAs and matched clinical data were accessed from TCGA database for differential and survival analyses. Bioinformatics databases were employed to predict the downstream targets of the potential miRNA, and enrichment analysis was performed on the miRNA and corresponding target gene using GSEA software. qRT-PCR was conducted to detect the expression levels of miR-29c-3p and CCNA2 mRNA in EC tissues and cells, and Western blot was performed for the examination of CCNA2, CDK1 and p53 protein levels. Subsequently, cells were harvested for MTT, Transwell as well as flow cytometry assays to examine cell viability, migration, invasion and cell cycle. Dual-luciferase reporter gene assay and RIP were carried out to further investigate and verify the targeted relationship between miR-29c-3p and CCNA2. Frontiers in Bioengineering and Biotechnology | www.frontiersin.org February 2020 | Volume 8 | Article 75 Wang et al. MiR-29c-3p Suppresses Development of EC was simultaneously inhibited, resulting in the promotion of cell migration, invasion and cell cycle arrest.Conclusion: MiR-29c-3p plays a regulatory role in EC tumorigenesis and development. MiR-29c-3p can target CCNA2 to mediate p53 signaling pathway, finally attributing to the inhibition of cell proliferation, migration and invasion, and making cells arrest in G0/G1 phase.

Objective To investigate the value of CEP55 as a diagnostic marker and independent prognostic factor in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), and to analyze its co-expression genes and related signaling pathways. Methods TCGA database and GEO database were used to analyze the expression of CEP55 in LUAD and LUSC compared with normal tissues. The co-expression genes of CEP55 in LUAD and LUSC were excavated by cBioPortal and enriched by KEGG and GO. Establishing Receiver operating characteristic (ROC) curve to evaluate the value of CEP55 as a diagnostic and prognostic factor. The association between CEP55 expression and the clinicopathological features was evaluated using χ2 tests. ROC curves for diagnosis and prognosis detection were constructed. Prognostic values were analyzed by univariate and multivariate Cox regression models. Results Compared with normal lung tissues, CEP55 expression was significantly upregulated in both LUAD and LUSC. ROC curve analysis showed that CEP55 could be used as an effective diagnostic target for LUAD (AUC = 0.969) and LUSC (AUC = 0.994). When CEP55 gene was selected as an independent prognostic factor, high expression of CEP55 was more disadvantageous to OS and RFS of LUAD patients (P<0.05), but no significant difference was found in LUSC patients (P>0.05). The number of co-expression genes of CEP55 in LUAD is more than that in LUSC, and is related to cell cycle, DNA replication and P53 signaling pathway.

This study aimed to establish a prognostic risk model for lung adenocarcinoma (LUAD). We firstly divided 535 LUAD samples in TCGA-LUAD into high-, medium-, and low-immune infiltration groups by consensus clustering analysis according to immunological competence assessment by single-sample gene set enrichment analysis (ssGSEA). Profile of long non-coding RNAs (lncRNAs) in normal samples and LUAD samples in TCGA was used for a differential expression analysis in the high- and low-immune infiltration groups. A total of 1,570 immune-related differential lncRNAs in LUAD were obtained by intersecting the above results. Afterward, univariate COX regression analysis and multivariate stepwise COX regression analysis were conducted to screen prognosis-related lncRNAs, and an eight-immune-related-lncRNA prognostic signature was finally acquired (AL365181.2, AC012213.4, DRAIC, MRGPRG-AS1, AP002478.1, AC092168.2, FAM30A, and LINC02412). Kaplan–Meier analysis and ROC analysis indicated that the eight-lncRNA-based model was accurate to predict the prognosis of LUAD patients. Simultaneously, univariate COX regression analysis and multivariate COX regression analysis were undertaken on clinical features and risk scores. It was illustrated that the risk score was a prognostic factor independent from clinical features. Moreover, immune data of LUAD in the TIMER database were analyzed. The eight-immune-related-lncRNA prognostic signature was related to the infiltration of B cells, CD4+ T cells, and dendritic cells. GSEA enrichment analysis revealed significant differences in high- and low-risk groups in pathways like pentose phosphate pathway, ubiquitin mediated proteolysis, and P53 signaling pathway. This study helps to treat LUAD patients and explore molecules related to LUAD immune infiltration to deeply understand the specific mechanism.