METTL7B serves as a prognostic biomarker and promotes metastasis of lung adenocarcinoma cells.

Background: To research the correlation between the prognosis of patients suffering from lung adenocarcinoma (LUAD) and methyltransferase like 7B (METTL7B) expression. Methods: The Cancer Genome Atlas (TCGA) database was utilized to verify METTL7B expression, and The Human Protein Atlas database was utilized to verify METTL7B expression at the tissue level. The relationship between METTL7B and LUAD prognostic data was then analyzed using the KM-plotter database. The correlation between METTL7B expression and immune cells was demonstrated through the TIMER database. For exploring the possible mechanism of action, gene set enrichment analysis (GSEA) was performed. Finally, the role of METTL7B in the adverse biological events of LUAD was further explored by in vitro experiments such as proliferation and invasion assays. Results: As per the TCGA database, METTL7B expression was increased in cancerous tissues compared with paracancerous tissues, and it was mostly located in the cytoplasm. Patients suffering from LUAD who had low METTL7B expression had a relatively better overall survival (OS) and disease-specific survival (DSS) according to the Kaplan-Meier-plotter (KM-plotter) database. METTL7B expression was significantly associated with immune cell infiltration in LUAD patients, as shown by correlation analysis. GSEA revealed that METTL7B may affect the physiological events of LUAD by playing a part in cell cycle regulation. In vitro cytological experiments demonstrated that METTL7B can markedly affect the metastasis of LUAD cells. Conclusions: The reduction of METTL7B expression can prolong OS and DSS in LUAD patients. It may be utilized as a novel predictive biomarker of LUAD, and may be associated with immune infiltration of LUAD. Interfering with METTL7B expression can significantly cause inhibition of LUAD by modulating the ability of cells to proliferate and migrate. These results point to a possible target for developing anti-cancer therapies against LUAD.

Gene signature to predict prognostic survival of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has a high incidence and poor prognosis and is the second most fatal cancer, and certain HCC patients also show high heterogeneity. This study developed a prognostic model for predicting clinical outcomes of HCC. RNA and microRNA (miRNA) sequencing data of HCC were obtained from the cancer genome atlas. RNA dysregulation between HCC tumors and adjacent normal liver tissues was examined by DESeq algorithms. Survival analysis was conducted to determine the basic prognostic indicators. We identified competing endogenous RNA (ceRNA) containing 15,364 pairs of mRNA-long noncoding RNA (lncRNA). An imbalanced ceRNA network comprising 8 miRNAs, 434 mRNAs, and 81 lncRNAs was developed using hypergeometric test. Functional analysis showed that these RNAs were closely associated with biosynthesis. Notably, 53 mRNAs showed a significant prognostic correlation. The least absolute shrinkage and selection operator's feature selection detected four characteristic genes (SAPCD2, DKC1, CHRNA5, and UROD), based on which a four-gene independent prognostic signature for HCC was constructed using Cox regression analysis. The four-gene signature could stratify samples in the training, test, and external validation sets (p <0.01). Five-year survival area under ROC curve (AUC) in the training and validation sets was greater than 0.74. The current prognostic gene model exhibited a high stability and accuracy in predicting the overall survival (OS) of HCC patients.

Revealing the Role of lncRNA CCDC144NL-AS1 and LINC01614 in Gastric Cancer via Integrative Bioinformatics Analysis and Experimental Validation.

Long non-coding RNAs (lncRNAs) are key regulators in the pathophysiology of gastric cancer, and lncRNAs have been regarded as potential biomarkers and therapeutic targets for gastric cancer. The present study performed the WGCNA analysis of the GSE70880 dataset and aimed to identify novel lncRNAs associated with gastric cancer progression. Based on the WGCNA, the lncRNAs and mRNA co-expression network were constructed. A total of four modules were identified and the eigengenes in different modules were involved in various key signaling pathways. Furthermore, the co-expression networks were constructed between the lncRNAs and mRNA; this leads to the identification of 6 modules, which participated in various cellular pathways. The survival analysis showed that high expression of CCDC144NL antisense RNA 1 (CCDC144NL-AS1) and LINC01614 was positively correlated with the poor prognosis of patients with gastric cancer. The in vitro validation results showed that CCDC144NL-AS1 and LINC01614 were both up-regulated in the gastric cancer cells. Silence of CCDC144NL-AS1 and LINC01614 both significantly suppressed the cell proliferation and migration of gastric cancer cells, and also promoted the chemosensitivity of gastric cancer cells to 5-fluorouracil. Collectively, our results suggested that the newly identified two lncRNAs (CCDC144NL-AS1 and LINC01614) may act as oncogenes in gastric cancer.

LncRNA PTENP1 inhibits cervical cancer progression by suppressing miR-106b.

LncRNA PTENP1 is a competitive endogenous RNA (ceRNA) involved in decoying miR-106b in multiple diseases. This study investigates the interaction of PTENP1 and miR-106b in cell proliferation, apoptosis and epithelial-mesenchymal transition (EMT) in cervical cancer. The expressions of PTENP1, miR-106b and PTEN were determined in cervical cancer tissues, adjacent normal tissues, cervical cancer cells (HeLa, SiHa, C33A and CasKi) and normal cervical epithelial H8 cells. Up-regulation of PTENP1 and down-regulation of miR-106b were conducted in HeLa and CasKi cells by transfecting cells with corresponding miRNA mimics and inhibitors. Bioinformatics analysis, luciferase reporter assay and RNA-pull down assay were performed to verify the association of miR-106b, PTEN, and PTENP1. Cell growth and cell apoptosis were determined by CCK-8 and flow cytometry analysis. It was found that the expressions of PTENP1 and PTEN were up-regulated and that of miR-106b were down-regulated in cervical cancer tissues and cells. PTENP1 localized in cytoplasm and competitively bound to miR-106b. Up-regulation of PTENP1 and down-regulation of miR-106b contributed to increased expressions of PTEN and E-cadherin. Decreased expression of miR-106b, ZEB1, Snail and Vimentin, resulted in inhibiting cell proliferation and promoting cell apoptosis. Over-expression of PTENP1 and miR-106b accelerated cell proliferation and slowed down cell apoptosis. miR-106b inhibited the expression of PTEN. Our results suggest that LncRNA PTENP1 inhibits cervical cancer progression by competitively binding to miR-106b, leading to promote PTEN expression, inhibit cell proliferation and EMT and induce cell apoptosis in cervical cancer cells.

Mutational Pattern in Multiple Pulmonary Nodules Are Associated With Early Stage Lung Adenocarcinoma.

The clinical significance of mutation in multiple pulmonary nodules is largely limited by single gene mutation-directed analysis and lack of validation of gene expression profiles. New analytic strategy is urgently needed for comprehensive understanding of genomic data in multiple pulmonary nodules. In this study, we performed whole exome sequencing in 16 multiple lung nodules and 5 adjacent normal tissues from 4 patients with multiple pulmonary nodules and decoded the mutation information from a perspective of cellular functions and signaling pathways. Mutated genes as well as mutation patterns shared in more than two lesions were identified and characterized. We found that the number of mutations or mutated genes and the extent of protein structural changes caused by different mutations is positively correlated with the degree of malignancy. Moreover, the mutated genes in the nodules are associated with the molecular functions or signaling pathways related to cell proliferation and survival. We showed a developing pattern of quantity (the number of mutations/mutated genes) and quality (the extent of protein structural changes) in multiple pulmonary nodules. The mutation and mutated genes in multiple pulmonary nodules are associated with cell proliferation and survival related signaling pathways. This study provides a new perspective for comprehension of genomic mutational data and might shed new light on deciphering molecular evolution of early stage lung adenocarcinoma.