Anoctamin6 (ANO6) plays a crucial role in several cancers, whereas the specific role of ANO6 in glioblastoma is unclear. Methods: Kaplan-Meier survival analysis was used to analysis the correlation between ANO6 and survival rate of patients with glioblastoma. Univariate Cox regression analysis was used to analysis the correlation among ANO6 expression level,and age, gender, WHO and overall survival rate. Immunohistocemical technique, RT-PCR and western blot were used to dected the ANO6 expression. CCK8, colony formation and transwell were used to detected cell viability, cell proliferation and cell invasion in glioblastoma cells transfected with sh-ANO6 and ANO6 overexpression. In addition, after SHG-44 cells trasfected with ANO6 overexpression were ERK inhibitor (PD98059), CCK8, colony formation and transwell were used to detected cell viability, cell proliferation and cell invasion. Western blot was used to detected ERK protein level and the phosphorylation level of ERK in T89G and U87MG cells tranfected wih sh-ANO6. Results: The results indicated that the ANO6 expression level was significantly associated with patients' age and tumor stage. Univariate Cox regression analysis showed that the ANO6 expression level, age, gender and tumor stage were not related to the overall survival rate. ANO6 inhibition significantly suppressed the viability, invasion and the ability of colony formation in glioma cells, while ANO6 overexpression led to the opposite results in SHG-44 cells. ANO6 knockdown strongly inhibits the phosphorylation level and nuclear translocation of extracellular signal-regulated kinase (ERK) protein to inhibit ERK signaling. ERK inhibitor significantly decreased the cell proliferation and invasion in SHG-44 cells transfected with sh-ANO6. Conclusion: This study revealed that ANO6 activited ERK signaling pathway through promoting the nuclear translocation of ERK to increase the proliferation and invasion of glioblastoma cells.

Lung squamous cell carcinoma (LUSC), a type of non-small cell lung carcinoma, has a poor therapeutic response, high relapse rate and poor prognosis. The present study was designed to reveal the key long non-coding RNAs (lncRNAs) associated with the prognosis of LUSC. The lncRNA expression profiles of LUSC and adjacent samples were downloaded from The Cancer Genome Atlas database. Based on the edgeR and DEseq packages, the differentially expressed lncRNAs (DELs) between LUSC and adjacent samples were obtained and the intersecting DELs were regarded as significant DELs. Subsequently, a prognostic risk model was established using Cox regression analysis and its classification effect was detected by survival analysis. Using survival analysis, the effect of the prognostic risk model was assessed in the validation set and other types of cancer. Finally, the co-expression genes of key lncRNAs were screened using the Multi-Experiment Matrix tool and the STRING database, and their functions were predicted via enrichment analysis using the Database for Annotation, Visualization and Integrated Discovery tool. A total of 2,041 significant DELs between LUSC and adjacent samples were screened. The prognostic risk model consisting of RP5-821D11.7, APCDD1L-AS1 and RP11-277P12.9 was established, which had a good classification effect. Cox multivariate regression analysis demonstrated that risk score may serve as an independent prognostic factor. Furthermore, certain co-expression genes of RP5-821D11.7 (including proliferating cell nuclear antigen), APCDD1L-AS1 (including semaphorin 5A, semaphorin 6D, ADAMTS like 1, ADAM metallopeptidase with thrombospondin type 1 motif 6, slit guidance ligand 3, and tenascin C) and RP11-277P12.9 (including Wnt family member 2B) were identified. Additionally, ‘positive regulation of cell migration’ and ‘proteinaceous extracellular matrix’ were enriched. In conclusion, the expression levels of the lncRNAs RP5-821D11.7, APCDD1L-AS1 and RP11-277P12.9 may affect the prognosis of LUSC.