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Background: Head and neck squamous cell carcinoma (HNSCC) is a common cancer that is characterized by a complex pathogenesis. Only limited data are available on the primary pathogenic genes and pathways in HNSCC. Objective: This study aimed to identify potential biomarkers of HNSCC and explore its underlying mechanisms. Methods: We screened differentially expressed genes (DEGs) using the Gene Expression Omnibus(GEO) database. Gene Ontology (GO) and Reactome pathway enrichment were analyzed using the STRING database. The protein-protein interaction network of the DEGs was reconstructed using Cytoscape software in STRING. The ONCOMINE and UNLCAN databases were used to identify the expression of hub genes. In addition, we employed UNLCAN to correlate tumor grade with key genes. Results: Finally, the effect of hub genes on overall survival (OS) was analyzed using the Kaplan- Meier method. In total, 22 DEGs were identified. These were related to the mitotic cell cycle, mitotic G1-G1, and S phases, G2/M transition, NOTCH signaling, and regulation of TP53 activity. Seven hub genes were screened with Cytoscape. Increased expression of five hub genes (AURKA, BIRC5, MKI67, UBE2C, and TOP2A) was related to a higher tumor grade and worse OS. Conclusion: We have identified five key genes that may help us understand the carcinogenic mechanisms related to the cell cycle in HNSCC. These genes may be used as biomarkers for survival and treatment of HNSCC.

Melanoma is an extremely malignant tumor with early metastasis and high mortality. Little is known about the process of by which melanoma occurs, as its mechanism is very complex and only limited data are available on its long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs). The purpose of this study was to screen out potential prognostic molecules and identify a ceRNA network related to the occurrence of melanoma. We screened 169 differentially expressed mRNAs (DEmRNAs) from E-MTAB-1862 and GSE3189; gene ontology (GO) enrichment analysis showed that these genes were closely related to the development of skin. In the protein-protein interaction network, we screened out a total of 19 hub genes. Furthermore, we predicted the microRNAs (miRNAs) that regulate hub genes using the miRWalk database and then intersected these with GSE35579, resulting in nine DEmiRNAs. We also predicted the lncRNAs that regulate the miRNAs using the LncBasev.2 database. According to the ceRNA hypothesis, and based on the intersection of the DElncRNAs with merged GTEx and TCGA data, we obtained 20 DElncRNAs. A total of four DEmRNAs, nine DEmiRNAs, and 20 DElncRNAs were included in the ceRNA network. Based on Cox stepwise regression and survival analysis, we identified five biomarkers, ZSCAN16-AS1, LINC00520, XIST, DTL, and let-7a-5p, and obtained risk scores. The results showed that most of the differentially expressed genes were related to epithelial-mesenchymal transition (EMT) in melanoma. Finally, we obtained a LINC00520/let-7a-5p/DTL molecular regulatory network. These results suggest that ceRNA networks have an important role in evaluating the prognosis of patients with melanoma and provide a new experimental basis for exploring the EMT process in the development of melanoma.

Objective. Autophagy and long noncoding RNAs (lncRNAs) have been the focus of research on the pathogenesis of melanoma. However, the autophagy network of lncRNAs in melanoma has not been reported. The purpose of this study was to investigate the lncRNA prognostic markers related to melanoma autophagy and predict the prognosis of patients with melanoma. Methods. We downloaded RNA sequencing data and clinical information of melanoma from the Cancer Genome Atlas. The coexpression of autophagy-related genes (ARGs) and lncRNAs was analyzed. The risk model of autophagy-related lncRNAs was established by univariate and multivariate Cox regression analyses, and the best prognostic index was evaluated combined with clinical data. Finally, gene set enrichment analysis was performed on patients in the high- and low-risk groups. Results. According to the results of the univariate Cox analysis, only the overexpression of LINC00520 was associated with poor overall survival, unlike HLA-DQB1-AS1, USP30-AS1, AL645929, AL365361, LINC00324, and AC055822. The results of the multivariate Cox analysis showed that the overall survival of patients in the high-risk group was shorter than that recorded in the low-risk group ( p < 0.001 ). Moreover, in the receiver operating characteristic curve of the risk model we constructed, the area under the curve (AUC) was 0.734, while the AUC of T and N was 0.707 and 0.658, respectively. The Gene Ontology was mainly enriched with the positive regulation of autophagy and the activation of the immune system. The results of the Kyoto Encyclopedia of Genes and Genomes enrichment were mostly related to autophagy, immunity, and melanin metabolism. Conclusion. The positive regulation of autophagy may slow the transition from low-risk patients to high-risk patients in melanoma. Furthermore, compared with clinical information, the autophagy-related lncRNA risk model may better predict the prognosis of patients with melanoma and provide new treatment ideas.

We employed RNA sequencing analysis to reveal dysregulated lncRNAs in lung cancer utilizing 461 lung adenocarcinomas and 156 normal lung tissues from 3 separate cohorts. We found that LINC00152 was highly overexpressed in lung tumors as compared to their adjacent normal tissues. Patients with high LINC00152 expression demonstrate a significantly poorer survival than those with low expression. We verified the diagnostic/prognostic potential of LINC00152 expression in an independent cohort of lung tumor tissues using quantitative RT-PCR. After knockdown of LINC00152 using siRNAs in lung cancer cell lines, both cell proliferation and colony formation were decreased. Cell fractionation and qRT-PCR analysis indicated that LINC00152 is found mainly in the cytoplasm. Treatment with Trichostatin A in cell lines having low LINC00152 expression indicated that histone acetylation may be one mechanism underlying LINC00152 overexpression in NSCLC. Western blot analyses indicated that p38a, STAT1, STAT3, CREB1, CCNE1 and c-MYC proteins were decreased after LINC00152 siRNA treatment. Our study indicates LINC00152 plays an important role in lung tumor growth and is potentially a diagnostic/prognostic marker. Further characterization of LINC00152 in regulating its target proteins may provide a novel therapeutic target of lung cancer.

Previous studies have suggested that long non-coding RNAs (lncRNAs) are closely associated with human diseases, particularly cancer, including cancer of the lung, breast and stomach. A variety of lncRNAs are abnormally expressed in cancer and participate in several pathways including cell proliferation and apoptosis; these elements are closely associated with the development of cancer. The Cancer Genome Atlas (TCGA) is an important cancer database. It consists of clinical data, genomic variation, mRNA, microRNA (miRNA) and lncRNAs expression, methylation and other data for various types of human cancer. In the present study, differential expression of RNA was identified using the edgeR package. A total 1,222 RNA sequencing profiles from patients with breast cancer were downloaded from TCGA. A competing endogenous RNA (ceRNA) network was constructed for breast cancer based on miRcode and miRTarBase. The top 10 lncRNAs were selected using Cox regression analysis. Survival analysis was performed using Kaplan-Meier analysis. A total of 1,028 breast cancer-associated lncRNAs and 89 miRNAs (fold change >2; P

The long noncoding RNA (lncRNA) MIR22HG has previously been identified as a prognostic marker in hepatocellular carcinoma. Here, we performed a comprehensive analysis of lncRNA expression profiles from RNA-Seq data and report that MIR22HG plays a similar role in lung cancer. Analysis of 918 lung cancer and normal lung tissues and lung cancer cell lines revealed that MIR22HG was significantly downregulated in lung cancer; this decreased expression was associated with poor patient survival. MIR22HG bound and stabilized the YBX1 protein. Silencing of MIR22HG triggered both cell survival and cell death signaling through dysregulation of the oncogenes YBX1, MET, and p21. In this MIR22HG network, p21 played an oncogenic role by promoting cell proliferation and antiapoptosis in lung cancers. MIR22HG played a tumor-suppressive role as indicated by inhibition of multiple cell cycle–related genes in human primary lung tumors. These data show that MIR22HG has potential as a new diagnostic and prognostic marker and as a therapeutic target for lung cancer. Significance: The lncRNA MIR22HG functions as a tumor suppressor, with potential use a diagnostic/prognostic marker and therapeutic target in lung cancer. Cancer Res; 78(12); 3207–19. ©2018 AACR.

Whole transcriptome analyses of next generation RNA sequencing (RNA-Seq) data from human cancer samples reveled thousands of uncharacterized non-coding RNAs including long non-coding RNA (lncRNA). Recent studies indicated that lncRNAs are emerging as crucial regulators in cancer processes and potentially useful as biomarkers for cancer diagnosis and prognosis. To delineate dysregulated lncRNAs in lung cancer, we analyzed RNA-Seq data from 461 lung adenocarcinomas (LUAD) and 156 normal lung tissues. FAM83H-AS1, one of the top dysregulated lncRNAs, was found to be overexpressed in tumors relative to normal lung and significantly associated with worse patient survival in LUAD. We verified this diagnostic/prognostic potential in an independent cohort of LUAD by qRT-PCR. Cell proliferation, migration and invasion were decreased after FAM83H-AS1 knockdown using siRNAs in lung cancer cells. Flow cytometry analysis indicated the cell cycle was arrested at the G2 phase after FAM83H-AS1 knockdown. Mechanistically, we found that MET/EGFR signaling was regulated by FAM83H-AS1. Our study indicated that FAM83H-AS1 plays an important role in lung tumor progression and may be potentially used as diagnostic/prognostic marker. Further characterization of this lncRNA may provide a novel therapeutic target impacting MET/EGFR signaling.

Lung cancer is a molecularly-heterogenous disease and the leading cause of cancer mortality. The molecular basis for this heterogeneity remains incompletely understood. In the past few years, long non-coding RNAs (lncRNAs) have emerged as novel mechanisms in mediating cancer biology, although most lncRNAs are still undiscovered. LINC00152 has been identified as highly associated with the tumorigenesis and development in gastric cancer, colon cancer and hepatocellular carcinoma, however, the expression level and its oncogenic roles in lung cancer remains unknown. In the present study, we employed next generation RNA sequencing analysis to reveal dysregulated lncRNAs in lung cancer utilizing datasets of 461 lung adenocarcinomas (LUAD) and 156 normal lung tissues from 3 separate institutions. We found that LINC00152 was 4-fold (p 0.8 in these 3 data sets. Patients with high LINC00152 expression have significantly poorer survival than those with low expression (log-rank test, p = 0.003). We verified this diagnostic/prognostic potential in an independent cohort of lung tumor tissues by quantitative RT-PCR. Cell proliferation and colony formation ability were decreased after knockdown of LINC00152 using siRNAs in lung cancer cell lines. The expression of LINC00152 was found primarily in the cytoplasm by qRT-PCR analysis. Trichostatin A treatment indicated that histone acetylation could be one of the mechanisms underlying LINC00152 overexpression in NSCLC and cell-based analyses showed p38 signaling was mainly affected by LINC00152 in vitro. Taken together, our study suggests that LINC00152 is involved in lung tumor growth, may have potential as diagnostic/prognostic marker and that further characterization of this lncRNA as a novel therapeutic target for lung cancer is warranted. Note: This abstract was not presented at the meeting. Citation Format: Shumei Feng, Jie Zhang, Wenmei Su, Shengbin Bai, Lei Xiao, Zhuwen Wang, Jules Lin, Rishindra Reddy, Andrew Chang, David Beer, Guoan Chen. LINC00152 regulates cell proliferation via p38 signaling and overexpression predicts poor patient survival in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3444. doi:10.1158/1538-7445.AM2017-3444