Dataset Information

Circulating small non-coding RNA signature in head and neck squamous cell carcinoma.

ABSTRACT: The Head and Neck Squamous Cell Carcinoma (HNSCC) is the sixth most common human cancer, causing 350,000 individuals die worldwide each year. The overall prognosis in HNSCC patients has not significantly changed for the last decade. Complete understanding of the molecular mechanisms in HNSCC carcinogenesis could allow an earlier diagnosis and the use of more specific and effective therapies. In the present study we used deep sequencing to characterize small non-coding RNAs (sncRNAs) in serum from HNSCC patients and healthy donors. We identified, for the first time, a multi-marker signature of 3 major classes of circulating sncRNAs in HNSCC, revealing the presence of circulating novel and known miRNAs, and tRNA- and YRNA-derived small RNAs that were significantly deregulated in the sera of HNSCC patients compared to healthy controls. By implementing a triple-filtering approach we identified a subset of highly biologically relevant miRNA-mRNA interactions and we demonstrated that the same genes/pathways affected by somatic mutations in cancer are affected by changes in the abundance of miRNAs. Therefore, one important conclusion from our work is that during cancer development, there seems to be a convergence of oncogenic processes driven by somatic mutations and/or miRNA regulation affecting key cellular pathways.

SUBMITTER: Victoria Martinez B

PROVIDER: S-EPMC4662488 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Circulating small non-coding RNA signature in head and neck squamous cell carcinoma.

Victoria Martinez Berta B Dhahbi Joseph M JM Nunez Lopez Yury O YO Lamperska Katarzyna K Golusinski Paweł P Luczewski Lukasz L Kolenda Tomasz T Atamna Hani H Spindler Stephen R SR Golusinski Wojciech W Masternak Michal M MM

Oncotarget 20150801 22

The Head and Neck Squamous Cell Carcinoma (HNSCC) is the sixth most common human cancer, causing 350,000 individuals die worldwide each year. The overall prognosis in HNSCC patients has not significantly changed for the last decade. Complete understanding of the molecular mechanisms in HNSCC carcinogenesis could allow an earlier diagnosis and the use of more specific and effective therapies. In the present study we used deep sequencing to characterize small non-coding RNAs (sncRNAs) in serum fro ...[more]

PMID: 26057471

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Project description:BackgroundThis study aimed to develop multi-RNA-based models using a competing endogenous RNA (ceRNA) regulatory network to provide survival risk prediction in head and neck squamous cell carcinoma (HNSCC).MethodsAll long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA expression data and clinicopathological features related to HNSCC were derived from The Cancer Genome Atlas. Differentially expressed RNAs were calculated using R. Prognostic factors were identified using univariate Cox regression analysis. Functional analysis was performed using GO, KEGG pathways, and PPI network. Based on the results, we derived a risk signature and compared high- and low-risk subgroups using LASSO regression analysis. Survival analysis and the relationship between risk signature and clinicopathological features were performed using log-rank tests and Cox regression analysis. A ceRNA regulatory network was constructed, and prognostic lncRNAs and miRNA expression levels were validated in vitro and in vivo.ResultsA list of 207 lncRNAs, 18 miRNAs and 362 mRNAs related to overall survival was established. Five lncRNAs (HOTTIP, LINC00460, RMST, SFTA1P, and TM4SF19-AS1), one miRNA (hsa-miR-206), and one mRNA (STC2) were used to construct the ceRNA network. Three prognostic models contained 13 lncRNAs, eight miRNAs, and 17 mRNAs, which correlated with the patient status, disease-free survival (DFS), stage, grade, T stage, N stage, TP53 mutation status, angiolymphatic invasion, HPV status, and extracapsular spread. KEGG pathway analysis revealed significant enrichment of "Transcriptional misregulation in cancer" and "Neuroactive ligand-receptor interaction." In addition, HOTTIP, LINC00460, miR-206 and STC2 were validated in GTEx data, GEO microarrays and six HNSCC cell lines.ConclusionsOur findings clarify the interaction of ceRNA regulatory networks and crucial clinicopathological features. These results show that prognostic biomarkers can be identified by constructing multi-RNA-based prognostic models, which can be used for survival risk prediction in patients with HNSCC.

Project description:Head and neck squamous cell carcinoma (HNSCC) has a poor prognosis. Considerable evidence indicates that autophagy and non-coding RNA play essential roles in the biological processes involved in cancers, but associations between autophagy-related long non-coding RNAs (lncRNAs) and HNSCC remain unclear. In the present study, HNSCC RNA sequences and autophagy-related gene data were extracted from The Cancer Genome Atlas database and the Human Autophagy Database. A total of 1,153 autophagy-related lncRNAs were selected via calculating Pearson's correlation coefficient. Three prognosis-related autophagy lncRNAs were identified via univariate Cox regression, least absolute shrinkage and selection operator analysis, and multivariate Cox regression analysis. We also constructed a prognostic model based on these autophagy-related lncRNAs and evaluated its ability to accurately and independently predict the prognosis of HNSCC patients. The area under the curve (AUC) was 0.864 (3-year) and 0.836 (5-year), and our model can independently predict the prognosis of HNSCC. The prognostic value of the three autophagy lncRNAs was confirmed via analysis of samples from five databases. To further identify the functions of the three lncRNAs, a co-expression network was constructed and pathway analysis was performed. In that analysis the lncRNAs were correlated with 189 related genes and 20 autophagy-related genes, and these lncRNAs mainly involved homologous recombination, the Fanconi anemia pathway, the autophagy-related pathway, and immune-related pathways. In addition, we validated the expression levels of three lncRNAs and autophagy markers (ATG12, BECN1, and MAP1LC3B) based on TIMER, Oncomine, and HPA database analysis. Our results indicated that TTTY15 was increased in HPV positive and HPV negative HNSCC patients, and three autophagy markers were up-regulated in all HNSCCC patients. Lastly, association between three lncRNAs and autophagy markers was performed, and our results showed that TTTY15 and MIF-AS1 were associated with autophagy markers. Collectively, these results suggested that three autophagy-related lncRNAs have prognostic value in HNSCC patients.

Project description:Background: Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor, which makes the prognosis prediction challenging. Ferroptosis is an iron-dependent form of non-apoptotic regulated cell death, which could affect cancer development. However, the prognostic value of ferroptosis-related long non-coding RNA (lncRNA) in HNSCC is still limited. Methods: In the current study, we employed the DESeq2 method to characterize the differentially expressed ferroptosis-related genes (FEGs) between cancer and normal samples. Next, the FEG-related lncRNAs (FElncRNAs) were identified using Spearman's correlation analysis and multiple permutation hypotheses. Subsequently, LASSO and stepwise multivariate Cox regression analyses were undertaken to recognize the prognosis-related FElncRNA signature (PFLS) and risk scores. Results: Herein, we first identified 60 dysregulated FEGs and their co-expressed FElncRNAs in HNSCC. Then, we recognized a set of six FElncRNAs PFLS (SLCO4A1-AS1, C1RL-AS1, PCED1B-AS1, HOXB-AS3, MIR9-3HG, and SFTA1P) for predicting patients' prognostic risks and survival outcomes. We also assessed the efficiency of PFLS in the test set and an external validation cohort. Further parsing of the tumor immune microenvironment showed the PFLS was closely associated with immune cell infiltration abundances. Notably, the low-risk group of the PFLS showed a higher MHC score and cytolytic activity (CYT) score than the high-risk group, implying the low-risk group may have greater tumor surveillance and killing ability. In addition, we observed that the expression levels of two immune checkpoints (ICPs), i.e., programmed cell death protein 1 (PD-1) and programmed cell death 1 ligand 1 (PD-L1), showed significant associations with patients' risk score, prompting the role of the PFLS in ICP blockade therapy. Finally, we also constructed a drug-PFLS network to reinforce the clinical utilities of the PFLS. Conclusion: In summary, our study indicated that FElncRNAs played an important role in HNSCC survival prediction. Identification of PFLS will contribute to the development of novel anticancer therapeutic strategies.

Dataset Information

Circulating small non-coding RNA signature in head and neck squamous cell carcinoma.

Publications

Circulating small non-coding RNA signature in head and neck squamous cell carcinoma.

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