Dataset Information

LINC00958 and HOXC13-AS as key candidate biomarkers in head and neck squamous cell carcinoma by integrated bioinformatics analysis.

ABSTRACT: Background:Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor with a strong tendency for metastasis and recurrence. Finding effective biomarkers for the early diagnosis of HNSCC is critical for the early treatment and prognosis of patients. Methods:RNA sequencing data including long non-coding RNAs (lncRNAs), messenger RNA (mRNAs) and microRNAs (miRNAs) of 141 HNSCC and 44 adjacent normal tissues were obtained from the TCGA. Differentially expressed genes were analyzed using the R package DESeq. GO terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. A competing endogenous RNAs (ceRNA) network was constructed. The most differentially expressed genes in the main ceRNA network were chosen for nasopharyngeal carcinoma (NPC) cell lines and NPEC2 Bmi-1 cell line verification. A receiver operating characteristic (ROC) curve was constructed for 141 specimens of HNSCC tissues from 44 control samples. Results:In our study, 79 HNSCC-associated abnormally expressed lncRNAs , 86 abnormally expressed miRNAs and 324 abnormally expressed mRNAs were identified. The public microarray results showed that LINC00958 and HOXC13-AS expression levels were upregulated in HNSCC tissues compared with the adjacent normal tissues in this study (p < 0.0001). LINC00958 and HOXC13-AS expression levels in NPC cell lines were higher than those in the NPEC2 Bmi-1 cell line (p < 0.05). The results showed that the area under the ROC curve (AUC) of LINC00958 reached up to 0.906 at a cutoff value of 7.96, with a sensitivity and specificity of 80.85% and 90.91%, respectively. The AUC of HOXC13-AS reached up to 0.898 at a cutoff value of 0.695, with sensitivity and specificity values of 86.23% and 83.78%, respectively. Conclusion:The current study indicates that LINC00958 and HOXC13-AS are new candidate diagnostic biomarkers for HNSCC patients.

SUBMITTER: Xiong D

PROVIDER: S-EPMC7024572 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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LINC00958 and HOXC13-AS as key candidate biomarkers in head and neck squamous cell carcinoma by integrated bioinformatics analysis.

Xiong Dan D Wu Wei W Kan Lijuan L Chen Dayang D Dou Xiaowen X Ji Xiang X Wang Mengmeng M Zong Zengyan Z Li Jian J Zhang Xiuming X

PeerJ 20200213

<h4>Background</h4>Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor with a strong tendency for metastasis and recurrence. Finding effective biomarkers for the early diagnosis of HNSCC is critical for the early treatment and prognosis of patients.<h4>Methods</h4>RNA sequencing data including long non-coding RNAs (lncRNAs), messenger RNA (mRNAs) and microRNAs (miRNAs) of 141 HNSCC and 44 adjacent normal tissues were obtained from the TCGA. Differentially expressed genes were anal ...[more]

PMID: 32095369

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Project description:BackgroundAccumulating evidence has demonstrated the pivotal role of long noncoding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks for predicting survival and evaluating prognosis in cancer patients. However, the pathogenesis of head and neck squamous cell carcinoma (HNSCC) remains unclear, and prognostic biomarkers for HNSCC are still lacking.MethodsA total of 546 RNA sequencing profiles of HNSCC patients with clinical outcome data were obtained from the Cancer Genome Atlas (TCGA) database, providing a large sample of RNA sequencing data. From these, 71 Long noncoding RNAs lncRNAs, 8 microRNAs (miRNAs), and 16 messenger RNAs (mRNAs) were identified to construct a HNSCC-specific ceRNA network (fold change >2, P < 0.05). Univariate and multivariate Cox proportional regression models were used to assess independent indicators of prognosis. Then the expression of lncRNAs harboring prognostic value was validated in human HNSCC cell lines and tumor samples from our cohort and another two datasets from GEO (Gene Expression Omnibus) databases.ResultsAs a result, a 3-mRNA signature and 6-lncRNA signature were identified. The six-lncRNA signature exhibited the highest prognostic value. Notably, in the six lncRNAs, HOTTIP showed the greatest prognostic value and was significantly correlated with clinical stage and histological grade of HNSCC patients. Furthermore, it was proved that HOTTIP was upregulated in HNSCC cell lines and cancerous tissues compared with corresponding normal cell lines and normal tissues. Functional assessment analysis revealed that HOTTIP might play a key role in the oncogenesis and progression of HNSCC.ConclusionThe present study deepened our understanding of the ceRNA-related regulatory mechanism in the pathogenesis of HNSCC and identified candidate prognostic biomarkers for clinical outcome prediction in HNSCC. HOTTIP may function as a key candidate biomarker in HNSCC and serve as a prognostic marker for HNSCC patients.

Project description:Head and neck squamous cell carcinomas (HNSCC) can arise from the oral cavity, oropharynx, larynx or hypopharynx, and is the sixth leading cancer by incidence worldwide. The 5-year survival rate of HNSCC patients remains static at 40-60%. Hence, biomarkers which can improve detection of HNSCC or early recurrences should improve clinical outcome. Mass spectrometry-based proteomics methods have emerged as promising approaches for biomarker discovery. As one approach, mass-spectrometric identification of proteins shed or secreted from cancer cells can contribute to the identification of potential biomarkers for HNSCC and our understanding of tumor behavior. In the current study, mass spectrometry-based proteomic profiling was performed on the conditioned media (i.e. secretome) of head and neck cancer (HNC) cell lines (FaDu, UTSCC8 and UTSCC42a) in addition to gene expression microarrays to identify over-expressed transcripts in the HNSCC cells in comparison to a normal control cell line. This integrated data set was systematically mined using publicly available resources (Human Protein Atlas and published proteomic/transcriptomic data) to prioritize putative candidates for validation. Subsequently, quantitative real-time PCR (qRT-PCR), Western blotting, immunohistochemistry (IHC), and ELISAs were performed to verify selected markers. Our integrated analyses identified 90 putative protein biomarkers that were secreted or shed to the extracellular space and over-expressed in HNSCC cell lines, relative to controls. Subsequently, the over-expression of five markers was verified in vitro at the transcriptional and translational levels using qRT-PCR and Western blotting, respectively. IHC-based validation conducted in two independent cohorts comprising of 40 and 39 HNSCC biopsies revealed that high tumor expression of PLAU, IGFBP7, MMP14 and THBS1 were associated with inferior disease-free survival, and increased risk of disease progression or relapse. Furthermore, as demonstrated using ELISAs, circulating levels of PLAU and IGFBP7 were significantly higher in the plasma of HNSCC patients compared with healthy individuals.

Project description:BackgroundNon-small cell lung cancer (NSCLC) is the most prevalent malignant tumor of the lung cancer, for which the molecular mechanisms remain unknown. In this study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC by bioinformatics analysis.MethodsFrom the Gene Expression Omnibus database, GSE118370 and GSE10072 microarray datasets were obtained. Identifying the differentially expressed genes (DEGs) between lung adenocarcinoma and normal samples was done. By using bioinformatics tools, a protein-protein interaction (PPI) network was constructed, modules were analyzed, and enrichment analyses were performed. The expression and prognostic values of 14 hub genes were validated by the GEPIA database, and the correlation between hub genes and survival in lung adenocarcinoma was assessed by UALCAN, cBioPortal, String and Cytoscape, and Timer tools.ResultsWe found three genes (PIK3R1, SPP1, and PECAM1) that have a clear correlation with OS in the lung adenocarcinoma patient. It has been found that lung adenocarcinoma exhibits high expression of SPP1 and that this has been associated with poor prognosis, while low expression of PECAM1 and PIK3R1 is associated with poor prognosis (P < 0.05). We also found that the expression of SPP1 was associated with miR-146a-5p, while the high expression of miR-146a-5p was related to good prognosis (P < 0.05). On the contrary, the lower miR-21-5p on upstream of PIK3R1 is associated with a higher surviving rate in cancer patients (P < 0.05). Finally, we found that the immune checkpoint genes CD274(PD-L1) and PDCD1LG2(PD-1) were also related to SPP1 in lung adenocarcinoma.ConclusionsThe results indicated that SPP1 is a cancer promoter (oncogene), while PECAM1 and PIK3R1 are cancer suppressor genes. These genes take part in the regulation of biological activities in lung adenocarcinoma, which provides a basis for improving detection and immunotherapeutic targets for lung adenocarcinoma.

Dataset Information

LINC00958 and HOXC13-AS as key candidate biomarkers in head and neck squamous cell carcinoma by integrated bioinformatics analysis.

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LINC00958 and HOXC13-AS as key candidate biomarkers in head and neck squamous cell carcinoma by integrated bioinformatics analysis.

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