Dataset Information

Identification and Validation of Novel Long Non-coding RNA Biomarkers for Early Diagnosis of Oral Squamous Cell Carcinoma.

ABSTRACT: Long non-coding RNAs (lncRNAs) are recently emerging as a novel promising biomarker for cancer diagnosis and prognosis. Despite these previous investigations, the expression pattern and diagnostic role of lncRNAs in oral squamous cell carcinoma (OSCC) remain unclear. In this study, we identified six novel lncRNA biomarkers (LINC01697, LINC02487, LOC105376575, AC005083.1, SLC8A1-AS1, and U62317.1) from a list of 29 differentially expressed lncRNAs using the least absolute shrinkage and selection operator (LASSO) method in the discovery dataset of 167 OSCC samples and 45 normal oral tissues. Using the logistic regression method, we constructed a six lncRNAs-based diagnostic risk model (6lncRNAScore) which was able to differentiate between OSCC samples and control samples with high performance with AUC of 0.995 and high diagnostic specificity of 88.9% and sensitivity of 98.2% in the discovery dataset. The diagnostic performance of the 6lncRNAScore was further validated in another two independent OSCC dataset with AUC of 0.968 and 1.0. Functional enrichment analysis for lncRNA biomarkers-related mRNAs suggested that lncRNAs biomarkers tended to be involved in the lipid metabolic process. Together, our study highlighted the importance of lncRNAs in OSCC and demonstrated the utility of lncRNA expression as a promising biomarker for early diagnosis of OSCC.

SUBMITTER: Li Y

PROVIDER: S-EPMC7174591 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification and Validation of Novel Long Non-coding RNA Biomarkers for Early Diagnosis of Oral Squamous Cell Carcinoma.

Li Yue Y Cao Xiaofang X Li Hao H

Frontiers in bioengineering and biotechnology 20200415

Long non-coding RNAs (lncRNAs) are recently emerging as a novel promising biomarker for cancer diagnosis and prognosis. Despite these previous investigations, the expression pattern and diagnostic role of lncRNAs in oral squamous cell carcinoma (OSCC) remain unclear. In this study, we identified six novel lncRNA biomarkers (LINC01697, LINC02487, LOC105376575, AC005083.1, SLC8A1-AS1, and U62317.1) from a list of 29 differentially expressed lncRNAs using t ...[more]

PMID: 32351944

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Project description:Oral squamous cell carcinoma (OSCC), characterized by a high recurrence rate, a poor prognosis and high morbidity, is the most prevalent malignancy of the oral cavity. The aberrant expression of long non-coding RNAs (lncRNAs) may lead to the development of various diseases, including cancer. Delayed diagnosis is the main reason for the poor prognosis. Therefore, the present study aimed to investigate the differential expression profiles of plasma lncRNAs in OSCC in order to screen target lncRNAs as biomarkers for the early diagnosis and staging of OSCC. The expression profiles of lncRNAs and mRNAs in OSCC were analyzed by microarray analysis. A total of 14 candidate lncRNAs were selected and analyzed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) using the array homologous samples. Subsequently, 4 target lncRNAs were measured by RT-qPCR in a large cohort, including 28 cases with TNM I/II [early-stage squamous cell carcinoma (ESCC) group], 36 cases with TNM III/IV [advanced-stage squamous cell carcinoma (ASCC) group], 16 cases with dysplasia [oral premalignant lesion (OPL) group] and 16 healthy controls (H group). Receiver operating characteristic (ROC) curves and logistic regression analysis were used to evaluate the diagnostic effects of the combined lncRNAs. In total, 6,606 differentially expressed lncRNAs and 4,196 mRNAs were identified in OSCC. The expression trend of the 14 candidate lncRNAs was consistent with the microarray data. The expression level of ENST00000412740, NR_131012, ENST00000588803 and NR_038323 exhibited significant differences in the H, OPL, ESCC and ASCC groups (P<0.05). ROC curve and logistic regression analyses revealed that the diagnostic efficacy of the combined lncRNAs was more prominent than that of a single lncRNA, particularly in the ESCC and ASCC groups. In conclusion, the present study identified the differential expression profiles of plasma lncRNAs in OSCC and demonstrated that ENST00000412740, NR_131012, ENST00000588803 and NR_038323 may be promising biomarkers for the early diagnosis and staging of OSCC. These findings may provide novel targets for the early diagnosis and staging of OSCC, which may provide an objective basis for clinical decision-making.

Project description:Oral squamous cell carcinoma (OSCC) is one of the most common malignancies worldwide, due to poor diagnosis and treatment. There is increasing evidence that demonstrates the involvement of long non-coding RNAs (lncRNAs) in carcinogenesis and cancer progression. Therefore, the aim of the present study was to explore potential lncRNA-associated features of patients with OSCC as a valuable and independent prognostic biomarker. A total of 268 lncRNA expression profiles and clinical patient information on OSCC were downloaded from The Cancer Genome Atlas database. The clinical information was exploited for prescreening, using Cox regression analysis, and differentially expressed lncRNAs (DElncRNAs) were identified using edgeR software. Using the 'caret' package, the datasets were categorized into test datasets and training datasets, respectively. Through bioinformatics, seven prognostic DElncRNAs were selected. Using the regression coefficients, a risk score based on the seven-DElncRNA signature was developed to assess the prognostic function of key DElncRNAs. According to the median risk score, patients were classified into high-risk and low-risk groups in the training and test datasets. Additionally, receiver operating characteristic (ROC) curve analysis was conducted to evaluate the sensitivity and specificity of the prognostic DElncRNAs, and the optimal cut-off point was obtained from ROC analysis. Based on the optimal cut-off point, the patients were also categorized into high-risk and low-risk groups. Notably, the optimal cut-off point was more sensitive than the median risk score, particularly in the test dataset. The Kaplan-Meier survival and log rank test analysis results indicated that the P-value, based on the optimal cut-off, was less than the median risk cut-off. Additionally, stratified analysis results revealed that the seven-DElncRNAs signature was also independent of OSCC age. Furthermore, the findings of the present study suggested that the seven-DElncRNA signature can be used as a potential prognostic indicator and may have important clinical significance in OSCC.

Project description:Objectives Recently long non-coding RNAs (lncRNAs) have emerged as novel gene regulators involved in tumorigenic processes, including oral squamous cell carcinoma (OSCC). Here, we identified a differentiation-related lncRNA, terminal differentiation-induced non-coding RNA (TINCR). However, its biological function and clinicopathological significance in OSCC still remain unclear. Methods The lncRNA expression profiles in OSCC tissues and paired adjacent non-tumor tissues (NATs) from 10 patients were detected by lncRNA microarrays. Weighted gene co-expression network analysis (WGCNA) and gene ontology (GO) enrichment were performed to identify the most significant module and module functional annotation, respectively. Potential differentiation-related lncRNAs were screened by differential expression analysis. TINCR was further confirmed in OSCC cell lines and tissues of another patient cohort by using qRT-PCR. The correlation between the TINCR expression level and clinicopathological characteristics was analyzed. The effects of TINCR on cell differentiation, migration and invasion were assessed by knockdown or knock-in in vitro and in vivo. Results WGCNA and GO enrichment analysis showed that one co-expression network was significantly enriched for epithelial cell differentiation, among which, TINCR was significantly downregulated. qRT-PCR analyses validated down-regulation of TINCR in tumor tissues compared with paired NATs, and its expression was closely correlated with pathological differentiation and lymph node metastasis in patients with OSCC. Patients with lower TINCR expression levels had worse survival. Cell function experiments showed that TINCR played a crucial role in epithelial differentiation. Both TINCR and epithelial differentiation-associated genes, including IVL and KRT4, were significantly upregulated during OSCC cell calcium-induced differentiation but were reduced when cell dedifferentiation occurred in tumor spheres. Overexpression of TINCR dramatically suppressed cell dedifferentiation, migration and invasion in vitro, while knockdown of TINCR had the opposite effects. Upregulation of TINCR significantly elevated the expression of terminal differentiation genes and repressed tumor growth in vivo. Moreover, TINCR significantly suppressed the activation of JAK2/STAT3 signaling in OSCC cells. Conclusion Our study suggests that TINCR functions as a tumor suppressor by inducing cell differentiation through modulating JAK2/STAT3 signaling in OSCC. TINCR may serve as a prognostic biomarker and therapeutic target for OSCC.

Dataset Information

Identification and Validation of Novel Long Non-coding RNA Biomarkers for Early Diagnosis of Oral Squamous Cell Carcinoma.

Publications

Identification and Validation of Novel Long Non-coding RNA Biomarkers for Early Diagnosis of Oral Squamous Cell Carcinoma.

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