Dataset Information

Identification and validation of seven prognostic long non-coding RNAs in oral squamous cell carcinoma.

ABSTRACT: 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.

SUBMITTER: Miao T

PROVIDER: S-EPMC7285779 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Identification and validation of seven prognostic long non-coding RNAs in oral squamous cell carcinoma.

Miao Tingting T Si Qingzong Q Wei Yuan Y Fan Ruihong R Wang Junjie J An Xiaoli X

Oncology letters 20200513 1

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 informati ...[more]

PMID: 32566023

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Project description:Background and objectiveOral squamous cell carcinoma (OSCC) is the most common malignant tumor in the head and neck, and its morbidity and mortality are increasing year by year. Changes in key genes are thought to be closely related to the occurrence and development of OSCC. Pyroptosis is an inflammatory form of programmed cell death that has been implicated in malignancies and inflammatory diseases. Changes in the expression of long noncoding RNAs may also affect tumorigenesis and progression. In this study, our main objective was to evaluate the association between pyroptosis-related lncRNAs and prognosis in patients with OSCC.MethodsThe RNA-seq data and clinicopathological data of OSCC patients are from The Cancer Genome Atlas database. The pyroptosis gene set is obtained from Gene Set Enrichment Analysis database. Univariate COX, Lasso and multivariate COX regression analyses were used for the construction of risk prognostic models of OSCC, eight lncRNAs were incorporated into prognostic models. The Kaplan-Meier method and log-rank test were used to evaluate the differences of overall survival between patients in high-risk and low-risk groups. The reliability of predictions across the dataset was analyzed by receiver operating characteristic (ROC) curves. The immune signature score was calculated using the single-sample gene set enrichment analysis.ResultsEight pyroptosis-related lncRNAs were used to construct prognostic signature of OSCC, including AC136475.2, AC024075.2, JPX, ZFAS1, TNFRSF10A-AS1, LINC00847, AC099850.3 and IER3-AS1. According to this prognostic signature, patients with OSCC were divided into high-risk and low-risk groups. Kaplan-Meier survival analysis showed that the survival rate of the high-risk group was significantly lower than the low-risk group. ROC area for risk score was 0.716, and ROC area of the 8 lncRNAs are all between 0.5 and 1, implied that these lncRNAs had high accuracy in predicting the prognosis of OSCC patients. Immune Infiltration findings suggested that these lncRNAs affected immune responses in the microenvironment of OSCC.ConclusionThe prognostic signature based on pyroptosis-related lncRNAs potentially serves as an independent prognostic indicator for OSCC patients. And this signature facilitates research on targeted diagnosis and treatment of patients diagnosed with OSCC.

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: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.

Dataset Information

Identification and validation of seven prognostic long non-coding RNAs in oral squamous cell carcinoma.

Publications

Identification and validation of seven prognostic long non-coding RNAs in oral squamous cell carcinoma.

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