A three-lncRNA expression signature predicts survival in head and neck squamous cell carcinoma (HNSCC).

Increasing evidence has shown that long non-coding RNAs (lncRNAs) have important biological functions and can be used as a prognostic biomarker in human cancers. However, investigation of the prognostic value of lncRNAs in head and neck squamous cell carcinoma (HNSCC) is in infancy. In the present study, we analyzed the lncRNA expression data in a large number of HNSCC patients (n=425) derived from The Cancer Genome Atlas (TCGA) to identify an lncRNA expression signature for improving the prognosis of HNSCC. Three lncRNAs are identified to be significantly associated with survival in the training dataset using Cox regression analysis. Three lncRNAs were integrated to construct an lncRNA expression signature that could stratify patients of training dataset into the high-risk group and low-risk group with significantly different survival time (median survival 1.85 years vs. 5.48 years; P=0.0018, log-rank test). The prognostic value of this three-lncRNA signature was confirmed in the testing and entire datasets, respectively. Further analysis revealed that the prognostic power of three-lncRNA signature was independent of clinical features by multivariate Cox regression and stratified analysis. These three lncRNAs were significantly associated with known genetic and epigenetic events by means of functional enrichment analysis. Therefore, our results indicated that the three-lncRNA expression signature can predict HNSCC patients' survival.

Wang P ，Jin M ，Sun CH ，Yang L ，Li YS ，Wang X ，Sun YN ，Tian LL ，Liu M ... -  《-》

Prediction of head and neck squamous cell carcinoma survival based on the expression of 15 lncRNAs.

Recent evidence suggests that long noncoding RNAs (lncRNAs) are essential regulators of many cancer-related processes, including cancer cell proliferation, invasion, and migration. There is thus a reason to believe that the detection of lncRNAs may be useful as a diagnostic and prognostic strategy for cancer detection, however, at present no effective genome-wide tests are available for clinical use, constraining the use of such a strategy. In this study, we performed a comprehensive assessment of lncRNAs expressed in samples in the head and neck squamous cell carcinoma (HNSCC) cohort available in The Cancer Genome Atlas database. A risk score (RS) model was constructed based on the expression data of these 15 lncRNAs in the validation data set of HNSCC patients and was subsequently validated in validation data set and the entire data set. We were able to stratify patients into high- and low-risk categories, using our lncRNA expression panel to determine an RS, with significant differences in overall survival (OS) between these two groups in our test set (median survival, 1.863 vs. 5.484 years; log-rank test, p < 0.001). We were able to confirm the predictive value of our 15-lncRNA signature using both a validation data set and a full data set, finding our signature to be reproducible and effective as a means of predicting HNSCC patient OS. Through the multivariate Cox regression and stratified analyses, we were further able to confirm that the predictive value of this RS was independent of other predictive factors such as clinicopathological parameters. The Gene set enrichment analysis revealed potential functional roles for these 15 lncRNAs in tumor progression. Our findings indicate that an RS established based on a panel of lncRNA expression signatures can effectively predict OS and facilitate patient stratification in HNSCC.

Zhang B ，Wang H ，Guo Z ，Zhang X ... -  《-》

A three-lncRNA signature derived from the Atlas of ncRNA in cancer (TANRIC) database predicts the survival of patients with head and neck squamous cell carcinoma.

Long non-coding RNAs (lncRNAs) have important biological functions and can be used as prognostic biomarkers in cancer. To identify a lncRNA prognostic signature for head and neck squamous cell carcinoma (HNSCC). We analysed RNA-seq data derived from the TANRIC database to identify a lncRNA prognostic signature model using the orthogonal partial least squares discrimination analysis (OPLS-DA) and 1.5-fold expression change criterion methods. The prognosis prediction model based on the lncRNA signatures and clinical parameters were evaluated using the 5-fold cross validation method. A total of 84 out of 3199 lncRNAs were significantly associated with the survival of patients with HNSCC (log-rank test P<0.01). Using the OPLS-DA and 1.5-fold change selection criterion, 5 lncRNAs (KTN1-AS1, LINC00460, GUSBP11, LINC00923 and RP5-894A10.6) were further selected. The prediction power of each combination of the 5 lncRNAs was evaluated through the receiver operating characteristic (ROC) curve and a three-lncRNA panel (KTN1-AS1, LINC00460 and RP5-894A10.6) achieved the highest prognostic prediction power (AUC 0.68, 95% CI 0.60-0.76, P<0.0001) in the cohort. The patients were categorized into high- and low-risk groups based on their three-lncRNA profiles. Patients with high-risk scores had worse overall survival than those with low risk scores in the cohort (log-rank test P=0.0003). Multivariable Cox regression analyses showed that the lncRNA signature and tumour grade were independent prognostic factors for patients with HNSCC. Our findings showed that the three-lncRNA signature might be a novel biomarker for the accurate prognosis prediction of patients with HNSCC.

Cao W ，Liu JN ，Liu Z ，Wang X ，Han ZG ，Ji T ，Chen WT ，Zou X ... -  《-》

A pyroptosis-related lncRNA signature predicts prognosis and immune microenvironment in head and neck squamous cell carcinoma.

Pyroptosis, a type of regulated cell death controlled by the gasdermin family of proteins to form plasma membrane pores is known. Nonetheless, the function of pyroptosis-related long non-coding RNAs (lncRNAs) in this process still lacks exhaustive elucidation in head and neck squamous cell carcinoma (HNSCC). Other attributes encompassing the function of such lncRNAs in the immune microenvironment and potential prognosis for HNSCC are yet to see the light of the day. This work was designed to probe the possible prognostic worth of pyroptosis-related lncRNAs along with their impact on the immune microenvironment in the case of HNSCC. The Cancer Genome Atlas (TCGA) database was the source of RNA-sequencing data of HNSCC patients. Pearson correlation analysis was employed to scour for lncRNAs linked to pyroptosis based on 40 genes related to the process. Following the construction of a pyroptosis-related lncRNA signature employing univariate, Least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses, survival and nomogram analyses ensued to scrutinize the predictive value of the prognostic signature. The segregation of patients into two risk groups was done by the constructed pyroptosis-related-lncRNA signature (encompassing 14 lncRNAs). The prognosis was poorer for individuals of the high-risk group versus (vs.) the low-risk group with the risk score emerging as an independent prognostic factor by regression analyses. The accuracy of this signature was corroborated by Receiver operating characteristic curve (ROC) analysis with the three-years area under time-dependent ROC curve (AUC) reaching 0.767. Further analyses unveiled a conspicuous enrichment of immune-related pathways in the low-risk group. The high-risk group demonstrated an immunologically "cold" profile based on the immune cell infiltration landscape. The lncRNA signature encompassing 14 pyroptosis-related lncRNAs could be a prognostic marker for HNSCC, suggesting pyroptosis might be a promising therapeutic target in HNSCC.

Zhu W ，Ye Z ，Chen L ，Liang H ，Cai Q ... -  《-》

HOTTIP Functions as a Key Candidate Biomarker in Head and Neck Squamous Cell Carcinoma by Integrated Bioinformatic Analysis.

Yin X ，Yang W ，Xie J ，Wei Z ，Tang C ，Song C ，Wang Y ，Cai Y ，Xu W ，Han W ... -  《-》