Predicting the Immune Microenvironment and Prognosis with a NETosis-Related lncRNA Signature in Head and Neck Squamous Cell Carcinoma.

The mechanistic aspects of the involvement of long noncoding RNAs (lncRNAs) in NETosis, the process of neutrophil extracellular trap (NET) formation in head and neck squamous cell carcinoma (HNSCC), lack comprehensive elucidation. The involvement of these molecules in the immune microenvironment and plausible HNSCC prognosis remain to see the light of the day. The plausible functioning of NETosis-related lncRNAs with their plausible prognostic impact in HNSCC was probed in this work. The scrutiny of lncRNAs linked to NETosis entailed the probing of twenty-four genes associated with the process employing Pearson's correlation analysis on HNSCC patients' RNA sequencing data from The Cancer Genome Atlas (TCGA) database. The application of univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses yielded a NETosis-related lncRNA signature that was subjected to probing for its suitability in prognosis employing survival and nomogram analyses. The NETosis-related lncRNA signature inclusive of five lncRNAs facilitated patients to be segregated as high-risk and low-risk groups with the former documenting a poor prognosis. Regression unearthed that the risk score was an independent factor for prognosis. The receiver operating characteristic (ROC) or receiver operating characteristic curve analysis documented a one-year area under time-dependent ROC curve (AUC) value of 0.711 that is corroborative of the accuracy of this signature. Additional probing documented an evident enriching of immune-linked pathways in the low-risk patients, while the high-risk patients documented an immunologically "cold" profile as per the infiltration of immune cells. We verified lncRNA expression from our NETosis-related lncRNA signature in vitro, which reflects the reliability of our model to a certain extent. Moreover, we also verified the function of the lncRNA. We found that LINC00426 contributes to the innate immune cGAS-STING signaling pathway, which explain to some extent the role of our prognostic model in predicting "hot" and "cold" tumors. The plausible prognostic relevance of the NETosis-related lncRNA signature (with five lncRNAs) emerges that is suggestive of its promise in targeting HNSCC.

He X ，Xiao Y ，Liu S ，Deng R ，Li Z ，Zhu 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 ... -  《-》

Identification and in vitro validation of prognostic lncRNA signature in head and neck squamous cell carcinoma.

Wang J ，Bian Q ，Liu J ，Moming A ... -  《-》

Identification of a nomogram based on an 8-lncRNA signature as a novel diagnostic biomarker for head and neck squamous cell carcinoma.

Mao R ，Chen Y ，Xiong L ，Liu Y ，Zhang T ... -  《Aging-US》

Necrotic related-lncRNAs: Prediction of prognosis and differentiation between cold and hot tumors in head and neck squamous cell carcinoma.

Treatment of head and neck squamous cell carcinoma (HNSCC) is a substantial clinical challenge due to the high local recurrence rate and chemotherapeutic resistance. This project seeks to identify new potential biomarkers of prognosis prediction and precision medicine to improve this condition. A synthetic data matrix for RNA transcriptome datasets and relevant clinical information on HNSCC and normal tissues was downloaded from the Genotypic Tissue Expression Project and The Cancer Genome Atlas (TCGA). The necrosis-associated long-chain noncoding RNAs (lncRNAs) were identified by Pearson correlation analysis. Then 8-necrotic-lncRNA models in the training, testing and entire sets were established through univariate Cox (uni-Cox) regression and Lasso-Cox regression. Finally, the prognostic ability of the 8-necrotic-lncRNA model was evaluated via survival analysis, nomogram, Cox regression, clinicopathological correlation analysis, and receiver operating characteristic (ROC) curve. Gene enrichment analysis, principal component analysis, immune analysis and prediction of risk group semi-maximum inhibitory concentration (IC50) were also conducted. Correlations between characteristic risk score and immune cell infiltration, immune checkpoint molecules, somatic gene mutations, and anti-cancer drug sensitivity were analyzed. Eight necrosis-associated lncRNAs (AC099850.3, AC243829.2, AL139095.4, SAP30L-AS1, C5orf66-AS1, LIN02084, LIN00996, MIR4435-2HG) were developed to improve the prognosis prediction of HNSCC patients. The risk score distribution, survival status, survival time, and relevant expression standards of these lncRNAs were compared between low- and high-risk groups in the training, testing and entire sets. Kaplan-Meier analysis showed the low-risk patients had significantly better prognosis. The ROC curves revealed the model had an acceptable predictive value in the TCGA training and testing sets. Cox regression and stratified survival analysis indicated that the 8 necrosis-associated lncRNAs were risk factors independent of various clinical parameters. We recombined the patients into 2 clusters through Consensus ClusterPlus R package according to the expressions of necrotic lncRNAs. Significant differences were found in immune cell infiltration, immune checkpoint molecules, and IC50 between clusters, suggesting these characteristics can be used to evaluate the clinical efficacy of chemotherapy and immunotherapy. This risk model may serve as a prognostic signature and provide clues for individualized immunotherapy for HNSCC patients.

Shi Y ，Zhang Y ，Zuo N ，Wang L ，Sun X ，Liang L ，Ju M ，Di X ... -  《-》