The prognosis of head and neck squamous cell carcinoma (HNSCC) patients remains poor. High-throughput sequencing data have laid a solid foundation for identifying genes related to cancer prognosis, but a gene marker is needed to predict clinical outcomes in HNSCC. In our study, we downloaded RNA Seq, single nucleotide polymorphism, copy number variation, and clinical follow-up data from TCGA. The samples were randomly divided into training and test. In the training set, we screened genes and used random forests for feature selection. Gene-related prognostic models were established and validated in a test set and GEO verification set. Six genes (PEX11A, NLRP2, SERPINE1, UPK, CTTN, D2HGDH) were ultimately obtained through random forest feature selection. Cox regression analysis confirmed the 6-gene signature is an independent prognostic factor in HNSCC patients. This signature effectively stratified samples in the training, test, and external verification sets (P < 0.01). The 5-year survival AUC in the training and verification sets was greater than 0.74. Thus, we have constructed a 6-gene signature as a new prognostic marker for predicting survival of HNSCC patients.

Head and neck squamous cell carcinoma (HNSCC) is a common malignant cancer that accounts for 5–10% of all cancers. This study aimed to identify essential genes associated with the prognosis of HNSCC and construct a powerful prognostic model for the risk assessment of HNSCC. RNAseq expression profile data for the patients with HNSCC were obtained from the TCGA database (GEO). A total of 500 samples with full clinical following-up were randomly divided into a training set and a validation set. The training set was used to screen for differentially expressed lncRNAs. Single-factor survival analysis was performed to obtain lncRNAs that associated with prognosis. A robust likelihood-based survival model was constructed to identify the lncRNAs that are essential for the prognosis of HNSCC. A co-expression network between genes and lncRNAs was also constructed to identify lncRNAs co-expressed with genes to serve as the final signature lncRNAs for prognosis. Finally, the prognostic effect of the signature lncRNAs was tested by multi-factor survival analysis and a scoring model for the prognosis of HNSCC was constructed. Moreover, the results of the validation set and the relative expression levels of the signature lncRNAs in the tumour and the adjacent tissue were consistent with the results of the training set. The 5 lncRNAs were distributed among 3 expression modules. Further KEGG pathway enrichment analysis showed that these 3 co-expressed modules participate in different pathways, and many of these pathways are associated with the development and progression of disease. Therefore, we proposed that the 5 validated lncRNAs can be used to predict the prognosis of HNSCC patients and can be applied in postoperative treatment and follow-up.

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Radioresistance continues to be a major problem in the treatment of nasopharyngeal carcinoma (NPC). This study aimed to identify novel proteins associated with NPC radioresistance. We used a mass spectrometry driven-proteomic strategy to identify novel proteins associated with NPC radioresistance, and differential proteins were subsequently processed by bioinformatic analysis. As a result, twelve proteins were identified with aberrant expression in radioresistant (RR) NPC tissues compare to radiosensitive (RS) NPC tissues. Among these proteins, ERp29, Mn-SOD, HSP27 and GST ω1 were found to be significantly up-regulated in RR NPC tissues, and ERp29 was selected for further validation. Immunohistochemistry analysis confirmed that ERp29 was overexpressed in RR NPC tissues compared with RS NPC tissues. To prove the role of ERp29 in the induction of NPC radioresistance, ERp29 was down-regulated in the ERp29 enriched NPC cells CNE-1 and 6-10B by specific shRNA. Radiosensitivity was measured using cell proliferation assay and clonogenic survival assay, and cell apoptosis was measured using flow cytometric analysis. We found that ERp29 knockdown attenuated CNE-1 and 6-10B cell radioresistance and enhanced cell apoptosis. These results suggest that ERp29 associates with radioresistance in NPC, and ERp29 could be a potential biomarker for predicting NPC response to radiotherapy.

Thus, these results indicated that lncRNA CASC2 was a predictor for LNM of PTC patients and may serve as a potential target of PTC treatment.