Identification of a Novel Signature Predicting Overall Survival in Head and Neck Squamous Cell Carcinoma

DNA Damage Response Mechanisms in Head and Neck Cancer: Significant Implications for Therapy and Survival

Head and neck cancer (HNC) is a term collectively used to describe a heterogeneous group of tumors that arise in the oral cavity, larynx, nasopharynx, oropharynx, and hypopharynx, and represents the sixth most common type of malignancy worldwide. Despite advances in multimodality treatment, the disease has a recurrence rate of around 50%, and the prognosis of metastatic patients remains poor. HNCs are characterized by a high degree of genomic instability, which involves a vicious circle of accumulating DNA damage, defective DNA damage repair (DDR), and replication stress. Nonetheless, the damage that is induced on tumor cells by chemo and radiotherapy relies on defective DDR processes for a successful response to treatment, and may play an important role in the development of novel and more effective therapies. This review summarizes the current knowledge on the genes and proteins that appear to be deregulated in DDR pathways, their implication in HNC pathogenesis, and the rationale behind targeting these genes and pathways for the development of new therapies. We give particular emphasis on the therapeutic targets that have shown promising results at the pre-clinical stage and on those that have so far been associated with a therapeutic advantage in the clinical setting.

The survival rate of laryngeal squamous cell carcinoma: impact of IL1RAP rs4624606, IL1RL1 rs1041973, IL-6 rs1800795, BLK rs13277113, and TIMP3 rs9621532 single nucleotide polymorphisms

PURPOSE

Results of laryngeal squamous cell carcinoma (LSCC) treatment and the 5 year survival rate of these patients remain poor. To purify therapeutic targets, investigation of new specific and prognostic blood-based markers for LSCC development is essential.

METHODS

In the present study, we evaluated five single nucleotide polymorphisms (SNPs): IL1RAP rs4624606, IL1RL1 rs1041973, IL-6 rs1800795, BLK rs13277113, and TIMP3 rs9621532, and determined their associations with the patients' 5 year survival rate. Also, we performed a detailed statistical analysis of different LSCC patients' characteristics impact on their survival rate.

RESULTS

Three hundred fifty-three LSCC patients and 538 control subjects were included in this study. The multivariable Cox regression analysis revealed a significant association between patients' survival rate and distribution of IL1RAP rs4624606 variants: patients carrying AT genotype at IL1RAP rs4624606 had a lower risk of death (p = 0.044). Also, it was revealed that tumor size (T) (p = 0.000), tumor differentiation grade (G) (p = 0.015), and IL1RAP rs4624606 genotype (p = 0.044) were effective variables in multivariable Cox regression analysis prognosing survival of LSCC patients. The specific-LSCC 5 year survival rate was 77%.

CONCLUSIONS

In summary, our findings indicate that the genotypic distribution of IL1RAP rs4624606 influences the 5 year survival rate of LSCC patients. The results of the present study facilitate a more complete understanding of LSCC at the biological level, thus providing the base for the identification of new specific and prognostic blood-based markers for LSCC development.

Construction and Validation of a UPR-Associated Gene Prognostic Model for Head and Neck Squamous Cell Carcinoma

Our study is aimed at constructing and validating a UPR-associated gene signature to predict HNSCC prognosis. We obtained 544 samples of RNA sequencing data and clinical characteristics from TCGA database and randomly grouped the samples into training and testing cohorts (1 : 1 ratio). After identifying 14 UPR-associated genes with LASSO and univariate Cox regression analysis, HNSCC samples were categorized into low-risk (LR) and high-risk (HR) subgroups depending on the risk score. Our analyses indicated that low-risk patients had a much better prognosis in the training and testing cohorts. To predict the HNSCC prognosis with the 14 UPR-associated gene signatures, we incorporated the UPR gene risk score, N stage, M stage, and age into a nomogram model. We further explored the sensitivity to anticancer drugs by using the IC50 analysis in two subgroups from the Cancer Genome Project database. The outcomes showed that the AKT inhibitor III and sorafenib were sensitive anticancer drugs in HR and LR patients, respectively. The immune cell infiltration analysis and GSEA provided strong evidence for elucidating the molecular mechanisms of UPR-associated genes affecting HNSCC. In conclusion, the UPR-associated gene risk score, N stage, M stage, and age can serve as a robust model for predicting prognosis and can improve decision-making at the individual patient level.