Abstract
Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease characterized by different molecular subgroups and clinical features. Therefore, it is important to uncover reliable molecular biomarkers for distinguishing different risk patient subgroup. Here, we conducted a multi-omics analysis to examine the joint predictive power of a multi-type RNA signature in the prognosis of HNSCC patients through integration analysis of mRNA, miRNA, and lncRNA expression profiles and clinical data in a large number of HNSCC patients. A multi-type RNA signature (15SigRS) was constructed which can classify patients into the high-risk group and low-risk group with the significantly different outcome [hazard ratio (HR) = 2.718, 95% confidence interval (CI), 2.258–3.272, p < 0.001] in the discovery data set, and subsequently validated in the Cancer Genome Atlas (TCGA) testing data set (HR = 1.299, 95% CI, 1.170–1.442, p < 0.001) and another independent GSE65858 data set (HR = 1.077, 95% CI, 1.016–1.143, p = 0.013). Further multivariate Cox regression analysis and stratification analysis demonstrated the independence of predictive performance of the 15SigRS relative to conventional clinicopathological factors. Furthermore, the 15SigRS has a prior performance in prognostic prediction than other single RNA type-based signatures. Functional analysis suggested that the 15SigRS are involved in immune- or metabolism-related KEGG pathways. In summary, our study demonstrated the potential application of mixed RNA types as molecular markers for predicting the outcome of cancer patients.
Highlights
Head and neck squamous cell carcinoma (HNSCC), the most frequent histological type of head and neck cancers, is the sixth most common cancers worldwide and account for nearly 5% of all malignancies worldwide (Marur and Forastiere, 2016)
Bai and colleagues identified a 12gene signature for predicting progression and prognosis (Bai et al, 2019) Another six-mRNA signature was identified by Tian et al to predict the death risk of HNSCC patients using gene expression profiles in the Cancer Genome Atlas (TCGA) (Tian et al, 2019)
All these candidate prognostic mRNAs, miRNAs, and lncRNAs were fitted into multivariate Cox regression analysis, 15 of 39 genes were identified as independent prognostic gene biomarkers
Summary
Head and neck squamous cell carcinoma (HNSCC), the most frequent histological type of head and neck cancers, is the sixth most common cancers worldwide and account for nearly 5% of all malignancies worldwide (Marur and Forastiere, 2016). TNM stage has been considered as an important clinical prognostic factor for guiding treatment options, some patients with the same clinical features may have different prognosis because of molecular heterogeneity. There is an urgent need to identify reliable biomarkers for predicting prognosis of HNSCC patients. For HNSCC, recent studies have revealed the altered expression of ncRNAs in the development and progression of HNSCC (Salyakina and Tsinoremas, 2016; Sannigrahi et al, 2018), and several miRNAor lncRNA-related signatures were identified to improve clinical outcome (Irani, 2016; Wong et al, 2016; Cao et al, 2017; Liu et al, 2018; Diao et al, 2019). Previous signatures often focus on one type of RNAs, and the joint predictive power of multiple types of RNAs was not investigated yet
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