Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures

Abstract

For many years, head and neck squamous cell carcinoma (HNSCC) has been considered as a single entity. However, in the last decades HNSCC complexity and heterogeneity have been recognized. In parallel, high-throughput omics techniques had allowed picturing a larger spectrum of the behavior and characteristics of molecules in cancer and a large set of omics web-based tools and informative repository databases have been developed. The objective of the present review is to provide an overview on biological, prognostic and predictive molecular signatures in HNSCC. To contextualize the selected data, our literature survey includes a short summary of the main characteristics of omics data repositories and web-tools for data analyses. The timeframe of our analysis was fixed, encompassing papers published between January 2015 and January 2019. From more than 1000 papers evaluated, 61 omics studies were selected: 33 investigating mRNA signatures, 11 and 13 related to miRNA and other non-coding-RNA signatures and 4 analyzing DNA methylation signatures. More than half of identified signatures (36) had a prognostic value but only in 10 studies selection of a specific anatomical sub-site (8 oral cavity, 1 oropharynx and 1 both oral cavity and oropharynx) was performed. Noteworthy, although the sample size included in many studies was limited, about one-half of the retrieved studies reported an external validation on independent dataset(s), strengthening the relevance of the obtained data. Finally, we highlighted the development and exploitation of three gene-expression signatures, whose clinical impact on prognosis/prediction of treatment response could be high. Based on this overview on omics-related literature in HNSCC, we identified some limits and strengths. The major limits are represented by the low number of signatures associated to DNA methylation and to non-coding RNA (miRNA, lncRNA and piRNAs) and the availability of a single dataset with multiple omics on more than 500 HNSCC (i.e. TCGA). The major strengths rely on the integration of multiple datasets through meta-analysis approaches and on the growing integration among omics data obtained on the same cohort of patients. Moreover, new approaches based on artificial intelligence and informatic analyses are expected to be available in the next future.

Human Endogenous Retrovirus Expression Is Associated with Head and Neck Cancer and Differential Survival

“…In particular, human papillomavirus (HPV) status, which is a risk factor for developing HNSCC, has also been shown to result in a distinct subtype of HNSCC [ 16 ]. Several existing studies have examined the transcriptome in HNSCC [ 17 , 18 , 19 ] and reviewed in Leemans et al [ 15 ] using protein-coding and non-coding genomic annotations. A few studies have examined HERV family-level expression in the pan-cancer The Cancer Genome Atlas (TCGA, ) cohort [ 20 , 21 , 22 , 23 ].…”

Gene Expression Clustering and Selected Head and Neck Cancer Gene Signatures Highlight Risk Probability Differences in Oral Premalignant Lesions

“…A number of signatures have been published providing evidence on their prognostic role in HNSCC [55]. Thus, we tested a number of biologically oriented signatures to verify their ability to stratify patients based on their risk of developing oral cancer.…”

Prognostic and Predictive Factors in Advanced Head and Neck Squamous Cell Carcinoma

“…Over the last years a growing number of research articles was published in the field of transcriptomics and epigenomics in HNSCC, with the majority focusing on prognostic signatures [ 105 ]. Some studies also developed gene expression models that could be used to predict treatment response.…”