Abstract
Head and neck cancer (HNC) is among the ten leading malignancies worldwide, with India solely contributing one-third of global oral cancer cases. The current focus of all cutting-edge strategies against this global malignancy are directed towards the heterogeneous tumor microenvironment that obstructs most treatment blueprints. Subsequent to the portrayal of established information, the review details the application of single cell technology, organoids and spheroid technology in relevance to head and neck cancer and the tumor microenvironment acknowledging the resistance pattern of the heterogeneous cell population in HNC. Bioinformatic tools are used for study of differentially expressed genes and further omics data analysis. However, these tools have several challenges and limitations when analyzing single-cell gene expression data that are discussed briefly. The review further examines the omics of HNC, through comprehensive analyses of genomics, transcriptomics, proteomics, metabolomics, and epigenomics profiles. Patterns of alterations vary between patients, thus heterogeneity and molecular alterations between patients have driven the clinical significance of molecular targeted therapies. The analyses of potential molecular targets in HNC are discussed with connotation to the alteration of key pathways in HNC followed by a comprehensive study of protein kinases as novel drug targets including its ATPase and additional binding pockets, non-catalytic domains and single residues. We herein review, the therapeutic agents targeting the potential biomarkers in light of new molecular targeted therapies. In the final analysis, this review suggests that the development of improved target-specific personalized therapies can combat HNC’s global plight.
Highlights
The origin of cancer is traced to the characteristic unresponsive cellular behavior towards signals that regulate survival, proliferation, differentiation, and eventual evasion of death [1]
Among the insights gained from bioinformatics analysis of Head and neck cancer (HNC) data sets at single cell levels, the foremost finding arguably is reported by Qi et al [61] in which it was shown that patient outcomes under all treatment regimens are highly dependent on the intrinsic cellular heterogeneity
The major hindrance in the treatment of head and neck cancers comes with the associated heterogeneity
Summary
The origin of cancer is traced to the characteristic unresponsive cellular behavior towards signals that regulate survival, proliferation, differentiation, and eventual evasion of death [1]. Among the insights gained from bioinformatics analysis of HNC data sets at single cell levels, the foremost finding arguably is reported by Qi et al [61] in which it was shown that patient outcomes under all treatment regimens are highly dependent on the intrinsic cellular heterogeneity. In view of the above results, the single-cell simulations can be a source of information to determine the heterogeneity and predict treatment strategy and outcomes These proved to be highly useful in improving the understanding of tumor development on a single-cell level and the differences/similarities from bulk tumor analysis [62]. Microarray analysis of cells obtained with LCM from 16 patients and compared these results GPL96 GSE3524 gene expression profile with 4 control cell epithelium identified expression profiles differentially expressed between and tumor invasion in normal and tissues.
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