Abstract:The total amount of scientific literature has grown rapidly in recent years. Specifically, there are several million citations in the field of cancer. This makes it difficult, if not impossible, to manually retrieve relevant information on the mechanisms that govern tumor behavior or the neoplastic process. Furthermore, cancer is a complex disease or, more accurately, a set of diseases. The heterogeneity that permeates many tumors is particularly evident in head and neck (HN) cancer, one of the most common typ… Show more
“…The available HNC data bases provide clinical and genomic information on HNC cell systems (102)(103)(104). A holistic HNdb database curates all major omics data and literature on HNC-related genes (105). This database has laid the foundation for identification of possible biomarkers and development of HNC personalized medicine.…”
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.
“…The available HNC data bases provide clinical and genomic information on HNC cell systems (102)(103)(104). A holistic HNdb database curates all major omics data and literature on HNC-related genes (105). This database has laid the foundation for identification of possible biomarkers and development of HNC personalized medicine.…”
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.
“…Although these web tools are valuable and simultaneously encompass two major HPV‐associated cancers (cervical cancer and head and neck cancer), they are not specifically designed for HPV‐associated cancers and do not emphasize the impact of HPV infection on the TIME. Additionally, databases and analysis tools, such as HNCDB [ 20 ], HNOCDB [ 21 ], HNdb [ 22 ], OrCGDB [ 23 ], and CCDB [ 24 ], exist for specific cancer types, even though they do not include information on most common types of HPV‐associated cancers. Moreover, these tools do not perform immune infiltration analysis.…”
The tumor immune microenvironment (TIME) is closely associated with tumor formation, particularly linked to the human papillomavirus (HPV), and regulates tumor initiation, proliferation, infiltration, and metastasis. With the rise of immunotherapy, an increasing amount of sample data used for TIME exploration is available in databases. However, no currently available web tool enables a comprehensive exploration of the TIME of HPV‐associated cancers by leveraging these data. We have developed a web tool called HPV‐associated Tumor Immune MicroEnvironment ExploreR (HPVTIMER), which provides a comprehensive analysis platform that integrates over 10,000 genes and 2290 tumor samples from 65 transcriptome data sets across 8 cancer types sourced from the Gene Expression Omnibus (GEO) database. The tool features four built‐in analysis modules, namely, the differential expression analysis module, correlation analysis module, immune infiltration analysis module, and pathway analysis module. These modules enable users to perform systematic and vertical analyses. We used several analytical modules in HPVTIMER to briefly explore the role of CDKN2A in head and neck squamous cell carcinomas. We expect that HPVTIMER will help users explore the immune microenvironment of HPV‐associated cancers and uncover potential immune regulatory mechanisms and immunotherapeutic targets. HPVTIMER is available at http://www.hpvtimer.com/.
“…HNOCDB is a comprehensive database of genes relevant to HNC and was constructed based on text mining on PubMed (4). HNdb is an integrated database of gene and protein information that covers genomics, transcriptomics, proteomics, and literature evidence for HNC (5). OrCGDB is a database of genes involved in oral cancer (6).…”
Head and neck cancer (HNC) is the sixth most common cancer worldwide. Over the last decade, an enormous amount of well-annotated gene and drug data has accumulated for HNC. However, a comprehensive repository is not yet available. Here, we constructed the Head and Neck Cancer Database (HNCDB:
http://hncdb.cancerbio.info
) using text mining followed by manual curation of the literature to collect reliable information on the HNC-related genes and drugs. The high-throughput gene expression data for HNC were also integrated into HNCDB. HNCDB includes the following three separate but closely related components: “HNC GENE,” “Connectivity Map,” and “ANALYSIS.” The “HNC GENE” component contains comprehensive information for the 1,173 HNC-related genes manually curated from 2,564 publications. The “Connectivity Map” includes information on the potential connections between the 176 drugs manually curated from 2,032 publications and the 1,173 HNC-related genes. The “ANALYSIS” component allows users to conduct correlation, differential expression, and survival analyses in the 2,403 samples from 78 HNC gene expression datasets. Taken together, we believe that HNCDB will be of significant benefit for the HNC community and promote further advances for precision medicine research on HNC.
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