Identifying Biomarkers and Therapeutic Targets by Multiomic Analysis for HNSCC: Precision Medicine and Healthcare Management.
Hafeeda KunhabdullaRam ManasAshok Kumar ShettihalliCh Ram Mohan ReddyMohammed S MustakRaghu JettiRiaz AbdullaDivijendra Natha Reddy SirigiriDeden RamdanMuhammad Imam AmmarullahPublished in: ACS omega (2024)
Background: Head and neck squamous cell carcinoma (HNSCC) is one of the major types of cancer, with 900,000 cases and over 400,000 deaths annually. It constitutes 3-4% of all cancers in Europe and western countries. As early diagnosis is the key to treating the disease, reliable biomarkers play an important role in the precision medicine of HNSCC. Despite treatments, the survival rate of cancer patients remains unchanged, and this is mainly due to the failure to detect the disease early. Thus, the objective of this study is to identify reliable biomarkers for head and neck cancers for better healthcare management. Methods: In this study, all available, curated human genes were screened for their expression against HNSCC TCGA patient samples using genomic and proteomic data by various bioinformatic approaches and datamining. Docking studies were performed using AutoDock or online virtual screening tools for identifying potential ligands. Results: Sixty genes were short-listed, and most of them show a consistently higher expression in head and neck patient samples at both the mRNA and the protein level. Irrespective of human papillomavirus (HPV) status, all of them show a higher expression in cancer samples. The higher expression of 30 genes shows adverse effects on patient survival. Out of the 60 genes, 12 genes have crystal structures and druggable potential. We show that genes such as GTF2H4, HAUS7, MSN, and MNDA could be targets of Pembrolizumab and Nivolumab, which are approved monoclonal antibodies for HNSCC. Conclusion: Sixty genes are identified as potential biomarkers for head and neck cancers based on their consistent and statistically significantly higher expression in patient samples. Four proteins have been identified as potential drug targets based on their crystal structure. However, the utility of these candidate genes has to be further tested using patient samples.
Keyphrases
- poor prognosis
- genome wide
- healthcare
- case report
- bioinformatics analysis
- genome wide identification
- binding protein
- crystal structure
- endothelial cells
- dna methylation
- social media
- copy number
- genome wide analysis
- high grade
- machine learning
- squamous cell
- climate change
- south africa
- artificial intelligence
- epidermal growth factor receptor
- health insurance
- deep learning
- advanced non small cell lung cancer
- amino acid