Exploring salivary gene expression clusters: A bioinformatics approach for advanced diagnosis and prognosis in head and neck squamous cell carcinoma
Objective: This study postulates that distinct patterns in salivary gene expression clusters among HNSCC patients provide valuable insights into diagnostic and prognostic markers for the disease. The aim is to identify critical genes and their protein-protein interactions through bio-computational a...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-06-01
|
| Series: | Oral Oncology Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772906024001468 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841553777004380160 |
|---|---|
| author | Rajesh Parsanathan Rishaba Byju D.S. Prabakaran |
| author_facet | Rajesh Parsanathan Rishaba Byju D.S. Prabakaran |
| author_sort | Rajesh Parsanathan |
| collection | DOAJ |
| description | Objective: This study postulates that distinct patterns in salivary gene expression clusters among HNSCC patients provide valuable insights into diagnostic and prognostic markers for the disease. The aim is to identify critical genes and their protein-protein interactions through bio-computational analyses, contributing to a deeper understanding of HNSCC progression. Ultimately, the hypothesis anticipates the discovery of novel molecular signatures in saliva, potentially enhancing early detection and prognostic precision in head and neck squamous cell carcinoma. Materials and methods: A comprehensive keyword search was conducted to extract 74 salivary gland secretion genes from the Human Protein Atlas. GeneMANIA and STRING databases were employed to analyse protein-protein interactions and predict functional partners. UALCAN facilitated the visualization of salivary gland secretion gene expression patterns in HNSCC, providing insights into survival analysis. Results: In HNSCC compared to normal tissue, CHRM3, GYLTL1B, MMP3, and WDR91 were identified as statistically upregulated genes, while the downregulated genes included AGFG2, CCDC64B, CD24, CRISP3, CXCL17, ELF5, KRT7, MANSC1, MYO5C, PRR4, SCGB3A1, SH3YL1, TCN1, TRPV6, and ZG16B. Kaplan–Meier survival curve analysis revealed that high expression of salivary genes such as AGFG2, AMY1A, CCDC64B, CCL28, C4ORF7, GYLTL1B, TMEM211, LMX1B, ODAM, SCGB3A1, and SLC26A9 was significantly associated with poorer overall survival outcomes in HNSCC patients. Conclusion: This study identifies distinct salivary gene expression patterns in HNSCC, highlighting potential diagnostic and prognostic markers. Specific upregulated genes, such as CHRM3 and GYLTL1B, and downregulated genes, including AGFG2 and CCDC64B, offer insights into HNSCC progression. Elevated expression of particular genes correlates with poorer overall survival, emphasising their prognostic significance. |
| format | Article |
| id | doaj-art-d786bfb28f1148f0a82009c86ab99081 |
| institution | Kabale University |
| issn | 2772-9060 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Oral Oncology Reports |
| spelling | doaj-art-d786bfb28f1148f0a82009c86ab990812025-01-09T06:15:43ZengElsevierOral Oncology Reports2772-90602024-06-0110100300Exploring salivary gene expression clusters: A bioinformatics approach for advanced diagnosis and prognosis in head and neck squamous cell carcinomaRajesh Parsanathan0Rishaba Byju1D.S. Prabakaran2Department of Biotechnology, School of Integrative Biology, Central University of Tamil Nadu, Neelakudi, Thiruvarur, 610005, Tamil Nadu, India; Corresponding author. Department of Biotechnology, School of Integrative Biology, Central University of Tamil Nadu, Neelakudi, Thiruvarur, 610005, Tamil Nadu, India.Department of Biotechnology, School of Integrative Biology, Central University of Tamil Nadu, Neelakudi, Thiruvarur, 610005, Tamil Nadu, IndiaDepartment of Radiation Oncology, College of Medicine, Chungbuk National University Hospital, Chungdae-ro-1, Seowon-gu, Cheongju, Chungbuk, 28644, Republic of KoreaObjective: This study postulates that distinct patterns in salivary gene expression clusters among HNSCC patients provide valuable insights into diagnostic and prognostic markers for the disease. The aim is to identify critical genes and their protein-protein interactions through bio-computational analyses, contributing to a deeper understanding of HNSCC progression. Ultimately, the hypothesis anticipates the discovery of novel molecular signatures in saliva, potentially enhancing early detection and prognostic precision in head and neck squamous cell carcinoma. Materials and methods: A comprehensive keyword search was conducted to extract 74 salivary gland secretion genes from the Human Protein Atlas. GeneMANIA and STRING databases were employed to analyse protein-protein interactions and predict functional partners. UALCAN facilitated the visualization of salivary gland secretion gene expression patterns in HNSCC, providing insights into survival analysis. Results: In HNSCC compared to normal tissue, CHRM3, GYLTL1B, MMP3, and WDR91 were identified as statistically upregulated genes, while the downregulated genes included AGFG2, CCDC64B, CD24, CRISP3, CXCL17, ELF5, KRT7, MANSC1, MYO5C, PRR4, SCGB3A1, SH3YL1, TCN1, TRPV6, and ZG16B. Kaplan–Meier survival curve analysis revealed that high expression of salivary genes such as AGFG2, AMY1A, CCDC64B, CCL28, C4ORF7, GYLTL1B, TMEM211, LMX1B, ODAM, SCGB3A1, and SLC26A9 was significantly associated with poorer overall survival outcomes in HNSCC patients. Conclusion: This study identifies distinct salivary gene expression patterns in HNSCC, highlighting potential diagnostic and prognostic markers. Specific upregulated genes, such as CHRM3 and GYLTL1B, and downregulated genes, including AGFG2 and CCDC64B, offer insights into HNSCC progression. Elevated expression of particular genes correlates with poorer overall survival, emphasising their prognostic significance.http://www.sciencedirect.com/science/article/pii/S2772906024001468HNSCCHead and neck squamous cell carcinomaSalivary biomarkersSalivary genesEarly diagnosisPrognostic markers |
| spellingShingle | Rajesh Parsanathan Rishaba Byju D.S. Prabakaran Exploring salivary gene expression clusters: A bioinformatics approach for advanced diagnosis and prognosis in head and neck squamous cell carcinoma Oral Oncology Reports HNSCC Head and neck squamous cell carcinoma Salivary biomarkers Salivary genes Early diagnosis Prognostic markers |
| title | Exploring salivary gene expression clusters: A bioinformatics approach for advanced diagnosis and prognosis in head and neck squamous cell carcinoma |
| title_full | Exploring salivary gene expression clusters: A bioinformatics approach for advanced diagnosis and prognosis in head and neck squamous cell carcinoma |
| title_fullStr | Exploring salivary gene expression clusters: A bioinformatics approach for advanced diagnosis and prognosis in head and neck squamous cell carcinoma |
| title_full_unstemmed | Exploring salivary gene expression clusters: A bioinformatics approach for advanced diagnosis and prognosis in head and neck squamous cell carcinoma |
| title_short | Exploring salivary gene expression clusters: A bioinformatics approach for advanced diagnosis and prognosis in head and neck squamous cell carcinoma |
| title_sort | exploring salivary gene expression clusters a bioinformatics approach for advanced diagnosis and prognosis in head and neck squamous cell carcinoma |
| topic | HNSCC Head and neck squamous cell carcinoma Salivary biomarkers Salivary genes Early diagnosis Prognostic markers |
| url | http://www.sciencedirect.com/science/article/pii/S2772906024001468 |
| work_keys_str_mv | AT rajeshparsanathan exploringsalivarygeneexpressionclustersabioinformaticsapproachforadvanceddiagnosisandprognosisinheadandnecksquamouscellcarcinoma AT rishababyju exploringsalivarygeneexpressionclustersabioinformaticsapproachforadvanceddiagnosisandprognosisinheadandnecksquamouscellcarcinoma AT dsprabakaran exploringsalivarygeneexpressionclustersabioinformaticsapproachforadvanceddiagnosisandprognosisinheadandnecksquamouscellcarcinoma |