High-Resolution Profiling of Head and Neck Squamous Cells Carcinoma Identifies Specific Biomarkers and Expression Subtypes of Clinically Relevant Vulnerabilities
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1. | Title | Title of document | High-Resolution Profiling of Head and Neck Squamous Cells Carcinoma Identifies Specific Biomarkers and Expression Subtypes of Clinically Relevant Vulnerabilities |
2. | Creator | Author's name, affiliation, country | Yingying Zhu; Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology |
2. | Creator | Author's name, affiliation, country | Bi Peng; Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology |
2. | Creator | Author's name, affiliation, country | Xiaoxiao Luo; Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology |
2. | Creator | Author's name, affiliation, country | Wei Sun; Department of Oncology, ongji Hospital, Tongji Medical College, Huazhong University of Science and Technology |
2. | Creator | Author's name, affiliation, country | Dongbo Liu; Department of Oncology, Tongji Hospital, Tongji Medical College,, Huazhong University of Science and Technology |
2. | Creator | Author's name, affiliation, country | Na Li; Department of Medical, Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therap |
2. | Creator | Author's name, affiliation, country | Ping Qiu; Department of Marketing, Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therap |
2. | Creator | Author's name, affiliation, country | Guoxian Long; Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology |
3. | Subject | Discipline(s) | |
3. | Subject | Keyword(s) | Head and neck squamous cells carcinoma; molecular subtypes; biomarkers; genomics; proteomics; HNSC. |
4. | Description | Abstract | Background:Head and neck squamous cell carcinoma (HNSC) is the seventh most common cancer worldwide. Although there are several options for the treatment of HNSC, there is still a lack of better biomarkers to accurately predict the response to treatment and thus be more able to correctly treat the therapeutic modality. Methods:First, we typed cases from the TCGA-HNSC cohort into subtypes by a Bayesian non-negative matrix factorization (BayesNMF)-based consensus clustering approach. Subsequently, genomic and proteomic data from HNSC cell lines were integrated to identify biomarkers of response to targeted therapies and immunotherapies. Finally, associations between HNSC subtypes and CD8 T-cell-associated effector molecules, common immune checkpoint genes, were compared to assess the potential of HNSC subtypes as clinically predictive immune checkpoint blockade therapy. Results:The 500 HNSC cases from TCGA were put through a consensus clustering approach to identify six HNSC expression subtypes. In addition, subtypes with unique proteomics and dependency profiles were defined based on HNSC cell line histology and proteomics data. Subtype 4 (S4) exhibits hyperproliferative and hyperimmune properties, and S4-associated cell lines show specific vulnerability to ADAT2, EIF5AL1, and PAK2. PD-L1 and CASP1 inhibitors have therapeutic potential in S4, and we have also demonstrated that S4 is more responsive to immune checkpoint blockade therapy. Conclusion:Overall, our HNSC typing approach identified robust tumor-expressing subtypes, and data from multiple screens also revealed subtype-specific biology and vulnerabilities. These HNSC expression subtypes and their biomarkers will help develop more effective therapeutic strategies. |
5. | Publisher | Organizing agency, location | Bentham Science |
6. | Contributor | Sponsor(s) | |
7. | Date | (DD-MM-YYYY) | 01.01.2024 |
8. | Type | Status & genre | Peer-reviewed Article |
8. | Type | Type | Research Article |
9. | Format | File format | |
10. | Identifier | Uniform Resource Identifier | https://rjpbr.com/0929-8673/article/view/644506 |
10. | Identifier | Digital Object Identifier (DOI) | 10.2174/0109298673276128231031112655 |
11. | Source | Title; vol., no. (year) | Current Medicinal Chemistry; Vol 31, No 17 (2024) |
12. | Language | English=en | |
13. | Relation | Supp. Files | |
14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
15. | Rights | Copyright and permissions |
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