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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 Copyright (c) 2024 Bentham Science Publishers