Open Access

ARTICLE

Comprehensive bioinformatics analysis and experimental validation: An anoikis-related gene prognostic model for targeted drug development in head and neck squamous cell carcinoma

LIN QIU^1,#, ANQI TAO^1,#, XIAOQIAN SUN^4,5, FEI LIU¹, XIANPENG GE^2,3,*, CUIYING LI^1,*

1 Central Laboratory, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, 100081, China
2 Department of Dentistry, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
3 National Clinical Research Center for Geriatric Disorders, Beijing, 100101, China
4 School of Medicine, Nankai University, Tianjin, 300071, China
5 Department of Oral and Maxillofacial Surgery, Tianjin Stomatological Hospital, School of Medicine, Nankai University, Tianjin, 300041, China

* Corresponding Authors: XIANPENG GE. Email: ; CUIYING LI. Email:
# Lin Qiu and Anqi Tao have contributed equally to this work

Oncology Research 2023, 31(5), 715-752. https://doi.org/10.32604/or.2023.029443

Received 19 February 2023; Accepted 17 May 2023; Issue published 21 July 2023

Abstract

We analyzed RNA-sequencing (RNA-seq) and clinical data from head and neck squamous cell carcinoma (HNSCC) patients in The Cancer Genome Atlas (TCGA) Genomic Data Commons (GDC) portal to investigate the prognostic value of anoikis-related genes (ARGs) in HNSCC and develop new targeted drugs. Differentially expressed ARGs were screened using bioinformatics methods; subsequently, a prognostic model including three ARGs (CDKN2A, BIRC5, and PLAU) was constructed. Our results showed that the model-based risk score was a good prognostic indicator, and the potential of the three ARGs in HNSCC prognosis was validated by the TISCH database, the model’s accuracy was validated in two independent cohorts of the Gene Expression Omnibus database. Immune correlation analysis and half-maximal inhibitory concentration were also performed to reveal the different landscapes of TIME between risk groups and to predict immuno- and chemo-therapeutic responses. Potential small-molecule drugs for HNSCC were subsequently predicted using the L1000FWD database. Finally, in vitro experiments were used to verify the database findings. The relative ARG mRNA expression levels in HNSCC and surrounding normal tissues remained consistent with the model results. BIRC5 knockdown inhibited anoikis resistance in WSU-HN6 and CAL-27 cells. Molecular docking, real-time PCR, cell counting kit-8 (CCK-8), plate clone, and flow cytometry analyses showed that small-molecule drugs predicted by the database may target the ARGs in the prognostic model, inhibit HNSCC cells survival rate, and promote anoikis in vitro. Therefore, we constructed a new ARG model for HNSCC patients that can predict prognosis and immune activity and identify a potential small-molecule drug for HNSCC, paving the way for clinically targeting anoikis in HNSCC.

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