ORIGINAL RESEARCH article
Front. Cell Dev. Biol.
Sec. Cancer Cell Biology
Characterization of ANXA1 in chemotherapy resistance of Head and neck squamous cell carcinoma: insights from artificial intelligence and integrative bioinformatic analysis
Ling Zheng 1,2
Haiyan YANG 2
Yan CHENG 3
Binxue XIA 1
Honghui LIU 1
Hong Xiong 2
1. Southwest Medical University School of Nursing, Luzhou, China
2. Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
3. Department of emergency medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
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Abstract
Background: Head and neck squamous cell carcinoma (HNSCC) exhibit intensive chemoresistance (CR), leading to frequent recurrence and poor prognosis, yet actionable biomarkers and therapeutic options remain limited. Methods: By utilizing bulk profiles of HNSCC patients(TCGA-HNSCC cohort and GSE6631) from TCGA cohort and GEO database, we confirmed CR-associated DEGs via Limma and WGCNA frameworks. Indeed, Lasso-cox regression was utilized for construction of predictive model and identification of CR-associated hub gene in TCGA-HNSCC cohort. Besides, predictive model performance was validated in HNSCC patient bulk profile(GSE65858). Furthermore, the molecular and immune characteristics of hub gene were estimated at HNSCC patient bulk(TCGA-HNSCC cohort) and single-cell (GSE163872) levels, especially in Artificial intelligence(AI) empowered virtual cells. . Indeed, AI-driven therapeutic framework(RefLector) and molecular docking were performed for recognition of optimal therapeutic framework for the treatment of HNSCC by targeting hub gene. Finally, the cariogenic role of hub gene was evaluated at in vitro study. Results: CR-associated DEGs can guide the risk stratification of HNSCC patients.ANXA1 was identified as down-regulated malignant distributed prognostic and druggable biomarker for HNSCC patients, which was also associated with HNSCC progression. BRD-K10482608 can be considered as potential therapeutic agent for the treatment of HNSCC. Conclusion: Our study highlighted the CR in risk stratification for HNSCC patients and ANXA1 in the pathogenesis of HNSCC, which guided the personalized and precision medicine for HNSCC patients.
Summary
Keywords
artifical inteligence, artificial intelligence, chemoresistance, Head and neck squamous cell carcinoma (HNSCC), multi-omics
Received
16 December 2025
Accepted
12 January 2026
Copyright
© 2026 Zheng, YANG, CHENG, XIA, LIU and Xiong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Hong Xiong
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