Abstract 6221: Tandem use of multi-omics and artificial intelligence identified novel prognostic and therapeutic biomarkers for head and neck squamous cell carcinoma

Abstract

Abstract Introduction: Head and neck squamous cell carcinoma (HNSCC) is categorized into Human Papilloma Virus positive (HPV+ve) and negative (HPV-ve) tumors, with the latter being more aggressive and displaying poor overall survival (OS). There is a need to identify aggressive biomarkers for patient stratification and improved patient care. Materials and Methods: Using the multi-omics data, including somatic mutations, copy number alterations, RNA sequencing, miRNA sequencing, and methylation from 513 HNSCC patients, we performed an integrative clustering analysis to differentiate HPV+ve and HPV-ve tumors and identify novel prognostic biomarkers for survival and treatment response. Using artificial intelligence (AI) based machine learning approach by implementing scikit-learn, we developed a model to predict the patient's OS. Results: Our clustering analysis robustly segregated HNSCC patients into HPV+ve and HPV-ve tumors. Artificial intelligence-based machine learning model identified a 30 gene signature panel specific to HPV-ve tumors precisely predicting poor OS with an accuracy of 90.5±0.8% (95% CI) and AUC of 80.2%. Furthermore, the multivariate Cox regression survival model identified 12 genes as independent prognostic biomarkers in HPV-ve tumors, including overexpression of novel genes NT5E and TRIML2. Interestingly, higher expression of NT5E and TRIML2 due to promoter hypomethylation predicted therapy resistance in 62.8% and 65.1% of HNSCC patients, respectively. The prognostic signature panel of 30 genes was further validated using three additional expression data sets (n = 450) of HNSCC. Conclusion: Our multi-omics and AI analysis revealed a novel HPV-ve molecular cluster with implications for predicting disease aggressiveness, therapeutic response, and OS in HNSCC patients. Citation Format: Ajaz A. Bhat, Tariq Masoodi, Deepika Mishra, Mayank Singh, Sabah Nisar, Sheema Hashem, Sana K. Baba, Puneet Bagga, Ravinder Reddy, Davide Bedognetti, Shahab Uddin, Wael El-Rifai, Muzafar A. Macha, Mohammad Haris. Tandem use of multi-omics and artificial intelligence identified novel prognostic and therapeutic biomarkers for head and neck squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6221.