Abstract A26: Network integration of epigenomic data in HPV-associated head and neck cancer

Abstract

Abstract The majority of published studies investigating driver genes have focused primarily on genomic mutations which have led to novel study designs (basket trials) where patients with a rare mutation, regardless of tumor histology, are matched to a drug expected to work through the mutated pathway. This dominant focus on genomic mutations has overshadowed consideration of inclusion of epigenetic information. Epigenetic silencing of driver genes leads to various genomic alterations, including mismatch repair deficiency, altered DNA repair and loss of chromosomal stability. In human papilloma virus (HPV) positive head and neck squamous cell carcinoma (HNSCC), recent studies are beginning to establish a mechanistic role for DNA methylation with potential to impact improved survival outcomes. The purpose of this study was to illustrate network integration of epigenomic data in head and neck cancer to prioritize elements that drive biological states. Causal Networks are small hierarchical networks of regulators whose activity can be modulated by the expression of downstream target genes to enhance understanding of the effect of upstream master regulators on disease or function. To further establish the driver potential of 11 genes: C14orf162/ CCDC177, CDH8, CRMP1, ELMO1, HTR1E, MEI1, MSX2, PCDH10, PCDHB11, PITX2, SYN2 previously reported as significantly differentially methylated between HPV positive and HPV negative HNSCC tumor samples, and subsequently validated by our group in two independent sample sets, their master regulatory networks were identified utilizing Causal Network Analysis (CNA) software from Ingenuity Pathway Analysis. To reflect expected gene expression direction implied by methylation changes, the inverse of the methylation ratio from HPV positive vs. HPV negative HNSCC was used for CNA. CNA identified 23 top hierarchical networks (significant z score of absolute 2) associated with HNSCC and their corresponding master regulatory molecules characterized as transcription regulators and kinase inhibitors among others. Of the 11 target genes, 7 had representation in multiple networks; CRMP1 in 21/23, MSX2 and SYN2 in 20/23, CDH8 and PITX2 in 17/23, PCDH10 in 10/23, and ELMO1 in 5/23 networks. Of the 23 networks, 12 indicated activation and 11 inhibition by at least 4 or more of the 7 target genes. Master regulators were within 2 or 3 hops (intermediate regulators) to the target genes. CNA raised the profile of CDH8, CRMP1, ELMO1, MSX2, PCDH10, SYN2, and PITX2 (7/11 target genes) for further consideration as epigenetic drivers of HPV-associated HNSCC. Support: Komen Foundation: KG110218 Citation Format: Maria J. Worsham, Kang Mei Chen, Indrani Datta, Josena K. Stephen, Dhananjay Chitale, Tamer Ghanem, Lamont Jones, Laura Garcia-Rodriquez, George Divine. Network integration of epigenomic data in HPV-associated head and neck cancer [abstract]. In: Proceedings of the AACR International Conference: New Frontiers in Cancer Research; 2017 Jan 18-22; Cape Town, South Africa. Philadelphia (PA): AACR; Cancer Res 2017;77(22 Suppl):Abstract nr A26.