Using high-throughput analyses and the TRANSFAC database, we characterized TF signatures of head and neck squamous cell carcinoma (HNSCC) subgroups by inferential analysis of target gene expression, correcting for the effects of DNA methylation and copy number. Using this discovery pipeline, we determined that human papillomavirus-related (HPV+) and HPV- HNSCC differed significantly based on the activity levels of key TFs including AP1, STATs, NF-κB and p53. Immunohistochemical analysis confirmed that HPV- HNSCC is characterized by co-activated STAT3 and NF-κB pathways and functional studies demonstrate that this phenotype can be effectively targeted with combined anti-NF-κB and anti-STAT therapies. These discoveries correlate strongly with previous findings connecting STATs, NF-κB and AP1 in HNSCC. We identified five top-scoring pair biomarkers from STATs, NF-κB and AP1 pathways that distinguish HPV+ from HPV- HNSCC based on TF activity and validated these biomarkers on TCGA and on independent validation cohorts. We conclude that a novel approach to TF pathway analysis can provide insight into therapeutic targeting of patient subgroup for heterogeneous disease such as HNSCC. What's new? Changes in transcription factor (TF) expression contribute to genetic and epigenetic abnormalities in cancer. In order to capitalize on those changes and advance diagnostic and therapeutic strategies for cancer, researchers must first find a way to detect and quantify changes in TF activity. Here, TF activity was estimated globally in primary head and neck squamous cell carcinoma (HNSCC) using a novel inferential approach that accounted for gene silencing and loss of heterozygosity and homozygosity. Top-scoring pair biomarkers were identified and linked to human papillomavirus (HPV) status, enabling HPV+ and HPV- HNSCC to be distinguished based on TF activity.
ASJC Scopus subject areas
- Cancer Research