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NF-κB and stat3 transcription factor signatures differentiate HPV-positive and HPV-negative head and neck squamous cell carcinoma

DA. Gaykalova, JB. Manola, H. Ozawa, V. Zizkova, K. Morton, JA. Bishop, R. Sharma, C. Zhang, C. Michailidi, M. Considine, M. Tan, EJ. Fertig, PT. Hennessey, J. Ahn, WM. Koch, WH. Westra, Z. Khan, CH. Chung, MF. Ochs, JA. Califano,

. 2015 ; 137 (8) : 1879-89. [pub] 20150623

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc16000176

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.

Department of Biostatistics and Computational Biology Dana Farber Cancer Institute Boston MA

Department of Oncology Johns Hopkins Medical Institutions Baltimore MD

Department of Otolaryngology Head and Neck Surgery Johns Hopkins Medical Institutions Baltimore MD

Department of Otolaryngology Head and Neck Surgery Johns Hopkins Medical Institutions Baltimore MD Department of Oncology Johns Hopkins Medical Institutions Baltimore MD

Department of Otolaryngology Head and Neck Surgery Johns Hopkins Medical Institutions Baltimore MD Department of Pathology Johns Hopkins Medical Institutions Baltimore MD

Department of Otolaryngology Head and Neck Surgery Johns Hopkins Medical Institutions Baltimore MD Laboratory of Molecular Pathology Institute of Molecular and Translational Medicine Palacky University Olomouc Czech Republic

Department of Otolaryngology Head and Neck Surgery Johns Hopkins Medical Institutions Baltimore MD Mid Michigan Ear Nose and Throat East Lansing MI

Department of Otolaryngology Head and Neck Surgery Johns Hopkins Medical Institutions Baltimore MD Milton J Dance Head and Neck Center Greater Baltimore Medical Center Baltimore MD

Department of Otolaryngology Head and Neck Surgery Johns Hopkins Medical Institutions Baltimore MD University of Virginia Charlottesville VA

Department of Pathology Johns Hopkins Medical Institutions Baltimore MD

Division of Oncology Biostatistics Johns Hopkins Medical Institutions Baltimore MD Department of Oncology Johns Hopkins Medical Institutions Baltimore MD

Division of Oncology Biostatistics Johns Hopkins Medical Institutions Baltimore MD Department of Oncology Johns Hopkins Medical Institutions Baltimore MD Department of Mathematics and Statistics The College of New Jersey Ewing NJ

Citace poskytuje Crossref.org

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$a 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.
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