Smad4-independent TGF-b signaling in p16-negative HNSCC

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DESCRIPTION (provided by applicant): Head and neck squamous cell carcinoma (HNSCC) is the sixth most frequent cancer worldwide, and risk factors for development include tobacco use, alcohol consumption, and human papillomavirus (HPV) infection. Patients with HPV positive (+)/p16 (+) tumors have a favorable prognosis [3-year overall survival (OS): ~80%] while patients with HPV-negative (-) tumors of similar stage, typically p16-negative (-), experience a worse OS (~50%). Consequently, there is a great need to improve the treatment and clinical response of HPV (-)/p16 (-) patients. Smad4 (or DPC4) plays a central role in transforming growth factor-beta (TGF-�) signaling. Recently, conditional Smad4 loss (Smad4-/-) in the mouse oral cavity was shown to cause spontaneous tumors with histology reminiscent of the human disease. In our preliminary investigations, Smad4 expression status was found to be differentially expressed across a panel of HNSCC cell lines and associated with epithelial-to- mesenchymal transition (EMT). Additionally, stable knockdown (KD) of Smad4 induced EMT-like phenotypes and increased invasion. After stimulation with TGF-�1, SCC25-Smad4 KD and FaDu (Smad4-null HNSCC cell line) demonstrated enhanced activation of Smad2 compared to SCC25-scramble control. We also determined Smad4 loss was evident in 14/77 (18%) tumors obtained from HNSCC patients demonstrating a significant association with p16 (-) tumors [13/53, 25% of p16 (-) vs. 1/24, 4% of p16 (+)]. As p16 positivity is a strong surrogate marker for HPV infection, the vast majority of Smad4 (-) tumors are HPV (-). Patients with Smad4 (-) tumors experienced poor survival and an increased incidence of metastasis. In this application, we propose to; 1) determine the mechanism of Smad4-independent Smad2 activation and its effect on TGF-� inhibitor sensitivity in HNSCC, and 2) determine the role of Smad4-independent Smad2 activation in the metastatic process using an in vivo orthotopic mouse model which allows for an unbiased evaluation of tumor- microenvironment interactions. Identification of novel therapeutic targets and predictive biomarkers of response will allow for appropriate patient selection in future clinical trials, and potentially impact the survival of HNSCC patients with particularly poor clinical outcome.