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Development of a microRNA signature predicting local recurrence and overall survival after surgical resection for patients with pancreatic adenocarcinoma.

Healthcare Portfolios
Life Sciences
College
College of Medicine (COM)
Researchers
Williams, Terence
Hite, Amy
Wald, Patrick
Licensing Manager
Flammang, Ann Marie
614-292-9839
flammang.2@osu.edu

TS-038461 — A molecular tool for predicting risk of local and regional recurrence of pancreatic adenocarcinoma.

The median survival for patients with pancreatic adenocarcinoma is less than 4 months without treatment, although quick and effective treatments can increase this to 8 months. The five year survival rate is equally dismal at 8% and the disease is the fourth leading cause of cancer deaths in the Un…

The Need

The median survival for patients with pancreatic adenocarcinoma is less than 4 months without treatment, although quick and effective treatments can increase this to 8 months. The five year survival rate is equally dismal at 8% and the disease is the fourth leading cause of cancer deaths in the United States. The standard of care treatment is surgical resection, followed with chemotherapy and radiation therapy.

However, the role for radiation therapy after surgical resection is controversial, with some studies showing benefit to adding radiation, while others showing no benefit. Since radiation is a local and regional therapy targeted to the tumor bed (local) and lymphatics (regional), a tool to predict a higher risk of local recurrence would likely benefit clinicians in making the decision whether to offer radiation therapy. Current clinical prediction relies on pathologic findings, particularly if a patient has a positive surgical margin. However, better tools are needed to predict a higher risk of local and regional recurrence and thus who might benefit most from post-operative radiation.

The Technology

Dr. Terence Williams and colleagues at The Ohio State University have developed a molecular tool to predict patients at higher risk of local and regional recurrence. First, the researchers utilized the NanoString nCounter miRNA expression assay to search over 800 miRNAs using tissue collected from 93 patients. From their results, they developed a signature of four relevant and unique miRNAs using the ElasticNet statistical analysis tool. The final molecular signature incorporates expression of these miRNA, and provides a risk score to patients. Risk scores factor in expression for each of the four miRNAs and relation to local-regional controls. Higher risk scores correspond with higher recurrence and worse overall survival. Patients with an increased risk are treated with additional rounds of radiation, in an attempt to improve survival rates.

Commercial Applications

  • Personalized medicine
  • Oncological treatment protocols
  • Clinical tools

Benefits/ Advantages

  • Identifies patients with pancreatic adenocarcinoma that might benefit from additional radiation
  • Could aid in faster and more efficient treatment of local or regional recurrence of pancreatic adenocarcinoma