NCI Grants for Cancer Research

Vanderbilt University has been awarded a five year $8.1 million grant from the National Cancer Institute https://www.cancer.gov to develop and serve as NCI’s “Cancer Systems Biology Consortium to be located at Vanderbilt.

The Vanderbilt Center will combine experimentation with mathematical modeling, computation, and machine learning, and to produce a comprehensive blueprint of the complex dynamics in small cell lung cancer that often resists treatment.

According to Dr. Vito Quaranta Professor of Biochemistry and Pharmacology in the Vanderbilt University School of Medicine  “The knowledge accumulated on small cell lung cancer is extensive. However, there has been little advance in treatment for the past half century.”

He reports, “Our multidisciplinary systems-level approach will break this log jam by looking into gene regulatory and cell-to cell communication networks to neutralize the strategies small cell lung cancer cells use to evade treatment.”

NCI is also providing $3 million for over five years to Johns Hopkins Kimmel Cancer Center and Johns Hopkins University School of Medicine https://www.hopkinsmedicine.org. The researchers are going to use computational modeling and software to understand biological data in combination with unique in-vitro and animal studies to further treat liver cancer.

The project “Integrating Bioinformatics into Multiscale Models for Hepatocellular Carcinoma” to be led by Elena Fertig PhD, is greatly needed since hepatocellular carcinoma, or liver cancer is responsible for over 12,000 deaths per year in the U.S.

The research team is going to look into new computational techniques and then build models that will be able to predict therapeutic responses to liver cancer to improve treatment. The data for the models will use information about molecules, cells, tumors, and organs learned from state-of-the-art 3D in-vitro models and in-vivo animal models of hepatocellular carcinoma. The research team hopes that new algorithms for predictive computational modeling of therapeutic response to hepatocellular carcinoma will result.

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