News Column

Regenerative medicine research tool allows researchers public access

August 29, 2014

By Jeff Hansel, Post-Bulletin, Rochester, Minn.



Aug. 29--A Mayo Clinic research team will provide open-access to a newly developed tool designed to help speed regenerative-medicine research.

Scientist Hu Li, Ph.D., and his team developed CellNet, "a free-use Internet platform that uses network biology methods to aid stem-cell engineering."

Li is a researcher in the Mayo Clinic Center for Individualized Medicine and the Department of Molecular Pharmacology and Experimental Therapeutics.

"We have a series of publications in this field and, also, we realized that there is no...accurate tool to measure these types of engineered cell types," he said. Research teams need the ability to produce cells for their research.

Often, errors occur in that process. Adjustments are made but repeated problems recur.

Li's team is providing a guide to help any team involved in regenerative-medicine research.

The Mayo CellNet platform "can be applied to almost any study and allows users to refine the engineering process," says a clinic announcement. "In the long run, it should provide a reliable shortcut to the early phases of drug development, individualized cancer therapies and pharmacogenomics."

"Based on the results, you can analyze why your cell types are not similar to the expected target cells," Li said. That will allow research teams to more-quickly refine their methods and develop the type of cell lines they must acquire prior to further research.

Cellular engineering is a growing field, Li said.

"The gold mine for this field is kind of urgent," he said. Patients who might benefit from regenerative medicine are often dealing with grave ailments, such as kidney failure, heart failure, ALS and other life-threatening ailments.

"So that's why we tried to contribute in this field," Li said.

According to Mayo, "CellNet uses 21 cell types and tissues and data from 56 published human- and mouse-engineering studies as a basis for analyzing and predicting cell fate and corresponding engineering strategies." It "reveals" when conversion to stem cells -- the kind that can be guided to develop into most any kind of tissue -- is incomplete.

In particular, the platform, so far, "is valuable in predicting success of engraftment of cancer tumors in mouse avatars for cancer and drug-development research."

CellNet is available at cellnet.hms.harvard.edu.

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Source: Post-Bulletin (Rochester, MN)


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