Regenerative Medicine
Researchers have develop an algorithm that takes the field of cell reprogramming forward, by helping to pinpoint potential errors and cancerous mutations when cells are changed from one type to another. The technique should help to advance the field of regenerative medicine dramatically.
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Cell types in the body are not fixed; cell type can be reprogrammed, or converted, to become another cell type by the addition of a unique set of cellular factors. This process was established by Shinya Yamanaka, in Nobel prize-winning work involved the reprogramming of fibroblast cells from the skin to induced pluripotent stem cells (iPS).Theoretically, stem cells can be reprogrammed for use in regenerative medicine techniques. To date the practice has not been perfected though. There are technical and safety concerns in converting cells because of the accumulation of unpredictable errors, including cancerous mutations in the reprogrammed cells.
Despite this development, determining the unique set of cellular factors that is needed to be manipulated for each cell conversion is a long and costly process that involved much trial and error. As a result, this first step of identifying the key set of cellular factors for cell conversion is the major obstacle researchers and doctors face in the field of cell reprogramming.
The researchers worked for five years to develop a computational algorithm to predict the cellular factors for cell conversions. The algorithm, called Mogrify(1), is able to predict the optimal set of cellular factors required for any given cell conversion.
Mogrify uses a network-based algorithm designed to find transcription factors that impart the most influence on changes in cellular state. This website will allow you to explore possible reprogramming experiments, different collections of transcription factors as well as the look at the changes in the regulatory network.
"One of the first clinical applications that we hope to achieve with this innovative approach would be to reprogram 'defective' cells from patients into 'functioning' healthy cells."
"Mogrify acts like a 'world atlas' for the cell and allows us to map out new territories in cell conversions in humans," explained Dr Rackham, who is from the Systems Genetics of Complex Disease Laboratory at Duke-NUS. "One of the first clinical applications that we hope to achieve with this innovative approach would be to reprogram 'defective' cells from patients into 'functioning' healthy cells, without the intermediate iPS step. These then can be re-implanted into patients, and should, in practice, effectively enable new regenerative medicine techniques."Associate Professor Enrico Petretto, co-author of the study and head of the Systems Genetics of Complex Disease Laboratory in the Centre for Computational Biology at Duke-NUS, highlighted that since Mogrify is completely data-driven, its robustness and accuracy can only continue to improve as more comprehensive data are collected and input into the framework.
"Mogrify is a game-changing method that leverages big-data and systems-biology; this will inspire new translational applications as the result of the work and expertise here at Duke-NUS," said Assoc Prof Petretto.
Mogrify is available online for other researchers and scientists. The team at Duke-NUS now plan to focus on Mogrify's application in translational medicine. Collaborative efforts between research groups within Duke-NUS are already in place to apply the algorithm to help develop treatments for specific diseases, such as cancer.
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