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New Tools To Detect, Track And Target Cancer Cells In Vivo


技術應用

This invention  could provide a new and unique platform for drug discovery. In addition to its application in cancer drug development, the model may also allow for development of diagnostic and prognostic kits for these diseases. The model could be used to identify and screen compounds that expand stem cell populations and trigger improved regeneration in a variety of tissues.


詳細技術說明

Detection of drug resistant residual oncologic disease is a major technical challenge since the cells can hide in low numbers at any spatial location and may not always be detected in blood draws or aspirates. Residual tumor cells can lie dormant for long periods and can reinitiate tumor growth leading to disease relapse. There is no way to visualize and track cancer stem cells in vivo. Moreover, there is a critical need for the development of methods to specifically target drug resistant residual disease, and to detect cancers at earlier stages. The researcher has focused on the role of Musashi (Msi), a highly conserved RNA binding protein originally identified in drosophila, since Msi is expressed in stem and progenitor cells across many tissues, and long been used as a marker of undifferentiated cells.


其他

State Of Development

The reporter mice have been developed and tested in pancreatic cancer.  These reporters allowed functional and image based tracking of stem cell signals within cancers in vivo, revealing that Msi expression rises as premalignant lesions progress to adenocarcinoma, and that Msi reporter+ tumor cells are the key drivers of pancreatic cancer: they preferentially harbor capacity to propagate adenocarcinoma, are enriched in circulating tumor cells, and are markedly drug resistant.


Intellectual Property Info

A provisional patent application has been filed.    
    


Related Materials

Fox RG, Lytle NK, Jaquish DV, Park FD, Ito T, Bajaj J, Koechlein CS, Zimdahl B, Yano M, Kopp J, Kritzik M, Sicklick J, Sander M, Grandgenett PM, Hollingsworth MA, Shibata S, Pizzo D, Valasek M, Sasik R, Scadeng M, Okano H, Kim Y, MacLeod AR, Lowy AM, Reya T. Image-based detection and targeting of therapy resistance in pancreatic adenocarcinoma. Nature 2016 Jun 16;534(7607):407-411. doi: 10.1038/nature17988. Epub 2016 Jun 6.


Tech ID/UC Case

25763/2016-095-0


Related Cases

2016-095-0


國家/地區

美國

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