Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8362258 | Seminars in Cancer Biology | 2015 | 9 Pages |
Abstract
This framework represents the logics of complex cancer biology as a myriad of phenotypic complexities governed by a limited set of underlying organizing principles. It therefore adds to our understanding of tumor evolution and tumorigenesis, and moreover, potential usefulness of predicting tumors' evolutionary paths and clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for cancer patients, as well as cancer risks for healthy individuals are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial impact on timely diagnosis, personalized treatment and personalized prevention of cancer.
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Authors
Edwin Wang, Naif Zaman, Shauna Mcgee, Jean-Sébastien Milanese, Ali Masoudi-Nejad, Maureen O'Connor-McCourt,