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dc.contributor.author Salter, KH
dc.contributor.author Acharya, CR
dc.contributor.author Walters, KS
dc.contributor.author Redman, R
dc.contributor.author Anguiano, A
dc.contributor.author Garman, KS
dc.contributor.author Anders, CK
dc.contributor.author Mukherjee, S
dc.contributor.author Dressman, HK
dc.contributor.author Barry, WT
dc.contributor.author Marcom, KP
dc.contributor.author Olson, J
dc.contributor.author Nevins, JR
dc.contributor.author Potti, A
dc.coverage.spatial United States
dc.date.accessioned 2011-06-21T17:31:23Z
dc.date.issued 2008-04-02
dc.identifier http://www.ncbi.nlm.nih.gov/pubmed/18382681
dc.identifier.citation PLoS One, 2008, 3 (4), pp. e1908 - ?
dc.identifier.uri http://hdl.handle.net/10161/4486
dc.description.abstract BACKGROUND: A major challenge in oncology is the selection of the most effective chemotherapeutic agents for individual patients, while the administration of ineffective chemotherapy increases mortality and decreases quality of life in cancer patients. This emphasizes the need to evaluate every patient's probability of responding to each chemotherapeutic agent and limiting the agents used to those most likely to be effective. METHODS AND RESULTS: Using gene expression data on the NCI-60 and corresponding drug sensitivity, mRNA and microRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel, 5-fluorouracil, adriamycin, and cyclophosphamide) chemotherapy regimen. To further dissect the biology of resistance, we applied signatures of oncogenic pathway activation and performed hierarchical clustering. We then used mRNA signatures of chemotherapy sensitivity to identify alternative therapeutics for patients resistant to TFAC. Profiles from mRNA and microRNA expression data represent distinct biologic mechanisms of resistance to common cytotoxic agents. The individual mRNA signatures were validated in an independent dataset of breast tumors (P = 0.002, NPV = 82%). When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was found to be greater in basal-like than non basal-like patients (P = 0.03 and P = 0.06). Samples from patients with co-activated Myc and E2F represented the cohort with the lowest percentage (8%) of responders. Using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04), representing a viable alternative therapy. CONCLUSIONS: Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding microRNA and mRNA expression profiles. Importantly, we also present evidence to support the concept that analysis of molecular variables can present a rational strategy to identifying alternative therapeutic opportunities.
dc.format.extent e1908 - ?
dc.language eng
dc.language.iso en_US en_US
dc.relation.ispartof PLoS One
dc.relation.isversionof 10.1371/journal.pone.0001908
dc.subject Antineoplastic Agents
dc.subject Antineoplastic Combined Chemotherapy Protocols
dc.subject Breast Neoplasms
dc.subject Cell Line, Tumor
dc.subject Cyclophosphamide
dc.subject Doxorubicin
dc.subject Drug Screening Assays, Antitumor
dc.subject Fluorouracil
dc.subject Humans
dc.subject Medical Oncology
dc.subject MicroRNAs
dc.subject Paclitaxel
dc.subject RNA, Messenger
dc.subject Treatment Outcome
dc.title An integrated approach to the prediction of chemotherapeutic response in patients with breast cancer.
dc.title.alternative en_US
dc.type Journal Article
dc.description.version Version of Record en_US
duke.date.pubdate 2008-4-2 en_US
duke.description.endpage e1908 en_US
duke.description.issue 4 en_US
duke.description.startpage e1908 en_US
duke.description.volume 3 en_US
dc.relation.journal Plos One en_US
pubs.author-url http://www.ncbi.nlm.nih.gov/pubmed/18382681
pubs.issue 4
pubs.organisational-group /Duke
pubs.organisational-group /Duke/Faculty
pubs.organisational-group /Duke/School of Medicine
pubs.organisational-group /Duke/School of Medicine/Basic Science Departments
pubs.organisational-group /Duke/School of Medicine/Basic Science Departments/Molecular Genetics and Microbiology
pubs.organisational-group /Duke/School of Medicine/Clinical Science Departments
pubs.organisational-group /Duke/School of Medicine/Clinical Science Departments/Medicine
pubs.organisational-group /Duke/School of Medicine/Clinical Science Departments/Medicine/Medicine, Gastroenterology
pubs.organisational-group /Duke/School of Medicine/Clinical Science Departments/Medicine/Medicine, Medical Oncology
pubs.organisational-group /Duke/School of Medicine/Institutes and Centers
pubs.organisational-group /Duke/School of Medicine/Institutes and Centers/Duke Cancer Institute
pubs.publication-status Published online
pubs.volume 3
dc.identifier.eissn 1932-6203

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