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1دورية أكاديمية
المؤلفون: Daemen, Anneleen, Griffith, Obi L, Heiser, Laura M, Wang, Nicholas J, Enache, Oana M, Sanborn, Zachary, Pepin, Francois, Durinck, Steffen, Korkola, James E, Griffith, Malachi, Hur, Joe S, Huh, Nam, Chung, Jongsuk, Cope, Leslie, Fackler, Mary Jo, Umbricht, Christopher, Sukumar, Saraswati, Seth, Pankaj, Sukhatme, Vikas P, Jakkula, Lakshmi R, Lu, Yiling, Mills, Gordon B, Cho, Raymond J, Collisson, Eric A, Van't Veer, Laura J, Spellman, Paul T, Gray, Joe W
المصدر: Genome biology. 16(1)
مصطلحات موضوعية: Bioinformatics, Environmental Sciences, Biological Sciences, Information and Computing Sciences
الوصف: During the type-setting of the final version of the article [1] some of the additional files were swapped. The correct files are republished in this Erratum.
وصف الملف: application/pdf
الوصول الحر: https://escholarship.org/uc/item/47h337rwTest
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2دورية أكاديمية
المؤلفون: Daemen, Anneleen, Griffith, Obi L, Heiser, Laura M, Wang, Nicholas J, Enache, Oana M, Sanborn, Zachary, Pepin, Francois, Durinck, Steffen, Korkola, James E, Griffith, Malachi, Hur, Joe S, Huh, Nam, Chung, Jongsuk, Cope, Leslie, Fackler, Mary, Umbricht, Christopher, Sukumar, Saraswati, Seth, Pankaj, Sukhatme, Vikas P, Jakkula, Lakshmi R, Lu, Yiling, Mills, Gordon B, Cho, Raymond J, Collisson, Eric A, van’t Veer, Laura J, Spellman, Paul T, Gray, Joe W
المصدر: Genome Biology. 14(10)
الوصف: Abstract Background First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. Results We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. Conclusions These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.
وصف الملف: application/pdf
الوصول الحر: https://escholarship.org/uc/item/60r9s7r2Test
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3دورية أكاديمية
المؤلفون: de Souza, Camila Ferreira, Sabedot, Thais S., Malta, Tathiane M., Stetson, Lindsay, Morozova, Olena, Sokolov, Artem, Laird, Peter W., Wiznerowicz, Maciej, Iavarone, Antonio, Snyder, James, deCarvalho, Ana, Sanborn, Zachary, McDonald, Kerrie L., Friedman, William A., Tirapelli, Daniela, Poisson, Laila, Mikkelsen, Tom, Carlotti, Carlos G., Kalkanis, Steven, Zenklusen, Jean, Salama, Sofie R., Barnholtz-Sloan, Jill S., Noushmehr, Houtan
المساهمون: São Paulo Research Foundation, Núcleo de Apoio à Pesquisa-Centro de Biologia Sistêmica Integrada, Department of Neurosurgery, Henry Ford Health System, Case Comprehensive Cancer Center, Foundation for Polish Science
المصدر: Cell Reports ; volume 23, issue 2, page 637-651 ; ISSN 2211-1247
مصطلحات موضوعية: General Biochemistry, Genetics and Molecular Biology
الإتاحة: https://doi.org/10.1016/j.celrep.2018.03.107Test
https://api.elsevier.com/content/article/PII:S2211124718304832?httpAccept=text/xmlTest
https://api.elsevier.com/content/article/PII:S2211124718304832?httpAccept=text/plainTest -
4دورية أكاديمية
المؤلفون: Wang, Nicholas J., Sanborn, Zachary, Arnett, Kelly L., Bayston, Laura J., Liao, Wilson, Proby, Charlotte M., Leigh, Irene M., Collisson, Eric A., Gordon, Patricia B., Jakkula, Lakshmi, Pennypacker, Sally, Zou, Yong, Sharma, Mimansa, North, Jeffrey P., Vemula, Swapna S., Mauro, Theodora M., Neuhaus, Isaac M., LeBoit, Philip E., Hur, Joe S., Park, Kyunghee, Huh, Nam, Kwok, Pui-Yan, Arron, Sarah T., Massion, Pierre P., Bale, Allen E., Haussler, David, Cleaver, James E., Gray, Joe W., Spellman, Paul T., South, Andrew P., Aster, Jon C., Blacklow, Stephen C., Cho, Raymond J.
المصدر: Proceedings of the National Academy of Sciences of the United States of America, 2011 Oct . 108(43), 17761-17766.
الوصول الحر: https://www.jstor.org/stable/41352591Test
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5
المؤلفون: Daemen, Anneleen, Griffith, Obi L., Heiser, Laura M., Wang, Nicholas J., Enache, Oana M., Sanborn, Zachary, Pepin, Francois, Durinck, Steffen, Korkola, James E., Griffith, Malachi, Hur, Joe S., Huh, Nam Samsung Advanced Inst. of Technology, Kyunggi-do, Chung, Jongsuk Samsung Advanced Inst. of Technology, Kyunggi-do, Cope, Leslie Johns Hopkins Univ., Baltimore, MD . Dept. of Oncology, Fackler, Mary Johns Hopkins Univ., Baltimore, MD . Dept. of Oncology, Umbricht, Christopher Johns Hopkins Univ., Baltimore, MD . Dept. of Oncology, Sukumar, Saraswati Johns Hopkins Univ., Baltimore, MD . Dept. of Oncology, Seth, Pankaj Harvard Medical School, Boston, MA . Beth Israel Deaconess Medical Center. Dept. of Medicine, Sukhatme, Vikas P. Harvard Medical School, Boston, MA . Beth Israel Deaconess Medical Center. Dept. of Medicine, Jakkula, Lakshmi R. Lawrence Berkeley National Lab. , Berkeley, CA . Life Sciences Division. Dept. of Cancer and DNA Damage Responses, Lu, Yiling MD Anderson Cancer Center, Houston, TX . Dept. of Systems Biology, Mills, Gordon B. MD Anderson Cancer Center, Houston, TX . Dept. of Systems Biology, Cho, Raymond J. Univ. of California, San Francisco, CA . Dept. of Dermatology, Collisson, Eric A. Lawrence Berkeley National Lab. , Berkeley, CA . Life Sciences Division. Dept. of Cancer and DNA Damage Responses, Univ. of California, San Francisco, CA . Lab. Medicine, van’t Veer, Laura J. Univ. of California, San Francisco, CA . Lab. Medicine, Spellman, Paul T. Lawrence Berkeley National Lab. , Berkeley, CA . Life Sciences Division. Dept. of Cancer and DNA Damage Responses, Oregon Health and Science Univ., Portland, OR . Dept. of Molecular and Medical Genetics, Gray, Joe W. Lawrence Berkeley National Lab. , Berkeley, CA . Life Sciences Division. Dept. of Cancer and DNA Damage Responses, Oregon Health and Science Univ., Portland, OR . Knight Cancer Inst. Center for Spatial Systems Biomedicine. Dept. of Biomedical Engineering
مصطلحات موضوعية: 59 BASIC BIOLOGICAL SCIENCES
الوصف: Background: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. Results: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. Conclusions: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.
وصف الملف: application/pdf
العلاقة: http://www.osti.gov/servlets/purl/1626741Test; https://www.osti.gov/biblio/1626741Test; https://doi.org/10.1186/gb-2013-14-10-r110Test
الإتاحة: https://doi.org/10.1186/gb-2013-14-10-r110Test
http://www.osti.gov/servlets/purl/1626741Test
https://www.osti.gov/biblio/1626741Test -
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المؤلفون: Daemen, Anneleen, Griffith, Obi L., Heiser, Laura M., Wang, Nicholas J., Enache, Oana M., Sanborn, Zachary, Pepin, Francois, Durinck, Steffen, Korkola, James E., Griffith, Malachi, Hur, Joe S., Huh, Nam, Chung, Jongsuk, Cope, Leslie, Fackler, Mary Jo, Umbricht, Christopher, Sukumar, Saraswati, Seth, Pankaj, Sukhatme, Vikas P., Jakkula, Lakshmi R., Lu, Yiling, Mills, Gordon B., Cho, Raymond J., Collisson, Eric A., van’t Veer, Laura J., Spellman, Paul T., Gray, Joe W.
مصطلحات موضوعية: 59 BASIC BIOLOGICAL SCIENCES
الوصف: During the type-setting of the final version of the article [1] some of the additional files were swapped. The correct files are republished in this Erratum
وصف الملف: application/pdf
العلاقة: http://www.osti.gov/servlets/purl/1629594Test; https://www.osti.gov/biblio/1629594Test; https://doi.org/10.1186/s13059-015-0658-5Test
الإتاحة: https://doi.org/10.1186/s13059-015-0658-5Test
http://www.osti.gov/servlets/purl/1629594Test
https://www.osti.gov/biblio/1629594Test -
7دورية أكاديمية
المؤلفون: Ferreira de Souza, Camila, Sabedot, Thais S., Malta, Tathiane M., Stetson, Lindsay, Morozova, Olena, Sokolov, Artem, Laird, Peter, Wiznerowicz, Maciej, Iavarone, Antonio, Snyder, James, deCarvalho, Ana, Sanborn, Zachary, McDonald, Kerrie, Friedman, William A., Tirapelli, Daniela, Poisson, Laila, Mikkelsen, Tom, Carlotti, Carlos G., Kalkanis, Steven, Zenklusen, Jean Claude, Salama, Sofie R., Barnholtz-Sloan, Jill, Noushmehr, Houtan
المصدر: SSRN Electronic Journal ; ISSN 1556-5068