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Synthetic lethal screen identification of chemosensitizer loci in cancer cells.

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Title: Synthetic lethal screen identification of chemosensitizer loci in cancer cells.
Authors: Whitehurst, Angelique W., Bodemann, Brian O., Cardenas, Jessica, Ferguson, Deborah, Girard, Luc, Peyton, Michael, Minna, John D., Michnoff, Carolyn, Weihua Hao, Roth, Michael G., Xian-Jin Xie, White, Michael A.
Source: Nature. 4/12/2007, Vol. 446 Issue 7137, p815-819. 5p. 1 Chart, 3 Graphs.
Subjects: Cancer cells, Molecular pathology, Cancer, Apoptosis, RNA
Abstract: Abundant evidence suggests that a unifying principle governing the molecular pathology of cancer is the co-dependent aberrant regulation of core machinery driving proliferation and suppressing apoptosis. Anomalous proteins engaged in support of this tumorigenic regulatory environment most probably represent optimal intervention targets in a heterogeneous population of cancer cells. The advent of RNA-mediated interference (RNAi)-based functional genomics provides the opportunity to derive unbiased comprehensive collections of validated gene targets supporting critical biological systems outside the framework of preconceived notions of mechanistic relationships. We have combined a high-throughput cell-based one-well/one-gene screening platform with a genome-wide synthetic library of chemically synthesized small interfering RNAs for systematic interrogation of the molecular underpinnings of cancer cell chemoresponsiveness. NCI-H1155, a human non-small-cell lung cancer line, was employed in a paclitaxel-dependent synthetic lethal screen designed to identify gene targets that specifically reduce cell viability in the presence of otherwise sublethal concentrations of paclitaxel. Using a stringent objective statistical algorithm to reduce false discovery rates below 5%, we isolated a panel of 87 genes that represent major focal points of the autonomous response of cancer cells to the abrogation of microtubule dynamics. Here we show that several of these targets sensitize lung cancer cells to paclitaxel concentrations 1,000-fold lower than otherwise required for a significant response, and we identify mechanistic relationships between cancer-associated aberrant gene expression programmes and the basic cellular machinery required for robust mitotic progression. [ABSTRACT FROM AUTHOR]
Copyright of Nature is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: <searchLink fieldCode="AR" term="%22Whitehurst%2C+Angelique+W%2E%22">Whitehurst, Angelique W.</searchLink><br /><searchLink fieldCode="AR" term="%22Bodemann%2C+Brian+O%2E%22">Bodemann, Brian O.</searchLink><br /><searchLink fieldCode="AR" term="%22Cardenas%2C+Jessica%22">Cardenas, Jessica</searchLink><br /><searchLink fieldCode="AR" term="%22Ferguson%2C+Deborah%22">Ferguson, Deborah</searchLink><br /><searchLink fieldCode="AR" term="%22Girard%2C+Luc%22">Girard, Luc</searchLink><br /><searchLink fieldCode="AR" term="%22Peyton%2C+Michael%22">Peyton, Michael</searchLink><br /><searchLink fieldCode="AR" term="%22Minna%2C+John+D%2E%22">Minna, John D.</searchLink><br /><searchLink fieldCode="AR" term="%22Michnoff%2C+Carolyn%22">Michnoff, Carolyn</searchLink><br /><searchLink fieldCode="AR" term="%22Weihua+Hao%22">Weihua Hao</searchLink><br /><searchLink fieldCode="AR" term="%22Roth%2C+Michael+G%2E%22">Roth, Michael G.</searchLink><br /><searchLink fieldCode="AR" term="%22Xian-Jin+Xie%22">Xian-Jin Xie</searchLink><br /><searchLink fieldCode="AR" term="%22White%2C+Michael+A%2E%22">White, Michael A.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Nature%22">Nature</searchLink>. 4/12/2007, Vol. 446 Issue 7137, p815-819. 5p. 1 Chart, 3 Graphs.
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  Data: Abundant evidence suggests that a unifying principle governing the molecular pathology of cancer is the co-dependent aberrant regulation of core machinery driving proliferation and suppressing apoptosis. Anomalous proteins engaged in support of this tumorigenic regulatory environment most probably represent optimal intervention targets in a heterogeneous population of cancer cells. The advent of RNA-mediated interference (RNAi)-based functional genomics provides the opportunity to derive unbiased comprehensive collections of validated gene targets supporting critical biological systems outside the framework of preconceived notions of mechanistic relationships. We have combined a high-throughput cell-based one-well/one-gene screening platform with a genome-wide synthetic library of chemically synthesized small interfering RNAs for systematic interrogation of the molecular underpinnings of cancer cell chemoresponsiveness. NCI-H1155, a human non-small-cell lung cancer line, was employed in a paclitaxel-dependent synthetic lethal screen designed to identify gene targets that specifically reduce cell viability in the presence of otherwise sublethal concentrations of paclitaxel. Using a stringent objective statistical algorithm to reduce false discovery rates below 5%, we isolated a panel of 87 genes that represent major focal points of the autonomous response of cancer cells to the abrogation of microtubule dynamics. Here we show that several of these targets sensitize lung cancer cells to paclitaxel concentrations 1,000-fold lower than otherwise required for a significant response, and we identify mechanistic relationships between cancer-associated aberrant gene expression programmes and the basic cellular machinery required for robust mitotic progression. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Nature is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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