Integrated analysis of breast cancer cell lines reveals unique signaling pathways Export

@article{citeulike:4219545, abstract = {BACKGROUND:Cancer is a heterogeneous disease resulting from the accumulation of genetic defects that negatively impact control of cell division, motility, adhesion and apoptosis. Deregulation in signaling along the EgfR-MAPK pathway is common in breast cancer, though the manner in which deregulation occurs varies between both individuals and cancer subtypes.RESULTS:We were interested in identifying subnetworks within the EgfR-MAPK pathway that are similarly deregulated across subsets of breast cancers. To that end, we mapped genomic, transcriptional and proteomic profiles for 30 breast cancer cell lines onto a curated Pathway Logic symbolic systems model of EgfR-MAPK signaling. This model was composed of 539 molecular states and 396 rules governing signaling between active states. We analyzed these models and identified several subtype-specific subnetworks, including one that suggested Pak1 is particularly important in regulating the MAPK cascade when it is over-expressed. We hypothesized that Pak1 over-expressing cell lines would have increased sensitivity to Mek inhibitors. We tested this experimentally by measuring quantitative responses of 20 breast cancer cell lines to three Mek inhibitors. We found that Pak1 over-expressing luminal breast cancer cell lines are significantly more sensitive to Mek inhibition compared to those that express Pak1 at low levels. This indicates that Pak1 over-expression may be a useful clinical marker to identify patient populations that may be sensitive to Mek inhibitors.CONCLUSIONS:All together, our results support the utility of symbolic system biology models for identification of therapeutic approaches that will be effective against breast cancer subsets.}, author = {Heiser, Laura and Wang, Nicholas and Talcott, Carolyn and Laderoute, Keith and Knapp, Merrill and Guan, Yinghui and Hu, Zhi and Ziyad, Safiyyah and Weber, Barbara and Laquerre, Sylvie and Jackson, Jeffrey and Wooster, Richard and Kuo, Wen and Gray, Joe and Spellman, Paul}, citeulike-article-id = {4219545}, citeulike-linkout-0 = {http://dx.doi.org/10.1186/gb-2009-10-3-r31}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/19317917}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=19317917}, day = {25}, doi = {10.1186/gb-2009-10-3-r31}, issn = {1465-6906}, journal = {Genome Biology}, keywords = {breast\_cancer, cell\_line, network, subtypes}, month = {March}, number = {3}, pages = {R31+}, posted-at = {2009-11-09 13:31:09}, priority = {2}, title = {Integrated analysis of breast cancer cell lines reveals unique signaling pathways}, url = {http://dx.doi.org/10.1186/gb-2009-10-3-r31}, volume = {10}, year = {2009} }

TY - JOUR ID - citeulike:4219545 L3 - citeulike-article-id:4219545 N2 - BACKGROUND:Cancer is a heterogeneous disease resulting from the accumulation of genetic defects that negatively impact control of cell division, motility, adhesion and apoptosis. Deregulation in signaling along the EgfR-MAPK pathway is common in breast cancer, though the manner in which deregulation occurs varies between both individuals and cancer subtypes.RESULTS:We were interested in identifying subnetworks within the EgfR-MAPK pathway that are similarly deregulated across subsets of breast cancers. To that end, we mapped genomic, transcriptional and proteomic profiles for 30 breast cancer cell lines onto a curated Pathway Logic symbolic systems model of EgfR-MAPK signaling. This model was composed of 539 molecular states and 396 rules governing signaling between active states. We analyzed these models and identified several subtype-specific subnetworks, including one that suggested Pak1 is particularly important in regulating the MAPK cascade when it is over-expressed. We hypothesized that Pak1 over-expressing cell lines would have increased sensitivity to Mek inhibitors. We tested this experimentally by measuring quantitative responses of 20 breast cancer cell lines to three Mek inhibitors. We found that Pak1 over-expressing luminal breast cancer cell lines are significantly more sensitive to Mek inhibition compared to those that express Pak1 at low levels. This indicates that Pak1 over-expression may be a useful clinical marker to identify patient populations that may be sensitive to Mek inhibitors.CONCLUSIONS:All together, our results support the utility of symbolic system biology models for identification of therapeutic approaches that will be effective against breast cancer subsets. IS - 3 JF - Genome Biology SN - 1465-6906 TI - Integrated analysis of breast cancer cell lines reveals unique signaling pathways VL - 10 SP - R31 KW - breast_cancer KW - cell_line KW - network KW - subtypes AU - Heiser, Laura AU - Wang, Nicholas AU - Talcott, Carolyn AU - Laderoute, Keith AU - Knapp, Merrill AU - Guan, Yinghui AU - Hu, Zhi AU - Ziyad, Safiyyah AU - Weber, Barbara AU - Laquerre, Sylvie AU - Jackson, Jeffrey AU - Wooster, Richard AU - Kuo, Wen AU - Gray, Joe AU - Spellman, Paul PY - 2009/03/25/ UR - http://dx.doi.org/10.1186/gb-2009-10-3-r31 ER -