Project description:BackgroundPancreatic cancer retains a poor prognosis among the gastrointestinal cancers. It affects 230,000 individuals worldwide, has a very high mortality rate, and remains one of the most challenging malignancies to treat successfully. Treatment with gemcitabine, the most widely used chemotherapeutic against pancreatic cancer, is not curative and resistance may occur. Combinations of gemcitabine with other chemotherapeutic drugs or biological agents have resulted in limited improvement.MethodsIn order to improve gemcitabine response in pancreatic cancer cells, we utilized a synthetic lethal RNAi screen targeting 572 known kinases to identify genes that when silenced would sensitize pancreatic cancer cells to gemcitabine.ResultsResults from the RNAi screens identified several genes that, when silenced, potentiated the growth inhibitory effects of gemcitabine in pancreatic cancer cells. The greatest potentiation was shown by siRNA targeting checkpoint kinase 1 (CHK1). Validation of the screening results was performed in MIA PaCa-2 and BxPC3 pancreatic cancer cells by examining the dose response of gemcitabine treatment in the presence of either CHK1 or CHK2 siRNA. These results showed a three to ten-fold decrease in the EC50 for CHK1 siRNA-treated cells versus control siRNA-treated cells while treatment with CHK2 siRNA resulted in no change compared to controls. CHK1 was further targeted with specific small molecule inhibitors SB 218078 and PD 407824 in combination with gemcitabine. Results showed that treatment of MIA PaCa-2 cells with either of the CHK1 inhibitors SB 218078 or PD 407824 led to sensitization of the pancreatic cancer cells to gemcitabine.ConclusionThese findings demonstrate the effectiveness of synthetic lethal RNAi screening as a tool for identifying sensitizing targets to chemotherapeutic agents. These results also indicate that CHK1 could serve as a putative therapeutic target for sensitizing pancreatic cancer cells to gemcitabine.

Project description:Recent data demonstrate that extracellular signals are transmitted through a network of proteins rather than hierarchical signaling pathways. This network model suggests why inhibition of a single component of a canonical pathway, even when targeting a mutationally activated driver of cancer, has insufficiently dramatic effects on the treatment of cancer. The biological outcome of signals propagated through a network is inherently more robust and resistant to inhibition of a single network component due to compensatory and redundant signaling events. In this study, we performed a functional chemical genetic screen analogous to synthetic lethal screening in yeast genetics to identify novel interactions between signaling inhibitors that would not be predicted based on our current understanding of signaling networks. We screened over 300 drug combinations in nine melanoma cell lines and have identified pairs of compounds that show synergistic cytotoxicity. Among the most robust and surprising results was synergy between sorafenib, a multi-kinase inhibitor with activity against Raf, and diclofenac, a non-steroidal anti-inflammatory drug (NSAID). This synergy did not correlate with the known RAS and BRAF mutational status of the melanoma cell lines. The NSAIDs celecoxib and ibuprofen could qualitatively substitute for diclofenac. Similarly, the MEK inhibitor PD325901 and the Raf inhibitor RAF265 could qualitatively substitute for sorafenib. These drug substitution experiments suggest that inhibition of cyclo-oxygenase and MAP kinase signaling are components of the observed synergistic cytotoxicity. Genome-wide expression profiling demonstrates synergy-specific down-regulation of survival-related genes. This study provides proof of principle that synthetic lethal screening can uncover novel functional drug combinations and suggests that the underlying signaling networks that control responses to targeted agents can vary substantially depending on unexplored components of the cell genotype. RNA from VMM39, DM331, and SLM2 cells with/without mutations in Ras and/or Braf, treated with Sorafenib and/or Diclofenac.

Project description:Recent data demonstrate that extracellular signals are transmitted through a network of proteins rather than hierarchical signaling pathways. This network model suggests why inhibition of a single component of a canonical pathway, even when targeting a mutationally activated driver of cancer, has insufficiently dramatic effects on the treatment of cancer. The biological outcome of signals propagated through a network is inherently more robust and resistant to inhibition of a single network component due to compensatory and redundant signaling events. In this study, we performed a functional chemical genetic screen analogous to synthetic lethal screening in yeast genetics to identify novel interactions between signaling inhibitors that would not be predicted based on our current understanding of signaling networks. We screened over 300 drug combinations in nine melanoma cell lines and have identified pairs of compounds that show synergistic cytotoxicity. Among the most robust and surprising results was synergy between sorafenib, a multi-kinase inhibitor with activity against Raf, and diclofenac, a non-steroidal anti-inflammatory drug (NSAID). This synergy did not correlate with the known RAS and BRAF mutational status of the melanoma cell lines. The NSAIDs celecoxib and ibuprofen could qualitatively substitute for diclofenac. Similarly, the MEK inhibitor PD325901 and the Raf inhibitor RAF265 could qualitatively substitute for sorafenib. These drug substitution experiments suggest that inhibition of cyclo-oxygenase and MAP kinase signaling are components of the observed synergistic cytotoxicity. Genome-wide expression profiling demonstrates synergy-specific down-regulation of survival-related genes. This study provides proof of principle that synthetic lethal screening can uncover novel functional drug combinations and suggests that the underlying signaling networks that control responses to targeted agents can vary substantially depending on unexplored components of the cell genotype.

Dataset Information

Identification of unique sensitizing targets for anti-inflammatory CDDO-Me in metastatic melanoma by a large-scale synthetic lethal RNAi screening.

Publications

Identification of unique sensitizing targets for anti-inflammatory CDDO-Me in metastatic melanoma by a large-scale synthetic lethal RNAi screening.

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