RNAi phenotype profiling of kinases identifies potential therapeutic targets in Ewing's sarcoma

Arora, Shilpi; Gonzales, Irma M.; Hagelstrom, R. Tanner; Beaudry, Christian; Choudhary, Ashish; Sima, Chao; Tibes, Raoul; Mousses, Spyro; Azorsa, David O.

doi:10.1186/1476-4598-9-218

Cited by 30 publications

(38 citation statements)

References 51 publications

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“…This procedure utilized a library of small interfering RNA (siRNA) to identify functional mediators of the cytotoxic response to chemotherapeutic agents. This HT-RNAi screen is also capable of identifying targets which, when silenced, would cause a decrease in cancer cell viability in the absence of additional therapeutics as previously reported (5). The targets identified by these types of HT-RNAi screens are referred to as Achilles’ Heel (AH) targets.…”

Section: Introductionmentioning

confidence: 69%

High-throughput RNAi Screening Identifies a Role for TNK1 in Growth and Survival of Pancreatic Cancer Cells

Henderson

Gonzales

Arora

et al. 2011

Molecular Cancer Research

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In order to identify novel targets in pancreatic cancer cells, we utilized high-throughput RNAi (HT-RNAi) to identify genes that, when silenced, would decrease viability of pancreatic cancer cells. The HT-RNAi screen involved reverse transfecting the pancreatic cancer cell line BxPC3 with a siRNA library targeting 572 kinases. From replicate screens, approximately thirty-two kinases were designated as hits, of which twenty-two kinase targets were selected for confirmation and validation. One kinase identified as a hit from this screen was tyrosine kinase non-receptor 1 (TNK1), a kinase previously identified as having tumor suppressor-like properties in embryonic stem cells. Silencing of TNK1 with siRNA showed reduced proliferation in a panel of pancreatic cancer cell lines. Furthermore, we demonstrated that silencing of TNK1 led to increased apoptosis through a caspase-dependent pathway and that targeting TNK1 with siRNA can synergize with gemcitabine treatment. Despite previous reports that TNK1 affects Ras and NFκB signaling, we did not find similar correlations with these pathways in pancreatic cancer cells. Our results suggest that TNK1 in pancreatic cancer cells does not possess the same tumor suppressor properties seen in embryonic cells, but appears to be involved in growth and survival. The application of functional genomics using HT-RNAi screens has allowed us to identify TNK1 as a growth-associated kinase in pancreatic cancer cells.

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Section: Introductionmentioning

confidence: 69%

High-throughput RNAi Screening Identifies a Role for TNK1 in Growth and Survival of Pancreatic Cancer Cells

Henderson

Gonzales

Arora

et al. 2011

Molecular Cancer Research

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“…7,12,13 Briefly, a validated siRNA library targeting 572 kinases (Kinome siRNA Library Version 1.0; QIAGEN) with 2 different siRNA sequences per kinase was printed onto 384-well plates (Fisher Scientific). Cationic lipid-based transfection reagents were diluted in Opti-MEM (Invitrogen) and added to assay plates using a Fill liquid dispenser (Bio-Tek).…”

Section: High-throughput Sirna Screensmentioning

confidence: 99%

“…We adapted a siRNAscreening platform in our laboratory 7,8,12,13 that uses transfection conditions without electroporation to myeloid suspension cells and performed the first kinome-wide siRNA-Ara-C sensitizer screen in leukemia cells. WEE-1 kinase family genes (WEE1 and PKMYT1) and CHEK1 emerged as top targets potentiating Ara-C activity.…”

Section: Introductionmentioning

confidence: 99%

RNAi screening of the kinome with cytarabine in leukemias

Tibes

Bogenberger

Chaudhuri

et al. 2012

Blood

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To identify rational therapeutic combinations with cytarabine (Ara-C), we developed a high-throughput, small-interference RNA (siRNA) platform for myeloid leukemia cells. Of 572 kinases individually silenced in combination with Ara-C, silencing of 10 (1.7%) and 8 (1.4%) kinases strongly increased Ara-C activity in TF-1 and THP-1 cells, respectively. The strongest molecular concepts emerged around kinases involved in cell-cycle checkpoints and DNA-damage repair. In confirmatory siRNA assays, inhibition of WEE1 resulted in more potent and universal sensitization across myeloid cell lines than siRNA inhibition of PKMYT1, CHEK1, or ATR. Treatment of 8 acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), and chronic myeloid leukemia (CML) cell lines with commercial and the first-in-class clinical WEE1 kinase inhibitor MK1775 confirmed sensitization to Ara-C up to 97-fold. Ex vivo, adding MK1775 substantially reduced viability in 13 of 14 AML, CML, and myelodysplastic syndrome patient samples compared with Ara-C alone. Maximum sensitization occurred at lower to moderate concentrations of both drugs. Induction of apoptosis was increased using a combination of Ara-C and MK1775 compared with using either drug alone. WEE1 is expressed in primary AML, ALL, and CML specimens. Data from this first siRNA-kinome sensitizer screen suggests that inhibiting WEE1 in combination with Ara-C is a rational combination for the treatment of myeloid and lymphoid leukemias.

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“…Compared to the first module, the second module (upper right in Figure 3(C)) is even more interesting because most of genes in this module are important for proliferation of Ewing's sarcoma cells. CDK5R2 , NEK9 , PRKCA , PXK and STK11 have significant effects on growth of cancer cells in all cancer cell lines [4]. Among these genes, CDK5R2 seems to be worth exploring as a multi-CDK inhibitor that potentially targets CDK5R2 has been studied clinically [39].…”

Section: Resultsmentioning

confidence: 99%

Posterior Association Networks and Functional Modules Inferred from Rich Phenotypes of Gene Perturbations

et al. 2012

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Combinatorial gene perturbations provide rich information for a systematic exploration of genetic interactions. Despite successful applications to bacteria and yeast, the scalability of this approach remains a major challenge for higher organisms such as humans. Here, we report a novel experimental and computational framework to efficiently address this challenge by limiting the ‘search space’ for important genetic interactions. We propose to integrate rich phenotypes of multiple single gene perturbations to robustly predict functional modules, which can subsequently be subjected to further experimental investigations such as combinatorial gene silencing. We present posterior association networks (PANs) to predict functional interactions between genes estimated using a Bayesian mixture modelling approach. The major advantage of this approach over conventional hypothesis tests is that prior knowledge can be incorporated to enhance predictive power. We demonstrate in a simulation study and on biological data, that integrating complementary information greatly improves prediction accuracy. To search for significant modules, we perform hierarchical clustering with multiscale bootstrap resampling. We demonstrate the power of the proposed methodologies in applications to Ewing's sarcoma and human adult stem cells using publicly available and custom generated data, respectively. In the former application, we identify a gene module including many confirmed and highly promising therapeutic targets. Genes in the module are also significantly overrepresented in signalling pathways that are known to be critical for proliferation of Ewing's sarcoma cells. In the latter application, we predict a functional network of chromatin factors controlling epidermal stem cell fate. Further examinations using ChIP-seq, ChIP-qPCR and RT-qPCR reveal that the basis of their genetic interactions may arise from transcriptional cross regulation. A Bioconductor package implementing PAN is freely available online at http://bioconductor.org/packages/release/bioc/html/PANR.html.

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RNAi phenotype profiling of kinases identifies potential therapeutic targets in Ewing's sarcoma

Cited by 30 publications

References 51 publications

High-throughput RNAi Screening Identifies a Role for TNK1 in Growth and Survival of Pancreatic Cancer Cells

High-throughput RNAi Screening Identifies a Role for TNK1 in Growth and Survival of Pancreatic Cancer Cells

RNAi screening of the kinome with cytarabine in leukemias

Posterior Association Networks and Functional Modules Inferred from Rich Phenotypes of Gene Perturbations

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