Fred Hutchinson Cancer Research Center – 1

Genetic Disruption of CTCF Destabilizes DNA Methylation

The CTD² Center at the Fred Hutchinson Cancer Research Center identified the DNA binding protein CTCF as a tumor suppressor and regulator of DNA methylation.

Functional Landscape of the Human Kinome in MYCN Amplified and Non-amplified Neuroblastoma

In order to identify candidate drugs targets that exhibit lethality only in the context of MYCN amplification, we carried out a set of siRNA screens focused on the kinome, targeting ~713 kinases, utilizing human neuroblastoma cells lines with or without MYCN amplification. The neuroblastoma cell lines were: SK-N-BE2 (MYCN amplified) and SK-N-AS (non-amplified). The kinase Hits for the MYCN amplified cell line were selected using a combination of their differential activity when compared to the non-MYCN amplified cells and also ranked by P-values, based on the replicates.

Experimental Approaches

Cells

Neuroblastoma cell lines, SK-N-BE2 (MYCN-amplified) and SK-N-AS (non-amplified) were obtained from the American Tissue Type Collection (ATCC) and cultured in RPMI with 10% FBS and Penicillin and Streptomycin at the concentration recommended.  25mM HEPES was added during the screens to minimize variation of pH during handling of the plates.

High-throughput siRNA transfections

Transfection feasibility for each cell line was established using a factorial-based optimization scheme with variable parameters in cell density, liposomal, and siRNA concentration. All transfection conditions were statistically evaluated using a simple Z-factor score to determine differentials between mock-transfected cells (transfection reagent only) versus a positive control for growth inhibition (KIF11) and a negative control (non-targeting siRNA).  Based on these preliminary experiments performed on each cell line, the optimal transfection condition selected for each cell line was: 1)SK-N-BE2, cells were seeded at 1600 cells/well in 384 well. The next day 5 μl of Dharmafect I (18.75 μl/ml) and siRNA (2.5 pM/well) mix was added and viability with CellTiter-Glo was read at 96 hr after plating; 2)SK-N-AS: seeded at 2000 cells/well and the next day 5 μl of Dharmafect I (18.75 μl/ml) and siRNA (2.5 pM/well) mix was added and viability with CellTiter-Glo was read at 96 hr after plating. The siRNA library targeting the human kinome (~713 kinases) was tested in triplicates to establish experimental variability and statistical validity.  A detailed description of the method is available in the supplementary information by Toyoshima et al [Toyoshima, 2012 #4918].

siRNA Library

The siRNA library targeting 713 human (MISSION® siRNA Human Gene Family Set, Sigma) was tested with viability as the phenotypic endpoint.  Cell viability was quantified using an Envision Multilabel detector/plate reader (PerkinElmer) with the CellTiter-Glo assay (Promega) that measures ATP concentrations in cell lysates.  siRNA libraries utilized pools of 3 independent siRNAs targeting each gene, in a one gene per well approach. RNAi screens were performed in 384-well format in triplicate, in independent plates, utilizing robotics instrumentation available at the University of Washington - Quellos facility.

Identification of Drug Targets for Combination Therapy with Retinoic Acid in Neuroblastoma

Retinoic Acid (RA) is employed in the clinic during the “consolidation” phase of treatment regimens for high-risk neuroblastoma.  While the addition of RA has greatly increased the survival of children with neuroblastoma, there is still a high frequency of relapse.  With the goal of identifying novel drug combinations that would enhance the effect of RA on neuroblastoma, an siRNA screen in the presence or absence of sub-lethal concentrations of RA was carried out. For this project, three neuroblastoma cell lines were selected based on their sensitivity to RA: 1) SY-5Y, a non-MYCN amplified line with high sensitivity to RA; 2) SK-N-BE2, intermediate sensitivity to RA; 3) SK-N-AS, a cell line insensitive to the effect of RA.  The siRNA library was a kinase targeting library as described for the previous screen (0001_NB_kinome).  The Hits from each cell line were determined based on their significance with respect to their differential activity in the presence or absence of RA within each cell line and also ranked on P-value, based the three replicates.

Experimental Approaches

Cells and Retinoic Acid

SY-5Y, SK-N-BE2 and SK-N-AS were obtained from the American Tissue Type Collection (ATCC) and cultured in RPMI with 10% FBS and Penicillin and Streptomycin at the concentration recommended.  25mM HEPES was added during the screens to minimize variation of pH during handling of the plates. Retinoic Acid (RA) was used at 5μM, which is half the optimal concentration used in vitro to obtain differentiation of most NB cell lines, and which is comparable to half of the therapeutic concentration achieved in vivo.

High-throughput siRNA transfections

Transfection feasibility for each cell line was established using a factorial-based optimization scheme with variable parameters in cell density, liposomal, and siRNA concentration. All transfection conditions were statistically evaluated using a simple Z-factor score to determine differentials between mock-transfected cell (transfection reagent only) versus a positive control for growth inhibition (KIF11) and a negative control (non-targeting siRNA).  Based on these preliminary experiments performed on each cell line, the optimal transfection condition was selected as the following for all the cell lines: cells were seeded at 500 cells/well; the next day 2.5 μl of Dharmafect I (6.25 μl/ml) and siRNA (1.25 pM/well) mix was added and viability with CellTiter-Glo was read at 96 hrs for SK-N-BE2 and SK-N-AS and 120 hr for SY-5Y cells, after plating. The siRNA library targeting the human kinome (~713 kinases) was tested in triplicates to establish experimental variability and statistical validity.  A detailed description of the method is available in the supplementary information by Toyoshima et al.

siRNA Library

A Kinome-wide siRNA library targeting 713 human (MISSION® siRNA Human Gene Family Set, Sigma) were tested with viability as the phenotypic endpoint. Cell viability was quantified using an Envision Multilabel detector/plate reader (PerkinElmer) with the CellTiter-Glo assay (Promega) that measures ATP concentrations in cell lysates.  siRNA libraries utilized pools of 3 independent siRNAs targeting each gene, in a one gene per well approach. RNAi screens were performed in 384-well format in triplicate, in independent plates, utilizing robotics instrumentation available at the University of Washington - Quellos facility.

Functional Exploration of the Druggable Genome in MYCN Amplified and Non-amplified Neuroblastoma

To identify candidate drugs targets for neuroblastoma with MYCN amplification we performed parallel siRNA screens with a druggable genome collection of ~6,700 genes comparing MYCN amplified and non-MYCN amplified cell lines: SK-N-BE2 (MYCN amplified) and SK-N-AS (non amplified). The Hits from each cell lines were determined based on their significance with respect to their differential activity in the presence or absence of RA within each cell line. Hits for each cell line were also ranked according to their P-value, based on the three replicates. Integration with gene expression data from several databases also allowed us to pinpoint genes whose expression is selective for MYCN amplified neuroblastoma (this analysis was carried out in collaboration with the CTD² group at Columbia University, led by Dr. Califano).

Experimental Methods

Cells

Neuroblastoma cell lines, SK-N-BE2 (MYCN-amplified) and SK-N-AS (non-amplified) were obtained from the American Tissue Type Collection (ATCC) and cultured in RPMI with 10% FBS and Penicillin and Streptomycin at the concentration recommended. 25mM HEPES was added during the screens to minimize variation of pH during handling of the plates.

High-throughput siRNA transfections

Transfection feasibility for each cell line was established using a factorial-based optimization scheme with variable parameters in cell density, liposomal, and siRNA concentration. All transfection conditions were statistically evaluated using a simple Z-factor score to determine differentials between mock-transfected cell (transfection reagent only) versus a positive control for growth inhibition (KIF11) and a negative control (non-targeting siRNA).  Based on these preliminary experiments, the optimal transfection condition was selected for each cell line as following: cells were seeded at 500 cells/well; the next day 2.5 μl of Dharmafect I (6.25 μl/ml) and siRNA (1.25 pM/well) mix was added and viability with CellTiter-Glo was read at 96 hrs. The siRNA library targeting the druggable genome (~6,700 genes) was tested in triplicates to establish experimental variability and statistical validity. A detailed description of the method is available in the supplementary information by Toyoshima et al.

siRNA Library

The siRNA library targeting the druggable genome (MISSION® siRNA Human Druggable Genome, Sigma) was tested with viability as the phenotypic endpoint. Cell viability was quantified using an Envision Multilabel detector/plate reader (PerkinElmer) with the CellTiter-Glo assay (Promega) that measures ATP concentrations in cell lysates. siRNA libraries utilized pools of 3 independent siRNAs targeting each gene, in a one gene per well approach. RNAi screens were performed in 384-well format in triplicate, in independent plates, utilizing robotics instrumentation available at the University of Washington-Quellos facility.

Identification of Candidate Therapeutic Targets in Head and Neck Cancer Using Functional Kinomics

Kinome-wide siRNA screens targeting 713 human (MISSION® siRNA Human Gene Family Set, Sigma) were performed with viability as the phenotypic endpoint on five HNSCC lines: JHU-019; PCI15A and 15B; UM-SCC14A and 14C.

Experimental Approaches

siRNA libraries were constructed and utilized in pools of 3 independent siRNAs targeting each gene, in a one gene per well approach. RNAi screens were performed in 384-well format utilizing robotics instrumentation available at the University of Washington-Quellos facility. Transfection feasibility of each cell line was established using a factorial optimization. Mock condition and a non-targeting universal siRNA control were utilized as negative controls, while a siRNA directed at KIF11 (kinesin-like protein), which arrests cells in mitosis was utilized as a positive control.

All reagent conditions were statistically evaluated using a simple Z-factor score to evaluate differentials and variability of replicates (i.e. potent cell killing with KIF11 at the lowest toxicity possible in the mock universal controls) to select an optimized transfection condition for each cell line. All kinases were tested in triplicate to establish experimental variability and statistical validity. Scrambled siRNA negative controls were used to monitor dynamic range and off-target effects and the results were standardized to mock-transfected cells.

Kinome-wide siRNA Screens (screen 1) to Discover Novel Vulnerabilities in Ras/Tp53 Mutant Murine Squamous Cell Carcinomas

Kinome-wide siRNA screens were performed on five low passage murine squamous cell carcinoma (MSCC) cell lines with mutations in Ras and the p53 tumor suppressor pathway to identify kinase targets important in Ras-driven tumor progression. 

Experimental Approaches

Cells: Murine squamous cell carcinoma (MSCC) cells were derived from NIH/Ola strain mice with germline mutations in p53 pathway genes and included MSCC-CK101 (Hras^Q61L Trp53^+/+), MSCC-CK102 (Hras^Q61L Trp53 ^+/-), MSCC-CK103 (Hras wt p19Arf ^-/-), MSCC-CK104 (KrasG^13R Atm^-/-)^1,2. MSCC-CK105 (Hras^Q61L Prkdc^mu/mu) cells were from SCID mutant mice of a mixed C3H/Balb/c background³. Mouse SCC lines were derived from DMBA/TPA-induced SCC using a standard outgrowth explant method.

siRNA Library: Ambion murine kinome siRNA library contains three siRNAs per gene targeting 571 murine kinase genes. The Ambion murine kinome siRNA working library was constructed and arrayed in a 384-well format with pools of 3 independent siRNAs targeting each gene, in a one gene per well approach (Ambion Murine Kinome Library-Table S4⁴.

Doxorubicin Modifier: Doxorubicin dose-response curves were generated on all 5 MSCC cell lines and IC₃₀ and IC₆₀ values were determined for each cell line. Each MSCC cell line siRNA screen was performed in parallel with vehicle and doxorubicin modifier at IC₃₀ and IC₆₀ concentrations.

High-throughput siRNA transfections: Kinome-wide siRNA screens were performed with viability as the phenotypic endpoint using a set of 5 low passage murine squamous cell carcinoma (MSCC) cells. MSCC cells were plated in 384-well plates in 50 μl per well of complete medium using a WellMate (Matrix Technologies, Canada) and transfected with siRNAs 24 hours later using Dharmafect1 Reagent (GE Dharmacon, USA), with three siRNAs targeting the same gene pooled at equal molarities. The siRNA library was tested in triplicate to establish experimental variability and statistical validity. Cells were treated with vehicle or with doxorubicin at IC₃₀ and IC₆₀ concentrations for 24 hours following transfection, and the plates were incubated at 37°C in a 5% CO₂ incubator for ~60 hours.  Cell viability was assessed by CellTiter-Glo assay (Promega, WI, USA), and luminescence was quantified using an Envision multilabel plate reader (PerkinElmer Life Sciences, MA, USA).  Raw luminescence values were mock normalized per plate and plotted for distribution and data mining using a negative control siRNA (non-targeting siRNA) and a positive control siRNA targeting the kinesin motor protein (Kif11). A detailed description of methods is available in Moser⁴ et al., Birmingham⁵ et al., and Cheung⁶ et al.

References

1. Kelly-Spratt KS, et al. p19Arf suppresses growth, progression, and metastasis of Hras-driven carcinomas through p53-dependent and -independent pathways. PLoS Biol. 2004 Aug; 2(8):E242 (PMID: 15314658)
2. Kemp CJ, et al. Reduction of p53 gene dosage does not increase initiation or promotion but enhances malignant progression of chemically induced skin tumors. Cell. 1993 Sep 10;74(5):813-22 (PMID: 8374952)
3. Kemp CJ, et al. Resistance to skin tumorigenesis in DNAPK-deficient SCID mice is not due to immunodeficiency but results from hypersensitivity to TPA-induced apoptosis. Carcinogenesis. 1999 Nov;20(11):2051-6 (PMID: 10545405)
4. Moser R, et al. Functional kinomics identifies candidate therapeutic targets in head and neck cancer. Clin Cancer Res. 2014 Aug 15;20(16):4274-88 (PMID: 25125259)
5. Birmingham A, et al. Statistical methods for analysis of high-throughput RNA interference screens. Nat Methods. 2009 Aug;6(8):569-75 (PMID: 19644458)
6. Chung N, et al. Median absolute deviation to improve hit selection for genome scale RNAi screens. J Biomol Screen. 2008 Feb;13(2):149-58 (PMID: 18216396)

Functional Exploration of the Druggable Genome in Cisplatin Resistant Ovarian Cancer

To identify genes that could be targeted to overcome cisplatin resistance, we carried out a druggable genome siRNA screen targeting 6,659 genes (MISSION® siRNA Human Druggable Genome, Sigma), utilizing human cisplatin resistant A2780CP70 ovarian cancer cells. 

Experimental Approaches

A2780CP ovarian cancer cells were plated in 384-well plates in 50 μl per well of complete medium using a WellMate (Matrix Technologies, Canada) and transfected with siRNAs 24 hrs later using Lipofectamine RNAi MAX Reagent (ThermoFisher Scientific, MA, USA), with three siRNAs targeting the same gene pooled at equal molarities (final concentration of each siRNA, 5 nM). The siRNA library was tested in triplicate to establish experimental variability and statistical validity. Cells were treated with cisplatin 0.01 μM (IC₂₀) or vehicle at 24 hrs following transfection, and the plates were incubated at 37°C in a 5% CO₂ incubator for 72 hrs. Cell viability was assessed by CellTiter-Glo assay (Promega, WI, USA), and chemiluminescence was quantified using an Envision multilabel plate reader (PerkinElmer Life Sciences, MA, USA). In-plate normalization was carried out for viability relative to mock as follows (Well Luminescence - mean (Blank Luminescence)) / (mean (Mock Luminescence) - mean (Blank Luminescence))* 100 on the same plate.

Functional Exploration of the Kinome in MYC Driven Ovarian Cancer

To identify kinases that could be targeted and that might be effective in ovarian cancers with MYC overexpression, we carried out an siRNA screen targeting the human kinome utilizing four ovarian cancer cell lines, TOV112D and IGROV-1 (both high cMYC expression), and CaOV3 and DOV-13 (low cMYC expression).

Experimental Approaches

RNA inhibition was carried out using an siRNA library of 713 human kinases (Sigma) containing 3 pooled siRNAs per gene in 384 well format. Additionally, 40 spike in controls (Qiagen) were pooled at equal molarities (final concentration of each siRNA, 5 nM). Technical controls for transfection efficiency were achieved via 16 Kif11, 8 mock,16 universal, and 1 (Sigma) positional constant controls on each plate. Cells were plated at 250 cells/well in DMEM 10% FCS 24 hrs prior to transfection and incubated at 37º C, 5% CO₂. Using predetermined conditions independent for each cell line, three replicate transfections per siRNA pool were performed. Final well concentrations varied between 50nM and 12.5nM siRNA for each cell line. 96 hrs post transfection 5 µL of CellTiter-Glow (Promega), was added to each well and luminescence was read on an Envision plate reader (Perkin Elmer). In-plate normalization was carried out for viability relative to mock as follows (Well Luminescence – mean (Blank Luminescence)) / (mean (Mock Luminescence) - mean (Blank Luminescence)) * 100 on the same plate.

Functional Exploration of the Kinome in Pancreatic Ductal Adenocarcinoma

RNA interference (RNAi) kinome screens were performed on seven pancreatic ductal adenocarcinoma (PDAC) cell lines, and HPNE: an hTERT-immortalized normal pancreas ductal epithelial cell line to identify kinases important in pancreatic cancer.

Experimental Approaches

Cells: Pancreatic ductal adenocarcinoma (PDAC) cell lines - Johns Hopkins University Set:  Panc_02.03 (CRL-2553), Panc_03.27 (CRL-2549), Panc_04.03 (CRL-2555), Panc_05.04 (CRL-2557), Panc_08.13 (CRL-2551), Panc _PL45 (CRL-2558), Panc_10.05 (CRL-2547)¹, and HPNE (CRL-4023): hTERT immortalized normal pancreas ductal epithelial cell line obtained from ATCC².

siRNA Library: MISSION® Human Kinome siRNA library (Sigma) consists of three siRNAs per gene targeting (713 genes) kinases. The human kinome siRNA working library was constructed and arrayed in a 384-well format with pools of the three independent siRNAs targeting each gene, in a one gene per well approach. We also designed a custom Moser_Pancreas_Library (267 genes) consisting of a pancreatic-specific oncolibrary [pancreatic-specific biomarkers³ (81 genes), pancreatic-specific extracellular/membrane associated genes from SAGE expression analysis⁴ (44 genes), pro- and anti-apoptotic and autophagic genes (90 genes), pancreatic pathway controls (46 genes), and select chromatin modifying enzymes (6 genes)], and a DNA damage and repair (DDR) library (318 genes) were also added to this kinome screen.

High-throughput siRNA transfections: RNAi extended kinome screens were performed utilizing an array-based siRNA platform on seven PDAC cell lines¹: Johns Hopkins University Set, and HPNE: hTERT immortalized normal pancreas ductal epithelial cell line². RNAi screens were performed in 384-well format in triplicate, in independent plates, utilizing robotics instrumentation. PDAC cell lines and HPNE were plated in 384-well plates in 50 μl per well of complete medium using a WellMate (Matrix Technologies, Canada) and transfected with siRNAs 24 hours later using Lipofectamine RNAi MAX Reagent (ThermoFisher Scientific, MA, USA), with three siRNAs targeting the same gene pooled at equal molarities. Plates were incubated at 37°C in a 5% CO² incubator for 72-96 hours and cell viability was measured as a phenotypic endpoint using the Cell-TiterGlo assay (Promega) and raw luminescence detected and quantified with an Envision Multilabel plate reader (PerkinElmer). Raw luminescence values were mock normalized per plate and plotted for distribution and data mining using a negative control siRNA (non-targeting siRNA) and a positive control siRNA targeting the kinesin motor protein (Kif11). A detailed description on methods of analysis of RNAi screens is available in Birmingham⁵ et al. and Cheung⁶ et al.

References

1. Jaffee EM, et al. Development and characterization of a cytokine-secreting pancreatic adenocarcinoma vaccine from primary tumors for use in clinical trials. Cancer J Sci Am. 1998 May-Jun;4(3):194-203 (PMID: 9612602)
2. Lee KM, et al. Immortalization with telomerase of the Nestin-positive cells of the human pancreas. Biochem Biophys Res Commun. 2003 Feb 21;301(4):1038-44 (PMID: 12589817)
3. Harsha HC, et al. A Compendium of Potential Biomarkers of Pancreatic Cancer. PLoS Med. 2009 Apr 7;6(4):e1000046 (PMID: 19360088)
4. Jones S, et al. Core Signaling Pathways in Human Pancreatic Cancers Revealed by Global Genomic Analyses. Science. 2008 Sep 26;321(5897):1801-6 (PMID: 18772397)
5.  Birmingham A, et al. Statistical methods for analysis of high-throughput RNA interference screens. Nat Methods. 2009 Aug;6(8):569-75 (PMID: 19644458)
6. Chung N, et al. Median absolute deviation to improve hit selection for genome scale RNAi screens. J Biomol Screen. 2008 Feb;13(2):149-58 (PMID: 18216396)

Functional Exploration of the Druggable Genome in Pancreatic Ductal Adenocarcinoma

Druggable genome siRNA screen were performed on a KRAS^G12V mutant patient-derived pancreatic adenocarcinoma (PDAC) cell culture to identify new druggable signaling nodes.

Experimental Approaches

Cells: A pancreatic adenocarcinoma low-passage cell culture (PancVH1) was isolated from a patient-derived xenograft (PDX) mouse model generated at Translational Genomics Research Institute (TGEN) from a 75-year old female patient that had undergone a pancreaticoduodenectomy. The PancVH1 low-passage cell culture was propagated in growth medium including RPMI1640 (ATCC), ITS supplement: insulin (5µg/ml), transferrin (5µg/ml), selenium (5ng/ml), IGF-I (100ng/ml), IGF-II (100ng/ml), 10% fetal bovine serum¹.

siRNA Library: MISSION® Human Druggable Genome siRNA library (Sigma) consists of three siRNAs per gene targeting 6,659 genes. The human druggable genome siRNA working library was constructed and arrayed in a 384-well format with pools of the three independent siRNAs targeting each gene, in a one gene per well approach.

High-throughput siRNA transfections: RNA interference (RNAi) druggable genome screen was performed utilizing an array-based siRNA platform on a patient-derived pancreatic ductal adenocarcinoma cell culture (PancVH1). RNAi screen was performed in 384-well format in triplicate, in independent plates, utilizing robotics instrumentation. PancVH1 cells were plated in 384-well plates in 50 μl per well of complete medium using a WellMate (Matrix Technologies, Canada) and transfected with siRNAs 24 hours later using Lipofectamine RNAi MAX Reagent (ThermoFisher Scientific, MA, USA), with three siRNAs targeting the same gene pooled at equal molarities. Plates were incubated at 37°C in a 5% CO² incubator for 72-96 hours and cell viability was measured as a phenotypic endpoint using the Cell-TiterGlo assay (Promega) and raw luminescence detected and quantified with an Envision Multilabel plate reader (PerkinElmer). Raw luminescence values were mock normalized per plate and plotted for distribution and data mining using a negative control siRNA (non-targeting siRNA) and a positive control siRNA targeting the kinesin motor protein (Kif11). A detailed description on methods of analysis of RNAi screens is available in Birmingham² et al. and Cheung³ et al.

References

1. Jaffee EM, et al. Development and characterization of a cytokine-secreting pancreatic adenocarcinoma vaccine from primary tumors for use in clinical trials. Cancer J Sci Am. 1998 May-Jun;4:194-203 (PMID: 9612602)
2. Birmingham A, et al. Statistical methods for analysis of high-throughput RNA interference screens. Nat Methods. 2009 Aug;6:569-575 (PMID: 19644458)
3. Chung N, et al. Median absolute deviation to improve hit selection for genome scale RNAi screens. J Biomol Screen. 2008 Feb;13:149-158 (PMID: 18216396)

Functional Exploration of the Druggable Genome in Head and Neck Squamous Cell Carcinoma

Druggable genome siRNA screens were performed on a head and neck squamous cell carcinoma (HNSCC) primary cell culture to identify new druggable signaling nodes.

Experimental Approaches

Cells
Tissue specimens were collected during surgery with the consent from a previously untreated 59-year-old male with a floor-of-mouth squamous cell carcinoma (T2N2b, HPV negative). Epithelial tumor cells were enriched by selective culturing and magnetic-activated cell sorting with EpCAM microbeads (Miltenyi Biotec, San Diego, CA). The established primary cell culture was confirmed by immunohistochemistry staining with cytokeratin antibody ab961 and vimentin antibody EPR868(2) (Abcam, Cambridge, MA), and named FHCRC_SCC_1¹. 

siRNA Library
MISSION® Human Druggable Genome siRNA library (Sigma) consists of three siRNAs per gene targeting 6,659 genes. The human druggable genome siRNA working library was constructed and arrayed in a 384-well format with pools of the three independent siRNAs targeting each gene, in a one gene per well approach. A DNA damage and repair (DDR) siRNA library (318 genes) was also added to this druggable genome screen.

Cisplatin Modifier
Cisplatin dose-response curve was generated on the FHCRC_SCC_1 primary cell culture and a IC₃₀ value was determined (ie. inhibitory concentration of cisplatin resulting in 30% reduced viability). The FHCRC_SCC_1 primary cell culture siRNA screen was performed in parallel with vehicle and cisplatin modifier at IC₃₀ concentration to identify cisplatin sensitizers and genes that demonstrate a role in cisplatin biology.

High-throughput siRNA transfections
RNA interference (RNAi) druggable genome screen was performed utilizing an array-based siRNA platform on FHCRC_SCC_1. RNAi screen was performed in 384-well format in triplicate, in independent plates, utilizing robotics instrumentation. FHCRC_SCC_1 cells were plated in 384-well plates in 50 μl per well of complete medium using a WellMate (Matrix Technologies, Canada) and transfected with siRNAs 24 hours later using Dharmafect 1 Reagent (GE Dharmacon, USA), with three siRNAs targeting the same gene pooled at equal molarities. The siRNA library was tested in triplicates to establish experimental variability and statistical validity. Cells were treated with vehicle or with cisplatin at IC₃₀ concentration at 24 hours following transfection, and were incubated at 37°C in a 5% CO² incubator for 72 hours. Cell viability was measured as a phenotypic endpoint using the Cell-TiterGlo assay (Promega) and raw luminescence detected and quantified with an Envision Multilabel plate reader (PerkinElmer). Raw luminescence values were mock normalized per plate and plotted for distribution and data mining using a negative control siRNA (non-targeting siRNA) and a positive control siRNA targeting the kinesin motor protein (Kif11). A detailed description on methods of analysis of RNAi screens is available in Moser² et al., Birmingham³ et al., and Cheung⁴ et al.

References

1. Xu C, et al. (2018). Functional Precision Medicine Identifies Novel Druggable Targets and Therapeutic Options in Head and Neck Cancer. Clin Cancer Res, 24(12):2828-2843. (PMID: 29599409)
2. Moser R, et at. (2014). Functional kinomics identifies candidate therapeutic targets in head and neck cancer. Clin. Cancer Res, 20:4274-4288 (PMID: 25125259)
3. Birmingham A, et al. (2009). Statistical methods for analysis of high-throughput RNA interference screens. Nat Methods, 6:569-575 (PMID: 19644458)
4. Chung N, et al. (2008). Median absolute deviation to improve hit selection for genome scale RNAi screens. J Biomol Screen, 13:149-158 (PMID: 18216396)

Kinome-wide siRNA Screens (screen 2) to Discover Novel Vulnerabilities in Ras/Tp53 Mutant Murine Squamous Cell Carcinomas

Cells: MSCC cells were derived from NIH/Ola strain mice with germline mutations in p53 pathway genes and included: MSCC-CK2 (Hras Q61L p53^+/+) and MSCC-CK4 (Hras Q61L p53^{-/- (Cre+ p53 lox/lox)})^1,2. MSCC cell lines were derived from DMBA/TPA induced squamous cell carcinoma using a standard outgrowth explant method. A normal murine keratinocyte cell line (NIHK1) was derived from NIH/Ola strain as described in Nowak³ et al. 

siRNA Library: Ambion murine kinome siRNA library contains three siRNAs per gene targeting 571 murine kinase genes. The Ambion murine kinome siRNA working library was constructed and arrayed in a 384-well format with pools of 3 independent siRNAs targeting each gene, in a one gene per well approach -Ambion Murine Kinome Library-Table S4⁴. A custom designed murine Ras physiological regulators siRNA gene panel targeting 44 genes (4 siRNAs/gene), and a DNA repair siRNA gene panel targeting 19 genes (3 siRNAs/gene) was also added to the kinome screen.

Doxorubicin Modifier: Doxorubicin dose-response curves were generated on the two MSCC cell lines and the normal keratinocyte cell line and IC₃₀ and IC₆₀ values were determined for each cell line. Each MSCC/NIHK1 cell line siRNA screen was performed in parallel with vehicle and doxorubicin modifier at IC₃₀ and IC₆₀ concentrations.

High-throughput siRNA transfections: Kinome-wide siRNA screens were performed on two low passage murine squamous cell carcinoma (MSCC) cell lines and a normal keratinocyte cell line (NIHK1) with cellular viability as the phenotypic endpoint. MSCC cells were plated in 384-well plates in 50 μl per well of complete medium using a WellMate (Matrix Technologies, Canada) and transfected with siRNAs 24 hours later using Dharmafect1 Reagent (GE Dharmacon, USA), with three siRNAs targeting the same gene pooled at equal molarities. The siRNA library was tested in triplicates to establish experimental variability and statistical validity. Cells were treated with vehicle or with doxorubicin at IC₃₀ and IC₆₀ concentrations at 24 hours following transfection, and the plates were incubated at 37°C in a 5% CO² incubator for ~60 hours. Cell viability was assessed by CellTiter-Glo assay (Promega, WI, USA), and luminescence was quantified using an Envision multilabel plate reader (PerkinElmer Life Sciences, MA, USA). Raw luminescence values were mock normalized per plate and plotted for distribution and data mining using a negative control siRNA (non-targeting siRNA) and a positive control siRNA targeting the kinesin motor protein (Kif11). A detailed description of methods is available in Moser⁴ et al., Birmingham⁵ et al., and Cheung⁶ et al. The NIHK1 keratinocyte control cell line has innate biological differences related to intensity of siRNA efficiency and universal negative control normalization yielded a more desirable relative assay range for comparing the control to the MSCC.

References

1. Kelly-Spratt KS, et al. p19Arf suppresses growth, progression, and metastasis of Hras-driven carcinomas through p53-dependent and -independent pathways. PLoS Biol. 2004 Aug;2(8):E242 (PMID: 15314658) 
2. Kemp CJ, et al. Reduction of p53 gene dosage does not increase initiation or promotion but enhances malignant progression of chemically induced skin tumors. Cell. 1993 Sep 10;74(5):813-22 (PMID: 8374952)
3. Nowak JA, et al. Isolation and Culture of Epithelial Stem Cells. Methods Mol Biol. 2009;482:215-32 (PMID: 19089359)
4. Moser R, et al. Functional kinomics identifies candidate therapeutic targets in head and neck cancer. Clin Cancer Res. 2014 Aug 15;20(16):4274-88 (PMID: 25125259)
5. Birmingham A, et al. Statistical methods for analysis of high-throughput RNA interference screens. Nat Methods. 2009 Aug;6(8):569-75 (PMID: 19644458)
6. Chung N, et al. Median absolute deviation to improve hit selection for genome scale RNAi screens. J Biomol Screen. 2008 Feb;13(2):149-58 (PMID: 18216396)

Identification of Novel Targets and Sensitizers to the PARP Inhibitor Rucaparib in Ovarian Cancer

Resistance to PARP inhibitors is a major clinical challenge in the treatment of ovarian cancer. This project used high-throughput siRNA and drug screening of patient-derived ovarian cancer cell lines to identify gene targets and drugs that synergize with rucaparib and could be advanced in clinical trials.

Experimental Approaches

Cells: This project utilized two patient-derived Ovarian Cancer Ince (OCI) cell lines, OCI-P5x from serous subtype and OCI-C5x from clear-cell subtype for target discovery¹.

siRNA Library: A custom siRNA working library was constructed targeting 2,187 unique genes and arrayed in a 384-well format and consisting of three independent siRNAs targeting each gene in a one-gene-per-well approach. The full custom siRNA library targets 2,400 genes in total and consists of an epigenome library (1195 genes - Ambion Silencer siRNA library – Catalog Number: 4404028), kinome library (713 genes) (Sigma), DNA damage and repair (DDR) library (318 genes) (Qiagen), and an ovarian cancer-specific library (174 genes) (Qiagen). All working libraries were arrayed at Quelllos High-throughput Screening Facility at University of Washington Institute for Stem Cell and Regenerative Medicine (ISCRM).

Rucaparib Modifier: Rucaparib concentration/dose-response curves were generated on OCI-P5x and OCI-C5x cell lines and an IC₃₀ value was determined (i.e., inhibitory concentration of rucaparib resulting in 30% reduced viability). The OCI-P5x and OCI-C5x cell lines’ siRNA screens were performed in parallel with vehicle and rucaparib modifier at 20 µM rucaparib (IC₃₀) in order to identify rucaparib sensitizer genes.

High-throughput siRNA transfections: RNA interference (RNAi) screens were performed utilizing an array-based siRNA platform on OCI-P5x and OCI-C5x cell lines. RNAi screens were performed in a 384-well format in triplicate, in independent plates, utilizing robotics instrumentation. OCI-P5x and OCI-C5x cell lines were plated in 384-well plates in 50 μl per well of complete medium using a WellMate (Matrix Technologies, Canada) and transfected with siRNAs (1.25 pmol/well) 24 hours later using Dharmafect 1 Reagent (Horizon Discovery), with three siRNAs targeting the same gene pooled at equal molarities. The siRNA library was tested in triplicate to establish experimental variability and statistical validity. Cells were treated with vehicle or with rucaparib at IC₃₀ concentration 24 hours following transfection, and the plates were incubated at 37°C in a 5% CO₂ incubator for 72 and 96 hr for OCI-C5x and OCI-P5x, respectively. Cell viability was measured as a phenotypic endpoint using the Cell-TiterGlo assay (Promega) and raw luminescence detected and quantified with an Envision Multilabel plate reader (PerkinElmer). Raw luminescence values were mock-treatment normalized per plate and plotted for distribution and data mining using a negative control siRNA (non-targeting siRNA) and a positive control siRNA targeting the kinesin motor protein (Kif11). RNAi screens were analyzed using methods in Birmingham et al.², and Cheung et al.³.

Drug Library: SelleckChem custom 395-compound library was purchased from SelleckChem targeting a broad range of cancer-related pathways and containing FDA-approved and tool compounds that target oncogenic processes and include PI3K, HDAC, mTOR, CDK, JAK, and RTK inhibitors (Catalog # L3000; anti-cancer compound library).

Drug Screens: Single-agent and combination drug screens were performed on OCI-C5x and OCI-P5x cell lines with rucaparib and a 395-compound SelleckChem custom drug library. Drug library working plates were generated as an 8-point concentration curve for all 395 compounds. Final concentrations for drug screening of all compounds range from 0.3 nM – 5 µM with DMSO/PBS vehicle at 0.05%. OCI-C5x and OCI-P5x cell lines were seeded at ~30% confluence in 384-well microtiter plates, and at 24 hours the working library (395 drugs; 8-point, maximum final – 5 µM) and Rucaparib (OCI-C5x-[10 µM], OCIP5x-[20 µM]) were added using a CyBio-FeliX liquid handler (Analytik Jena AG), and cells were incubated for 144 hr. Cell viability was determined using CellTiter-Glo 2.0 and a BioTek H4 Synergy plate reader. Single-agent responses were normalized to the solvent concentration (0.05% PBS/DMSO) while the combination drug responses were normalized to the solvent concentration and rucaparib.