Characterisation of novel niraparib resistance mechanisms in ovarian cancer
Lead Research Organisation:
University of Dundee
Department Name: School of Life Sciences
Abstract
1. Depending on progress in creating the novel PARPi-resistant cell lines, the student will either have immediate access to the cell line panel and associated bioinformatics data, or will spend the first few months of the studentship helping to complete creation of the cell line panel, and co-ordinate RNASeq, RPPA and associated bioinformatics analysis.
2. MTT and clonogenic assays will be used to compare sensitivity and investigate cross-resistance to additional PARPi, and to a panel of structurally and functionally diverse chemotherapy drugs.
3. To continue the clinically relevant drug transporter story, quantitative drug efflux assays will be performed in collaboration with Professor Kevin Read, Head of Drug Metabolism and Pharmacokinetics, Drug Discovery Unit, University of Dundee. These studies in polarised cell lines will allow us to confirm drug transporter substrate specificity of the various PARPi, focussing on ABCB1 (P-glycoprotein), ABCG2 (BCRP), and other transporters identified in our novel cell line models, or ongoing clinical studies.
4. In collaboration with GSK investigators, additional novel targets, differentially expressed in resistant cells, will be prioritised for detailed experimental validation. Targets will be prioritised based on novelty, actionability (e.g. availability of specific small molecule inhibitors) and synergy with GSK pre-clinical data and drug development pipeline.
5. Targets will be validated using a combination of siRNA transient knockdown and small molecule inhibitor studies, with chemosensitivity endpoints assessed as described above. Validated targets will be "rescued" in over-expression studies, with virally-transduced stable shRNA knockdown cell lines created for more detailed phenotypic assessment of validated genes.
6. Depending on bioinformatics predictions, various quantitative phenotypic assays (e.g. Incucyte cell proliferation assays, Boyden chamber-based invasion and migration assays) will be used to confirm predicted drug resistance phenotypes.
7. Validated candidate genes will be prioritised for prognostic biomarker development, for example combining quantitative ELISA methods, with circulating tumour (ctDNA) liquid biopsy approaches.
2. MTT and clonogenic assays will be used to compare sensitivity and investigate cross-resistance to additional PARPi, and to a panel of structurally and functionally diverse chemotherapy drugs.
3. To continue the clinically relevant drug transporter story, quantitative drug efflux assays will be performed in collaboration with Professor Kevin Read, Head of Drug Metabolism and Pharmacokinetics, Drug Discovery Unit, University of Dundee. These studies in polarised cell lines will allow us to confirm drug transporter substrate specificity of the various PARPi, focussing on ABCB1 (P-glycoprotein), ABCG2 (BCRP), and other transporters identified in our novel cell line models, or ongoing clinical studies.
4. In collaboration with GSK investigators, additional novel targets, differentially expressed in resistant cells, will be prioritised for detailed experimental validation. Targets will be prioritised based on novelty, actionability (e.g. availability of specific small molecule inhibitors) and synergy with GSK pre-clinical data and drug development pipeline.
5. Targets will be validated using a combination of siRNA transient knockdown and small molecule inhibitor studies, with chemosensitivity endpoints assessed as described above. Validated targets will be "rescued" in over-expression studies, with virally-transduced stable shRNA knockdown cell lines created for more detailed phenotypic assessment of validated genes.
6. Depending on bioinformatics predictions, various quantitative phenotypic assays (e.g. Incucyte cell proliferation assays, Boyden chamber-based invasion and migration assays) will be used to confirm predicted drug resistance phenotypes.
7. Validated candidate genes will be prioritised for prognostic biomarker development, for example combining quantitative ELISA methods, with circulating tumour (ctDNA) liquid biopsy approaches.
People |
ORCID iD |
| Gillian Smith (Primary Supervisor) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| MR/R015791/1 | 03/09/2018 | 30/09/2025 | |||
| 2471602 | Studentship | MR/R015791/1 | 05/10/2020 | 04/01/2025 |