Characterisation of novel niraparib resistance mechanisms in ovarian cancer

1. 根据创建新的抗parpi细胞系的进展情况，学生将可以立即访问细胞系面板和相关的生物信息学数据，或者将花费学生的前几个月帮助完成细胞系面板的创建，并协调RNASeq， RPPA和相关的生物信息学分析。2. MTT和克隆测定将用于比较敏感性和研究对额外PARPi的交叉耐药性，以及对一组结构和功能不同的化疗药物的交叉耐药性。3. 为了继续临床相关的药物转运体故事，将与邓迪大学药物发现部门药物代谢和药代动力学负责人Kevin Read教授合作进行定量药物外排测定。这些在极化细胞系中的研究将使我们能够确认各种PARPi的药物转运蛋白底物特异性，重点关注ABCB1 （p -糖蛋白）、ABCG2 （BCRP）和其他在我们的新细胞系模型中发现的转运蛋白，或正在进行的临床研究。4. 与GSK研究人员合作，将优先考虑在耐药细胞中差异表达的其他新靶点，以进行详细的实验验证。靶点的优先顺序将基于新颖性、可操作性（例如，特定小分子抑制剂的可用性）以及与GSK临床前数据和药物开发管道的协同作用。5. 靶标将使用siRNA瞬时敲除和小分子抑制剂研究的组合进行验证，化学敏感性终点评估如上所述。验证的靶标将在过表达研究中被“拯救”，通过病毒转导的稳定shRNA敲低细胞系创建，对验证的基因进行更详细的表型评估。根据生物信息学预测，各种定量表型测定（如诱导细胞增殖测定，基于Boyden室的侵袭和迁移测定）将用于确认预测的耐药表型。经过验证的候选基因将优先用于预后生物标志物的开发，例如将定量ELISA方法与循环肿瘤（ctDNA）液体活检方法相结合。

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.