Resistance to chemotherapeutics and targeted drugs is one of the main barriers to successful cancer therapy. Various mechanisms have been identified to contribute to drug resistance, some more well-characterised than others. One under-explored area of resistance is alterations to intracellular drug concentration, which can impact target engagement and ultimately treatment outcome. Our lab focuses on membrane transporters, a class of membrane proteins that can directly influence drug response by mediating drug uptake and efflux, but that have also been suggested to indirectly play a role in therapeutic response via their endogenous roles in cellular metabolism. In this project we focus on investigating the different roles membrane transporters may have in drug resistance with a view to understanding how they could be modulated to improve the efficacy of targeted cancer therapies.

We performed an in silico analysis using two publicly available datasets; Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopaedia (CCLE), to investigate the role of membrane transporters in drug accumulation. The GDSC project has screened 518 anti-cancer drugs across a panel of 988 cell lines to determine IC50 values. For each compound, we correlated IC50 to gene expression data from the CCLE dataset across the panel of cell lines tested. This analysis identified a strong association between the expression levels of the SLC35 family members and resistance to 27% of the screened compounds, including all the PARP inhibitors (PARPi) within the GDSC dataset. To validate these findings experimentally, we established an arrayed phenotypic screening platform using CRISPR knockout/activation (CRISPRko/a) to target all 32 SLC35 genes. Three complementary readouts were employed; live-cell imaging, immunofluorescence and cell viability assays.

Using Rucaparib, a PARPi compound that possesses intrinsic fluorescence, we successfully established a screening platform using high content imaging of the drug and DNA damage markers, alongside cell viability assays to assess PARPi response. Since PARPi work by inducing lethal DNA damage in homologous recombination (HR)–deficient cells, CRISPRko/a models were generated and validated in five HR–deficient ovarian cancer cell lines, two of which were used in the screen. The screen identified two SLC35 family members as potential contributors to PARPi resistance across multiple readouts. Further validation demonstrated that stable knockdown of these transporters increased intracellular drug accumulation in two HR–deficient ovarian cancer cell lines.

While further investigation is required to better understand the functional impact of SLC35 expression on drug response, these data highlight the need to understand drug-transporter relationships to be able to predict patient response and toxicity in the context of personalised medicine.