| dc.description.abstract | Antifolates such as trimethoprim (TMP) and methotrexate (MTX) widely used for treating bacterial infections and certain cancers respectively, inhibit dihydrofolate reductase (DHFR) in the folate pathway. However, the use of these drugs is limited by the emergence of resistance. Resistance arises primarily due to mutations in DHFR and DHFR overexpression, and in bacteria, also through plasmid-borne naturally resistant DHFRs. Moreover, antifolate resistance provides cross-resistance to other drugs indicating that it is a complex phenomenon involving more than just DHFR-based mechanisms. Therefore, for the successful management of infections and cancers, it becomes necessary to identify resistance mechanisms and based on those, targets and inhibitors. Towards this, in this thesis, structural and systems biology tools have been used to identify (a) antifolates that can inhibit TMP-resistant E. coli DHFRs (b) new drug targets based on the folate pathway dynamics in resistant cancers and (c) targets and inhibitors based on the global mechanisms of TMP-resistance in E. coli and MTX-resistance in cancers.
In order to identify antifolates for resistant DHFRs, first, the interaction profiles of antifolates and target DHFRs are studied in the light of the differences in the druggable spaces of DHFRs. Briefly, druggable spaces or supersites of DHFRs from different species are extracted and classified into ‘site-types’ based on structural similarity. It is observed that antifolates have similar affinity towards DHFRs of the same ‘site-type’. Encouraged by this, a repurposing strategy is designed that allows identification of new target DHFRs for known antifolates. This strategy leverages benefit from the knowledge of high affinity antifolates for a target DHFR and similarity between the druggable spaces of the target DHFR and other DHFRs in the dataset. Through the repurposing exercise, 9963 new associations are made between existing antifolates and target DHFRs. It is found that the top-ranked antifolates repurposed to the E. coli DHFR have comparable affinities for both the wild type and the TMP-resistant mutants of the DHFR.
Next, following reports on cross-resistance of TMP-resistant E. coli to other classes of antibiotics, the transcriptomes of laboratory-evolved TMP-resistant E. coli are profiled to identify global perturbations that contribute to resistance. Specifically, the gene expression data is integrated into a newly constructed knowledge-based genome-scale protein interaction network of E. coli and the network is mined to fetch the most-perturbed communication paths. The top-perturbed paths in the network are seen to be enriched in genes involved in the SOS response, acid stress response, biofilm formation and several metabolic pathways. Through a systematic analysis of these processes and the cross-talk between them, the critical dependence on the activity of serine hydroxymethyltransferase (GlyA), an enzyme in the folate pathway is identified as an emergent vulnerability in resistant E. coli. It is shown that deletion of glyA rescues sensitivity to TMP in both the laboratory-evolved resistant strains and a multi-drug resistant clinical isolate of E. coli. Further, through a comparative evolution experiment, it is observed that E. coli devoid of GlyA activity adapt to TMP slower than the wild type E. coli indicating the GlyA is necessary not just for sustenance but also the acquisition of TMP-resistance.
Upon finding that a target for TMP-resistant E. coli lies in the folate pathway itself, the folate pathway dynamics in seven MTX-resistant cancer cell lines of different tissue origins are studied using kinetic models of folate metabolism for target identification. For most resistant cancer cell lines, a revival in the pathway activity is observed. Using metabolic control analysis, a tool that allows identification of enzymes that exert the most control on pathway dynamics, methenyltetrahydrofolate cyclohydrolase (MTCH) and GAR transformylase (PGT) are identified as targets in a majority of the resistant cell lines. The optimality of the targets is confirmed using models in which the non-competitive inhibition of MTCH is simulated. It is observed that inhibiting MTCH neutralizes the revival in flux caused by DHFR overexpression in resistant cancers.
An interaction network based approach, similar to the one used for studying TMP-resistance in E. coli, is used to identify additional mechanisms of resistance in the aforementioned MTX-resistant cell lines. Several signalling and metabolic pathways are seen to be perturbed in the resistant cells and many pathways are seen to be cell line specific. Although the underlying perturbations are different, all resistant cell lines are seen to exhibit common phenotypic trends such as activation of epithelial to mesenchymal transition (EMT), stemness and DNA repair pathways. Further, drug targets are identified based on parameters such as fold change in expression and network metrics such as centrality. For most resistant cancers, proteins involved in EMT and DNA repair are identified as targets. Finally, NCI-60 cell lines exhibiting gene expression patterns similar to those associated with the resistance mechanisms in a MTX-resistant cell line are identified. Inhibitors of these NCI-60 cell lines are repurposed to tthe MTX resistant cell line and further, ranked based on the correlation between their efficacy and perturbations in gene expression associated with resistance. FDA-approved drugs such as dasatinib, erlotinib, geldanamycin and fenretinide are identified are inhibitors of MTX-resistant cancers.
In the last part of the thesis, an interaction network based approach is used to identify prognostic biomarkers for cyclophosphamide-methotrexate-fluorouracil (CMF) therapy outcome in triple negative breast cancer patients of the mesenchymal and basal-like-1 subtypes. Genes in the top-active processes common across intrinsically MTX-resistant TNBC cell lines of a subtype are identified. These genes are further ranked based on the extent of their upregulation and association with resistance-conferring signalling pathways. The expression of the top-ranked genes is examined in relapsed and recovered TNBC patients and genes showing significant upregulation in relapsed patients are identified as candidate prognostic biomarkers. A three gene and two gene signature is derived for the mesenchymal and basal-like 1 subtypes of TNBC patients respectively.
The work presented in this thesis represents a comprehensive study of antifolate resistance, and avenues for overcoming it. Global perturbations contributing to resistance have been studied in TMP-resistant E. coli and MTX-resistant cancers. In both cases, it has been found that besides revival of the folate pathway activity, mechanisms such as SOS response and biofilm formation in E. coli and EMT in cancer sustain antifolate-resistance. Novel targets for combating antifolate resistance are identified both within the folate pathway itself, and in other pathways upregulated in resistant systems. Prognostic biomarkers for therapy in intrinsically MTX-resistant TNBC have also been identified, facilitating appropriate matching of patients and CMF therapy. In summary, the work presented in this thesis presents novel strategies for predicting and targeting antifolate resistance. | en_US |
