Identifying biomarkers of treatment response in gestational trophoblastic disease through quantitative proteomics analysis of patient samples

Gestational trophoblastic disease (GTD) is a group of pregnancy related disorders which arise after abnormal fertilization of the egg. GTD affects about 1800 women/yr in the UK and is a spectrum of disorders including the pre-malignant hydatidiform moles (HM) through to the malignant choriocarcinoma. Although much progress has been done in the clinical management of GTD, several problems remain to be addressed. In particular, informed choice of the most appropriate therapeutic strategy is impaired by the lack of adequate predictive biomarkers. Indeed. While methotrexate (MTX)-based monotherapy cures the vast majority of cases, our current stratification scoring system (FIGO score) misclassifies a large proportion of patients, leading to unnecessary delays in administration of curative combination chemotherapy. In addition, patients resistant to combination agent treatment may require further different combination chemotherapy including high dose treatment and/or immune-checkpoint therapy to achieve a sustained remission but biomarkers to select patients between these therapies are lacking. Thus, patients may go through multiple rounds of different treatments. These could potentially have been avoided along with the associated toxicities if we had an appropriate stratification biomarker. Finally, although most patient eventually get cured, some continue to fail all existing treatments and would benefit from the identification of novel targets for new therapies.

Here, we intend to use proteomics profiling of clinically annotated patient tissue samples to identify better biomarkers for stratification of GTD patients into existing treatments and discover targets (known or novel) to enable new therapeutic strategies. Our previous proteomics profiling of a single MTX-sensitive/resistant choriocarcinoma cell line pair revealed DNA repair and cell cycle checkpoints as potential new therapeutic targets to tackle MTX resistance. However, follow-on validation of these findings in GTD tissue samples showed these to be only relevant to a subset of patients. Therefore, a less focused approach is needed to discover more changes associated with resistance to single versus multi-chemotherapeutic agents.
Specifically, the aims of this project are:
1. Identification of molecular pathways associated with distinct therapy resistance profiles using quantitative mass-spectrometry (MS)-based proteomics analysis of GTD tissue samples
2. Confirmation of the role of the identified pathways in the resistance to the relevant therapeutic regimen in vitro and in vivo using GTD cell lines
3. Validation of the clinical relevance of the above findings in a large number of tissue samples to statistically assess the strength of association between these biomarkers and therapeutic response