Investigating prognostic biomarkers and tumour suppressor biology in high grade serous ovarian cancer
File(s)
Author(s)
Lu, Haonan
Type
Thesis
Abstract
High grade serous ovarian cancer (HGSOC) is the leading cause of death among all gynaecological malignancies. Despite recent advances in maximal effort surgery and systematic treatment, the 5-year survival remains as low as 35-40%. The response to treatment is heterogeneous even among the HGSOC population, although most of the patients are treated without stratification. It is therefore crucial to identify novel predictive and prognostic biomarkers to guide appropriate treatment, and discover novel therapeutic options for this lethal disease.
Medical images, including computed tomography (CT) scans, are often used as a diagnostic tool during HGSOC treatment. In the first part of this project, we hypothesised that prognosis- relevant information could be hidden within CT scans and may be used as novel biomarker in HGSOC. We thus extracted 657 image features from each CT scan using a customised software; we then successfully generated and validated a prognostic model, based on a weighted four-feature signature. This CT-based prognostic model can accurately predict at least 5% of patients with median overall survival of less than 2 years, as well as 67% of patients with median overall survival over 5 years. Using genetic, transcriptomic, proteomic and histological analyses, we have uncovered stroma-activating pathways as well as proliferation and DNA damage response as the underlying biology of the CT-based prognostic signature. We therefore proposed treatment options accordingly to the CT-stratified patient subgroups. These results suggest a great potential for CT-images as a non-invasive, cost-effective and real-time biomarker platform in HGSOC.
OPCML is a tumour suppressor gene that belongs to the IgLON protein family and is frequently silenced through promoter hyper-methylation in HGSOC. OPCML has been demonstrated to negatively regulate a panel of receptor tyrosine kinases in HGSOC and it is currently under development as a therapeutic agent. It has been suggested that other IgLON family members could be transcriptionally induced by TGFb1 and play essential functions in cancer, however, the role of OPCML in the TGFb pathway is not clear. Therefore, in the second part of this project, we investigated the transcriptional regulation and functions of OPCML in the TGFb pathway in HGSOC. We demonstrated that OPCML could be transcriptionally induced by TGFb1 in non-malignant cells via the canonical Smad pathway, while this induction is completely lost in ovarian cancer cells. Through transcriptomic and proteomic profiling, we discovered that OPCML could contribute to DNA double strand break repair, possibly via the upregulation of ATM. In summary, we have discovered novel functions of OPCML as a feedback gene in the TGFb pathway and suggested new functions for OPCML during tumorigenesis of HGSOC.
With this study, we have contributed to improve the knowledge of the biology of HGSOC, and identified possible new stratification biomarkers to achieve personalised medicine in the near future.
Medical images, including computed tomography (CT) scans, are often used as a diagnostic tool during HGSOC treatment. In the first part of this project, we hypothesised that prognosis- relevant information could be hidden within CT scans and may be used as novel biomarker in HGSOC. We thus extracted 657 image features from each CT scan using a customised software; we then successfully generated and validated a prognostic model, based on a weighted four-feature signature. This CT-based prognostic model can accurately predict at least 5% of patients with median overall survival of less than 2 years, as well as 67% of patients with median overall survival over 5 years. Using genetic, transcriptomic, proteomic and histological analyses, we have uncovered stroma-activating pathways as well as proliferation and DNA damage response as the underlying biology of the CT-based prognostic signature. We therefore proposed treatment options accordingly to the CT-stratified patient subgroups. These results suggest a great potential for CT-images as a non-invasive, cost-effective and real-time biomarker platform in HGSOC.
OPCML is a tumour suppressor gene that belongs to the IgLON protein family and is frequently silenced through promoter hyper-methylation in HGSOC. OPCML has been demonstrated to negatively regulate a panel of receptor tyrosine kinases in HGSOC and it is currently under development as a therapeutic agent. It has been suggested that other IgLON family members could be transcriptionally induced by TGFb1 and play essential functions in cancer, however, the role of OPCML in the TGFb pathway is not clear. Therefore, in the second part of this project, we investigated the transcriptional regulation and functions of OPCML in the TGFb pathway in HGSOC. We demonstrated that OPCML could be transcriptionally induced by TGFb1 in non-malignant cells via the canonical Smad pathway, while this induction is completely lost in ovarian cancer cells. Through transcriptomic and proteomic profiling, we discovered that OPCML could contribute to DNA double strand break repair, possibly via the upregulation of ATM. In summary, we have discovered novel functions of OPCML as a feedback gene in the TGFb pathway and suggested new functions for OPCML during tumorigenesis of HGSOC.
With this study, we have contributed to improve the knowledge of the biology of HGSOC, and identified possible new stratification biomarkers to achieve personalised medicine in the near future.
Version
Open Access
Date Issued
2018-09
Date Awarded
2019-05
Copyright Statement
Creative Commons Attribution NonCommercial NoDerivatives Licence
Advisor
Recchi, Chiara
Gabra, Hani
Fotopoulou, Christina
Publisher Department
Department of Surgery & Cancer
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)