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DeFazio, A.

Publications and source records attributed to DeFazio, A..

6 recordsLinked to original sources

Comprehensive drug efficacy data for mucinous ovarian carcinoma using a novel and extensive biobank of patient-derived organoid models

Mucinous Ovarian Carcinoma (MOC) is a rare ovarian cancer histological subtype with distinct pathology, genomics and clinical outcomes compared to other epithelial ovarian cancers. Accordingly, there is little evidence to guide clinical care, particularly in the use of systemic therapies, and the field has lacked informative and diverse pre-clinical models. We developed MOC-specific methods for generating tumour organoids with a success rate of 70% for long-term cultured lines (n=19). Organoid lines were developed from localised, advanced and recurrent tumours, including from biopsy tissue, and represent diverse genomic features not previously captured by existing cell lines. The organoid lines were highly similar to the tumours of origin for genomic and immunohistochemical markers. Screening using a panel of 11 chemotherapy agents highlighted resistance to standard-of-care agents such as carboplatin. Gastrointestinal cancer chemotherapy agents and their combination regimens lacked activity. Paclitaxel was often highly potent at low doses but failed to kill all cells. However, less frequently used drugs such as gemcitabine, topotecan and doxorubicin inhibited many of the lines more effectively than paclitaxel. Available, but non-standard of care, chemotherapy agents should be considered for clinical management of MOC. This is the largest (by [~]10 fold) cohort of fully characterised patient-derived MOC organoid lines described and the first with extensive drug screening data affording an opportunity for drug discovery and screening for personalised treatment.

cancer biology↗

Demethylating agents drive PARP inhibitor resistance in ovarian carcinomas with BRCA1 gene silencing

DNA methyltransferase 1 inhibitor (DNMT1i) therapy is a promising option for increasing immune response as part of combination cancer therapy. High-grade serous ovarian carcinoma (HGSOC) is a highly aggressive cancer with poor survival outcomes, where DNMT1i therapy is being increasingly explored. HGSOC with epigenetically silenced BRCA1 has been shown to respond to PARP inhibitor (PARPi) treatment - a core targeted therapy for HGSOC. However, loss of silencing of even a single BRCA1 allele causes PARPi and platinum chemotherapy resistance. We tested whether BRCA1 silencing was robust to DNMT1i therapy, or would be reversed, thus driving PARPi resistance. We previously generated two homozygously silenced BRCA1 HGSOC cell lines: WEHI-CS62 and an OVCAR8 derivative. DNMT1i treatment caused sustained BRCA1 promoter methylation loss, gene re-expression and PARPi resistance in both of these silenced BRCA1 lines, but not in mutated BRCA1/2 or RAD51C lines. Methylation arrays confirmed transient global CpG methylation losses following DNMT1i. CRISPR deletion of the re-expressed BRCA1 copy in WEHI-CS62 restored silencing and PARPi sensitivity. Furthermore, DNMT1i treatment of a silenced BRCA1 PDX caused heterogeneous BRCA1 promoter methylation loss. In summary, DNMT1 inhibitors caused sustained reduction of BRCA1 promoter methylation in HGSOC cells. This resulted in BRCA1 re-expression and PARP inhibitor resistance, presenting a significant risk for up to 17% of HGSOC patients with BRCA1 gene silencing who could benefit from PARP inhibitor therapy. We conclude that DNA demethylation therapy should be avoided for HGSOC patients with epigenetically silenced BRCA1.

cancer biology↗

Federated deep learning enables cancer subtyping by proteomics

Artificial intelligence applications in biomedicine face major challenges from data privacy requirements. To address this issue for clinically annotated tissue proteomic data, we developed a Federated Deep Learning (FDL) approach (ProCanFDL), training local models on simulated sites containing data from a pan-cancer cohort (n=1,260) and 29 cohorts held behind private firewalls (n=6,265), representing 19,930 replicate data-independent acquisition mass spectrometry (DIA-MS) runs. Local parameter updates were aggregated to build the global model, achieving a 43% performance gain on the hold-out test set (n=625) in 14 cancer subtyping tasks compared to local models, and matching centralized model performance. The approachs generalizability was demonstrated by retraining the global model with data from two external DIA-MS cohorts (n=55) and eight acquired by tandem mass tag (TMT) proteomics (n=832). ProCanFDL presents a solution for internationally collaborative machine learning initiatives using proteomic data, e.g., for discovering predictive biomarkers or treatment targets, while maintaining data privacy. Statement of SignificanceA federated deep learning approach applied to human proteomic data, acquired using two distinct proteomic technologies from 40 tumor cohorts from eight countries, enabled accurate cancer histopathological subtyping while preserving data privacy. This approach will enable privacy-compliant development of large-scale proteomic AI models, including foundation models, across institutions globally.

cancer biology↗

Cell-autonomous BMP signalling plays a key role in the maintenance of tumour cell EMT and migration programs in human ovarian carcinoma

Epithelial-mesenchymal transition (EMT) plays a key role in tumour initiation, metastasis and resistance to therapy. Cells undergoing EMT, assume multiple semi-stable transitional states along the epithelial-mesenchymal axis that necessitates tight regulatory cascades. Although more is known about pathways involved in the initial induction of EMT, cascades that mediate/maintain the transitional states and/or the final mesenchymal phenotype are yet to be elucidated. In this study, we have assessed the role of bone morphogenic protein (BMP) signalling pathway in the regulation of cancer cell EMT and migration. Mining existing data from ovarian carcinomas, we defined the BMP pathway among the key pathways enriched in tumours with elevated EMT signatures, with a significant correlation in the expression of EMT markers with BMP ligands and downstream targets of the BMP pathway. Functional inhibition of the BMP pathway in ovarian cancer cells by a small molecule inhibitor, DMH1, resulted in impaired migration and depressed EMT signatures in both in vitro and in vivo models. Finally, ectopic induction of EMT in ovarian cancer cells through activation of an independent pathway, TNF, resulted in the selective induction of Smad-mediated BMP pathway suggesting a role in maintenance of EMT, secondary to EMT induction.

cancer biology↗

Acquired RAD51C promoter methylation loss causes PARP inhibitor resistance in high grade serous ovarian carcinoma

While loss of BRCA1 promoter methylation has been shown to cause PARP inhibitor (PARPi) resistance in high-grade serous ovarian carcinoma (HGSC), the impacts of RAD51C methylation (meRAD51C) remain unresolved. In this study, three PARPi-responsive HGSC patient-derived xenografts (PDX) with RAD51C gene silencing and homologous recombination deficiency were found to have either homogeneous or heterogeneous patterns of meRAD51C. PDX could lose meRAD51C following PARPi treatment (rucaparib/niraparib), where a single unmethylated RAD51C copy was sufficient to drive PARPi-resistance. Genomic profiling revealed this resistance was acquired independently in two distinct PDX lineages. Furthermore, we describe a patient sample where 1/3 RAD51C gene copies lost methylation following neoadjuvant chemotherapy. We show meRAD51C is a positive predictive biomarker for PARPi response and should be screened for routinely in patients. However, methylation loss in a single gene copy is sufficient to cause PARPi resistance and should be carefully assessed in previously treated patients considering PARPi therapy.

cancer biology↗

Ovarian carcinosarcoma genomics and pre-clinical models highlight the N-MYC pathway as a key driver and susceptibility to EMT-targeting therapy

Ovarian carcinosarcoma (OCS) is an aggressive and rare tumour type with limited treatment options. OCS is hypothesised to develop via the combination theory from a single progenitor, resulting in carcinomatous and sarcomatous components, or alternatively via the conversion theory, with the sarcomatous component developing from the carcinomatous component through epithelial-to-mesenchymal transition (EMT). We show OCS from 18 women to be monoclonal through analysis of DNA variants from isolated carcinoma and sarcoma components. RNA sequencing indicated the carcinoma components were more mesenchymal when compared with pure ovarian carcinomas, supporting the conversion theory. We used pre-clinical OCS models to test the efficacy of microtubule-targeting drugs, including eribulin, which has been shown to reverse EMT characteristics. We demonstrated that microtubule inhibitors, vinorelbine and eribulin, were more effective than standard-of-care platinum-based chemotherapy. Eribulin reduced mesenchymal characteristics, N-MYC expression and cholesterol biosynthesis. Finally, eribulin induced a strong immune response, supporting immunotherapy combinations in the clinic.

cancer biology↗