Medical Biology - Theses
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ItemThe role of venetoclax in the treatment of breast cancer( 2023-03)Breast cancer is the most commonly diagnosed cancer in women. The 5-year overall survival for metastatic breast cancer is approximately 30%. Despite rapid developments of new systemic therapies, cancer progression is almost inevitable. Ongoing research about treatment-resistance in breast cancer and mechanisms to overcome this are crucial to improving the lives of women with metastatic disease. Apoptosis is an important process for eliminating cancer cells. The BCL-2 pro-survival proteins and BH3-only proteins are key regulators of cell death. Cancer cells can evade apoptosis through over-expression of the pro-survival proteins. A new class of drug, the BH3 mimetics, inhibit the pro-survival proteins and have undergone extensive investigation in haematological malignancies. These drugs target BCL-2, BCLxL and MCL-1 and have shown promising activity in pre-clinical models. Venetoclax is a BH3 mimetic that specifically and potently binds to BCL-2. Venetoclax has transformed the treatment landscape for BCL-2- positive chronic lymphocytic leukaemia. It achieved fast-track FDA approval due to its success in the clinic. BCL-2 is overexpressed in approximately 70% of oestrogen receptor-positive metastatic breast cancers and approximately 30% of triple negative breast cancers. The aim of this thesis is to investigate the role of venetoclax in the treatment of BCL-2-positive breast cancer. We aim to achieve this through the design and implementation of three phase 1b clinical trials combining venetoclax with standard systemic therapy in the following clinical settings: (1) oestrogen receptor-positive and BCL-2-positive breast cancer in any line of metastatic treatment, (2) oestrogen receptor and BCL-2- positive breast cancer in the early lines of metastatic treatment (1st – 3rd line), (3) metastatic triple negative breast cancer. These clinical trials will firstly explore the safety and tolerability of venetoclax when combined with standard systemic therapy in metastatic breast cancer. Secondly, they will provide data on efficacy, survival and exploratory endpoints that inform future phase II and phase III studies. Findings from these later phase studies would determine whether venetoclax improves clinical outcomes in breast cancer and identify which patient subset might benefit. It is anticipated that due to the rapidly growing drug development in the area of BH3 mimetics, venetoclax may not be the most clinically relevant BH3 mimetic in the future. Therefore our clinical trial protocols could form a basis for future studies that investigate the next generation of BH3 mimetics or novel therapies targeting pro-survival proteins. The mBEP phase Ib clinical trial treated women with oestrogen receptor-positive and BCL-2-postive breast cancer in any line of metastatic treatment. This is the only study forming my thesis that has reached the primary and secondary endpoints. mBEP showed that the combination of tamoxifen and venetoclax was safe and tolerable. Secondary endpoints have confirmed that there is no adverse survival outcome from the addition of venetoclax to standard of care endocrine therapy.
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ItemStatistical and Machine Learning models for estimation of missing values in label-free mass spectrometry quantification( 2022)Mass spectrometry (MS) enables high throughput identification and quantification of proteins in complex biological samples and can provide insights into the global function of biological systems, aberrations and disease progression. Label-free quantification is cost effective, suitable for analysis of human samples and can profile proteins from a broad range of abundance. Despite rapid developments in label-free data acquisition workflows, the number of proteins commonly quantified across samples can be limited. This results in missing values in the measurements between samples, which present substantial challenges for downstream data analysis tasks and biomedical discoveries. This thesis provides two solutions for the treatment of missing values in label- free mass spectrometry: (i) imputation of missing values after quantification using Barycenter computation from Optimal Transport discipline in Machine Learning research, and (ii) a deep learning solution for sequence identification transfer between precursor ions across samples at the quantification step. In the two methodological manuscripts arose from this thesis, I demonstrate how these two solutions enhance data completeness in label-free mass spectrometry acquisition, thereby facilitating biomedical discoveries. I then provide a perspective on the future directions of these two works. The tools developed in this work are available on open-source software repositories and are used by the proteomics and bioinformatics community in medical research projects.
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ItemUnderstanding retinal diseases with genotypic and transcriptomic data analysis( 2021)The retina is light-sensitive eye tissue responsible for vision, but little is known about the genetic regulation of retinal gene expression. Investigating key drivers of gene regulation in the retina in healthy and diseased individuals remains a fundamental challenge in macular degeneration research, especially given the difficulty of accessing human retinal tissue. Deciphering the effects of genetic variation on retinal gene expression will underpin the development of novel treatment avenues for otherwise untreatable diseases causing blindness. A method to investigate these further focuses on the effects of genetic variants on gene expression levels derived from transcriptomic data. This type of ‘omics analysis, known as expression quantitative trait (eQTL) analysis integrates genotype and gene-expression data. The genotyping data for this thesis was generated in collaboration with scientists from the TIGEM, Italy, who first assembled the retinal transcriptome. We aimed to identify the genetic variants that modulate gene expression using a cohort of 41 individual donors of healthy retinal tissue. We performed retinal eQTL analysis using this independent cohort and compared our results with recently published retinal eQTL studies. After observing a weak eQTL signal potentially due to the small sample size, we explored potential strategies to mitigate the multiple testing burden so as to improve statistical power. To this end, we performed eQTL power analyses and limited both the set of variants and genes under consideration by thresholding on allele frequency and gene transcriptional abundance as well as disease relevance. Further, eQTL analysis was used to interpret the genetics of Macular Telangiectasia II, a blinding retinal degenerative disease. This included genome-wide and targeted interrogation of the signals from the largest genome-wide association study to date for this disease.
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ItemIdentifying Novel Strategies to Enhance the Anti-cancer Activity of Venetoclax by Manipulating NOXA Expression( 2021)Apoptosis is a form of programmed cell death. The intrinsic pathway of apoptosis is governed by the BCL2 family proteins. Targeting BCL2 proteins by small molecules that mimicking the BH3-only proteins to induce apoptosis has proven to be a successful strategy for cancer therapy. Venetoclax, a specific inhibitor of BCL2, has exhibited remarkable efficacy in treating cancers that rely on BCL2 for survival. However, the activity of venetoclax is often limited in other cancers whose survival relies on MCL1, another BCL2 family member. Selective MCL1 inhibitors have been developed and are currently being evaluated in clinical trials. However, the clinical development of these agents has been hampered by toxicity, especially cardiac toxicity. Potentially, another strategy to target MCL1 is by modulating NOXA, a BH3-only protein that selectively binds to MCL1 and mediates its degradation. I hypothesised that increased NOXA expression would prime cancer cells to venetoclax killing and that this would reduce their co-dependence on MCL1. In order to identify new targets to modulate NOXA expression, I generated and validated cell lines that report on NOXA transcription and then carried out CRISPR-Cas9 genetic screens in those NOXA reporter cell lines. In CRISPR-Cas9 loss-of-function screens focused on epigenetic regulators, I found several genes whose mutation or loss modulated NOXA expression, including CTBP1, CHTOP, ZMYM3, SPEN, HSPA1A, KEAP1, FOXA1, HDAC3 and SAP30. Some of these factors have been targeted for cancer therapies, for example KEAP1 and HDAC3, while the others have not yet been recognized for their therapeutic possibilities. Subject to their validation, my results have identified interesting novel mechanisms of NOXA regulation, thus providing the rationale basis for the development of new anti-cancer agents. In CRISPR-Cas9 tiling screens that focused on the NOXA promoter region, five cis-regulatory elements were identified that contributed to regulation of NOXA expression. Among them, a hypermethylated element on the NOXA promoter was found to be important for repressing NOXA expression across diverse cell lines derived from blood cancers. Disrupting this region led to NOXA induction. Potentially, the findings could provide a rational basis of combining hypomethylating agents with venetoclax in a range of haematological malignancies. In summary, several potential NOXA regulating proteins and DNA elements were discovered by the CRISPR-Cas9 screening approaches. Once validated, these findings should provide new insights into NOXA regulation.
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ItemDevelopment of an Editable Approach to the Study Parasite-Erythroid Interactions( 2020)Malaria remains responsible for an enormous health burden worldwide; considerable research effort is being devoted to finding ways to combat the disease and its transmission. Malaria is caused by Plasmodium species, and P. falciparum causes the most serious disease. The blood stage of the P. falciparum remains critically important to understand for development of treatments and vaccines. To initiate invasion, the P. falciparum merozoite recognises specific proteins on the host red cell membrane, known as invasion receptors. In order to study parasite–host interactions, laboratory adapted P. falciparum strains that invade mature human red cells have been used. Gene modification methods are well established for P. falciparum; however, genetic manipulation of the red cell has not been extensively applied because erythrocytes are not nucleated. The in vitro cultivation of erythroid cell lines facilitates both the scalable production of host cells to support P. falciparum invasion and editing of nucleated precursors that can be genetically modified in a precise manner. In this project, two erythroid cell lines – the Human Umbilical cord blood Derived Erythroid Progenitors (HUDEP-2) and the Bristol Erythroid Line- Adult (BEL-A), both of which can differentiate to more mature forms in vitro – were studied as possible host models. A FACS antibody panel, based on the stage-specific profile of HUDEP-2 and BEL-A cells, provided the means to analyse host invasion receptors as well as erythroid maturation markers. Band 3 is a red cell membrane protein with an uncertain role in merozoite invasion. A gene knockout was constructed in expansion stage BEL-A cells using the lentiviral CRISPR/Cas9 system, targeting band 3 which may be involved in merozoite invasion of human erythrocytes. Single-cell-derived clones were isolated and preliminary validation using PCR and flow cytometry was performed to verify disruption of band 3. Completion of work to validate and functionally characterise the band 3 knockout, and experiments to assess effects on invasion, were curtailed by COVID-19 stay-at-home orders issued to Melbourne between March and July 2020. In summary, a genetically editable in vitro erythroid model was defined to study the function of host invasion receptors for P. falciparum merozoite invasion. Clonal band 3- deficient BEL-A cells were generated, thus paving the way for studying their role as invasion receptors.