SACM - Australia
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Item Restricted Assessment of Immunotherapy-Related Adverse Events Among Patients with Cancer in Saudi Arabia: A Mixed Methods Study(Queensland university of techonology, 2024) Alquzi, Fatimah; Bradford, NatalieThis thesis contributes significantly to cancer care by focusing on patients undergoing immunotherapy in Saudi Arabia. it is the first study to explore the challenges these patients face, offering valuable insight into their experience. the research translated and validated an immunotherapy assessment tool and assessed its real world use by evaluating its acceptability, feasibility, and clinical utility. this study deepens the understanding of immune related adverse events and provide critical perspectives for clinicians, patients, and researcher. Ultimately, it contributes to improving the management of adverse events in cancer immunotherapy. Background: Cancer is a rapidly growing healthcare system challenge, with more than 19.3 million incidences recorded globally in 2020; this is projected to surpass 29.5 million by 2040. The emergence of immunotherapy has positively changed many advanced cancer outcomes and improved survival rates. Despite immunotherapy being an efficacious and reliable treatment option for cancer, its success is tempered by associated immune-related adverse events (irAEs). Limited understanding of proactive irAE assessment further complicates this issue. Patient Reported Outcome (PRO) measures are standardised tools used to systematically collect data from patients about their health status, symptoms, functioning, and well-being, and are increasingly advocated for use in routine clinical care. However, their use in clinical care, and more specifically to assess irAEs and symptoms, is an understudied area. Objectives: To investigate the feasibility, acceptability, and usefulness of systematic assessment of irAEs from the perspectives of patients with cancer living in Saudi Arabia. Methods: The doctorate project involved five inter-related studies, underpinned by the theory of Symptoms Experience in Time (SET), a conceptual framework aimed at understanding the temporal dynamics of symptom manifestation and progression. In Study 1, a systematic literature review was completed. A comprehensive search strategy was employed to identify relevant literature on symptom assessment and management strategies related to irAEs in cancer patients. The review identified a PRO tool developed specifically for irAEs to assess 20 symptom and six interference items. In Study 2, the PRO tool identified for irAEs assessment from the review underwent robust translation from English into Arabic using the Brislin translation method. This involved forward and backward translations, consensus committees with health experts and linguists, and iterative adjustments to ensure linguistic accuracy and cultural appropriateness. Study 3 was an observational study undertaken in Saudi Arabia to evaluate the psychometric properties of the tool among Saudi Arabian cancer patients undergoing immunotherapy. The assessment involved mixed methods, including cognitive interviewing to assess item clarity and relevance, content validity and test–retest reliability analysis, and a post-assessment feedback survey to assess acceptability. Study 4 was a prospective observational cohort study over four weeks that investigated the feasibility, acceptability, and usefulness of the translated tool to assess irAEs and symptom experiences of patients undergoing immunotherapy for cancer in Saudi Arabia. Finally, in Study 5, a subset of participants from Study 4 participated in in-depth semi-structured interviews, which were analysed using qualitative content analysis. Results: Study 1: The systematic literature review identified a suitable PRO tool for assessing diverse irAEs among cancer patients undergoing immunotherapy. The review also identified gaps in evidence, including the unclear frequency of symptom assessment and the role of non-pharmacological approaches for managing mild irAEs. In Study 2, the PRO tool was translated, creating the Arabic version of the tool: the Arabic Immunotherapy Symptom Assessment Inventory (AISAI). Study 3 evaluated the psychometric properties of the AISAI, which demonstrated content validity, reliability, linguistic precision, and cultural relevance. The Cronbach’s alpha coefficients for the internal consistency were calculated as 0.90 for the 20 symptom items and 0.88 for the interference scale, indicating satisfactory reliability. The test–retest reliability, assessed through intraclass correlation coefficients (ICC), showed excellent agreement between Time 1 and Time 2, with ICC values above 0.90. In Study 4, a real-world, 4-week evaluation involving a cohort of 69 patients undergoing cancer immunotherapy treatment was completed. The feasibility and acceptability of administering the AISAI were high, with 97.1% affirming its acceptability and applicability. The five most prevalent and severe symptoms, based on mean scores, were: numbness or tingling; pain; rash or skin change; interference with general activity; and impaired walking. Over the 4- week immunotherapy period, there was a notable increase in the severity of symptoms, with statistically significant changes observed. The number of participants with moderate (score 4–6) and severe (score 6–10) symptoms increased, indicating a worsening pattern over time. In Study 5, a qualitative evaluation affirmed that the AISAI was perceived as a valuable tool for early recognition and assessment of irAEs, with a preference for routine usage. The evaluation also highlighted knowledge gaps, emphasising the need for educational interventions to enhance comprehension and management capabilities among patients. Conclusion: This thesis represents a novel contribution to the field, particularly in the context of cancer patients undergoing immunotherapy treatment in Saudi Arabia. It introduces an innovative approach by incorporating PROs in Saudi Arabia. This marks a significant advancement in the assessment practices related to irAEs. Notably, it is the first study to explore the experience of irAEs in Saudi Arabia using PRO, providing a comprehensive understanding of the challenges faced by these patients. Moreover, this research pioneers the investigation of the use of the AISAI in real-world settings for cancer patients undergoing immunotherapy. It assesses the tool’s acceptability, feasibility, and usefulness, shedding light on its practical implications in the clinical setting. The research contributes a valid and comprehensive tool, the AISAI, designed specifically for assessing irAEs in Arabic cancer patients. This research makes a valuable contribution to clinicians, patients, and researchers, enhancing the overall understanding and approach to assessment of adverse events in the context of cancer immunotherapy.22 0Item Restricted Using Artificial Intelligence to Improve the Diagnosis and Treatment of Cancer(The University of Melbourne, 2024-02-01) Aljarf, Raghad; Ascher, DavidCancer is a complex and heterogeneous disease driven by the accumulation of mutations at the genetic and epigenetic levels—making it particularly challenging to study and treat. Despite Whole-genome sequencing approaches identifying thousands of variations in cancer cells and their perturbations, fundamental gaps persist in understanding cancer causes and pathogenesis. Towards this, my PhD focused on developing computational approaches by leveraging genomic and experimental data to provide fundamental insights into cancer biology, improve patient diagnosis, and guide therapeutic development. The increased mutational burden in most cancers can make it challenging to identify mutations essential for tumorigenesis (drivers) and those that are just background accumulation (passenger), impacting the success of targeted treatments. To overcome this, I focused on using insights about the mutations at the protein sequence and 3D structure level to understand the genotype-phenotype relationship to tumorigenesis.I have looked at proteins that participate in two DNA repair processes: primarily non homologous end joining (NHEJ) along with eukaryotic homologous recombination (HR), where missense mutations have been linked to many diverse cancers. The molecular consequences of these mutations on protein dynamics, stability, and binding affinities to other interacting partners were evaluated using in silico biophysical tools. This highlighted that cancer-causing mutations were associated with structure destabilization and altered protein conformation and network topology, thus impacting cell signalling and function. Interestingly, my work on NHEJ DNA repair machinery highlighted diverse driving forces for carcinogenesis among core components like Ku70/80 and DNA-PKcs. Cancer-causing mutations in anchor proteins (Ku70/80) impacted crucial protein-protein interactions, while those in catalytic components (DNA-PKcs) were likely to occur in regions undergoing purifying selection. This insight led to a consensus predictor for identifying driving mutations in NHEJ. While when assessing the functional consequences of BRCA1 and BRCA2 genes of HR DNA repair at the protein sequence level, this methodology underlined that cancer-causing mutations typically clustered in well-established structural domains. Using this insight, I developed a more accurate predictor for classifying pathogenic mutations in HR repair compared to existing approaches.This broad heterogeneity of cancers complicates potential treatment opportunities. I, therefore, next explored the properties of compounds potentially active against one or various types of cancer, including screens against 74 distinct cancer cell lines originating from 9 tumour types. Overall, the identified active molecules were shown to be enriched in benzene rings, aligning with Lipinski's rule of five, although this might reflect screening library biases. These insights enabled the development of a predictive platform for anticancer activity, thereby optimizing screening libraries with potentially active anticancer molecules.Similarly, I used compounds' structural and molecular properties to accurately predict those compounds with increased teratogenicity early in the drug development process and prioritize drug combinations to augment combinatorial screening libraries, potentially alleviating acquired drug resistance. The outcomes of this doctoral work highlight the potential benefits of using computational approaches in unravelling the underlying mechanisms of carcinogenesis and guiding drug discovery for designing more effective therapies. Ultimately, the predictions generated by these tools would improve our understanding of the genotype-phenotype association, enabling promising patient diagnosis and treatment.26 0Item Restricted Iron-gold Nano-delivery Approaches for Cancer Cell Targeting and T-cell Redirecting(Saudi Digital Library, 2023-12-09) Tarkistani, Mariam; Kayser, VayselCancer is one of the most significant global public health issues. During the past several decades, substantial efforts have been undertaken to fight cancer. Traditional cancer treatments involve chemotherapy, surgery, and radiotherapy. However, these treatments are quite invasive and have varying success rates and adverse effects. Thus, more innovative strategies are required to treat cancer. Targeted drug delivery is among the most promising innovative strategies. Every tumour has overexpressed special receptors; hence, delivery of a specifically targeted drug to those receptors can induce tumour regression. Drug delivery to the tumour can be achieved using nanoparticles. However, bioavailability could still be poor even with targeted drug delivery and when administered directly into the bloodstream. The bioavailability of nanomaterials can be improved greatly when delivered using a T-cell engager nanoparticles-based carrier system. The aim of this thesis is to develop a next generation nanoparticle (NPs) based on immunotherapy T-cell engager. The NP complex will activate and recruit immune cells to cancer site in order to facilitate their killing effect. The new platform described in this thesis could potentially be used for a variety of solid cancer types. We thoroughly characterised our bispecifics and evaluated their cytotoxic capacity. Based on cytotoxic tests, our bispecifics are excellent drug candidates for various types of cancer. This idea paves the way to target two mechanisms. The mechanisms include recognising and targeting cancer cells and activating T-cells to induce an immune response involving T-cell proliferation and cytokine production, which leads to the elimination of cancer cells. These concepts are further discussed in subsequent chapters of this thesis.17 0