2026-10-11T04:57:58Z https://api.figshare.com/v2/oai

oai:figshare.com:article/32638533 2026-10-01T16:46:11Z portal_1172 item_type_8 month_year_10_2026

Systems medicine approaches to cancer drug resistance and response, towards new clinical tools Kelsey J McCulloch (24168108) PUREID: 527683816 network analysis systems biology bioinformatics prostate cancer Systems biology is a useful approach to modelling complex biological interactions, by using networks to visualise mechanisms controlling disease progression, treatment resistance, or different cancer stages. Cellular biology is very modular, with groups of genes forming pathways. Network analysis to identify clusters is one method to determine the active pathways in each biological state. Prostate cancer is the second most commonly diagnosed cancer in males, and the fifth leading cause of death by cancer globally. <br><br>NetNC is a network analysis tool used to identify clusters in a functional gene network using a list of genes of interest. I further developed this tool to integrate interaction confidence values (as edge weights) and gene activity values (as node weights), known as wNetNC. I predicted that inclusion of these additional data will improve the tool’s performance. I generated new gold-standard datasets to access the performance of the new weighted methods and implemented a training workflow for wNetNC to utilise high-performance cluster computing to reduce the computational time requirements and manage the high number of output files generated.<br><br>Benchmarking against existing network analysis methods (NetNC, NEST, and HC-PIN) showed that wNetNC performed well, often showing significantly better performance, especially when using low or medium noise level genelists. NEST and HC-PIN achieved higher performance than wNetNC at high noise levels. <br>I applied NetNC and wNetNC to an RNA-seq dataset to investigate how network analysis can be applied to single sample data. Additionally, I interpreted the network models for this data to determine the driving mechanisms controlling resistance to radiotherapy in prostate cancer. I developed an analytical workflow to rank the network genes as suitable druggable targets and predicted two novel candidates for drug repurposing to reduce resistance to radiotherapy in prostate cancer.<br><br><br> 2026-10-01T16:46:11Z Text Thesis 10.17034/32638533.v1 https://figshare.com/articles/thesis/Systems_medicine_approaches_to_cancer_drug_resistance_and_response_towards_new_clinical_tools/32638533 All Rights Reserved