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Oliver, S. M.

Publications and source records attributed to Oliver, S. M..

2 recordsLinked to original sources

Investigating the Impact of Omental Adipocytes on Ovarian Cancer: Insights from a 3D in-silico model

1Ovarian cancer is responsible for the most deaths of all gynaecological cancers in the Western world [1]. The symptoms of ovarian cancer are typically subtle and alike to less lethal diseases found more prevalently in the population, frequently resulting in late diagnoses and advanced tumour stages upon treatment initiation [2]. While surgery and platinum-based treatments can be curative, ovarian cancers found at the latter, metastasised stages are likely to be recurrent and more tailored towards palliative care [3]. Metastasised ovarian cancer spreads to surrounding organs and tissues such as the greater omentum [4], a large fat pad composed of adipose tissue stretching from the stomach and hanging over the intestines. The location of this is key in its role towards ovarian cancer and its progression [5]. In this study, we develop a mathematical model to investigate the role that adipocytes found in adipose tissue can have in ovarian cancer progression. Observations of biological experiments from two cell lines create foundations to build a multiscale agent-based model in a Physicell framework. The impact of the adipose derived media concentration, treatment dosage, and initial tumour size are explored to find how these conditions affect the spatio-temporal dynamics of cancer tumours.

cancer biology↗

Exploring the role of EMT in Ovarian Cancer Progression: Insights from a multiscale mathematical model

Epithelial-to-mesenchymal transition (EMT) plays a key role in the progression of cancer tumours and can make treatment significantly less successful for patients. EMT occurs when a cell gains a different phenotype and possesses different behaviours to those previously exhibited. This may result in enhanced drug resistance, higher cell plasticity, and increased metastatic abilities. It has therefore has become essential to encapsulate this change and study tumour progression and its response to treatments. Here, we use a 3D agent-based multiscale modelling framework based on Physicell to investigate the role of EMT over time in two cell lines, OVCAR-3 and SKOV-3. The impact of conditions in the microenvironment are incorporated into the model by modifying cellular behaviours dependant on variables such as substrate concentrations and proximity to neighbouring cells. OVCAR-3 and SKOV-3 cell lines possess highly contrasting tumour layouts, allowing a vast array of different tumour dynamics and morphologies to be tested and studied. The model encapsulates the biological observations and trends seen in tumour growth and development, thus can help to obtain further insights into OVCAR-3 and SKOV-3 cell line dynamics. Sensitivity analysis was performed to investigate the impact of parameter sensitivity on model outcome. Sensitivity analysis showed that parameters used in generating the rate of EMT and cycle rates within the cells are relatively more sensitive than other parameters used.

cancer biology↗