Conveners
Mathematical models of cell motility and cancer progression in microenvironment: design, experiments, mathematical framework, and hypothesis test: Part A
- Hans Othmer ()
- Yanjin Kim (Konkuk University)
Mathematical models of cell motility and cancer progression in microenvironment: design, experiments, mathematical framework, and hypothesis test: Part B
- Yangjin Kim (Konkuk University)
- Hans Othmer (Dr. and Mrs.)
Description
Cancer is a complex, multi-scale process, in which genetic mutations occurring at a sub-cellular level manifest themselves as functional changes at the cellular and tissue scale. The main aim of this session is to discuss current stages and challenges in modelling tumour growth and developing therapeutic strategies. Specific goals of the session include: (i) to analyse both computational and analytical solutions to mathematical models from tumour modelling (ii) to discuss creative ways of laboratory experimentation for better clinical diagnosis (iii) to improve our biochemical/biomechanical understanding of fundamental mechanism of tumour growth such as analysis of signalling pathways in relative balances between oncogenes and suppressors. Both the immediate microenvironment (cell-cell or cell-matrix interactions) and the extended microenvironment (e.g. vascular bed, stromal cells) are considered to play major roles in tumour progression as well as suppression. Microenvironment is known to control tumour growth and cancer cell invasion to surrounding stromal tissue. However, it also prohibits therapeutics from accessing the tumour cells, thus causing drug resistance. Therefore, a thorough understanding of the microenvironment would provide a foundation to generate new strategies in therapeutic drug development. At the cellular level, cancer cell migration is a main step for metastasis and further progression of cancer and metastasis in a given microenvironment. Thus, understanding of cell motility under the control of signal transduction pathways in the presence of fibril network of ECM would improve technical and specific advances in cancer therapy by targeting the specific pathways that are associated with the diseases. Analysis of mathematical models would identify fundamental (abstract) structure of the model system and shed a light on our understanding of tumour growth in the specific host tissue environment and biochemical and biomechanical interactions between players in cancer progression. More comprehensive multi-scale (hybrid) models can be used to meet the needs of designing patient-specific agents.
Cell locomotion is essential for early development, angiogenesis, tissue regeneration, the immune response, and wound healing in multicellular organisms, and plays a very deleterious role in cancer metastasis in humans. Locomotion involves the detection and transduction of extracellular chemical and mechanical signals, integration of the signals into an intracellular signal, and the...
Oncolytic viruses such as herpes simplex virus-1 (oHSV) are genetically modified to target and kill cancer cells while not harming healthy normal cells and are currently under multiple clinical trials for safety and efficacy [1]. Bortezomib is a peptide-based proteasome inhibitor and is an FDA-approved drug for myeloma and mantle cell lymphoma. Yoo et al. [2] have previously demonstrated...
The mathematical modelling of metastasis is a challenge. The occurrence of metastasis is basically random, hence the use of stochastic modelling seems appropriate. We introduce a stochastic process called branched random walk with settlement to derive equations for the expected number of particles, the variance, the furthest particle and the extinction probability. We are able to identify a...
To date we have no understanding of why two patients with similar clinical stage and molecular profile would have different radiotherapy outcomes. Reliable biomarkers are direly needed to predict which patients will be cured, with the hope to de-escalate dose when possible or increase where necessary. It is increasingly appreciated that radiation can induce a robust antitumour immune response...
Epithelial Ovarian Cancer (EOC) is one of the deadliest cancers in women. It is the fifth leading cause of cancer-related deaths in the United States. Due to the lack of early detection, this cancer has an average 5-year survival of only 27%. We know, that like other epithelial cancers, ovarian tumour cells remodel the extracellular matrix (ECM) components in healthy tissue in order to promote...
