Investigating the evolution of cancer cells through single cell genomic data.
Lead Research Organisation:
University of Oxford
Department Name: Mathematical Institute
Abstract
BBSRC : Thomas Pak : BB/M011224/1
Cancer evolution is inherent to tumour progression. Cell-intrinsic processes such as mutation accumulation, epigenetic modification or translation regulation induce diversity within tumour-comprising cell populations, providing a substrate for evolutionary selection in microenvironmental and therapeutic contexts. Yet, little is known about how to anticipate evolutionary dynamics of a malignant cell population. As such, evolution in cancers is often observed after selection has occurred, for example in the relapsed or metastatic settings-often too late for effective intervention. In this research project, we consider modelling cancer progression processes so as to anticipate, with statistical rigour, the likely growth trajectory of a cancer cell population in the context of unperturbed and perturbed states. Core open questions derived from this concept remain, including the most fundamental: "How can fitness be calculated and used as a predictive property in the growth trajectory of cancer cells?".
Cancer evolution is inherent to tumour progression. Cell-intrinsic processes such as mutation accumulation, epigenetic modification or translation regulation induce diversity within tumour-comprising cell populations, providing a substrate for evolutionary selection in microenvironmental and therapeutic contexts. Yet, little is known about how to anticipate evolutionary dynamics of a malignant cell population. As such, evolution in cancers is often observed after selection has occurred, for example in the relapsed or metastatic settings-often too late for effective intervention. In this research project, we consider modelling cancer progression processes so as to anticipate, with statistical rigour, the likely growth trajectory of a cancer cell population in the context of unperturbed and perturbed states. Core open questions derived from this concept remain, including the most fundamental: "How can fitness be calculated and used as a predictive property in the growth trajectory of cancer cells?".
| Description | This funding is for a GlobalLink placement for a student in my group. Due to COVID-19 it has not been possible for that placement to happen, and so there are no outcomes associated with this award. |
| Exploitation Route | N/A |
| Sectors | Healthcare |