Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks. (February 2015)
- Record Type:
- Journal Article
- Title:
- Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks. (February 2015)
- Main Title:
- Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks
- Authors:
- Gerlee, Philip
Kim, Eunjung
Anderson, Alexander R.A. - Abstract:
- Abstract: In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-inducedAbstract: In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions. … (more)
- Is Part Of:
- Seminars in cancer biology. Volume 30(2015)
- Journal:
- Seminars in cancer biology
- Issue:
- Volume 30(2015)
- Issue Display:
- Volume 30, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 30
- Issue:
- 2015
- Issue Sort Value:
- 2015-0030-2015-0000
- Page Start:
- 30
- Page End:
- 41
- Publication Date:
- 2015-02
- Subjects:
- Genotype to phenotype map -- Microenvironment -- Neural network -- Drug resistance -- Evolution
Cancer -- Periodicals
Neoplasms -- Periodicals
Review Literature
Cancer -- Périodiques
Electronic journals
616.994 - Journal URLs:
- http://www.sciencedirect.com/science/journal/1044579X ↗
http://www.clinicalkey.com/dura/browse/journalIssue/1044579X ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/1044579X ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.semcancer.2014.04.013 ↗
- Languages:
- English
- ISSNs:
- 1044-579X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8239.448340
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 6146.xml