Synchronisation and control of proliferation in cycling cell population models with age structure

International audienceWe present and analyse in this article a mathematical question with a biological origin, the theoretical treatment of which may have far-reaching implications in the practical treatment of cancers. Starting from biological and clinical observations on cancer cells, tumourbearing laboratory rodents, and patients with cancer, we ask from a theoretical biology viewpoint questions that may be transcribed, using physiologically based modelling of cell proliferation dynamics, into mathematical questions. We then show how recent fluorescence-based image modelling techniques performed at the single cell level in proliferating cell populations allow to identify model parameters and how this may be applied to investigate healthy and cancer cell populations. Finally, we show how this modelling approach allows us to design original optimisation methods for anticancer therapeutics, in particular chronotherapeutics, by controlling eigenvalues of the differential operators underlying the cell proliferation dynamics, in tumour and in healthy cell populations. We propose a numerical algorithm to implement these principles

Colorectal Cancer Through Simulation and Experiment

Colorectal cancer has continued to generate a huge amount of research interest over several decades, forming a canonical example of tumourigenesis since its use in Fearon and Vogelstein’s linear model of genetic mutation. Over time, the field has witnessed a transition from solely experimental work to the inclusion of mathematical biology and computer-based modelling. The fusion of these disciplines has the potential to provide valuable insights into oncologic processes, but also presents the challenge of uniting many diverse perspectives. Furthermore, the cancer cell phenotype defined by the ‘Hallmarks of Cancer’ has been extended in recent times and provides an excellent basis for future research. We present a timely summary of the literature relating to colorectal cancer, addressing the traditional experimental findings, summarising the key mathematical and computational approaches, and emphasising the role of the Hallmarks in current and future developments. We conclude with a discussion of interdisciplinary work, outlining areas of experimental interest which would benefit from the insight that mathematical and computational modelling can provide

Investigating the role of a FAM111B mutation in hereditary fibrosing poikiloderma (POIKTMP) using induced pluripotent stem cell (iPSC) model

Hereditary fibrosing poikiloderma is an autosomal dominant disorder that is characterised by mottled pigmentation and telangiectasia, accompanied by tendon contractures, myopathy and pulmonary fibrosis (POIKTMP). Mutations in POIKTMP cases have been shown to harbour the Family with sequence similarity 111B (FAM111B) gene. However, its function is unknown. The aim of this study was to investigate the causative role of the FAM111B mutation (c.1861T>G) in the multi-systemic fibrosis affecting the South African kindred with POIKTMP. Dermal fibroblasts from two affected siblings and a familial control were reprogrammed into induced pluripotent stem cells (iPSCs) via the Sendai virus vector (SeVdp) packaged with pluripotency transgenes (OCT4; SOX2; KLF4; C-MYC). The derived iPSCs successfully showed a) endogenous expression of pluripotency markers (OCT4; NANOG; TRA-1-60), b) in vitro differentiation into the three germ layers (endoderm; mesoderm; ectoderm) and c) normal karyotyping. Next, the iPSCs from two patients, a Familial control and a Non-familial control were differentiated into mesenchymal stem/stromal cells (iPSC-MSCs) as a cell model in this study. Characterisation of derived iPSC-MSCs indicated positive expression of MSC markers (CD73; CD90; α-SMA). Differentiation of iPSC-MSCs demonstrated adequate osteogenicity but limited adipogenicity. Patient-derived iPSC-MSCs were thereafter analysed by qPCR and collagen staining to determine whether the FAM111B mutation alters endogenous expression of pro-fibrotic markers as well as collagen synthesis in patient cells compared to controls. Messenger RNA expression of pro-fibrotic markers (COL1A1; COL3A1; α-SMA) was similar between patient and control iPSC-MSCs. Collagen staining and quantification also showed no statistical differences between patient and control cells. These results suggest that FAM111B does not directly alter the expression of these profibrotic genes in this in vitro model system. Growth curves were then carried out to investigate if the FAM111B mutation modulates cell proliferation and it was found that patient cells proliferated at a higher rate compared to controls. To explore the mechanisms underlying the rate change, analyses of FAM111B expression during cell cycle progressions were conducted. Extensive optimization experiments using the double thymidine block approach were necessary to establish the appropriate synchronization protocol, keeping in mind the extended doubling time of iPSCMSCs. The results revealed that FAM111B mRNA expression was temporally regulated, with a peak at the S-phase and low at the G2/M phase. While there were no pattern differences between patient and control cells, FAM111B mRNA expression was significantly higher in the patient cells compared to controls at the G1- and S-phase. These results suggest that the mutation in FAM111B might affect the stability or perdurance of the mRNA. Unfortunately, analysis of the FAM111B protein data was inconclusive. Problems related to synchronization of the cells and the specificity of the antibody would have to be rectified in order to follow this further. The overall findings in this in vitro study reveal that the FAM111B mutation does not alter expression of pro-fibrotic markers but does affect the cell proliferation rate of patient cells compared to controls. Future work will focus on further optimisation of iPSC-MSCs synchronisation to determine correlation of FAM111B mRNA and protein expression during cell cycle progression in the patient cells. Furthermore, 3D in vitro cellular models that recapitulate some parts of the POIKTMP phenotype will need to be created. Future work will also explore the gain-of-function hypothesis to further understand the role of FAM111B in fibrosis and cancer phenotype in POIKTMP