Biology subjects

Ramirez-Santiago, G.

Publications and source records attributed to Ramirez-Santiago, G..

4 recordsLinked to original sources

bioRxiv2024

A mathematical model for pancreatic cancer during intraepithelial neoplasia

Cancer is the result of complex interactions of intrinsic and extrinsic cell processes, which promote sustained proliferation, resistance to apoptosis, reprogramming and reorganization. To understand the evolution of any type of cancer it is necessary to understand the role of the microenvironmental conditions and the impact of some molecular complexes and mechanisms on certain signalling pathways. As in most cancer quantitative models, the understanding of the early onset of cancer requires a multiscale analysis of the cellular microenvironment. In this paper we analyse a multiscale model of pancreatic adenocarcinoma by modelling the cellular microenvironment through elastic cell interactions and their intercellular communication mechanisms, such as growth factors and cytokines. We focus on the low-grade dysplasia (PanIN 1) and moderate dysplasia (PanIN 2) stages of the pancreatic adenocarcinoma. To this end we propose a gene regulatory network associated with the processes of proliferation and apoptosis of pancreatic cells and its kinetics in terms delayed differential equations to mimic cell development. Likewise, we couple the cell cycle with the spatial distribution of cells and the transport of growth factors to show that the adenocarcinoma evolution is triggered by inflammatory processes. We show that the oncogene RAS may be an important target to develop anti-inflammatory strategies that limit the emergence of more aggressive adenocarcinomas.

cancer biology↗

bioRxiv2021

Microenvironmental factors in cell segregation and heterogeneity in breast cancer development

We analyzed a quantitative model that describes the epigenetic dynamics during the growth and evolution of an avascular tumor. A gene regulatory network (GRN) formed by a set of ten genes that are believed to play an important role in breast cancer development was kinetically coupled to the microenvironmental agents: glucose, estrogens and oxygen. The dynamics of spontaneous mutations was described by a Yule-Furry master equation whose solution represents the probability that a given cell in the tissue undergoes a certain number of mutations at a given time. We assumed that mutations rate is modified by nutrients spatial gradients. The tumor mass was grown by means of a cellular automata supplemented with a set of reaction diffusion equations that described the transport of the microenvironmental agents. By analyzing the epigenetic states space described by the GRN dynamics, we found three attractors that were identified with the cellular epigenetic states: normal, precancer and cancer. For two-dimensional (2D) and three-dimensional (3D) tumors we calculated the spatial distributions of the following quantities: (i) number of mutations, (ii) mutations of each gene and, (iii) phenotypes. Using estrogens as the principal microenvironmental agent that regulates cells proliferation process, we obtained the tumor shapes for different values of the estrogen consumption and supply rates. It was found that he majority of mutations occurred in cells that were located close to the 2D tumor perimeter or close to the 3D tumor surface. Also It was found that the occurrence of different phenotypes in the tumor are controlled by the levels of estrogen concentration since they can change the individual cell threshold and gene expression levels. All the results were consistently observed for 2D and 3D tumors.

cancer biology↗

bioRxiv2021

DYNAMICS OF NEUROMUSCULAR TRANSMISSION REPRODUCED BY CALCIUM-DEPENDENT SERIAL TRANSITIONS IN THE VESICLE FUSION COMPLEX

Neuromuscular transmission, from spontaneous release to facilitation and depression was accurately reproduced by a mechanistic kinetic model of sequential maturation transitions in the molecular fusion complex. The model incorporates three predictions. First, sequential calcium-dependent forward transitions take vesicles from docked to pre-primed to primed states, followed by fusion. Second, pre-priming and priming are reversible. Third, fusion and recycling are unidirectional. The model was fed with experimental data from previous studies while the backward ({beta}) and recycling ({rho}) rate constant values were fitted. Classical experiments were successfully reproduced when every forward () rate constant had the same value, and both backward rate constants were 50-100 times larger. Such disproportion originated an abruptly decreasing gradient of resting vesicles from docked to primed states. Simulations also predict that: i. Spontaneous release reflects primed to fusion spontaneous transitions. ii. Calcium elevations synchronize the series of forward transitions that lead to fusion. iii Facilitation reflects a transient increase of priming following calcium-dependent transitions. iv. Backward transitions and recycling restore the resting state. v. Depression reflects backward transitions and slow recycling after intense release. Such finely-tuned kinetics offers a mechanism for collective non-linear transitional adaptations of a homogeneous vesicle pool to an ever-changing pattern of electrical activity.

neuroscience↗

bioRxiv2018

Model for breast cancer diversity and spatial heterogeneity

We present and analyze a growth model of an avascular tumor that considers the basic biological principles of proliferation, motility, death and genetic mutations of the cell. From a regulatory network analysis and an analysis of genomic data we identify two sets of genes-a set of six genes and a set of sixteen genes-that are believed to play an important role in the evolution of breast cancer. Considering that cancer cells shape the tissue microenvironment and niches to their competitive advantage, the model assumes that cancer and normal cells compete for essential nutrients and that the rate of the \"driver\" mutations depends on nutrient availability. To this end, we propose a coupling between the transport of nutrients and gene mutations dynamics. Gene mutation dynamics are modeled as a Yule-Furry Markovian process, while transport of nutrients is described with a system of reaction-diffusion equations. For each representative tumor we calculate its diversity, represented by the Shannon index, and its spatial heterogeneity, measured by its fractal dimension. These quantities are important in the clinical diagnosis of tumor malignancy. A tumor malignancy diagram, obtained by plotting diversity versus fractal dimension, is calculated for different values of a parameter {beta}, which is related to the occurrence of driver mutations. It is found that when {beta} < 1, tumors show greater diversity and more spatial heterogeneity as compared with {beta} > 1. More importantly, it is found that the results and conclusions are similar when we use the six-gene set versus sixteen-gene set.

cancer biology↗