scholarly journals Integrating experimental data to calibrate quantitative cancer models

2015 ◽  
Author(s):  
Heiko Enderling
Keyword(s):  
Differential Equation ◽  
Experimental Data ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Cancer Cells ◽  
Unknown Parameters ◽  
Agent Based ◽  
Cancer Models ◽  
Differential Equation Models ◽  
Model Dynamics

For quantitative cancer models to be meaningful and interpretable the number of unknown parameters must be kept minimal. Experimental data can be utilized to calibrate model dynamics rates or rate constants. Proper integration of experimental data, however, depends on the chosen theoretical framework. Using live imaging of cell proliferation as an example, we show how to derive cell cycle distributions in agent-based models and averaged proliferation rates in differential equation models. We focus on a tumor hierarchy of cancer stem and progenitor non-stem cancer cells.

scholarly journals Learning differential equation models from stochastic agent-based model simulations

2021 ◽  
Vol 18 (176) ◽  
Author(s):  
John T. Nardini ◽  
Ruth E. Baker ◽  
Matthew J. Simpson ◽  
Kevin B. Flores
Keyword(s):  
Differential Equation ◽  
Cell Biology ◽  
Coarse Grained ◽  
Disease Spread ◽  
Agent Based Model ◽  
Agent Based Models ◽  
Agent Based ◽  
Model Simulations ◽  
Differential Equation Models ◽  
Model Dynamics

Agent-based models provide a flexible framework that is frequently used for modelling many biological systems, including cell migration, molecular dynamics, ecology and epidemiology. Analysis of the model dynamics can be challenging due to their inherent stochasticity and heavy computational requirements. Common approaches to the analysis of agent-based models include extensive Monte Carlo simulation of the model or the derivation of coarse-grained differential equation models to predict the expected or averaged output from the agent-based model. Both of these approaches have limitations, however, as extensive computation of complex agent-based models may be infeasible, and coarse-grained differential equation models can fail to accurately describe model dynamics in certain parameter regimes. We propose that methods from the equation learning field provide a promising, novel and unifying approach for agent-based model analysis. Equation learning is a recent field of research from data science that aims to infer differential equation models directly from data. We use this tutorial to review how methods from equation learning can be used to learn differential equation models from agent-based model simulations. We demonstrate that this framework is easy to use, requires few model simulations, and accurately predicts model dynamics in parameter regions where coarse-grained differential equation models fail to do so. We highlight these advantages through several case studies involving two agent-based models that are broadly applicable to biological phenomena: a birth–death–migration model commonly used to explore cell biology experiments and a susceptible–infected–recovered model of infectious disease spread.

Cancer Treatment with Liposomes Based Drugs and Genes Co-delivery Systems

2018 ◽  
Vol 25 (28) ◽  
pp. 3319-3332 ◽  
Author(s):  
Chuanmin Zhang ◽  
Shubiao Zhang ◽  
Defu Zhi ◽  
Jingnan Cui
Keyword(s):  
Cell Cycle ◽  
Cancer Cells ◽  
Synergistic Effects ◽  
Resistance Mechanisms ◽  
Delivery Systems ◽  
Cell Cycle Checkpoints ◽  
Drug Efflux ◽  
Cancer Resistance ◽  
Cancer Models ◽  
Anti Cancer

There are several mechanisms by which cancer cells develop resistance to treatments, including increasing anti-apoptosis, increasing drug efflux, inducing angiogenesis, enhancing DNA repair and altering cell cycle checkpoints. The drugs are hard to reach curative effects due to these resistance mechanisms. It has been suggested that liposomes based co-delivery systems, which can deliver drugs and genes to the same tumor cells and exhibit synergistic anti-cancer effects, could be used to overcome the resistance of cancer cells. As the co-delivery systems could simultaneously block two or more pathways, this might promote the death of cancer cells by sensitizing cells to death stimuli. This article provides a brief review on the liposomes based co-delivery systems to overcome cancer resistance by the synergistic effects of drugs and genes. Particularly, the synergistic effects of combinatorial anticancer drugs and genes in various cancer models employing multifunctional liposomes based co-delivery systems have been discussed. This review also gives new insights into the challenges of liposomes based co-delivery systems in the field of cancer therapy, by which we hope to provide some suggestions on the development of liposomes based co-delivery systems.

scholarly journals Matrix degradation and cell proliferation are coupled to promote invasion and escape from an engineered human breast microtumor

2021 ◽  
Vol 13 (1) ◽  
pp. 17-29
Author(s):  
Emann M Rabie ◽  
Sherry X Zhang ◽  
Andreas P Kourouklis ◽  
A Nihan Kilinc ◽  
Allison K Simi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Type I ◽  
Matrix Degradation ◽  
Human Breast ◽  
Rate Of Invasion

Abstract Metastasis, the leading cause of mortality in cancer patients, depends upon the ability of cancer cells to invade into the extracellular matrix that surrounds the primary tumor and to escape into the vasculature. To investigate the features of the microenvironment that regulate invasion and escape, we generated solid microtumors of MDA-MB-231 human breast carcinoma cells within gels of type I collagen. The microtumors were formed at defined distances adjacent to an empty cavity, which served as an artificial vessel into which the constituent tumor cells could escape. To define the relative contributions of matrix degradation and cell proliferation on invasion and escape, we used pharmacological approaches to block the activity of matrix metalloproteinases (MMPs) or to arrest the cell cycle. We found that blocking MMP activity prevents both invasion and escape of the breast cancer cells. Surprisingly, blocking proliferation increases the rate of invasion but has no effect on that of escape. We found that arresting the cell cycle increases the expression of MMPs, consistent with the increased rate of invasion. To gain additional insight into the role of cell proliferation in the invasion process, we generated microtumors from cells that express the fluorescent ubiquitination-based cell cycle indicator. We found that the cells that initiate invasions are preferentially quiescent, whereas cell proliferation is associated with the extension of invasions. These data suggest that matrix degradation and cell proliferation are coupled during the invasion and escape of human breast cancer cells and highlight the critical role of matrix proteolysis in governing tumor phenotype.

scholarly journals The potential oncogenic and MLN4924-resistant effects of CSN5 on cervical cancer cells

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Huilin Zhang ◽  
Ping He ◽  
Qing Zhou ◽  
Yan Lu ◽  
Bingjian Lu
Keyword(s):  
Cell Cycle ◽  
Cervical Cancer ◽  
Cell Proliferation ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Cervical Cancer Cell ◽  
Cervical Cancers ◽  
Cervical Cancer Cells

Abstract Background CSN5, a member of Cop9 signalosome, is essential for protein neddylation. It has been supposed to serve as an oncogene in some cancers. However, the role of CSN5 has not been investigated in cervical cancer yet. Methods Data from TCGA cohorts and GEO dataset was analyzed to examine the expression profile of CSN5 and clinical relevance in cervical cancers. The role of CSN5 on cervical cancer cell proliferation was investigated in cervical cancer cell lines, Siha and Hela, through CSN5 knockdown via CRISPR–CAS9. Western blot was used to detect the effect of CSN5 knockdown and overexpression. The biological behaviors were analyzed by CCK8, clone formation assay, 3-D spheroid generation assay and cell cycle assay. Besides, the role CSN5 knockdown in vivo was evaluated by xenograft tumor model. MLN4924 was given in Siha and Hela with CSN5 overexpression. Results We found that downregulation of CSN5 in Siha and Hela cells inhibited cell proliferation in vitro and in vivo, and the inhibitory effects were largely rescued by CSN5 overexpression. Moreover, deletion of CSN5 caused cell cycle arrest rather than inducing apoptosis. Importantly, CSN5 overexpression confers resistance to the anti-cancer effects of MLN4924 (pevonedistat) in cervical cancer cells. Conclusions Our findings demonstrated that CSN5 functions as an oncogene in cervical cancers and may serve as a potential indicator for predicting the effects of MLN4924 treatment in the future.

scholarly journals Induction of apoptosis and cell cycle arrest by chloroform fraction of Juniperus phoenicea and chemical constituents analysis

2021 ◽  
Vol 19 (1) ◽  
pp. 119-127
Author(s):  
Ibrahim O. Barnawi ◽  
Fahd A. Nasr ◽  
Omar M. Noman ◽  
Ali S. Alqahtani ◽  
Mohammed Al-zharani ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Proliferation ◽  
Cell Cycle Arrest ◽  
Cancer Cells ◽  
Chloroform Fraction ◽  
Active Fraction ◽  
Cycle Arrest ◽  
Juniperus Phoenicea ◽  
Medicinal Properties ◽  
Mcf 7

Abstract Different phytochemicals from various plant species exhibit promising medicinal properties against cancer. Juniperus phoenicea is a plant species that has been found to present medicinal properties. Herein, crude extract and fractions of J. phoenicea were examined to determine its anticancer properties against several cancer cells. The active fraction was chosen to assess its activity on cell cycle progression and apoptosis induction by annexin and propidium iodide (PI) biomarkers. Further, phytochemical screening for possible contents of active fraction using gas chromatography–mass spectrometry (GC-MS) analysis was conducted. It was demonstrated that cell proliferation was suppressed, and the MCF-7 cell line was the most sensitive to J. phoenicea chloroform fraction (JPCF), with the IC50 values of 24.5 μg/mL. The anti-proliferation activity of JPCF in MCF-7 cells was linked to the aggregation of cells in the G1 phase, increases in early and late apoptosis as well as necrotic cell death. Contents analysis of JPCF using GC-MS analysis identified 3-methyl-5-(2′,6′,6′-trimethylcyclohex-1′-enyl)-1-penten-3-ol (16.5%), methyl 8-oxooctanoate (15.61%), cubenol (13.48%), and 7-oxabicyclo [2.2.1] heptane (12.14%) as major constituents. Our present study provides clear evidence that J. phoenicea can inhibit cell proliferation, trigger cell cycle arrest, and induce apoptosis in tested cancer cells.

scholarly journals Maximum Likelihood Inference for Univariate Delay Differential Equation Models with Multiple Delays

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-14
Author(s):  
Ahmed A. Mahmoud ◽  
Sarat C. Dass ◽  
Mohana S. Muthuvalu ◽  
Vijanth S. Asirvadam
Keyword(s):  
Differential Equation ◽  
Maximum Likelihood ◽  
Delay Differential Equation ◽  
Information Matrix ◽  
Likelihood Inference ◽  
Multiple Delays ◽  
Unknown Parameters ◽  
Differential Equation Models ◽  
Delay Differential ◽  
Initial Starting

This article presents statistical inference methodology based on maximum likelihoods for delay differential equation models in the univariate setting. Maximum likelihood inference is obtained for single and multiple unknown delay parameters as well as other parameters of interest that govern the trajectories of the delay differential equation models. The maximum likelihood estimator is obtained based on adaptive grid and Newton-Raphson algorithms. Our methodology estimates correctly the delay parameters as well as other unknown parameters (such as the initial starting values) of the dynamical system based on simulation data. We also develop methodology to compute the information matrix and confidence intervals for all unknown parameters based on the likelihood inferential framework. We present three illustrative examples related to biological systems. The computations have been carried out with help of mathematical software: MATLAB® 8.0 R2014b.

scholarly journals ZIC1 Is a Putative Tumor Suppressor in Thyroid Cancer by Modulating Major Signaling Pathways and Transcription Factor FOXO3a

2014 ◽  
Vol 99 (7) ◽  
pp. E1163-E1172 ◽  
Author(s):  
Wei Qiang ◽  
Yuan Zhao ◽  
Qi Yang ◽  
Wei Liu ◽  
Haixia Guan ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Proliferation ◽  
Transcription Factor ◽  
Thyroid Cancer ◽  
Tumor Suppressor ◽  
Cancer Cells ◽  
Colony Formation ◽  
Promoter Hypermethylation ◽  
Migration And Invasion ◽  
Thyroid Cancer Cells

Context: ZIC1 has been reported to be overexpressed and plays an oncogenic role in some brain tumors, whereas it is inactivated by promoter hypermethylation and acts as a tumor suppressor in gastric and colorectal cancers. However, until now, its biological role in thyroid cancer remains totally unknown. Objectives: The aim of this study is to explore the biological functions and related molecular mechanism of ZIC1 in thyroid carcinogenesis. Setting and Design: Quantitative RT-PCR (qRT-PCR) was performed to evaluate mRNA expression of investigated genes. Methylation-specific PCR was used to analyze promoter methylation of the ZIC1 gene. The functions of ectopic ZIC1 expression in thyroid cancer cells were determined by cell proliferation and colony formation, cell cycle and apoptosis, as well as cell migration and invasion assays. Results: ZIC1 was frequently down-regulated by promoter hypermethylation in both primary thyroid cancer tissues and thyroid cancer cell lines. Moreover, our data showed that ZIC1 hypermethylation was significantly associated with lymph node metastasis in patients with papillary thyroid cancer. Notably, restoration of ZIC1 expression in thyroid cancer cells dramatically inhibited cell proliferation, colony formation, migration and invasion, and induced cell cycle arrest and apoptosis by blocking the activities of the phosphatidylinositol-3-kinase (PI3K)/Akt and RAS/RAF/MEK/ERK (MAPK) pathways, and enhancing FOXO3a transcriptional activity. Conclusions: Our data demonstrate that ZIC1 is frequently inactivated by promoter hypermethyaltion and functions as a tumor suppressor in thyroid cancer through modulating PI3K/Akt and MAPK signaling pathways and transcription factor FOXO3a.

The Potential Oncogenic and MLN4924-Resistant Effects of CSN5 on Cervical Cancer Cells

2021 ◽  
Author(s):  
Huilin Zhang ◽  
Ping He ◽  
Qing Zhou ◽  
Yan Lu ◽  
Bingjian Lu
Keyword(s):  
Cell Cycle ◽  
Cervical Cancer ◽  
Cell Proliferation ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Cervical Cancer Cell ◽  
Cervical Cancers ◽  
Cervical Cancer Cells

Abstract BackgroundsCSN5, a member of Cop9 signalosome, is essential for protein neddylation. It has been supposed to serve as an oncogene in some cancers. However, the role of CSN5 has not been investigated in cervical cancer yet.MethodsData from TCGA cohorts and GEO dataset was analyzed to examine the expression profile of CSN5 in cervical cancers. The role of CSN5 on cervical cancer cell proliferation was investigated in cervical cancer cell lines, Siha and Hela, through CSN5 knockdown via CRISPR-CAS9. Western blot was used to detect the effect of CSN5 knockdown and overexpression. CCK8, clone formation assay and cell cycle assay were also employed. Besides, the role CSN5 knockdown in vivo was evaluated by xenograft tumor model. Moreover, MLN4924 was applied in Siha and Hela with CSN5 overexpression.ResultsWe found that downregulation of CSN5 in Siha and Hela cells inhibited cell proliferation in vitro and in vivo, and the inhibitory effects were largely rescued by CSN5 overexpression. Moreover, deletion of CSN5 caused cell cycle arrest rather than inducing apoptosis. Importantly, CSN5 overexpression confers resistance to the anti-cancer effects of MLN4924 (pevonedistat) in cervical cancer cells.ConclusionsOur findings demonstrated that CSN5 functions as an oncogene in cervical cancers and may serve as a potential indicator for predicting the effects of MLN4924 treatment in the future.

scholarly journals MSH2 is required for cell proliferation, cell cycle control and cell invasiveness in colorectal cancer cells

2012 ◽  
Vol 57 (20) ◽  
pp. 2580-2585
Author(s):  
Kai Shen ◽  
YingJiang Ye ◽  
KeWei Jiang ◽  
Bin Liang ◽  
XiaoDong Yang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Cancer Cells ◽  
Cell Cycle Control ◽  
Colorectal Cancer Cells ◽  
Cell Invasiveness

scholarly journals Protein Kinase A-Independent Inhibition of Proliferation and Induction of Apoptosis in Human Thyroid Cancer Cells by 8-Cl-Adenosine

2008 ◽  
Vol 93 (3) ◽  
pp. 1020-1029 ◽  
Author(s):  
Audrey J. Robinson-White ◽  
Hui-Pin Hsiao ◽  
Wolfgang W. Leitner ◽  
Elizabeth Greene ◽  
Andrew Bauer ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Proliferation ◽  
Thyroid Cancer ◽  
Protein Kinase ◽  
Protein Kinase A ◽  
Cancer Cells ◽  
Human Thyroid ◽  
Inhibition Of Proliferation ◽  
Thyroid Cancer Cells ◽  
Kinase A

Abstract Purpose: Protein kinase A (PKA) affects cell proliferation in many cell types and is a potential target for cancer treatment. PKA activity is stimulated by cAMP and cAMP analogs. One such substance, 8-Cl-cAMP, and its metabolite 8-Cl-adenosine (8-Cl-ADO) are known inhibitors of cancer cell proliferation; however, their mechanism of action is controversial. We have investigated the antiproliferative effects of 8-Cl-cAMP and 8-CL-ADO on human thyroid cancer cells and determined PKA’s involvement. Experimental Design: We employed proliferation and apoptosis assays and PKA activity and cell cycle analysis to understand the effect of 8-Cl-ADO and 8-Cl-cAMP on human thyroid cancer and HeLa cell lines. Results: 8-Cl-ADO inhibited proliferation of all cells, an effect that lasted for at least 4 d. Proliferation was also inhibited by 8-Cl-cAMP, but this inhibition was reduced by 3-isobutyl-1-methylxanthine; both drugs stimulated apoptosis, and 3-isobutyl-1-methylxanthine drastically reduced 8-Cl-cAMP-induced cell death. 8-Cl-ADO induced cell accumulation in G1/S or G2/M cell cycle phases and differentially altered PKA activity and subunit levels. PKA stimulation or inhibition and adenosine receptor agonists or antagonists did not significantly affect proliferation. Conclusions: 8-Cl-ADO and 8-Cl-cAMP inhibit proliferation, induce cell cycle phase accumulation, and stimulate apoptosis in thyroid cancer cells. The effect of 8-Cl-cAMP is likely due to its metabolite 8-Cl-ADO, and PKA does not appear to have direct involvement in the inhibition of proliferation by 8-Cl-ADO. 8-Cl-ADO may be a useful therapeutic agent to be explored in aggressive thyroid cancer.

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