A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

Computational analysis of 5-fluorouracil anti-tumor activity in colon cancer using a mechanistic pharmacokinetic/pharmacodynamic model.

5-Fluorouracil (5-FU) is a standard chemotherapeutic agent to treat solid cancers such as breast, colon, head, and neck. Computational modeling plays an essential role in predicting the outcome of chemotherapy and developing optimal dosing strategies. We developed an integrated mechanistic pharmacokinetics/pharmacodynamics (PK/PD) model examining the influence of 5-FU, as an S-phase specific double-strand break (DSB)-inducing agent, on tumor proliferation. The proposed mechanistic PK/PD model simulates the dynamics of critical intermediate components and provides the accurate tumor response prediction. The integrated model is composed of PK, cellular, and tumor growth inhibition (TGI) sub-models, quantitatively capturing the essential drug-related physiological processes. In the cellular model, thymidylate synthase (TS) inhibition, resultant deoxynucleoside triphosphate (dNTP) pool imbalance, and DSB induction are considered, as well as 5-FU incorporation into RNA and DNA. The amount of 5-FU anabolites and DSBs were modeled to drive the kinetics of the pharmacological tumor response. Model parameters were estimated by fitting to literature data. Our simulation results successfully describe the kinetics of the intermediates regulating the 5-FU cytotoxic events and the pattern of tumor suppression. The comprehensive model simulated the tumor volume change under various dose regimens, and its generalizability was attested by comparing it with literature data. The potential causes of the tumor resistance to 5-FU are also investigated through Monte Carlo analysis. The simulation of various dosage regimens helps quantify the relationship between treatment protocols and chemotherapy potency, which will lead to the development of efficacy optimization.

Sickle cell disease biochip: a functional red blood cell adhesion assay for monitoring sickle cell disease.

Sickle cell disease (SCD) afflicts millions of people worldwide and is associated with considerable morbidity and mortality. Chronic and acute vaso-occlusion are the clinical hallmarks of SCD and can result in pain crisis, widespread organ damage, and early movtality. Even though the molecular underpinnings of SCD were identified more than 60 years ago, there are no molecular or biophysical markers of disease severity that are feasibly measured in the clinic. Abnormal cellular adhesion to vascular endothelium is at the root of vaso-occlusion. However, cellular adhesion is not currently evaluated clinically. Here, we present a clinically applicable microfluidic device (SCD biochip) that allows serial quantitative evaluation of red blood cell (RBC) adhesion to endothelium-associated protein-immobilized microchannels, in a closed and preprocessing-free system. With the SCD biochip, we have analyzed blood samples from more than 100 subjects and have shown associations between the measured RBC adhesion to endothelium-associated proteins (fibronectin and laminin) and individual RBC characteristics, including hemoglobin content, fetal hemoglobin concentration, plasma lactate dehydrogenase level, and reticulocyte count. The SCD biochip is a functional adhesion assay, reflecting quantitative evaluation of RBC adhesion, which could be used at baseline, during crises, relative to various long-term complications, and before and after therapeutic interventions.

Computational analysis of androgen receptor dependent radiosensitivity in prostate cancer.

In this study, we quantitatively analyze the mechanism by which androgen deprivation therapy (ADT) is enhancing radiosensitivity in prostate cancer (PCa) patients. It has been shown in laboratory experiments, as well as in patient data in the literature, that the androgen receptor (AR) reduces the effectiveness of ionizing radiation treatment by enhancing the non-homologous end joining (NHEJ) repair of radiation damage. The suppression of AR by ADT suppresses the activity of NHEJ that leads to radiosensitivity in PCa patients. In this paper, we have studied this positive interaction between AR and NHEJ using mathematical models of the NHEJ that we have developed using both the experimental and clinical data for PCa. Our results show that the biological observation of suppression of AR by ADT leading to down-regulation of the first NHEJ protein Ku and NHEJ is a plausible biological mechanism that explains both the experimental and clinical observations in the literature. The presented analysis is the first step in quantitatively analyzing possible treatment scenarios to find the optimal treatment strategies for PCa using the combination treatment with ADT, NHEJ inhibitors, and IR.

Quantitative analysis of the effects of iododeoxyuridine and ionising radiation treatment on the cell cycle dynamics of DNA mismatch repair deficient human colorectal cancer cells.

DNA mismatch repair (MMR) is involved in processing DNA damage following treatment with ionising radiation (IR) and various classes of chemotherapy drugs including iododeoxyuridine (IUdR), a known radiosensitiser. In this study, the authors have developed asynchronous probabilistic cell cycle models to assess the isolated effects of IUdR and IR and the combined effects of IUdR + IR treatments on MMR damage processing. The authors used both synchronous and asynchronous MMR-proficient/MMR-deficient cell populations and followed treated cells for up to two cell cycle times. They have observed and quantified differential cell cycle responses to MMR damage processing following IR and IUdR + IR treatments, principally in the duration of both G1 and G2/M cell cycle phases. The models presented in this work form the foundation for the development of an approach to maximise the therapeutic index for IR and IUdR + IR treatments in MMR-deficient (damage tolerant) cancers.

Developing an in silico model of the modulation of base excision repair using methoxyamine for more targeted cancer therapeutics.

Base excision repair (BER) is a major DNA repair pathway involved in the processing of exogenous non-bulky base damages from certain classes of cancer chemotherapy drugs as well as ionising radiation (IR). Methoxyamine (MX) is a small molecule chemical inhibitor of BER that is shown to enhance chemotherapy and/or IR cytotoxicity in human cancers. In this study, the authors have analysed the inhibitory effect of MX on the BER pathway kinetics using a computational model of the repair pathway. The inhibitory effect of MX depends on the BER efficiency. The authors have generated variable efficiency groups using different sets of protein concentrations generated by Latin hypercube sampling, and they have clustered simulation results into high, medium and low efficiency repair groups. From analysis of the inhibitory effect of MX on each of the three groups, it is found that the inhibition is most effective for high efficiency BER, and least effective for low efficiency repair.

Integration of Principles of Systems Biology and Radiation Biology: Toward Development of in silico Models to Optimize IUdR-Mediated Radiosensitization of DNA Mismatch Repair Deficient (Damage Tolerant) Human Cancers.

Over the last 7 years, we have focused our experimental and computational research efforts on improving our understanding of the biochemical, molecular, and cellular processing of iododeoxyuridine (IUdR) and ionizing radiation (IR) induced DNA base damage by DNA mismatch repair (MMR). These coordinated research efforts, sponsored by the National Cancer Institute Integrative Cancer Biology Program (ICBP), brought together system scientists with expertise in engineering, mathematics, and complex systems theory and translational cancer researchers with expertise in radiation biology. Our overall goal was to begin to develop computational models of IUdR- and/or IR-induced base damage processing by MMR that may provide new clinical strategies to optimize IUdR-mediated radiosensitization in MMR deficient (MMR(-)) "damage tolerant" human cancers. Using multiple scales of experimental testing, ranging from purified protein systems to in vitro (cellular) and to in vivo (human tumor xenografts in athymic mice) models, we have begun to integrate and interpolate these experimental data with hybrid stochastic biochemical models of MMR damage processing and probabilistic cell cycle regulation models through a systems biology approach. In this article, we highlight the results and current status of our integration of radiation biology approaches and computational modeling to enhance IUdR-mediated radiosensitization in MMR(-) damage tolerant cancers.

Analysis of cell cycle dynamics using probabilistic cell cycle models.

In this study, we develop asynchronous probabilistic cell cycle models to quantitatively assess the effect of ionizing radiation on a human colon cancer cell line. We use both synchronous and asynchronous cell populations and follow treated cells for up to 2 cell cycle times. The model outputs quantify the changes in cell cycle dynamics following ionizing radiation treatment, principally in the duration of both Gi and G(2)/M phases.