Stacey D. Finley

Computational modeling of breast cancer metastases predicts response to dual checkpoint inhibition and reveals spatially-informed treatments

The paper develops an agent-based model of breast cancer metastases to predict responses to dual checkpoint inhibition and identifies spatially-informed treatment strategies.

Computational modeling of VEGF-A signaling predicts lymphatic junction state

The paper develops a computational model of VEGF-A signaling in lymphatic endothelial cells to predict junction state transitions and shows how obesity affects these dynamics in different LEC populations.

A Mechanistic Model of Caspase-mediated Apoptosis Signaling Reveals Regulators of Drug Resistance in Prostate Cancer Cells

The paper develops a mechanistic model of caspase-mediated apoptosis in prostate cancer to identify regulators of drug resistance and predict therapeutic strategies.

Metabolic Reprogramming and Therapeutic Vulnerabilities in the Tumor Microenvironment Revealed by Multi-scale Network Geometry

The paper uses multi-scale network geometry to analyze metabolic reprogramming in colorectal cancer, identifying therapeutic vulnerabilities and architectural changes in metabolic networks.

Prolactin receptor localization and dynamics: Insights from quantitative imaging and mathematical modeling

The paper uses live-cell imaging and mathematical modeling to study PRLR internalization dynamics and their impact on signaling in pancreatic β-cells.

Cancer-associated fibroblasts drive metabolic heterogeneity in KRAS-mutant colorectal cancer cells

This study uses computational methods to show that CAF-conditioned media increases metabolic heterogeneity in KRAS-mutant CRC cells following enzyme knockdowns.

Multiscale Probabilistic Modeling: A Bayesian Approach to Augment Mechanistic Models of Cell Signaling with Machine-Learning Predictions of Binding Affinity

This paper introduces a multiscale probabilistic framework to improve cell signaling model parameter estimation by integrating protein sequence and structure data from databases.

Merging metabolic modeling and imaging for screening therapeutic targets in colorectal cancer

The paper integrates computational metabolic modeling with experimental validation to identify hexokinase as a therapeutic target in colorectal cancer by analyzing CAF-conditioned tumor organoids.

Integrating mechanism-based T cell phenotypes into a model of tumor-immune cell interactions

The paper develops an integrated Boolean-ABM framework to study how CD8+ T cell properties affect tumor composition, spatial organization, and immune checkpoint blockade efficacy.

Flux Sampling in Genome-scale Metabolic Modeling of Microbial Communities

This study compares flux balance analysis and flux sampling in microbial community metabolism, finding significant differences in predicted interactions and flux patterns.

Information-theoretic analysis of a model of CAR-4-1BB-mediated NFκB activation

The paper applies information theory to analyze CAR-4-1BB-mediated NFκB activation in cell signaling, finding that fold change in nuclear NFκB concentration has higher channel capacity than absolute response.

Agent-based modeling of tumor-immune interactions reveals determinants of final tumor states

The paper uses an agent-based model to simulate tumor-immune interactions and identifies how macrophages and T cells influence tumor progression and final states.

Ensemble-based genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer

The paper uses ensemble-based genome-scale modeling to predict metabolic differences between M1 and M2 macrophage subtypes in colorectal cancer and identifies metabolic perturbations that shift M2 metabolism toward M1.

A data-driven Boolean model explains memory subsets and evolution in CD8+ T cell exhaustion

The paper uses a Boolean model to analyze gene regulatory interactions in CD8+ T cell exhaustion, identifying gene expression states and pathways leading to T cell exhaustion.

Fitting agent-based models to tumor images using representation learning

This paper introduces a method to estimate ABM parameters by quantitatively comparing tumor images and ABM simulations using neural networks.

Systematic Bayesian posterior analysis guided by Kullback-Leibler divergence facilitates hypothesis formation

This paper introduces a KL divergence-based Bayesian framework to systematically rank parameters for hypothesis formation, demonstrating its effectiveness in two computational models.

Kinetic and data-driven modeling of pancreatic β-cell central carbon metabolism and insulin secretion

This paper develops a kinetic and data-driven model of pancreatic β-cell metabolism to understand its role in glucose-stimulated insulin secretion and predict therapeutic interventions.

Computational analysis of 4-1BB-induced NF κB signaling suggests improvements to CAR cell design

The paper models 4-1BB-induced NFκB signaling in CAR cells to identify design improvements for enhanced antigen response.

Multiscale modeling of tumor adaption and invasion following anti-angiogenic therapy

This study uses agent-based modeling to show that anti-angiogenic therapy creates hypoxic and acidic conditions that increase tumor cell survival and invasiveness, but combining it with chemotherapy improves treatment response.

Phosphatases are predicted to govern prolactin-mediated JAK-STAT signaling in pancreatic beta cells

The paper uses a computational model to show that phosphatase concentrations and prolactin receptor levels influence JAK-STAT signaling in pancreatic beta cells, suggesting targets for diabetes treatment.

Modeling predicts differences in CAR T cell signaling due to biological variability

The paper uses mathematical modeling to show that CD28-bearing CARs lead to faster and more consistent T cell responses under variability, with LCK activity influencing response times.

Elucidating Tumor-stromal Metabolic Crosstalk in Colorectal Cancer through Integration of Constraint-Based Models and LC-MS Metabolomics

This study investigates tumor-stromal metabolic interactions in colorectal cancer by integrating constraint-based models with metabolomics data, revealing how cancer-associated fibroblasts reprogram tumor cell metabolism.

Multi-scale modeling of macrophage - T cell interactions within the tumor microenvironment and impacts of macrophage-based immunotherapies

This study develops an agent-based model to evaluate macrophage-based immunotherapies in the tumor microenvironment, finding that reeducation is the most effective strategy.

An Optimal Control Approach for Enhancing Natural Killer Cells' Secretion of Cytolytic Molecules

This paper develops a mathematical framework to enhance NK cell secretion of cytolytic molecules by optimizing phosphatase inhibition and synthetic Notch signaling based on stimulation frequency.

Dynamic regulation of JAK-STAT signaling through the prolactin receptor predicted by computational modeling

The paper develops a computational model of JAK-STAT signaling through the prolactin receptor in beta cells, showing that receptor upregulation and regulatory modules are needed to match experimental STAT5 dynamics.

Enhancing network activation in Natural Killer cells: Predictions from in silico modeling

This study uses in silico modeling to predict strategies for enhancing NK cell activation by analyzing the CD16, 2B4, and NKG2D signaling pathways.

ERK activation in CAR T cells is amplified by CD28-mediated increase in CD3ζ phosphorylation

The paper constructs a computational model of CAR T cell activation, showing CD28 enhances ERK activation by increasing CD3ζ phosphorylation kinetics.

Data-Driven Analysis of a Mechanistic Model of CAR T Cell Signaling Predicts Effects of Cell-to-cell Heterogeneity

The paper uses computational modeling to analyze CAR T cell signaling and finds that receptor and MAPK cascade protein expressions are key to cellular response, while increased receptor levels can inhibit response due to negative feedback.

Exploring the extracellular regulation of the tumor angiogenic interaction network using a systems biology model

The paper constructs a systems biology model to explore how extracellular pro- and anti-angiogenic factors regulate tumor angiogenesis, revealing a counterintuitive role for PF4 in enhancing pro-angiogenic signaling.

Metabolic reprogramming dynamics in tumor spheroids: Insights from a multicellular, multiscale model

The paper presents a multiscale mathematical model of avascular tumor growth in pancreatic cancer, simulating metabolic reprogramming and its effects on tumor dynamics.