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Article: Endothelial cells signaling and patterning under hypoxia: a mechanistic integrative computational model including the Notch-Dll4 pathway.

Oliveira, Rebeca Hannah de Melo / Annex, Brian H / Popel, Aleksander S

2024 Volume 15, Page(s) 1351753

Abstract: Introduction: ...

Abstract	Introduction:
Language	English
Publishing date	2024-02-22
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2564217-0
ISSN	1664-042X
ISSN	1664-042X
DOI	10.3389/fphys.2024.1351753
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Article ; Online: Immunoactivating the tumor microenvironment enhances immunotherapy as predicted by integrative computational model.

Popel, Aleksander S

Proceedings of the National Academy of Sciences of the United States of America

2020 Volume 117, Issue 9, Page(s) 4447–4449

MeSH term(s)	Humans ; Immunologic Factors ; Immunotherapy ; Neoplasms ; Tumor Microenvironment
Chemical Substances	Immunologic Factors
Language	English
Publishing date	2020-02-26
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Comment
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.2001050117
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Article ; Online: From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling.

Wang, Hanwen / Arulraj, Theinmozhi / Ippolito, Alberto / Popel, Aleksander S

ArXiv

2024

Abstract: Virtual patients and digital patients/twins are two similar concepts gaining increasing attention in health care with goals to accelerate drug development and improve patients' survival, but with their own limitations. Although methods have been proposed ...

Abstract	Virtual patients and digital patients/twins are two similar concepts gaining increasing attention in health care with goals to accelerate drug development and improve patients' survival, but with their own limitations. Although methods have been proposed to generate virtual patient populations using mechanistic models, there are limited number of applications in immuno-oncology research. Furthermore, due to the stricter requirements of digital twins, they are often generated in a study-specific manner with models customized to particular clinical settings (e.g., treatment, cancer, and data types). Here, we discuss the challenges for virtual patient generation in immuno-oncology with our most recent experiences, initiatives to develop digital twins, and how research on these two concepts can inform each other.
Language	English
Publishing date	2024-03-05
Publishing country	United States
Document type	Preprint
ISSN	2331-8422
ISSN (online)	2331-8422
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Article: Endothelial cells signaling and patterning under hypoxia: a mechanistic integrative computational model including the Notch-Dll4 pathway.

Oliveira, Rebeca Hannah M / Annex, Brian H / Popel, Aleksander S

bioRxiv : the preprint server for biology

2023

Abstract: Several signaling pathways are activated during hypoxia to promote angiogenesis, leading to endothelial cell patterning, interaction, and downstream signaling. Understanding the mechanistic signaling differences between normoxia and hypoxia can guide ... ...

Abstract	Several signaling pathways are activated during hypoxia to promote angiogenesis, leading to endothelial cell patterning, interaction, and downstream signaling. Understanding the mechanistic signaling differences between normoxia and hypoxia can guide therapies to modulate angiogenesis. We present a novel mechanistic model of interacting endothelial cells, including the main pathways involved in angiogenesis. We calibrate and fit the model parameters based on well-established modeling techniques. Our results indicate that the main pathways involved in the patterning of tip and stalk endothelial cells under hypoxia differ, and the time under hypoxia affects how a reaction affects patterning. Interestingly, the interaction of receptors with Neuropilin1 is also relevant for cell patterning. Our simulations under different oxygen concentrations indicate time- and oxygen-availability-dependent responses for the two cells. Following simulations with various stimuli, our model suggests that factors such as period under hypoxia and oxygen availability must be considered for pattern control. This project provides insights into the signaling and patterning of endothelial cells under hypoxia, contributing to studies in the field.
Language	English
Publishing date	2023-05-06
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.05.03.539270
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Article ; Online: Vascular phenotyping of the invasive front in breast cancer using a 3D angiogenesis atlas.

Bhargava, Akanksha / Popel, Aleksander S / Pathak, Arvind P

Microvascular research

2023 Volume 149, Page(s) 104555

Abstract: ... that spans the ITF and TC (i.e. ∼4-5 mm from the tumor's edge). Since such data are often challenging ... 1 mm from the tumor's edge) and TC (i.e. >1 mm from the tumor's edge) of each tumor xenograft ... in terms of distance from the tumor's edge.: Results: The angiogenesis atlas enabled the 3D ...

Abstract	Objective: Vascular remodeling at the invasive tumor front (ITF) plays a critical role in progression and metastasis of triple negative breast cancer (TNBC). Therefore, there is a crucial need to characterize the vascular phenotype (i.e. changes in the structure and function of vasculature) of the ITF and tumor core (TC) in TNBC. This requires high-resolution, 3D structural and functional microvascular data that spans the ITF and TC (i.e. ∼4-5 mm from the tumor's edge). Since such data are often challenging to obtain with most conventional imaging approaches, we employed a unique "3D whole-tumor angiogenesis atlas" derived from orthotopic xenografts to characterize the vascular phenotype of the ITF and TC in TNBC. Methods: First, high-resolution (8 μm) computed tomography (CT) images of "whole-tumor" microvasculature were acquired from eight orthotopic TNBC xenografts, of which three tumors were excised at post-inoculation day 21 (i.e. early-stage) and five tumors were excised at post-inoculation day 35 (i.e. advanced-stage). These 3D morphological CT data were combined with soft tissue contrast from MRI as well as functional data generated in silico using image-based hemodynamic modeling to generate a multi-layered "angiogenesis atlas". Employing this atlas, blood vessels were first spatially stratified within the ITF (i.e. ≤1 mm from the tumor's edge) and TC (i.e. >1 mm from the tumor's edge) of each tumor xenograft. Then, a novel method was developed to visualize and characterize microvascular remodeling and perfusion changes in terms of distance from the tumor's edge. Results: The angiogenesis atlas enabled the 3D visualization of changes in tumor vessel growth patterns, morphology and perfusion within the ITF and TC. Early and advanced stage tumors demonstrated significant differences in terms of their edge-to-center distributions for vascular surface area density, vascular length density, intervessel distance and simulated perfusion density (p ≪ 0.01). Elevated vascular length density, vascular surface area density and perfusion density along the circumference of the ITF was suggestive of a preferential spatial pattern of angiogenic growth in this tumor cohort. Finally, we demonstrated the feasibility of differentiating the vascular phenotypes of ITF and TC in these TNBC xenografts. Conclusions: The combination of a 3D angiogenesis atlas and image-based hemodynamic modeling heralds a new approach for characterizing the role of vascular remodeling in cancer and other diseases.
MeSH term(s)	Humans ; Triple Negative Breast Neoplasms ; Vascular Remodeling ; Neovascularization, Pathologic ; Magnetic Resonance Imaging ; Microvessels/diagnostic imaging ; Microvessels/pathology
Language	English
Publishing date	2023-05-29
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	80307-8
ISSN	1095-9319 ; 0026-2862
ISSN (online)	1095-9319
ISSN	0026-2862
DOI	10.1016/j.mvr.2023.104555
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Article ; Online: Combining Multikinase Tyrosine Kinase Inhibitors Targeting the Vascular Endothelial Growth Factor and Cluster of Differentiation 47 Signaling Pathways Is Predicted to Increase the Efficacy of Antiangiogenic Combination Therapies.

Zhang, Yu / Popel, Aleksander S / Bazzazi, Hojjat

ACS pharmacology & translational science

2023 Volume 6, Issue 5, Page(s) 710–726

Abstract: Angiogenesis is a critical step in tumor growth, development, and invasion. Nascent tumor cells secrete vascular endothelial growth factor (VEGF) that significantly remodels the tumor microenvironment through interaction with multiple receptors on ... ...

Abstract	Angiogenesis is a critical step in tumor growth, development, and invasion. Nascent tumor cells secrete vascular endothelial growth factor (VEGF) that significantly remodels the tumor microenvironment through interaction with multiple receptors on vascular endothelial cells, including type 2 VEGF receptor (VEGFR2). The complex pathways initiated by VEGF binding to VEGFR2 lead to enhanced proliferation, survival, and motility of vascular endothelial cells and formation of a new vascular network, enabling tumor growth. Antiangiogenic therapies that inhibit VEGF signaling pathways were among the first drugs that targeted stroma rather than tumor cells. Despite improvements in progression-free survival and higher response rates relative to chemotherapy in some types of solid tumors, the impact on overall survival (OS) has been limited, with the majority of tumors eventually relapsing due to resistance or activation of alternate angiogenic pathways. Here, we developed a molecularly detailed computational model of endothelial cell signaling and angiogenesis-driven tumor growth to investigate combination therapies targeting different nodes of the endothelial VEGF/VEGFR2 signaling pathway. Simulations predicted a strong threshold-like behavior in extracellular signal-regulated kinases 1/2 (ERK1/2) activation relative to phosphorylated VEGFR2 levels, as continuous inhibition of at least 95% of receptors was necessary to abrogate phosphorylated ERK1/2 (pERK1/2). Combinations with mitogen-activated protein kinase/ERK kinase (MEK) and spingosine-1-phosphate inhibitors were found to be effective in overcoming the ERK1/2 activation threshold and abolishing activation of the pathway. Modeling results also identified a mechanism of resistance whereby tumor cells could reduce pERK1/2 sensitivity to inhibitors of VEGFR2 by upregulation of Raf, MEK, and sphingosine kinase 1 (SphK1), thus highlighting the need for deeper investigation of the dynamics of the crosstalk between VEGFR2 and SphK1 pathways. Inhibition of VEGFR2 phosphorylation was found to be more effective at blocking protein kinase B, also known as AKT, activation; however, to effectively abolish AKT activation, simulations identified Axl autophosphorylation or the Src kinase domain as potent targets. Simulations also supported activating cluster of differentiation 47 (CD47) on endothelial cells as an effective combination partner with tyrosine kinase inhibitors to inhibit angiogenesis signaling and tumor growth. Virtual patient simulations supported the effectiveness of CD47 agonism in combination with inhibitors of VEGFR2 and SphK1 pathways. Overall, the rule-based system model developed here provides new insights, generates novel hypothesis, and makes predictions regarding combinations that may enhance the OS with currently approved antiangiogenic therapies.
Language	English
Publishing date	2023-04-18
Publishing country	United States
Document type	Journal Article
ISSN	2575-9108
ISSN (online)	2575-9108
DOI	10.1021/acsptsci.3c00008
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Article ; Online: Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology.

Arulraj, Theinmozhi / Wang, Hanwen / Ippolito, Alberto / Zhang, Shuming / Fertig, Elana J / Popel, Aleksander S

Briefings in bioinformatics

2024 Volume 25, Issue 3

Abstract: Understanding the intricate interactions of cancer cells with the tumor microenvironment (TME) is a pre-requisite for the optimization of immunotherapy. Mechanistic models such as quantitative systems pharmacology (QSP) provide insights into the TME ... ...

Abstract	Understanding the intricate interactions of cancer cells with the tumor microenvironment (TME) is a pre-requisite for the optimization of immunotherapy. Mechanistic models such as quantitative systems pharmacology (QSP) provide insights into the TME dynamics and predict the efficacy of immunotherapy in virtual patient populations/digital twins but require vast amounts of multimodal data for parameterization. Large-scale datasets characterizing the TME are available due to recent advances in bioinformatics for multi-omics data. Here, we discuss the perspectives of leveraging omics-derived bioinformatics estimates to inform QSP models and circumvent the challenges of model calibration and validation in immuno-oncology.
MeSH term(s)	Humans ; Multiomics ; Network Pharmacology ; Neoplasms/drug therapy ; Neoplasms/genetics ; Medical Oncology ; Computational Biology ; Pharmacology ; Tumor Microenvironment
Language	English
Publishing date	2024-04-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbae131
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Article ; Online: Protocol for simulating macrophage signal transduction and phenotype polarization using a large-scale mechanistic computational model.

Zhao, Chen / Popel, Aleksander S

STAR protocols

2021 Volume 2, Issue 3, Page(s) 100739

Abstract: The ability to measure and analyze the complex dynamic multi-marker features of macrophages is critical for the understanding of their diverse phenotypes and functions in health and disease. To that end, we have recently developed a multi-pathway ... ...

Abstract	The ability to measure and analyze the complex dynamic multi-marker features of macrophages is critical for the understanding of their diverse phenotypes and functions in health and disease. To that end, we have recently developed a multi-pathway computational model that for the first time enables a systems-level characterization of macrophage signaling and activation from quantitative, temporal, dose-dependent, and single-cell aspects. This protocol includes instructions to utilize this model to computationally explore different biological scenarios with high resolution and efficiency. For complete details on the use and execution of this protocol, please refer to Zhao et al. (2021).
MeSH term(s)	Animals ; Computer Simulation ; Macrophages/chemistry ; Macrophages/classification ; Macrophages/cytology ; Models, Biological ; Phenotype ; Signal Transduction/physiology ; Single-Cell Analysis/methods
Language	English
Publishing date	2021-08-12
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	2666-1667
ISSN (online)	2666-1667
DOI	10.1016/j.xpro.2021.100739
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Article: Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition.

Wang, Hanwen / Arulraj, Theinmozhi / Kimko, Holly / Popel, Aleksander S

NPJ precision oncology

2023 Volume 7, Issue 1, Page(s) 55

Abstract: Generating realistic virtual patients from a limited amount of patient data is one of the major challenges for quantitative systems pharmacology modeling in immuno-oncology. Quantitative systems pharmacology (QSP) is a mathematical modeling methodology ... ...

Abstract	Generating realistic virtual patients from a limited amount of patient data is one of the major challenges for quantitative systems pharmacology modeling in immuno-oncology. Quantitative systems pharmacology (QSP) is a mathematical modeling methodology that integrates mechanistic knowledge of biological systems to investigate dynamics in a whole system during disease progression and drug treatment. In the present analysis, we parameterized our previously published QSP model of the cancer-immunity cycle to non-small cell lung cancer (NSCLC) and generated a virtual patient cohort to predict clinical response to PD-L1 inhibition in NSCLC. The virtual patient generation was guided by immunogenomic data from iAtlas portal and population pharmacokinetic data of durvalumab, a PD-L1 inhibitor. With virtual patients generated following the immunogenomic data distribution, our model predicted a response rate of 18.6% (95% bootstrap confidence interval: 13.3-24.2%) and identified CD8/Treg ratio as a potential predictive biomarker in addition to PD-L1 expression and tumor mutational burden. We demonstrated that omics data served as a reliable resource for virtual patient generation techniques in immuno-oncology using QSP models.
Language	English
Publishing date	2023-06-08
Publishing country	England
Document type	Journal Article
ISSN	2397-768X
ISSN	2397-768X
DOI	10.1038/s41698-023-00405-9
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Article: Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition.

Wang, Hanwen / Arulraj, Theinmozhi / Kimko, Holly / Popel, Aleksander S

bioRxiv : the preprint server for biology

2023

Abstract	Generating realistic virtual patients from a limited amount of patient data is one of the major challenges for quantitative systems pharmacology modeling in immuno-oncology. Quantitative systems pharmacology (QSP) is a mathematical modeling methodology that integrates mechanistic knowledge of biological systems to investigate dynamics in a whole system during disease progression and drug treatment. In the present analysis, we parameterized our previously published QSP model of the cancer-immunity cycle to non-small cell lung cancer (NSCLC) and generated a virtual patient cohort to predict clinical response to PD-L1 inhibition in NSCLC. The virtual patient generation was guided by immunogenomic data from iAtlas portal and population pharmacokinetic data of durvalumab, a PD-L1 inhibitor. With virtual patients generated following the immunogenomic data distribution, our model predicted a response rate of 18.6% (95% bootstrap confidence interval: 13.3-24.2%) and identified CD8/Treg ratio as a potential predictive biomarker in addition to PD-L1 expression and tumor mutational burden. We demonstrated that omics data served as a reliable resource for virtual patient generation techniques in immuno-oncology using QSP models.
Language	English
Publishing date	2023-04-28
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.04.25.538191
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