A Spatial Quantitative Systems Pharmacology Platform spQSP-IO for Simulations of Tumor—Immune Interactions and Effects of Checkpoint Inhibitor Immunotherapy

Quantitative systems pharmacology (QSP) models have become increasingly common in fundamental mechanistic studies and drug discovery in both academic and industrial environments. With imaging techniques widely adopted and other spatial quantification of tumor such as spatial transcriptomics gaining traction, it is crucial that these data reflecting tumor spatial heterogeneity be utilized to inform the QSP models to enhance their predictive power. We developed a hybrid computational model platform, spQSP-IO, to extend QSP models of immuno-oncology with spatially resolved agent-based models (ABM), combining their powers to track whole patient-scale dynamics and recapitulate the emergent spatial heterogeneity in the tumor. Using a model of non-small-cell lung cancer developed based on this platform, we studied the role of the tumor microenvironment and cancer–immune cell interactions in tumor development and applied anti-PD-1 treatment to virtual patients and studied how the spatial distribution of cells changes during tumor growth in response to the immune checkpoint inhibition treatment. Using parameter sensitivity analysis and biomarker analysis, we are able to identify mechanisms and pretreatment measurements correlated with treatment efficacy. By incorporating spatial data that highlight both heterogeneity in tumors and variability among individual patients, spQSP-IO models can extend the QSP framework and further advance virtual clinical trials.

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Transcript levels of spindle and kinetochore-associated complex 1/3 as prognostic biomarkers correlated with immune infiltrates in hepatocellular carcinoma

Scientific Reports ◽

10.1038/s41598-021-89628-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

De-Chen Yu ◽

Xiang-Yi Chen ◽

Xin Li ◽

Hai-Yu Zhou ◽

De-Quan Yu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Protein Complex ◽

Immune Cell ◽

Prognostic Significance ◽

Tumor Development ◽

Disease Free Survival ◽

Tumor Grade ◽

Tumor Stage ◽

Prognostic Biomarkers ◽

High Expression

AbstractThe spindle and kinetochore-associated protein complex (Ska) is an essential component in chromosome segregation. It comprises three proteins (Ska1, Ska2, and Ska3) with theorized roles in chromosomal instability and tumor development, and its overexpression has been widely reported in a variety of tumors. However, the prognostic significance and immune infiltration of Ska proteins in hepatocellular carcinoma (HCC) are not completely understood. The bioinformatics tools Oncomine, UALCAN, gene expression profiling interactive analysis 2 (GEPIA2), cBioPortal, GeneMANIA, Metascape, and TIMER were used to analyze differential expression, prognostic value, genetic alteration, and immune cell infiltration of the Ska protein complex in HCC patients. We found that the mRNA expression of the Ska complex was markedly upregulated in HCC. High expression of the Ska complex is closely correlated with tumor stage, patient race, tumor grade, and TP53 mutation status. In addition, high expression of the Ska complex was significantly correlated with poor disease-free survival, while the high expression levels of Ska1 and Ska3 were associated with shorter overall survival. The biological functions of the Ska complex in HCC primarily involve the amplification of signals from kinetochores, the mitotic spindle, and (via a MAD2 invasive signal) unattached kinetochores. Furthermore, the expression of the complex was positively correlated with tumor-infiltrating cells. These results may provide new insights into the development of immunotherapeutic targets and prognostic biomarkers for HCC.

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Dynamical systems analysis as an additional tool to inform treatment outcomes: The case study of a quantitative systems pharmacology model of immuno-oncology

Chaos An Interdisciplinary Journal of Nonlinear Science ◽

10.1063/5.0022238 ◽

2021 ◽

Vol 31 (2) ◽

pp. 023124

Author(s):

Aymen Balti ◽

Didier Zugaj ◽

Frédérique Fenneteau ◽

Pierre-Olivier Tremblay ◽

Fahima Nekka

Keyword(s):

Dynamical Systems ◽

Treatment Outcomes ◽

Systems Analysis ◽

Systems Pharmacology ◽

Quantitative Systems Pharmacology ◽

Additional Tool ◽

Dynamical Systems Analysis ◽

Systems Pharmacology Model

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DDRE-09. DEVELOPING IDO-PROTACS TO IMPROVE IMMUNOTHERAPEUTIC EFFICACY IN PATIENTS WITH GLIOBLASTOMA

Neuro-Oncology ◽

10.1093/neuonc/noaa215.254 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii63-ii63

Author(s):

Lakshmi Bollu ◽

Derek Wainwright ◽

Lijie Zhai ◽

Erik Ladomersky ◽

Kristen Lauing ◽

...

Keyword(s):

Protein Degradation ◽

Time Course ◽

Immune Cell ◽

Enzyme Inhibitors ◽

Tumor Development ◽

Ubiquitin Proteasome System ◽

Degradation Pathway ◽

Specific Protein ◽

Cell Functions

Abstract INTRODUCTION Indoleamine 2,3-dioxygenase 1 (IDO; IDO1) is a rate-limiting enzyme that metabolizes the essential amino acid tryptophan into kynurenine. Recent work by our group has revealed that IDO promotes tumor development and suppresses immune cell functions independent of its enzyme activity. Moreover, pharmacologic IDO enzyme inhibitors that currently serve as the only class of drugs available for targeting immunosuppressive IDO activity, fail to improve the survival of patients with GBM. Here, we developed IDO-Proteolysis Targeting Chimeras (IDO-PROTACs). PROTACs bind to a specific protein and recruit an E3 ubiquitin ligase that enhance proteasome-mediated degradation of the target protein. METHODS A library of ≥100 IDO-PROTACs were developed by joining BMS986205 (IDO binder) with a linker group to various E3-ligase ligands. Western blot analysis of PROTAC-induced IDO degradation was tested in vitro among multiple human and mouse GBM cell lines including U87, GBM6, GBM43 and GL261 along a time course ranging between 1–96 hours of treatment and at varying concentrations. The mechanism of IDO protein degradation was investigated using pharmacologic ligands that inhibit or compete with the proteasome-mediated protein degradation pathway. RESULTS Primary screening identified several IDO-PROTACs with IDO protein degradation potential. Secondary screening showed that our lead compound has a DC50 value of ~0.5µM with an ability to degrade IDO in all GBM cells analyzed, and an initial activity within 12 hours of treatment that extended for up to 96 hours. Mutating the CRBN-binding ligand, pretreatment with the ubiquitin proteasome system inhibitors MG132 or MLN4924 or using unmodified parental compound all inhibited IDO protein degradation. CONCLUSIONS This study developed an initial IDO-PROTAC technology that upon further optimization, can neutralize both IDO enzyme and non-enzyme immunosuppressive effects. When combined with other forms of immunotherapy, IDO-PROTACs have the potential to substantially enhance immunotherapeutic efficacy in patients with GBM.

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Non-radioactive imaging strategies for in vivo immune cell tracking

Physical Sciences Reviews ◽

10.1515/psr-2020-0205 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Łukasz Kiraga ◽

Paulina Kucharzewska ◽

Damian Strzemecki ◽

Tomasz P. Rygiel ◽

Magdalena Król

Keyword(s):

Diagnostic Imaging ◽

Contrast Agents ◽

Cell Tracking ◽

Immune Cell ◽

Imaging Techniques ◽

Diagnostic Technique ◽

Cell Labeling ◽

X Ray Imaging ◽

Disease Study

Abstract In vivo tracking of administered cells chosen for specific disease treatment may be conducted by diagnostic imaging techniques preceded by cell labeling with special contrast agents. The most commonly used agents are those with radioactive properties, however their use in research is often impossible. This review paper focuses on the essential aspect of cell tracking with the exclusion of radioisotope tracers, therefore we compare application of different types of non-radioactive contrast agents (cell tracers), methods of cell labeling and application of various techniques for cell tracking, which are commonly used in preclinical or clinical studies. We discuss diagnostic imaging methods belonging to three groups: (1) Contrast-enhanced X-ray imaging, (2) Magnetic resonance imaging, and (3) Optical imaging. In addition, we present some interesting data from our own research on tracking immune cell with the use of discussed methods. Finally, we introduce an algorithm which may be useful for researchers planning leukocyte targeting studies, which may help to choose the appropriate cell type, contrast agent and diagnostic technique for particular disease study.

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Quantitative systems pharmacology model of thrombopoiesis and platelet life‐cycle, and its application to thrombocytopenia based on chronic liver disease

CPT Pharmacometrics & Systems Pharmacology ◽

10.1002/psp4.12623 ◽

2021 ◽

Author(s):

Ryosuke Shimizu ◽

Takayuki Katsube ◽

Toshihiro Wajima

Keyword(s):

Life Cycle ◽

Liver Disease ◽

Chronic Liver Disease ◽

Chronic Liver ◽

Systems Pharmacology ◽

Quantitative Systems Pharmacology ◽

Systems Pharmacology Model

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Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18031056 ◽

2021 ◽

Vol 18 (3) ◽

pp. 1056

Author(s):

Yu Chen ◽

Mengke Zhu ◽

Qian Zhou ◽

Yurong Qiao

Keyword(s):

Spatial Heterogeneity ◽

Spatial Correlation ◽

Spatial Data ◽

Central Area ◽

Urban System ◽

Entropy Method ◽

Driving Factors ◽

Spatial Data Analysis ◽

Eastern Region ◽

Urban Resilience

Urban resilience in the context of COVID-19 epidemic refers to the ability of an urban system to resist, absorb, adapt and recover from danger in time to hedge its impact when confronted with external shocks such as epidemic, which is also a capability that must be strengthened for urban development in the context of normal epidemic. Based on the multi-dimensional perspective, entropy method and exploratory spatial data analysis (ESDA) are used to analyze the spatiotemporal evolution characteristics of urban resilience of 281 cities of China from 2011 to 2018, and MGWR model is used to discuss the driving factors affecting the development of urban resilience. It is found that: (1) The urban resilience and sub-resilience show a continuous decline in time, with no obvious sign of convergence, while the spatial agglomeration effect shows an increasing trend year by year. (2) The spatial heterogeneity of urban resilience is significant, with obvious distribution characteristics of “high in east and low in west”. Urban resilience in the east, the central and the west are quite different in terms of development structure and spatial correlation. The eastern region is dominated by the “three-core driving mode”, and the urban resilience shows a significant positive spatial correlation; the central area is a “rectangular structure”, which is also spatially positively correlated; The western region is a “pyramid structure” with significant negative spatial correlation. (3) The spatial heterogeneity of the driving factors is significant, and they have different impact scales on the urban resilience development. The market capacity is the largest impact intensity, while the infrastructure investment is the least impact intensity. On this basis, this paper explores the ways to improve urban resilience in China from different aspects, such as market, technology, finance and government.

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