Browse
Submit Data
Databases
API
Help

Dataset Information

9 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Cancer-on-a-Chip for Modeling Immune Checkpoint Inhibitor and Tumor Interactions.

ABSTRACT: Cancer immunotherapies, including immune checkpoint inhibitor (ICI)-based therapies, have revolutionized cancer treatment. However, patient response to ICIs is highly variable, necessitating the development of methods to quickly assess efficacy. In this study, an array of miniaturized bioreactors has been developed to model tumor-immune interactions. This immunotherapeutic high-throughput observation chamber (iHOC) is designed to test the effect of anti-PD-1 antibodies on cancer spheroid (MDA-MB-231, PD-L1+) and T cell (Jurkat) interactions. This system facilitates facile monitoring of T cell inhibition and reactivation using metrics such as tumor infiltration and interleukin-2 (IL-2) secretion. Status of the tumor-immune interactions can be easily captured within the iHOC by measuring IL-2 concentration using a micropillar array where sensitive, quantitative detection is allowed after antibody coating on the surface of array. The iHOC is a platform that can be used to model and monitor cancer-immune interactions in response to immunotherapy in a high-throughput manner.

SUBMITTER: Jiang X

PROVIDER: S-EPMC7939119 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Mathematical modeling of tumor-immune cell interactions.

Project description:The anti-tumor activity of the immune system is increasingly recognized as critical for the mounting of a prolonged and effective response to cancer growth and invasion, and for preventing recurrence following resection or treatment. As the knowledge of tumor-immune cell interactions has advanced, experimental investigation has been complemented by mathematical modeling with the goal to quantify and predict these interactions. This succinct review offers an overview of recent tumor-immune continuum modeling approaches, highlighting spatial models. The focus is on work published in the past decade, incorporating one or more immune cell types and evaluating immune cell effects on tumor progression. Due to their relevance to cancer, the following immune cells and their combinations are described: macrophages, Cytotoxic T Lymphocytes, Natural Killer cells, dendritic cells, T regulatory cells, and CD4+ T helper cells. Although important insight has been gained from a mathematical modeling perspective, the development of models incorporating patient-specific data remains an important goal yet to be realized for potential clinical benefit.

| S-EPMC6579737 | biostudies-literature

Phytochemicals in Cancer Immune Checkpoint Inhibitor Therapy.

Project description:The interaction of immune checkpoint molecules in the tumor microenvironment reduces the anti-tumor immune response by suppressing the recognition of T cells to tumor cells. Immune checkpoint inhibitor (ICI) therapy is emerging as a promising therapeutic option for cancer treatment. However, modulating the immune system with ICIs still faces obstacles with severe immunogenic side effects and a lack of response against many cancer types. Plant-derived natural compounds offer regulation on various signaling cascades and have been applied for the treatment of multiple diseases, including cancer. Accumulated evidence provides the possibility of efficacy of phytochemicals in combinational with other therapeutic agents of ICIs, effectively modulating immune checkpoint-related signaling molecules. Recently, several phytochemicals have been reported to show the modulatory effects of immune checkpoints in various cancers in in vivo or in vitro models. This review summarizes druggable immune checkpoints and their regulatory factors. In addition, phytochemicals that are capable of suppressing PD-1/PD-L1 binding, the best-studied target of ICI therapy, were comprehensively summarized and classified according to chemical structure subgroups. It may help extend further research on phytochemicals as candidates of combinational adjuvants. Future clinical trials may validate the synergetic effects of preclinically investigated phytochemicals with ICI therapy.

| S-EPMC8393583 | biostudies-literature

Annexin A5 as an immune checkpoint inhibitor and tumor-homing molecule for cancer treatment.

Project description:The interaction between immune cells and phosphatidylserine (PS) molecules exposed on the surface of apoptotic-tumor bodies, such as those induced by chemotherapies, contributes to the formation of an immunosuppressive tumor microenvironment (TME). Annexin A5 (AnxA5) binds with high affinity to PS externalized by apoptotic cells, thereby hindering their interaction with immune cells. Here, we show that AnxA5 administration rescue the immunosuppressive state of the TME induced by chemotherapy. Due to the preferential homing of AnxA5 to the TME enriched with PS+ tumor cells, we demonstrate in vivo that fusing tumor-antigen peptide to AnxA5 significantly enhances its immunogenicity and antitumor efficacy when administered after chemotherapy. Also, the therapeutic antitumor effect of an AnxA5-peptide fusion can be further enhanced by administration of other immune checkpoint inhibitors. Our findings support the administration of AnxA5 following chemotherapy as a promising immune checkpoint inhibitor for cancer treatment.

| S-EPMC7048819 | biostudies-literature

Decoupling FcRn and tumor contributions to elevated immune checkpoint inhibitor clearance in cancer cachexia.

Project description:High baseline clearance of immune checkpoint inhibitors (ICIs), independent of dose or systemic exposure, is associated with cachexia and poor outcomes in cancer patients. Mechanisms linking ICI clearance, cachexia and ICI therapy failure are unknown. Here, we evaluate in four murine models and across multiple antibodies whether altered baseline catabolic clearance of administered antibody requires a tumor and/or cachexia and whether medical reversal of cachexia phenotype can alleviate altered clearance. Key findings include mild cachexia phenotype and lack of elevated pembrolizumab clearance in the MC38 tumor-bearing model. We also observed severe cachexia and decreased, instead of increased, baseline pembrolizumab clearance in the tumor-free cisplatin-induced cachexia model. Liver Fcgrt expression correlated with altered baseline catabolic clearance, though elevated clearance was still observed with antibodies having no (human IgA) or reduced (human H310Q IgG1) FcRn binding. We conclude cachexia phenotype coincides with altered antibody clearance, though tumor presence is neither sufficient nor necessary for altered clearance in immunocompetent mice. Magnitude and direction of clearance alteration correlated with hepatic Fcgrt, suggesting changes in FcRn expression and/or recycling function may be partially responsible, though factors beyond FcRn also contribute to altered clearance in cachexia.

| S-EPMC10798214 | biostudies-literature

Analysis of Tumor Microenvironment Characteristics in Bladder Cancer: Implications for Immune Checkpoint Inhibitor Therapy.

Project description:The tumor microenvironment (TME) plays a crucial role in cancer progression and recent evidence has clarified its clinical significance in predicting outcomes and efficacy. However, there are no studies on the systematic analysis of TME characteristics in bladder cancer. In this study, we comprehensively evaluated the TME invasion pattern of bladder cancer in 1,889 patients, defined three different TME phenotypes, and found that different subtypes were associated with the clinical prognosis and pathological characteristics of bladder cancer. We further explored the signaling pathways, cancer-immunity cycle, copy number, and somatic mutation differences among the different subtypes and used the principal component analysis algorithm to calculate the immune cell (IC) score, a tool for comprehensive evaluation of TME. Univariate and multivariate Cox regression analyses showed that ICscore is a reliable and independent prognostic biomarker. In addition, the use of anti-programmed death-ligand (PD-L1) treatment cohort, receiver operating characteristic (ROC) curve, Tumor Immune Dysfunction and Exclusion (TIDE), Subnetwork Mappings in Alignment of Pathways (SubMAP), and other algorithms confirmed that ICscore is a reliable prognostic biomarker for immune checkpoint inhibitor response. Patients with higher ICscore showed a significant therapeutic advantage in immunotherapy. In conclusion, this study improves our understanding of the characteristics of TME infiltration in bladder cancer and provides guidance for more effective personalized immunotherapy strategies.

| S-EPMC8082152 | biostudies-literature

Mapping the functional interactions at the tumor-immune checkpoint interface.

Project description:The interactions between tumor intrinsic processes and immune checkpoints can mediate immune evasion by cancer cells and responses to immunotherapy. It is, however, challenging to identify functional interactions due to the prohibitively complex molecular landscape of the tumor-immune interfaces. We address this challenge with a statistical analysis framework, immuno-oncology gene interaction maps (ImogiMap). ImogiMap quantifies and statistically validates tumor-immune checkpoint interactions based on their co-associations with immune-associated phenotypes. The outcome is a catalog of tumor-immune checkpoint interaction maps for diverse immune-associated phenotypes. Applications of ImogiMap recapitulate the interaction of SERPINB9 and immune checkpoints with interferon gamma (IFNγ) expression. Our analyses suggest that CD86-CD70 and CD274-CD70 immunoregulatory interactions are significantly associated with IFNγ expression in uterine corpus endometrial carcinoma and basal-like breast cancer, respectively. The open-source ImogiMap software and user-friendly web application will enable future applications of ImogiMap. Such applications may guide the discovery of previously unknown tumor-immune interactions and immunotherapy targets.

| S-EPMC10140040 | biostudies-literature

Combined Assessment of the Tumor-Stroma Ratio and Tumor Immune Cell Infiltrate for Immune Checkpoint Inhibitor Therapy Response Prediction in Colon Cancer.

Project description:The best current biomarker strategies for predicting response to immune checkpoint inhibitor (ICI) therapy fail to account for interpatient variability in response rates. The histologic tumor-stroma ratio (TSR) quantifies intratumoral stromal content and was recently found to be predictive of response to neoadjuvant therapy in multiple cancer types. In the current work, we predicted the likelihood of ICI therapy responsivity of 335 therapy-naive colon adenocarcinoma tumors from The Cancer Genome Atlas, using bioinformatics approaches. The TSR was scored on diagnostic tissue slides, and tumor-infiltrating immune cells (TIICs) were inferred from transcriptomic data. Tumors with high stromal content demonstrated increased T regulatory cell infiltration (p = 0.014) but failed to predict ICI therapy response. Consequently, we devised a hybrid tumor microenvironment classification of four stromal categories, based on histological stromal content and transcriptomic-deconvoluted immune cell infiltration, which was associated with previously established transcriptomic and genomic biomarkers for ICI therapy response. By integrating these biomarkers, stroma-low/immune-high tumors were predicted to be most responsive to ICI therapy. The framework described here provides evidence for expansion of current histological TIIC quantification to include the TSR as a novel, easy-to-use biomarker for the prediction of ICI therapy response.

| S-EPMC8616493 | biostudies-literature

How to use immune checkpoint inhibitor in ovarian cancer?

Project description: Not available

| S-EPMC6658602 | biostudies-literature

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

Project description: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.

| S-EPMC8345161 | biostudies-literature

Carfilzomib modulates tumor microenvironment to potentiate immune checkpoint therapy for cancer

Project description:Impressive clinical benefit is seen in clinic with PD-1 inhibitors on portion of cancer patients. Yet, there remains an urgent need to develop effective synergizers to expand their clinical application. Tumor associated macrophage (TAM), a type of M2-polarized macrophage, eliminates or suppresses T cell mediated anti-tumor responses. Transforming TAMs into M1 macrophages is an attractive strategy of anti-tumor therapy. Here we conducted a high-throughput screening and found that Carfilzomib potently drove M2 macrophages to express M1 cytokines, phagocytose tumor cells and present antigens to T cells. Mechanistically, Carfilzomib elicited unfolded protein response (UPR), activated IRE1α to recruit TRAF2, and activated NF-κB to transcribe genes encoding M1 markers in M2 macrophages. In vivo, Carfilzomib effectively rewired tumor microenvironment through reprogramming TAMs into M1-like macrophages and shrank autochthonous lung cancers in transgenic mouse model. More importantly, Carfilzomib synergized with PD-1 antibody to almost completely regress autochthonous lung cancers. Given the safety profiles of Carfilzomib in clinic, our work suggested a potentially immediate application of combinational treatment with Carfilzomib and PD-1 inhibitors for patients with solid tumors.

| S-SCDT-EMM-2021-14502 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data