Systematic Screening of Chemokines to Identify Candidates to Model and Create Ectopic Lymph Node Structures for Cancer Immunotherapy

Yohsuke Yagawa; Mark Robertson-Tessi; Susan L Zhou; Alexander R A Anderson; James J Mulé; Adam W Mailloux

doi:10.1038/s41598-017-15924-2

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Systematic Screening of Chemokines to Identify Candidates to Model and Create Ectopic Lymph Node Structures for Cancer Immunotherapy

Journal article

Open access

Peer reviewed

Systematic Screening of Chemokines to Identify Candidates to Model and Create Ectopic Lymph Node Structures for Cancer Immunotherapy

Yohsuke Yagawa, Mark Robertson-Tessi, Susan L Zhou, Alexander R A Anderson, James J Mulé and Adam W Mailloux

Scientific reports, Vol.7(1), pp.15996-16

11/22/2017

DOI: 10.1038/s41598-017-15924-2

PMCID: PMC5700067

PMID: 29167448

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Abstract

The induction of ectopic lymph node structures (ELNs) holds great promise to augment immunotherapy against multiple cancers including metastatic melanoma, in which ELN formation has been associated with a unique immune-related gene expression signature composed of distinct chemokines. To investigate the therapeutic potential of ELNs induction, preclinical models of ELNs are needed for interrogation of these chemokines. Computational models provide a non-invasive, cost-effective method to investigate leukocyte trafficking in the tumor microenvironment, but parameterizing such models is difficult due to differing assay conditions and contexts among the literature. To better achieve this, we systematically performed microchemotaxis assays on purified immune subsets including human pan-T cells, CD4 T cells, CD8 T cells, B cells, and NK cells, with 49 recombinant chemokines using a singular technique, and standardized conditions resulting in a dataset representing 238 assays. We then outline a groundwork computational model that can simulate cellular migration in the tumor microenvironment in response to a chemoattractant gradient created from stromal, lymphoid, or antigen presenting cell interactions. The resulting model can then be parameterized with standardized data, such as the dataset presented here, and demonstrates how a computational approach can help elucidate developing ELNs and their impact on tumor progression.

B-Lymphocytes - metabolism

CD8-Positive T-Lymphocytes - metabolism

Chemokines - analysis

Computer Simulation

Early Detection of Cancer - methods

Humans

Immunotherapy

Tertiary Lymphoid Structures - diagnosis

Tumor Microenvironment - physiology

Details

Title: Subtitle: Systematic Screening of Chemokines to Identify Candidates to Model and Create Ectopic Lymph Node Structures for Cancer Immunotherapy
Creators: Yohsuke Yagawa - Moffitt Cancer Center
Mark Robertson-Tessi - Moffitt Cancer Center
Susan L Zhou - Moffitt Cancer Center
Alexander R A Anderson - Moffitt Cancer Center
James J Mulé - Moffitt Cancer Center
Adam W Mailloux - Moffitt Cancer Center
Resource Type: Journal article
Publication Details: Scientific reports, Vol.7(1), pp.15996-16
DOI: 10.1038/s41598-017-15924-2
PMID: 29167448
PMCID: PMC5700067
NLM abbreviation: Sci Rep
ISSN: 2045-2322
eISSN: 2045-2322
Grant note: U01 CA151924 / NCI NIH HHS U54 CA193489 / NCI NIH HHS P50 CA168536 / NCI NIH HHS R01 CA184845 / NCI NIH HHS R01 CA148995 / NCI NIH HHS P30 CA076292 / NCI NIH HHS
Language: English
Date published: 11/22/2017
Academic Unit: Microbiology and Immunology
Record Identifier: 9984297429202771

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