A multispecies framework for modeling adaptive immunity and immunotherapy in cancer.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
04 2023
04 2023
Historique:
received:
06
07
2022
accepted:
24
02
2023
revised:
03
05
2023
medline:
5
5
2023
pubmed:
21
4
2023
entrez:
21
04
2023
Statut:
epublish
Résumé
Predator-prey theory is commonly used to describe tumor growth in the presence of selective pressure from the adaptive immune system. These interactions are mediated by the tumor immunopeptidome (what the tumor "shows" the body) and the T-cell receptor (TCR) repertoire (how well the body "sees" cancer cells). The tumor immunopeptidome comprises neoantigens which can be gained and lost throughout tumorigenesis and treatment. Heterogeneity in the immunopeptidome is predictive of poor response to immunotherapy in some tumor types, suggesting that the TCR repertoire is unable to support a fully polyclonal response against every neoantigen. Importantly, while tumor and T-cell populations are known to compete with each other for intratumoral resources, whether between-lineage competition among peripheral T cells influences the TCR repertoire is unknown and difficult to interrogate experimentally. Computational models may offer a way to investigate these phenomena and deepen our understanding of the tumor-immune axis. Here, we construct a predator-prey-like model and calibrate it to preclinical and clinical data to describe tumor growth and immunopeptidome diversification. Simultaneously, we model the expansion of antigen-specific T-cell lineages and their consumption of both lineage-specific antigenic resources and lineage-agnostic, shared resources. This predator-prey-like framework accurately described clinically observed immunopeptidomes; recapitulated response-associated effects of immunotherapy, including immunoediting; and allowed exploration of treatment of tumors with varying growth and mutation rates.
Identifiants
pubmed: 37083574
doi: 10.1371/journal.pcbi.1010976
pii: PCOMPBIOL-D-22-01031
pmc: PMC10155959
doi:
Substances chimiques
Antigens
0
Receptors, Antigen, T-Cell
0
Antigens, Neoplasm
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1010976Subventions
Organisme : NIGMS NIH HHS
ID : R35 GM119661
Pays : United States
Informations de copyright
Copyright: © 2023 Qi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Déclaration de conflit d'intérêts
I have read the journal’s policy and the authors of this manuscript have the following competing interests: B.V. is a shareholder of and consultant for GeneCentric.
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