title: Detection of suppressor T lymphocytes and estimation of their frequency in limiting dilution assays by generalized linear regression modeling.
abstract: The estimate of the frequency of suppressor T lymphocytes in unfractionated cell populations remains challenging, mainly because these regulatory cells do not display specific immunophenotypic markers. In this paper, we describe a novel theoretical approach for quantifying the frequency of suppressor cells. This method is based on limiting dilution data modeling, and allows the simultaneous estimation of the frequencies of both proliferating and suppressor cells. We used previously published biological data, characterizing the inhibiting activity of suppressor T cell clones. Starting from these data, we propose a mathematical model describing the interaction between suppressor and proliferating T cells, and applied to a Poisson process. Limiting dilution data corresponding to this non-single-hit, suppressor two-target Poisson model were artificially generated, then modeled according to a generalized linear regression procedure. Deviation from the single-hit Poisson model was revealed by a statistical slope test, and a stepwise analysis of the regression appeared to be an efficient method that strongly argued in favor of the presence of suppressor cells. By using the frequency of proliferating T cells calculated in the first step of the regression, we demonstrated the possibility to provide a reasonable estimate of the frequency of suppressor T cells. Based on these findings, a practical decision-making procedure is given to perform standard analyses of limiting dilution data.
authors.affiliation: Groupe de Recherche sur les Lymphomes, Equipe Mixte INSERM 0353, Institut Albert Bonniot, Université Joseph-Fourier, Rond-Point de la Chantourne, and Centre Hospitalo-Universitaire Michallon, La Tronche, France. Thierry.Bonnefoix@ujf-grenoble.fr
authors.forename: Thierry
authors.initials: T
authors.lastname: Bonnefoix
authors.forename: Philippe
authors.initials: P
authors.lastname: Bonnefoix
authors.forename: Jian-Qing
authors.initials: JQ
authors.lastname: Mi
authors.forename: Jean-Jacques
authors.initials: JJ
authors.lastname: Lawrence
authors.forename: Jean-Jacques
authors.initials: JJ
authors.lastname: Sotto
authors.forename: Dominique
authors.initials: D
authors.lastname: Leroux
mesh_terms: D000818:Animals; D002455:Cell Division / Q000276:immunology; D017635:Clonal Anergy; D002999:Clone Cells; D003198:Computer Simulation; D003601:Cytotoxicity Tests, Immunologic / Q000379:methods / Q000706:statistics & numerical data*; D018984:Epitopes, T-Lymphocyte / Q000276:immunology; D019267:Hemagglutinin Glycoproteins, Influenza Virus / Q000276:immunology; D006801:Humans; D016014:Linear Models; D008213:Lymphocyte Activation / Q000276:immunology; D018655:Lymphocyte Count / Q000379:methods / Q000706:statistics & numerical data*; D051379:Mice; D018448:Models, Immunological; D016012:Poisson Distribution; D016176:T-Lymphocyte Subsets / Q000166:cytology / Q000276:immunology / Q000821:virology; D050378:T-Lymphocytes, Regulatory / Q000166:cytology* / Q000276:immunology* / Q000821:virology
chemical_list: D018984:Epitopes, T-Lymphocyte; D019267:Hemagglutinin Glycoproteins, Influenza Virus