title: Predicting full thickness skin sensitization using a support vector machine.
abstract: To assess the public's propensity for allergic contact dermatitis (ACD), many alternatives to in vivo chemical screening have been developed which generally incorporate a small panel of cell surface and secreted dendritic cell biomarkers. However, given the underlying complexity of ACD, one cell type and limited cellular metrics may be insufficient to predict contact sensitizers accurately. To identify a molecular signature that can further characterize sensitization, we developed a novel system using RealSkin, a full thickness skin equivalent, in co-culture with MUTZ-3 derived Langerhan's cells. This system was used to distinguish a model moderate pro-hapten isoeugenol (IE) and a model strong pre-hapten p-phenylenediamine (PPD) from irritant, salicylic acid (SA). Commonly evaluated metrics such as CD86, CD54, and IL-8 secretion were assessed, in concert with a 27-cytokine multi-plex screen and a functional chemotaxis assay. Data were analyzed with feature selection methods using ANOVA, hierarchical cluster analysis, and a support vector machine to identify the best molecular signature for sensitization. A panel consisting of IL-12, IL-9, VEGF, and IFN-γ predicted sensitization with over 90% accuracy using this co-culture system analysis. Thus, a multi-metric approach that has the potential to identify a molecular signature may be more predictive of contact sensitization.
authors.affiliation: Department of Biomedical Engineering, Rutgers, The State University of New Jersey, 599 Taylor Road, Piscataway, NJ 08854, United States.
authors.forename: Serom
authors.initials: S
authors.lastname: Lee
authors.affiliation: Department of Biomedical Engineering, Rutgers, The State University of New Jersey, 599 Taylor Road, Piscataway, NJ 08854, United States.
authors.forename: David Xu
authors.initials: DX
authors.lastname: Dong
authors.affiliation: Department of Biomedical Engineering, Rutgers, The State University of New Jersey, 599 Taylor Road, Piscataway, NJ 08854, United States.
authors.forename: Rohit
authors.initials: R
authors.lastname: Jindal
authors.affiliation: Department of Biomedical Engineering, Rutgers, The State University of New Jersey, 599 Taylor Road, Piscataway, NJ 08854, United States.
authors.forename: Tim
authors.initials: T
authors.lastname: Maguire
authors.affiliation: Department of Biomedical Engineering, Rutgers, The State University of New Jersey, 599 Taylor Road, Piscataway, NJ 08854, United States.
authors.forename: Bhaskar
authors.initials: B
authors.lastname: Mitra
authors.affiliation: Department of Biomedical Engineering, Rutgers, The State University of New Jersey, 599 Taylor Road, Piscataway, NJ 08854, United States.
authors.forename: Rene
authors.initials: R
authors.lastname: Schloss
authors.affiliation: Department of Biomedical Engineering, Rutgers, The State University of New Jersey, 599 Taylor Road, Piscataway, NJ 08854, United States; Center for Engineering in Medicine and the Department of Surgery, Massachusettes General Hospital and the Shriners Burns Hospital, Boston, MA 02114, United States. Electronic address: yarmush@rci.rutgers.edu.
authors.forename: Martin
authors.initials: M
authors.lastname: Yarmush
mesh_terms: D000328:Adult; D051940:B7-2 Antigen / Q000032:analysis; D002460:Cell Line; D016000:Cluster Analysis; D006801:Humans; D018799:Intercellular Adhesion Molecule-1 / Q000032:analysis; D016209:Interleukin-8 / Q000378:metabolism; D023422:Skin Irritancy Tests / Q000379:methods*; D060388:Support Vector Machine
chemical_list: D051940:B7-2 Antigen; D016209:Interleukin-8; D018799:Intercellular Adhesion Molecule-1
keywords: Co-culture; In vitro; MUTZ-3; Skin equivalent; Skin sensitization; Support vector machine