Predictive model for risk of severe gastrointestinal toxicity following chemotherapy using patient immune genetics and type of cancer: a pilot study

Abstract

PURPOSE: Severe chemotherapy-induced gastrointestinal toxicity (CIGT) is common and results in treatment delays, dose reductions, and potential premature treatment discontinuation. Currently, there is no diagnostic marker to predict CIGT. Proinflammatory cytokines, produced via toll-like receptor signaling, are key mediators of this toxicity. Hence, this pilot study investigated the association between immune genetic variability and severe CIGT risk. METHODS: Genomic DNA from 34 patients (10 with severe CIGT) who had received 5-fluoruracil-based chemotherapy regimens was analyzed for variants of IL-1B, IL-2, IL-6, IL-6R, IL-10, TNF-a, TGF-b, TLR2, TLR4, MD2, MYD88, BDNF, CRP, ICE, and OPRM1. Multivariate logistic regression created a prediction model of severe CIGT risk. RESULTS: There were no significant differences between patients with and without severe CIGT with regards to age, sex, type of cancer, or chemotherapy treatment regimens. The prediction model of severe CIGT risk included TLR2 and TNF-a genetic variability and cancer type (colorectal and gastric). This prediction model was both specific and sensitive, with a receiver operator characteristic area under the curve of 87.3 %. CONCLUSIONS: This is the first report of immune genetic variability, together with cancer type, being predictive of severe CIGT risk. These outcomes are being validated in a larger patient population.