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

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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.

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Acknowledgments

JM Bowen was a recipient of a National Health and Medical Research Council (Australia) Post-doctoral Training Fellowship. This research was supported by an Australian Dental Research Foundation Inc. Project grant.

Conflict of interest

The authors have no financial relationship with the Australian Dental Research Foundation Inc, have full control of the primary data of this research study, and agree to allow to data review if requested by the journal.

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Authors and Affiliations

  1. Discipline of Pharmacology, School of Medical Sciences, University of Adelaide, Level 5 Medical School North, Frome Road, Adelaide, South Australia, 5005, Australia

    Janet K. Coller

  2. Discipline of Medicine, School of Medicine, University of Adelaide, Adelaide, SA, Australia

    Imogen A. White

  3. School of Dentistry, University of Adelaide, Adelaide, SA, Australia

    Richard M. Logan

  4. School of Mathematical Sciences, University of Adelaide, Adelaide, SA, Australia

    Jonathan Tuke

  5. Flinders Medical Centre, Bedford Park, SA, 5042, Australia

    Alison M. Richards, Kelly R. Mead & Christos S. Karapetis

  6. Flinders Centre for Innovation in Cancer, Flinders University, Bedford Park, SA, 5042, Australia

    Christos S. Karapetis

  7. Discipline of Physiology, School of Medical Sciences, University of Adelaide, Adelaide, SA, Australia

    Joanne M. Bowen

Authors
  1. Janet K. Coller
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  2. Imogen A. White
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  3. Richard M. Logan
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  4. Jonathan Tuke
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  5. Alison M. Richards
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  6. Kelly R. Mead
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  7. Christos S. Karapetis
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  8. Joanne M. Bowen
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Corresponding author

Correspondence to Janet K. Coller.

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Coller, J.K., White, I.A., Logan, R.M. et al. Predictive model for risk of severe gastrointestinal toxicity following chemotherapy using patient immune genetics and type of cancer: a pilot study. Support Care Cancer 23, 1233–1236 (2015). https://doi.org/10.1007/s00520-014-2481-z

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  • DOI: https://doi.org/10.1007/s00520-014-2481-z

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