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Front Immunol. 2017 Oct 5;8:1247. doi: 10.3389/fimmu.2017.01247. eCollection 2017.

Predicting Risk of Infection in Patients with Newly Diagnosed Multiple Myeloma: Utility of Immune Profiling.

Teh BW1,2,3,4, Harrison SJ2,5, Allison CC3, Slavin MA1,2,4,6,7, Spelman T4,7, Worth LJ1,4,6, Thursky KA1,2,4,6,7, Ritchie D5,6, Pellegrini M3,4,8.

Author information

1
Department of Infectious Diseases, Peter MacCallum Cancer Centre, Parkville, VIC, Australia.
2
Sir Peter MacCallum Department of Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
3
Walter and Eliza Hall Institute, Parkville, VIC, Australia.
4
National Centre for Infections in Cancer, Parkville, VIC, Australia.
5
Department of Haematology, Victorian Comprehensive Cancer Centre, Parkville, VIC, Australia.
6
Department of Medicine, University of Melbourne, Parkville, VIC, Australia.
7
Victorian Infectious Diseases Service, Doherty Institute for Infection and Immunity, Parkville, VIC, Australia.
8
Department of Medical Biology, University of Melbourne, Parkville, VIC, Australia.

Abstract

BACKGROUND:

A translational study in patients with myeloma to determine the utility of immune profiling to predict infection risk in patients with hematological malignancy was conducted.

METHODS:

Baseline, end of induction, and maintenance peripheral blood mononuclear cells from 40 patients were evaluated. Immune cell populations and cytokines released from 1 × 106 cells/ml cultured in the presence of a panel of stimuli (cytomegalovirus, influenza, S. pneumoniae, phorbol myristate acetate/ionomycin) and in media alone were quantified. Patient characteristics and infective episodes were captured from clinical records. Immunological variables associated with increased risk for infection in the 3-month period following sample collection were identified using univariate analysis (p < 0.05) and refined with multivariable analysis to define a predictive immune profile.

RESULTS:

525 stimulant samples with 19,950 stimulant-cytokine combinations across three periods were studied, including 61 episodes of infection. Mitogen-stimulated release of IL3 and IL5 were significantly associated with increased risk for subsequent infection during maintenance therapy. A lower Th1/Th2 ratio and higher cytokine response ratios for IL5 and IL13 during maintenance therapy were also significantly associated with increased risk for infection. On multivariable analysis, only IL5 in response to mitogen stimulation was predictive of infection. The lack of cytokine response and numerical value of immune cells were not predictive of infection.

CONCLUSION:

Profiling cytokine release in response to mitogen stimulation can assist with predicting subsequent onset of infection in patients with hematological malignancy during maintenance therapy.

KEYWORDS:

immune; infection; myeloma; prediction; profiling; risk

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