Successful identification of predictive profiles for infection utilising systems-level immune analysis: a pilot study in patients with relapsed and refractory multiple myeloma

利用系统级免疫分析成功识别感染预测特征:针对复发和难治性多发性骨髓瘤患者的一项初步研究

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作者:Marcel Doerflinger, Alexandra L Garnham, Saskia Freytag, Simon J Harrison, H Miles Prince, Hang Quach, Monica A Slavin, Marc Pellegrini, Benjamin W Teh

Conclusion

Immune cell counts were not useful predictors of infection risk. Functional assessment of stimulated PBMCs has identified potential immune profiles that may predict future infection risk in patients with RRMM.

Methods

Patients with relapsed and/or refractory MM (RRMM) who participated in a treatment trial of lenalidomide and dexamethasone were evaluated. Data on patient demographics, disease and episodes of infection were extracted from clinical records. Peripheral blood mononuclear cells (PBMCs) collected at defined intervals were analysed, with or without mitogen re-stimulation, using RNA sequencing and mass cytometry (CyTOF). CyTOF-derived cell subsets and RNAseq gene expression profiles were compared between patients that did and did not develop infection to identify immune signatures that predict infection over a 3-month period.

Results

Twenty-three patients participated in the original treatment trial, and we were able to access samples from 17 RRMM patients for further evaluation in our study. Nearly half the patients developed an infection (8/17) within 3 months of sample collection. Infections were mostly clinically diagnosed (62.5%), and the majority involved the respiratory tract (87.5%). We did not detect phenotypic or numerical differences in immune cell populations between patients that did and did not develop infections. Transcriptional profiling of stimulated PBMCs revealed distinct Th2 immune pathway signatures in patients that developed infection.

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