Predicting therapeutic response to fingolimod treatment in multiple sclerosis patients

Quirant‐Sánchez, Bibiana; Hervás-García, J.V.; Teniente‐Serra, Aina; Brieva, Luís; Moral‐Torres, Ester; Cano, Antonio; Munteis, Elvira; Mansilla, María José; Presas-Rodríguez, Silvia; Navarro‐Barriuso, Juan; Ramo‐Tello, C.; Martı́nez-Cáceres, Eva

doi:10.1111/cns.12851

Cited by 30 publications

(36 citation statements)

References 27 publications

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“…Nevertheless, we could not prove an increased incidence of infectious adverse events in the lower vs. higher-level lymphopenia group. These data are in line with several studies presenting primarily mild to moderate infections during fingolimod ( 8 , 18 , 28 ) The most relevant infectious complication in fingolimod treated patients is defined by varicella-zoster virus (VZV) and herpes simplex virus (HSV) infection or reactivation ( 8 , 18 , 33 ). However, individual variation of VZV specific T cell responses are assumed to be more relevant for upcoming VZV activation rather than absolute lymphocyte counts ( 34 , 35 ).…”

Section: Discussionsupporting

confidence: 87%

Real World Lab Data: Patterns of Lymphocyte Counts in Fingolimod Treated Patients

et al. 2018

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Objective:Fingolimod is approved for the treatment of highly active relapsing remitting multiple sclerosis (MS) patients and acts by its unique mechanism of action via sphingosine-1-phosphate receptor-modulation. Although fingolimod-associated lymphopenia is a well-known phenomenon, the exact cause for the intra- and inter-individual differences of the fluctuation of lymphocyte count and its subtypes is still subject of debate. In this analysis, we aim to estimate the significance of the individual variation of distinct lymphocyte subsets for differences in absolute lymphocyte decrease in fingolimod treated patients and discuss how different lymphocyte subset patterns are related to clinical presentation in a long-term real life setting.Methods/Design:One hundred and thirteen patients with MS were characterized by complete blood cell count and immune cell phentopying of peripheral lymphocyte subsets before, at month 1 and every 3 months up to 36 months of fingolimod treatment. In addition, patients were monitored regarding clinical parameters (relapses, disability, MRI).Results:There was no significant association of baseline lymphocyte count and lymphocyte subtypes with lymphocyte decrease after fingolimod start. The initial drop of the absolute lymphocyte count could not predict the level of lymphocyte count during steady state on fingolimod. Variable CD8+ T cell and NK cell counts account for the remarkable intra- and inter-individual differences regarding initial drop and steady state level of lymphocyte count during fingolimod treatment, whereas CD4+ T cells and B cells mostly present a quite uniform decrease in all treated patients. Selected patients with lymphocyte count >1.0 GPT/l differed by higher CD8+ T cells and NK cell counts compared to lymphopenic patients but presented comparable clinical effectiveness during treatment.Conclusion:Monitoring of the absolute lymphocyte count at steady state seems to be a rough estimate of fingolimod induced lymphocyte redistribution. Our results suggest, that evaluation of distinct lymphocyte subsets as CD4+ T cells allow a more detailed evaluation to weigh and interpret degree of lymphopenia and treatment response in fingolimod treated patients.

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Section: Discussionsupporting

confidence: 87%

Real World Lab Data: Patterns of Lymphocyte Counts in Fingolimod Treated Patients

et al. 2018

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“…In a previous report, pretreatment differences were found between the responder and NR patients in the transitional B and RTE cells ( 34 , 35 ). Our study differed from those results probably due to differences in patient selection.…”

Section: Discussionmentioning

confidence: 81%

Immunophenotype and Transcriptome Profile of Patients With Multiple Sclerosis Treated With Fingolimod: Setting Up a Model for Prediction of Response in a 2-Year Translational Study

Torres

Garcı́a²,

Marconi

et al. 2018

Front. Immunol.

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BackgroundFingolimod is a functional sphingosine-1-phosphate antagonist approved for the treatment of multiple sclerosis (MS). Fingolimod affects lymphocyte subpopulations and regulates gene expression in the lymphocyte transcriptome. Translational studies are necessary to identify cellular and molecular biomarkers that might be used to predict the clinical response to the drug. In MS patients, we aimed to clarify the differential effects of fingolimod on T, B, and natural killer (NK) cell subsets and to identify differentially expressed genes in responders and non-responders (NRs) to treatment.Materials and methodsSamples were obtained from relapsing–remitting multiple sclerosis patients before and 6 months after starting fingolimod. Forty-eight lymphocyte subpopulations were measured by flow cytometry based on surface and intracellular marker analysis. Transcriptome sequencing by next-generation technologies was used to define the gene expression profiling in lymphocytes at the same time points. NEDA-3 (no evidence of disease activity) and NEDA-4 scores were measured for all patients at 1 and 2 years after beginning fingolimod treatment to investigate an association with cellular and molecular characteristics.ResultsFingolimod affects practically all lymphocyte subpopulations and exerts a strong effect on genetic transcription switching toward an anti-inflammatory and antioxidant response. Fingolimod induces a differential effect in lymphocyte subpopulations after 6 months of treatment in responder and NR patients. Patients who achieved a good response to the drug compared to NR patients exhibited higher percentages of NK bright cells and plasmablasts, higher levels of FOXP3, glucose phosphate isomerase, lower levels of FCRL1, and lower Expanded Disability Status Scale at baseline. The combination of these possible markers enabled us to build a probabilistic linear model to predict the clinical response to fingolimod.ConclusionMS patients responsive to fingolimod exhibit a recognizable distribution of lymphocyte subpopulations and a different pretreatment gene expression signature that might be useful as a biomarker.

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“…Cell markers used to define each leukocyte subpopulations are specified in Table S1. The gating strategy used is based on an international consensus and was previously described by Teniente‐Serra and Quirant‐Sánchez …”

Section: Methodsmentioning

confidence: 99%

“…Leukocyte subpopulations were analyzed by using the following four panels of monoclonal antibodies, previously reported by Quirant‐Sánchez et al: (a) T‐cell panel: CD3‐V450, CD4‐PerCP‐Cy5.5, CD45RA‐PE‐Cy7, CCR7‐PE, CD38‐APC, CD8‐APC‐H7, HLA‐DR‐V500 (BD Biosciences), CXCR3‐AF488, CCR6‐BV605, and CD45‐AF700 (BioLegend); (b) Treg panel: CD4‐PerCP‐Cy5.5, CD25‐PE, CCR4‐PE‐Cy7, CD127‐AF647, CD45RO‐APC‐H7, CD3‐V450, HLA‐DR‐V500 (BD Biosciences), and CD45‐AF700 (BioLegend); (c) B‐cell panel: CD24‐FITC, CD19‐PerCP‐Cy5.5, CD38‐APC, CD20‐APC‐H7, CD3‐V500 (BD Biosciences), IgD‐PE‐Cy7, CD27‐BV421, and CD45‐AF700 (BioLegend); and (d) DC/monocyte/NK panel: CD3 + CD19‐APC‐H7, CD56‐PE, CD16‐APC, CD14‐V450, CD123‐PerCP‐Cy5.5, CD11c‐PE‐Cy7, HLA‐DR‐V500 (BD Biosciences), and slan‐FITC (Miltenyi Biotec).…”

Section: Methodsmentioning

confidence: 99%

Optimal response to dimethyl fumarate is mediated by a reduction of Th1‐like Th17 cells after 3 months of treatment

et al. 2019

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Aim Dimethyl fumarate (DMF) is one of the most promising therapies for relapsing‐remitting multiple sclerosis (RRMS) patients since it has shown immunomodulatory and neuroprotective effects. However, a percentage of RRMS patients do not exhibit an optimal response to DMF. The objective of this study was to identify early biomarkers of treatment response by analyzing changes in peripheral leukocyte subpopulations directly in whole blood samples. Methods A longitudinal and prospective study analyzing peripheral blood leukocyte subpopulations in 22 RRMS patients before initiating DMF treatment (baseline) and at 1, 3, 6, and 12 months of follow‐up was performed. Differences between no evidence of disease activity (NEDA) and ongoing disease activity (ODA) patients were analyzed. Results The beneficial effect of DMF was associated with a specific depletion of memory CD4+ and CD8+ T lymphocytes and B cells. Importantly, only NEDA patients showed (a) a shift from a pro‐ to an antiinflammatory profile, with an increase of Th2 cells and a decrease of Th1‐like Th17 lymphocytes; and (b) an increase of regulatory CD56bright NK cells. Conclusion The optimal response to DMF is mediated by a shift to antiinflammatory and immunoregulatory profile, which puts forward Th1‐like Th17 lymphocytes as a potential early biomarker of treatment response.

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Predicting therapeutic response to fingolimod treatment in multiple sclerosis patients

Abstract: The results support that immune-monitoring of lymphocyte subpopulations in peripheral blood is a promising tool to select RRMS candidate for fingolimod treatment.

Cited by 30 publications

References 27 publications

Real World Lab Data: Patterns of Lymphocyte Counts in Fingolimod Treated Patients

Real World Lab Data: Patterns of Lymphocyte Counts in Fingolimod Treated Patients

Immunophenotype and Transcriptome Profile of Patients With Multiple Sclerosis Treated With Fingolimod: Setting Up a Model for Prediction of Response in a 2-Year Translational Study

Optimal response to dimethyl fumarate is mediated by a reduction of Th1‐like Th17 cells after 3 months of treatment

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