Biomarkers for response to therapies

[frodo]

Having several disease modifying drugs available, is interesting to know what kind of response is expected for each one of the different drugs in a given patient. Several studies are aiming this question.

Several surrogates have been proposed to measure the efficacy of a drug, like time to relapse, or recently, NEDA-3 and NEDA-4 (no evidence of disease advance)

There are several recent studies focusing into biomarkers for disease response. This one focuses on first-line agents like IFNβ and glatiramer acetate, with limited data on mitoxantrone:

Pharmacogenetic Biomarkers to Predict Treatment Response in Multiple Sclerosis: Current and Future Perspectives
Source: https://www.hindawi.com/journals/msi/2017/6198530/

Is a large review summarising all data available at the beginning of 2017 regarding genetic predictors associated to responses to interferons, glatimer acetate and mitoxantrone. Though limited, it could be interesting anyway.

This other review speaks about some other biomarkers, which are also able to predict poor response to interferons:

Immunometabolic profiling of patients with multiple sclerosis identifies new biomarkers to predict disease activity during treatment with interferon beta-1a

Source: http://www.sciencedirect.com/science/ar ... 1617302577

Highlights

• Identification of possible biomarkers assessing therapeutic efficacy is a major goal in MS monitoring and prognosis.
• Baseline lower levels of MCP-1 positively correlate with MS activity.
• Baseline higher levels of IL-6 and leptin positively correlate with MS severity.
• sCD40-L, leptin and IL-6 act as predictors of number of relapses.
• sTNF-R levels are related with risk to develop acute lesions on MRI.

Finally, a new study shows that blood lymphocyte subsets identify optimal responders to IFN-beta in MS

Blood lymphocyte subsets identify optimal responders to IFN-beta in MS

https://link.springer.com/article/10.10 ... 017-8625-6

Response to interferon-beta (IFN-beta) treatment is heterogeneous in multiple sclerosis (MS). We aimed to search for biomarkers predicting no evidence of disease activity (NEDA) status upon IFN-beta treatment in MS. 119 patients with relapsing–remitting MS (RRMS) initiating IFN-beta treatment were included in the study, and followed prospectively for 2 years. Neutralizing antibodies (NAb) were explored in serum samples obtained after 6 and 12 months of IFN-beta treatment.

Soluble cytokines and blood lymphocytes were studied in basal samples by ELISA and flow cytometry, respectively. 9% of patients developed NAb. These antibodies were more frequent in patients receiving IFN-beta 1b than in those treated subcutaneous (p = 0.008) or intramuscular (p < 0.0001) IFN-beta 1a. No patient showing NAb remained NEDA during follow-up.

Basal immunological variables are also associated with patient response. Percentages below 3% of CD19 + CD5 + cells (AUC 0.74, CI 0.63–0.84; OR 10.68, CI 3.55–32.15, p < 0.0001; Likelihood ratio 4.28) or above 2.6% of CD8 + perforin + T cells (AUC 0.79, CI 0.63–0.96; OR 6.11, CI 2.0–18.6, p = 0.0009; Likelihood ratio 5.47) increased the probability of achieving NEDA status during treatment. Basal blood immune cell subsets contribute to identify MS patients with a high probability of showing an optimal response to IFN-beta.

[frodo]

And here there is a review summarising the complete situation as of 2015

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4245485/

Conclusions:

A lack of understanding of the cause of MS, as well as disease heterogeneity, make it unlikely that one single biomarker will satisfy the needs for disease monitoring in MS. The identification of individual biomarker patterns is rapidly evolving into more complex biomarker panels or signatures.

In this regard, significant progress has been made since 2009 with respect to biomarker changes in response to therapy [7]. The challenge of biomarker development continues to be the lack of sensitivity and reproducibility. Furthermore, these studies rely on a large number of patients in an environment where research and clinical practice are closely integrated.

Despite these limitations, continued progress in biomarker research has led to early-stage clinical application of biomarkers in MS. Optimal treatment of individual patients with MS will ultimately require validated biomarker panels that are capable of predicting and monitoring the efficacy of the growing number of available therapeutic options.