Des scientifiques ont découvert que le profilage moléculaire des tissus articulaires malades peut influencer considérablement l’efficacité de certains traitements médicamenteux destinés aux patients atteints de polyarthrite rhumatoïde (PR).
Une étude récente démontre que les gènes peuvent prédire la réponse des personnes aux traitements contre l’arthrite.
Selon une nouvelle étude de l’Université Queen Mary de Londres, le profilage moléculaire des tissus articulaires malades pourrait avoir un impact important sur l’efficacité de certains traitements médicamenteux contre la polyarthrite rhumatoïde (PR). L’étude a été publiée dans la revue Nature Medicine le 19 mai 2022. Les chercheurs ont également découvert certains gènes liés à la résistance à la plupart des thérapies médicamenteuses actuelles, souvent appelée maladie réfractaire, ce qui pourrait donner la clé pour trouver de nouveaux médicaments efficaces pour aider ces patients.
Bien que le traitement de l’arthrite se soit considérablement amélioré au cours des dernières décennies, une grande proportion d’individus (environ 40 %) ne répond pas à certains traitements médicamenteux, et 5 à 20 % des personnes atteintes sont résistantes à tous les types de médicaments existants.
Les chercheurs ont mené une étude clinique basée sur une biopsie auprès de 164 patients atteints d’arthrite, afin de tester leurs réactions au rituximab ou au tocilizumab – deux médicaments couramment utilisés pour traiter la PR. Les résultats de l’essai original, publiés dans ;” data-gt-translate-attributes=”[{” attribute=””>The Lancet in 2021, showed that in individuals with a low synovial B-cell molecular signature, just 12% reacted to a treatment that targets B cells (rituximab), whereas 50% responded to an alternate medication (tocilizumab). Both medications were equally effective when patients had high amounts of this genetic signature.
As part of the first-of-its-kind study, funded by the Efficacy and Mechanism Evaluation (EME) Programme, an MRC and NIHR partnership, the Queen Mary team also looked at the cases where patients did not respond to treatment via any of the drugs and found that there were 1,277 genes that were unique to them specifically.
Building on this, the researchers applied a data analysis technique called machine learning models to develop computer algorithms that could predict drug responses in individual patients. The machine learning algorithms, which included gene profiling from biopsies, performed considerably better at predicting which treatment would work best compared to a model which used only tissue pathology or clinical factors.
The study strongly supports the case for performing gene profiling of biopsies from arthritic joints before prescribing expensive so-called biologic targeted therapies. This could save the NHS and society considerable time and money and help avoid potential unwanted side effects, joint damage, and worse outcomes that are common among patients. As well as influencing treatment prescription, such testing could also shed light on which people may not respond to any of the current drugs on the market, emphasizing the need for developing alternative medications.
Professor Costantino Pitzalis, Versus Arthritis Professor of Rheumatology at the Queen Mary University of London, said: “Incorporating molecular information prior to prescribing arthritis treatments to patients could forever change the way we treat the condition. Patients would benefit from a personalized approach that has a far greater chance of success, rather than the trial-and-error drug prescription that is currently the norm.
“These results are incredibly exciting in demonstrating the potential at our fingertips, however, the field is still in its infancy and additional confirmatory studies will be required to fully realize the promise of precision medicine in RA.
“The results are also important in finding solutions for those people who unfortunately don’t have a treatment that helps them presently. Knowing which specific molecular profiles impact this, and which pathways continue to drive disease activity in these patients, can help in developing new drugs to bring better results and much-needed relief from pain and suffering.”
The incorporation of these signatures in future diagnostic tests will be a necessary step to translate these findings into routine clinical care.
Reference: “Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial” by Felice Rivellese, Anna E. A. Surace, Katriona Goldmann, Elisabetta Sciacca, Cankut Çubuk, Giovanni Giorli, Christopher R. John, Alessandra Nerviani, Liliane Fossati-Jimack, Georgina Thorborn, Manzoor Ahmed, Edoardo Prediletto, Sarah E. Church, Briana M. Hudson, Sarah E. Warren, Paul M. McKeigue, Frances Humby, Michele Bombardieri, Michael R. Barnes, Myles J. Lewis, Costantino Pitzalis, and the R4RA collaborative group, 19 May 2022, Nature Medicine.
DOI: 10.1038/s41591-022-01789-0
