Novel approaches to develop biomarkers predicting treatment responses to TNF-blockers. (3rd April 2021)

• Record Type: Journal Article
• Authors: Mezghiche, Ikram; Yahia-Cherbal, Hanane; Rogge, Lars; Bianchi, Elisabetta
• Is Part Of: Expert review of clinical immunology. Volume 17:Number 4(2021)
• Page Start: 331
• Page End: 354
• Publication Date: 2021-04-03
• Subjects: Spondyloarthritis -- ankylosing spondylitis -- chronic inflammatory disease -- rheumatoid arthritis -- inflammatory bowel disease -- anti-TNF therapy -- biomarkers -- treatment response -- prediction -- transcriptome -- immune responses; Clinical immunology -- Periodicals; 616.079
• DOI: 10.1080/1744666X.2021.1894926
• Languages: English
• ISSNs: 1744-666X

Abstract

ABSTRACT: Introduction : Chronic inflammatory diseases (CIDs) cause significant morbidity and are a considerable burden for the patients in terms of pain, impaired function, and diminished quality of life. Important progress in CID treatment has been obtained with biological therapies, such as tumor-necrosis-factor blockers. However, more than a third of the patients fail to respond to these inhibitors and are exposed to the side effects of treatment, without the benefits. Therefore, there is a strong interest in developing tools to predict response of patients to biologics. Areas covered : The authors searched PubMed for recent studies on biomarkers for disease assessment and prediction of therapeutic responses, focusing on the effect of TNF blockers on immune responses in spondyloarthritis (SpA), and other CID, in particular rheumatoid arthritis and inflammatory bowel disease. Conclusions will be drawn about the possible development of predictive biomarkers for response to treatment. Expert opinion : No validated biomarker is currently available to predict treatment response in CID. New insight could be generated through the development of new bioinformatic modeling approaches to combine multidimensional biomarkers that explain the different genetic, immunological and environmental determinants of therapeutic responses.