Deep molecular profiling of synovial biopsies in the STRAP trial identifies signatures predictive of treatment response to biologic therapies in rheumatoid arthritis
Abstract
Abstract Approximately 40% of patients with rheumatoid arthritis do not respond to individual biologic therapies, while biomarkers predictive of treatment response are lacking. Here we analyse RNA-sequencing (RNA-Seq) of pre-treatment synovial tissue from the biopsy-based, precision-medicine STRAP trial (n = 208), to identify gene response signatures to the randomised therapies: etanercept (TNF-inhibitor), tocilizumab (interleukin-6 receptor inhibitor) and rituximab (anti-CD20 B-cell depleting antibody). Machine learning models applied to RNA-Seq predict clinical response to etanercept, tocilizumab and rituximab at the 16-week primary endpoint with area under receiver operating characteristic curve (AUC) values of 0.763, 0.748 and 0.754 respectively (n = 67-72) as determined by repeated nested cross-validation. Prediction models for tocilizumab and rituximab are validated in an independent cohort (R4RA): AUC 0.713 and 0.786 respectively (n = 65-68). Predictive signatures are converted for use with a custom synovium-specific 524-gene nCounter panel and retested on synovial biopsy RNA from STRAP patients, demonstrating accurate prediction of treatment response (AUC 0.82-0.87). The converted models are combined into a unified clinical decision algorithm that has the potential to transform future clinical practice by assisting the selection of biologic therapies.
Article Details
Authors (76)
Myles J. Lewis
Centre for Experimental Medicine & Rheumatology, William Harvey Research Institute and Barts and The London School of Medicine and Dentistry, Queen Mary University of London
Cankut Cubuk
Centre for Experimental Medicine & Rheumatology, William Harvey Research Institute and Barts and The London School of Medicine and Dentistry, Queen Mary University of London
Anna E. A. Surace
Elisabetta Sciacca
Rachel Lau
Katriona Goldmann
Centre for Experimental Medicine & Rheumatology, William Harvey Research Institute and Barts and The London School of Medicine and Dentistry, Queen Mary University of London
Giovanni Giorli
Liliane Fossati-Jimack
Alessandra Nerviani
Felice Rivellese
Costantino Pitzalis
Louise Warren
Edyta Jaworska
Michele Bombardieri
Frances Humby
Arthur G. Pratt
Andrew Filer
Nagui Gendi
Alberto Cauli
Ernest Choy
Iain McInnes
Patrick Durez
Christopher J. Edwards
Maya H. Buch
Elisa Gremese
Peter C. Taylor
Nora Ng
Juan D. Cañete
Sabrina Raizada
Neil D. McKay
Deepak Jadon
Pier Paolo Sainaghi
Richard Stratton
Royal Free Hospital, London
Michael R. Ehrenstein
Pauline Ho
Joaquim P. Pereira
Bhaskar Dasgupta
Medical Technology Research Centre, Anglia Ruskin University, Chelmsford, United Kingdom
Claire Gorman
Ahmed Zayat
Ana Rita Machado
Andrea Cuervo
Arti Mahto
Charlotte Rawlings
Chijioke Mosanya
Christopher D. Buckley
Chris Holroyd
Deborah Maskall
Francesco Carlucci
Georgina Thorburn
Gina Tan
Gloria Lliso-Ribera
Hasan Rizvi
Joanna Peel
João Eurico Fonseca
John D. Isaacs
Julio Ramírez
Laurent Meric de Bellefon
Mary Githinji
Mattia Congia
Neal Millar
Nirupam Purkayastha
Rakhi Seth
Raquel Celis
Rebecca Hands-Greenwood
Robert Landewé
Simone Perniola
Stefano Alivernini
Friedrich Alexander Universität Erlangen–Nürnberg, Erlangen, Germany
Stefano Marcia
Stefano Marini
Stephen Kelly
Vasco Romão
James Galloway
Hector Chinoy
Désirée van der Heijde
Peter Sasieni
Anne Barton