Deep molecular profiling of synovial biopsies in the STRAP trial identifies signatures predictive of treatment response to biologic therapies in rheumatoid arthritis
Myles Lewis, Cankut Çubuk, Anna E. A. Surace, Elisabetta Sciacca, Rachel Lau, Katriona Goldmann, Giovanni Giorli, Liliane Fossati‐Jimack, Alessandra Nerviani, Felice Rivellese, Costantino Pitzalis, the STRAP collaborative group, 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, Michael R. Ehrenstein, Pauline Ho, Joaquim P. Pereira, Bhaskar Dasgupta, 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, Stefano Marcia, Stefano Marini, Stephen Kelly, Vasco Romão, James Galloway, Hector Chinoy, Désirée van der Heijde, Peter Sasieni, Anne Barton
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.