Large-scale immune monitoring is becoming routinely used in clinical trials to identify determinants of treatment responsiveness, particularly to immunotherapies. Flow cytometry remains one of the most versatile and high throughput approaches for single-cell analysis; however, manual interpretation of multidimensional data poses a challenge when attempting to capture full cellular diversity and provide reproducible results. We present FlowCT, a semi-automated workspace empowered to analyze large data sets. It includes pre-processing, normalization, multiple dimensionality reduction techniques, automated clustering, and predictive modeling tools. As a proof of concept, we used FlowCT to compare the T-cell compartment in bone marrow (BM) with peripheral blood (PB) from patients with smoldering multiple myeloma (SMM), identify minimally invasive immune biomarkers of progression from smoldering to active MM, define prognostic T-cell subsets in the BM of patients with active MM after treatment intensification, and assess the longitudinal effect of maintenance therapy in BM T cells. A total of 354 samples were analyzed and immune signatures predictive of malignant transformation were identified in 150 patients with SMM (hazard ratio [HR], 1.7; P < .001). We also determined progression-free survival (HR, 4.09; P < .0001) and overall survival (HR, 3.12; P = .047) in 100 patients with active MM. New data also emerged about stem cell memory T cells, the concordance between immune profiles in BM and PB, and the immunomodulatory effect of maintenance therapy. FlowCT is a new open-source computational approach that can be readily implemented by research laboratories to perform quality control, analyze high-dimensional data, unveil cellular diversity, and objectively identify biomarkers in large immune monitoring studies. These trials were registered at www.clinicaltrials.gov as #NCT01916252 and #NCT02406144.

Centre de Recherche en Cancérologie de Toulouse Unité 1037 INSERM Toulouse France; and

Centro de Investigacion Medica Aplicada Instituto de Investigacion Sanitaria de Navarra Hematology Unit Clinica Universidad de Navarra Centro de Investigación Biomédica en Red Cancér Hematology Unit Pamplona Spain

Ciências Biomédicas Laboratoriais Escola Superior de Tecnologia da Saúde de Coimbra Instituto Politécnico de Coimbra Coimbra Portugal

Clinical and Experimental Medicine Department Magna Graecia University Catanzaro Italy

Clinical Research Development and Phase 1 Unit Azienda Socio Sanitaria Territoriale Spedali Civili di Brescia Brescia Italy

Department of Clinical Therapeutics Alexandra General Hospital National and Kapodistrian University of Athens School of Medicine Athens Greece

Department of Haemato oncology University Hospital Ostrava Ostrava Czech Republic

Department of Health Promotion Mother and Child Care Internal Medicine and Medical Specialties University of Palermo Palermo Italy

Faculty of Medicine Coimbra Institute for Clinical and Biomedical Research University of Coimbra Coimbra Portugal

Hematology Unit Department of Oncology Annunziata Hospital of Cosenza Cosenza Italy

Hospital Clínic Institut d'Investigacions Biomèdiques August Pi i Sunyer Barcelona Spain

Hospital Universitario 12 de Octubre Madrid Spain

Hospital Universitario de Salamanca Hematología Instituto de Investigación Biomédica de Salamanca Salamanca Spain

Medical Oncology Unit Great Metropolitan Hospital Riuniti of Reggio Calabria Reggio Calabria Italy

Sidney Kimmel Comprehensive Cancer Center Johns Hopkins University Baltimore MD

Unidade de Gestão Operacional de Citometria Centro Hospitalar e Universitário de Coimbra Coimbra Portugal

University Hospital Heidelberg Internal Medicine 5 and National Center for Tumor Diseases Heidelberg Germany

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ClinicalTrials.gov
NCT02406144, NCT01916252