Scientific publications

FlowCT for the analysis of large immunophenotypic datasets and biomarker discovery in cancer immunology

Sep 29, 2021 | Magazine: Blood Advances

Cirino Botta  1 , Catarina Da Silva Maia  2 , Juan-José Garcés  3 , Rosalinda Termini  4 , Cristina Perez  5 , Irene Manrique  6 , Leire Burgos  1 , Aintzane Zabaleta  7 , Diego Alignani  8 , Sarai Sarvide  9 , Juana Merino  10 , Noemi Puig  11 , Maria-Teresa Cedena  12 , Marco Rossi  13 , Pierfrancesco Tassone  13 , Massimo Gentile  14 , Pierpaolo Correale  15 , Ivan Borrello  16 , Evangelos Terpos  17 , Tomas Jelinek  18 , Artur Paiva  19 , Aldo M Roccaro  20 , Hartmut Goldschmidt  21 , Hervé Avet-Loiseau  22 , Laura Rosinol Dachs  23 , Maria-Victoria Mateos  24 , Joaquin Martinez-Lopez  25 , Juan-Jose Lahuerta  26 , Joan Bladé  27 , Jesus F San-Miguel  28 , Bruno Paiva  29


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 to capture full cellular diversity and provide reproducible results.

We present FlowCT, a semi-automated workspace empowered to analyze large datasets that 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) vs peripheral blood (PB) of patients with smoldering multiple myeloma (MM); 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 in 150 smoldering MM patients (hazard ratio [HR]: 1.7; P <.001), and of progression-free (HR: 4.09; P <.0001) and overall survival (HR: 3.12; P =.047) in 100 active MM patients, were identified.

New data also emerged about stem cell memory T cells, the concordance between immune profiles in BM vs 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.

CITATION  Blood Adv. 2022 Jan 25;6(2):690-703.  doi: 10.1182/bloodadvances.2021005198.