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

Επιστημονική δημοσίευση - Άρθρο Περιοδικού uoadl:3034202 121 Αναγνώσεις

Μονάδα:
Ερευνητικό υλικό ΕΚΠΑ
Τίτλος:
FlowCT for the analysis of large immunophenotypic data sets and
biomarker discovery in cancer immunology
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
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 5 .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.
Έτος δημοσίευσης:
2022
Συγγραφείς:
Botta, Cirino
Maia, Catarina
Garces, Juan-Jose
Termini,
Rosalinda
Perez, Cristina
Manrique, Irene
Burgos, Leire and
Zabaleta, Aintzane
Alignani, Diego
Sarvide, Sarai
Merino,
Juana
Puig, Noemi
Cedena, Maria-Teresa
Rossi, Marco and
Tassone, Pierfrancesco
Gentile, Massimo
Correale, Pierpaolo and
Borrello, Ivan
Terpos, Evangelos
Jelinek, Tomas
Paiva, Artur
and Roccaro, Aldo
Goldschmidt, Hartmut
Avet-Loiseau, Herve and
Rosinol, Laura
Mateos, Maria-Victoria
Martinez-Lopez, Joaquin
and Lahuerta, Juan-Jose
Blade, Joan
San-Miguel, Jesus F. and
Paiva, Bruno
Programa Estudio Terapeutica Hemop
iMMunocell Study
Grp
Περιοδικό:
Blood advances
Εκδότης:
Elsevier
Τόμος:
6
Αριθμός / τεύχος:
2
Σελίδες:
690-703
Επίσημο URL (Εκδότης):
DOI:
10.1182/bloodadvances.2021005198
Το ψηφιακό υλικό του τεκμηρίου δεν είναι διαθέσιμο.