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.
- MeSH
- biologické markery MeSH
- doutnající mnohočetný myelom * MeSH
- imunofenotypizace MeSH
- kostní dřeň MeSH
- lidé MeSH
- průtoková cytometrie metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
The reason why a few myeloma cells egress from the bone marrow (BM) into peripheral blood (PB) remains unknown. Here, we investigated molecular hallmarks of circulating tumor cells (CTCs) to identify the events leading to myeloma trafficking into the bloodstream. After using next-generation flow to isolate matched CTCs and BM tumor cells from 32 patients, we found high correlation in gene expression at single-cell and bulk levels (r ≥ 0.94, P = 10-16), with only 55 genes differentially expressed between CTCs and BM tumor cells. CTCs overexpressed genes involved in inflammation, hypoxia, or epithelial-mesenchymal transition, whereas genes related with proliferation were downregulated in CTCs. The cancer stem cell marker CD44 was overexpressed in CTCs, and its knockdown significantly reduced migration of MM cells towards SDF1-α and their adhesion to fibronectin. Approximately half (29/55) of genes differentially expressed in CTCs were prognostic in patients with newly-diagnosed myeloma (n = 553; CoMMpass). In a multivariate analysis including the R-ISS, overexpression of CENPF and LGALS1 was significantly associated with inferior survival. Altogether, these results help understanding the presence of CTCs in PB and suggest that hypoxic BM niches together with a pro-inflammatory microenvironment induce an arrest in proliferation, forcing tumor cells to circulate in PB and seek other BM niches to continue growing.
- MeSH
- epitelo-mezenchymální tranzice genetika MeSH
- exprese genu genetika MeSH
- genetická transkripce genetika MeSH
- hypoxie genetika patologie MeSH
- kostní dřeň patologie MeSH
- lidé MeSH
- mnohočetný myelom genetika patologie MeSH
- nádorové buněčné linie MeSH
- nádorové cirkulující buňky patologie MeSH
- nádorové kmenové buňky patologie MeSH
- nádorové mikroprostředí genetika MeSH
- pohyb buněk genetika MeSH
- prognóza MeSH
- proliferace buněk genetika MeSH
- zánět genetika patologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
