Abstract
Earlier evaluation of therapy effect in patients with CML would assist in optimal use of available tyrosine kinase inhibitors (TKI). Single cell analysis by mass cytometry has enabled the quantification of up to 46 antibody epitopes, making it ideally suited for exhaustive immunophenotyping of the haematological hierarchy, and evaluation of associated dynamic signal transduction events, in a clinical setting. By integrating time resolved single cell signalling data with clinical parameters, we searched for prognostic and efficacy-response mass cytometry biomarkers within a month of TKI therapy. We report data from experiments used to validate the custom panels of antibodies, highlighting the power of mass cytometry in the analysis of primary patient material obtained on clinical studies.
Peripheral Blood (PB) samples were collected before, 3 hours, 7 days and 28 days, after start of nilotinib (300 mg BID) treatment in a subset of patients (n=55) enrolled in the ENEST1st trial.
PB cells were stained with two panels of antibodies, allowing a comprehensive immunophenotyping of numerous cellular subsets, and also the evaluation of intracellular phosphorylation status of several epitopes. Moreover, using a straightforward barcoding scheme, the time-resolved samples from each individual patient were pooled after barcoding and stained with the antibody panels to minimize sample variation.
In a pilot study, 7 and 10 cell subsets were identified in PB samples from 4 untreated healthy donors and 2 complete sets of 4 patients enrolled in this sub study, respectively. Furthermore, a robust signal was measured for pCrkL, pStat5, pStat3, pCreb, pAbl Y412 and pAbl Y245. The two sets of samples from study patients showed substantial changes in activation status over the course of therapy. Some changes, such as pStat3 alterations are only detectable in neutrophils and monocytes, while the activity of others i.e. pCreb was found to be ubiquitous. CD34+ cells indicated decreased phosphorylation of CrkL, Stat5, and Abl Y412/245.
To increase the immunophenotyping resolution of the myeloid lineage, 3 additional cell surface markers were incorporated into the cell surface panel. In 1 healthy donor, and in diagnostic samples from three patients enrolled in this sub study, this allowed the identification of 13 cell subsets: CD3+, CD4+, and CD8+ T cells, regulatory T cells (Tregs), monocytes, dendritic cells (DCs), plasmacytoid dendritic cells (pDC's), neutrophils, basophils, B cells, hematopoietic stem cells (Lin- CD34+ CD38-) and progenitor cells (Lin- CD34+ CD38-) (Figure 1 A,B). With respect to the relative number of cells identified for each cell type, the three diagnosis samples differed from the single healthy control. In the patients, we observed an expansion of the granulocytic compartment, as well as the emergence of CD34+ progenitor and stem cells in the peripheral blood.
In conclusion, the here presented developed assay is able to resolve most of the cell subpopulations found in the hematopoietic tree, and also robustly measure the activity of central signalling substrates known to be involved in CML pathogenesis. With the addition of new phospho-specific antibodies, the methodology may facilitate the detailed characterization of CML in an immunological context, and may shed new light on both the disease and therapeutic mechanism. Analysis of variation in signal responses and immune profile are now in progress in the subset of patients (n=55) in the ENEST1st trial.
Figure 1. Manually annotated SPADE tree from healthy donor and patient (3581_0002). With the incorporation of additional cell surface markers, the protocol was able to identify 13 cellular subsets in healthy donors (A) and a typical CML patient (B): CD3+, CD4+, and CD8+ T cells, regulatory T cells (Tregs), monocytes, dendritic cells (DCs), plasmacytoid dendritic cells (pDC's), neutrophils, basophils, B cells, hematopoietic stem cells (Lin- CD34+ CD38-) and progenitor cells (Lin- CD34+ CD38-). Figure 1. Manually annotated SPADE tree from healthy donor and patient (3581_0002). With the incorporation of additional cell surface markers, the protocol was able to identify 13 cellular subsets in healthy donors (A) and a typical CML patient (B): CD3+, CD4+, and CD8+ T cells, regulatory T cells (Tregs), monocytes, dendritic cells (DCs), plasmacytoid dendritic cells (pDC's), neutrophils, basophils, B cells, hematopoietic stem cells (Lin- CD34+ CD38-) and progenitor cells (Lin- CD34+ CD38-).
Disclosures
Thaler: AOP Orphan: Research Funding. Lang:Celgene: Consultancy. Hjorth-Hansen:Bristol-Myers Squibb: Research Funding; Ariad: Honoraria; Novartis: Honoraria; Pfizer: Honoraria, Research Funding. Hellmann:Novartis: Consultancy, Other: funding of travel, accomodations or expenses, Research Funding, Speakers Bureau; BMS: Consultancy, Other: funding of travel, accomodations or expenses, Speakers Bureau. Giles:Novartis: Consultancy, Honoraria, Research Funding. Hochhaus:Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; ARIAD: Honoraria, Research Funding. Janssen:ARIAD: Consultancy; Bristol Myers Squibb: Consultancy; Pfizer: Consultancy; Novartis: Research Funding. Porkka:Bristol-Myers Squibb: Honoraria; Celgene: Honoraria; Novartis: Honoraria; Pfizer: Honoraria. Ossenkoppele:Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding; ARIAD: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding. Mustjoki:Signe and Ane Gyllenberg Foundation: Research Funding; Finnish Cancer Institute: Research Funding; Sigrid Juselius Foundation: Research Funding; Pfizer: Honoraria, Research Funding; the Finnish Cancer Societies: Research Funding; Academy of Finland: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Gjertsen:Bergen University Hospital: Research Funding.