Multi-Parametric Single Cell Profiling Defines Distinct Drug Responses in Healthy Hematological Cell Lineages That Are Retained in Corresponding Malignant Cell Types

Abstract

▪BackgroundDuring hematopoiesis, multipotent stem cells and pluripotent precursors undergo a complex differentiation program to generate a diverse set of blood cell types with wide-ranging phenotypes and functions that may shape their initial response to therapies. Therefore, innate drug sensitivity in healthy cells provides insight into cell specific responses, aids identification of lineage specific anticancer therapies and reveals off-target effects. To characterize the diversity in drug response and intracellular signal transduction patterns in the major hematopoietic cell types, we simultaneously assessed their sensitivity to 71 small molecules utilizing a multi-parametric flow cytometry assay and mapped onto their proteomic and basal signaling profiles.MethodsHuman BM aspirates and PB samples were collected after written informed consent in compliance with the Declaration of Helsinki. Mononuclear cells from 331 BM aspirates or PB samples were isolated by density gradient centrifugation (Ficoll-Paque Premium; GE Healthcare). Cytometric analyses of drug responses were performed assay using a high throughput flow cytometer (iQue®Screener PLUS) in both 384 well (in 3 healthy samples, 71 drugs) and 96 well plate formats (in 26 samples, 6 drugs) to study drug effects in 5 concentrations (1-10,000 nM). Effect of bortezomib, clofarabine, dexamethasone, omipalisib, venetoclax and navitoclax were assessed on 10 cell populations, namely hematopoietic stem cells (HSCs) (CD34+CD38-), common progenitor cells (CPCs) (CD34+CD38+), monocytes (CD14+), B cells (CD45+CD19+), cytotoxic T cells (CD45+CD3+CD8+), T helper cells (CD45+CD3+CD4+), NK-T cells (CD45+CD3+CD56+), NK cells (CD45+CD56+CD3-), plasma cells (CD138+CD38) and granulocytes (CD45+, SSC++). Mass cytometry (CyTOF) was applied to investigate basal signaling activity of 9 proteins involved in MAPK, JAK-STAT, NF-κB and PI3K-mTOR signaling. Protein abundances in CD3+, CD14+ and CD19+ cells were investigated in six samples using mass spectrometry. To evaluate whether the distinct drug sensitivities detected in the cells of origin could be exploited in the malignant cell counterpart cell, ex vivo drug responses detected in healthy cells were compared to a cohort of 281 primary samples derived from multiple hematological malignancies.ResultsUnsupervised hierarchical clustering of drug response to 71 small molecules identified distinct drug responses in healthy cell subsets based on their cellular lineage. Compared to other cell types, B and NK cells were more sensitive to dexamethasone, venetoclax and midostaurin. Monocytes were more sensitive to trametinib which did not correlate to resting ERK1/2 phosphorylation. Venetoclax exhibited dose dependent cell selectivity to lymphocytes that inversely correlated to STAT3 phosphorylation. Elevated expression of catalase (CAT) and calprotectin (S100A8/S100A9) in monocytes corresponded to their intrinsic resistance to dexamethasone and venetoclax. Comparison of drug responses for six aforementioned drugs in healthy and neoplastic cells across 281 patient samples showed that healthy cell responses are predictive of the corresponding malignant cell response.ConclusionApplying a high content, multi-parametric single-cell assay, we could assess the diversity in drug effects on 10 different cell populations in individual donor samples. Our results demonstrate that cell subtypes are drastically different from each other with respect to protein abundance, signaling profiles and drug-response patterns against a diverse collection of anticancer drugs. Importantly, cell subset specific sensitivity and resistance mechanisms were clearly reflected in their malignant state. Taken together, understanding drug sensitivity in the healthy cell-of-origin provides opportunities to obtain a new level of therapy precision and avoid off-target toxicity. DisclosuresMustjoki:Ariad: Research Funding; Pfizer: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria, Research Funding. Wennerberg:Novartis: Research Funding. Porkka:Novartis: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Gjertsen:Seattle Genetics: Consultancy; BerGenBio: Consultancy; Kinn Therapeutics: Membership on an entity's Board of Directors or advisory committees; Alden Cancer Therapy 2: Equity Ownership; Boehringer Ingelheim: Research Funding; Alden Cancer Therapy 2: Membership on an entity's Board of Directors or advisory committees; Alden Cancer Therapy 2: Patents & Royalties: Alden Cancer Therapy II patent application in relation to CryoIT trial.; Kinn Therapeutics: Equity Ownership; Novartis: Consultancy. Heckman:Novartis: Research Funding; Orion Pharma: Research Funding; Celgene: Research Funding.