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ed that blast cells from myelodysplastic syndrome (MDS) patients induce changes in MSC reflecting reprograming of the stromal cells.24 MSC may also influence hematopoi- etic precursors to promote leukemogenesis as evidenced by the development of AML and MDS in mice where the MSC osteo-progenitors were engineered to lack Dicer, a key regulator of microRNA (miR) processing.2 Furthermore, a recent study from Zhao et al. reported that p21 could be critical for inducing senescence in MSC from MDS patients with concomitant induction of interleukin- 6 (IL6) and transforming growth factor β (TGF-β).25 This study is consistent with findings that support the role of Dicer in regulating MSC biology and also establish a pos- sible mechanism of aberrant survival functions in malig- nant MSC that may be associated with p21 and senes- cence. The ability of malignant MSC to withstand senes- cence may depend on the expression of the anti-apoptotic molecule BCL-XL.26,27
The cellular composition of stromal cells in a cancer microenvironment, such as the leukemic BM niche, is like- ly markedly different from that of the normal BM. We, therefore, set out to study the protein expression and acti- vation in leukemic MSC (AML-MSC) and compared and contracted these to normal MSC (NL-MSC) to determine if and how they are functionally different. Reverse phase protein array analysis (RPPA, pioneered in our laborato- ry)28-32 was used to examine expression of 151 proteins in MSC derived from AML BM (n=106) with those derived from healthy donors (n=71). The results presented here identify 28 that were differentially expressed between the two. Importantly, the 28 proteins identified as differential- ly expressed in the AML versus normal MSC could be grouped into four protein constellation (PC) expression signatures with different biological properties and clinical implications regarding patient response to therapy.
Methods
Patients’ samples
Bone marrow was obtained from AML patients (n=106) under- going diagnostic BM aspiration and from healthy donors (n=71) who were undergoing BM harvest for use in allogeneic BM trans- plantation. Samples were acquired in accordance with the regula- tions and protocols approved by the Investigational Review Board of MD Anderson Cancer Center. Informed consent was obtained in accordance with the Declaration of Helsinki. Samples were ana- lyzed under an Institutional Review Board-approved laboratory protocol. Patients' characteristics are presented in Table 1. Details of isolation of MSC are available in the Online Supplementary Methods.
RPPA
Proteomic profiling was carried out on MSC samples from patients with AML and healthy donors using RPPA. The RPPA method and sample validation technique are described fully else- where.28-32 Antibodies against 151 proteins were used for analysis. (A list and the source of the antibodies and the concentrations uti- lized is provided in the Online Supplementary Table S1). The sources of antibodies have been been reported previously.30 An IgG sub- type-specific secondary antibody was used to amplify the signal, and finally a stable dye was precipitated. The stained slides were analyzed using the Microvigene software (version 3.0, Vigene Tech, Carlise, MA, USA) to produce quantified data. Statistical analyses are described in the Online Supplementary Methods.
Cell senescence assessment
haematologica | 2018; 103(5)
Proteomic profiling reveals complexity of AML MSC
Microscopy assessment of β-galactosidase staining was used to detect cell senescence using a detection kit from Cell Signal Technology (Boston, MA, USA). Early passage cells (passage 2) were imaged using a Nikon Coolpix 950 camera attached to a Nikon TMS light microscope (Nikon Instruments Inc.). AML-MSC (n=4) and NL-MSC (n=5) were lysed in kit buffer. Measurement of β-galactosidase was performed using an in vitro fluorometric assay with fluorescein di-β-D-galactopyranoside (FDG) as substrate. Incubation time was 2 hours (h). Fluorescence was measured using an Optima Fluorometer (Durham, NC, USA). Activity is pre- sented as fluorescence units/1000 cells/minute.
Pathway analysis
String software (String 10.1; available from: http://string-db.org)33 was used to determine protein associations. Pathway analysis to identify canonical pathways, upstream regulators, and protein net- works was performed using Ingenuity Pathway software (Qiagen).
Results
Proteins are differentially expressed in AML versus healthy MSC
We have routinely utilized RPPA to analyze protein expression from clinical samples from many hematologic malignancies.28-32 We examined protein expression in blasts from newly diagnosed AML patients (n=85), CD34+ cells from normal donors (n=10), MSC from healthy donors (n=71), and MSC from newly diagnosed AML patients (n=54). Both normal MSC and AML-MSC expressed MSC defining lineage markers CD73, CD90, and CD 105 as determined by flow cytometry (Online Supplementary Figure S1). MSC from salvage samples (i.e. relapse/refrac- tory) were also studied (n=46). The RPPA was probed with 151 antibodies targeting 119 different proteins (114 targeting total protein with 32 paired antibodies targeting phosphoepitopes on 26 proteins, and 5 with only a phos- phoepitope but not total protein epitope) covering a wide variety of cellular functions and pathways (Online Supplementary Table S1). Protein expression in AML-MSC, NL-MSC, AML blasts and normal CD34+ cells was com- pared using principle component analysis (Online Supplementary Figure S1) and unbiased hierarchical cluster- ing (Online Supplementary Figure S2B). NL-MSC and AML- MSC formed a cluster distinct from AML blasts and NL- CD34+ cells with the vast majority of the 151 proteins test- ed showing statistically significant differential expression (143 of 151, P=0.01; 124 of 151, P≤10-6) between MSC and the blast/CD34+ cells. This unsurprising observation is consistent with a previous report that gene expression profiles are distinct between blood cells and MSC.34 Principal component analysis (PCA) also shows that pro- tein expression in NL-CD34+ cells is distinct from that of AML blasts. These findings were identical to those observed when the analysis was restricted to samples from newly diagnosed patients alone.
Next we investigated whether protein expression in AML-MSC was different from that of NL-MSC. In PCA, the NL-MSC occupied a distinct space from that of the AML-MSC (Figure 1A). Unbiased hierarchical clustering comparing AML-MSC and NL-MSC revealed differential expression of 28 of those proteins (P<0.001; Q=0.0059). The Q-value, a measure of the false discovery rate deter- mined by a β-uniform mixture model highlights that these
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