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Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis
Biochemical and Biophysical Research Communications xxx (xxxx) xxx
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Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis Shu Zhou a, Xiaoying Zhu a, Wen Liu a, Fanjun Cheng a, **, Ping Zou a, Yong You a, Yi Xiao c, Anyuan Guo b, Xiaojian Zhu c, * a
Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China c Department of Hematology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 November 2019 Received in revised form 14 November 2019 Accepted 14 November 2019 Available online xxx
Tyrosine kinase inhibitors (TKIs) that target BCR-ABL are the standard first-line therapy for patients with chronic-phase CML. However, TKIs cannot eliminate quiescent leukemia stem cells (LSCs) which persist in all patients on long-term therapy and provides a reservoir for disease progression and recurrence. Many researches have confirmed that TKI-resistant LSCs compartment can be captured within CD26 þ fraction. In order to analyze distinctive biological characteristics of TKI-resistant LSCs, we isolated the CD34 þ CD38CD26þ, CD34 þ CD38CD26and CD34 þ CD38 þ cells from 8 CML patients utilizing magnetic and flow sorting, and analyzed the global proteomic expression through high-resolution LCMS/MS analysis. In the work, we discovered that a list of dysregulated proteins involved in energy metabolism and carcinogenesis, including PPARD, IL1-RAP, HNF, S15A2, PCLO, VA0D1, CKLF5, were extremely upregulated in the CD26 þ LSCs while some majoring in DNA mismatch repair or related to cell senescence, such as MLH3, NOLC1, were downregulated. Additionally, we verified the upregulation of PPARD in both CML patients-derived CD26 þ LSCs and donor-derived BCR-ABL1 overexpressed HSCs. These results open in turn new therapeutic avenues for targeting TKI-insensitive LSCs. © 2019 Elsevier Inc. All rights reserved.
Keywords: Chronic myeloid leukemia Leukemia stem cells CD26 Global proteome analysis
1. Introduction Chronic myeloid leukemia originates in a leukemia stem cell (LSC) caused by the acquisition of BCR-ABL in a hematopoietic stem cell (HSC) [1]. Tyrosine kinase inhibitor (TKI) that target BCR-ABL has revolutionized CML therapeutics, transforming CML into a chronic disease which can be well-controlled in the outpatient setting [2]. Under the proper treatment of TKI, the majority of cases achieve major molecular response (MMR), and approximately 10%e20% of all patients can develop even deeper molecular responses called complete molecular response (CMR) with
* Corresponding author. Department of Hematology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan 430030, China. ** Corresponding author. Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Road, Wuhan, 430022, China. E-mail addresses: [email protected] (F. Cheng), [email protected]. cn (X. Zhu).
undetectable BCR-ABL transcripts by qPCR [3]. Recently, treatmentfree remission (TFR) has been proposed as a goal for patients who achieved CMR [4]. However, in almost all TKI-discontinuation trials, approximate 40%e60% of patients relapsed within 12 months [5e8]. The main cause could be that quiescent CML-LSCs are resistant to TKIs and persist in all patients on long-term therapy, which provides a reservoir for disease progression and recurrence [1]. LSCs eradication has long been a challenge of great interest in a wide range of fields. Imatinib has antiproliferative effect on CML -LSCs but does not induce apoptosis [9]. Dasatinib, a second generation TKI, inhibits BCR-ABL activity more efficiently than Imatinib but still does not induce apoptosis of the quiescent LSCs subpopulation [10]. Further evidence has shown that LSCs survival is not dependent on BCR-ABL kinase activity [11]. Alternative mechanisms, including PI3K/AKT/mTOR and JAK-STAT signaling pathways, contribute to the maintenance of LSCs [12]. However, many pathways are also active in normal HSCs. Potential therapeutic targets must be validated to effectively eradicate CML-LSCs while
https://doi.org/10.1016/j.bbrc.2019.11.092 0006-291X/© 2019 Elsevier Inc. All rights reserved.
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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sparing normal counterparts. Researches have defined CD26 as a robust surface biomarker of CML-LSCs via analyzing CD34 þ CD38subpopulations separately derived from CML patients and healthy donors [13,14]. In the study, we isolated CD34 þ CD38CD26 þ subset from 8 CML patients, as well as CD34 þ CD38CD26, CD34 þ CD38 þ subsets, and applied a High-resolution LC-MS/MS analysis to identify proteomic expression difference among these three groups. 2. Materials and methods 2.1. Patients and isolation of cells After the informed consent was obtained from all individual participants, bone marrow samples from 8 CML patients and mobilized peripheral blood from 3 healthy donors were obtained. The CD34 þ cells were isolated from mononuclear cells (MNC) by positive selection using CD34 microbeads (Miltenyi Biotech, Germany). Furthermore, the three subpopulations were sorted by flow sorting after labeling with CD34-APC, CD38-PE-CY7, and CD26-PE (BD Biosciences, USA) according to the manufacturer’s instructions. After sorting the cells, we pooled the cells together; and measured the purity of isolation by flow analysis. All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Review Board of Tongji medical college and the Hubei committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. 2.2. Global proteomic analysis The cell deposit lysed in RIPA lysis buffer on ice. The protein concentrations were determined using a BCA protein assay kit (Pierce Biotechnology, USA). After trypsin digestion, peptide was desalted and reconstituted, and iTRAQ reagents (AB Sciex, USA) were added to peptide solution according to the manufacturer’s protocol. The dried and labeled peptide was reconstituted with HPLC solution A (2%ACN, pH 10) and then fractionated into fractions by high pH reverse-phase HPLC according to manufacturer’s instructions. The proteomic analysis was performed by NanoLC 1000 LC-MS/ MS using a Proxeon EASY-nLC 1000 coupled to Thermo Fisher Q Exactive. The raw data were searched against the reviewed Homo sapiens database downloaded from Uniprot database. Gene Ontology (GO) annotation proteome was derived from the UniProtGOA database (www. http://www.ebi.ac.uk/GOA/). 2.3. Confocal microscopy Cell smears were fixed in cold acetone/methanol (1:1 v/v) for 15 min, washed with PBS for 3 times, and treated with 0.5% TritonX100 (Beyotime, china) for 20 min, and incubated overnight at 4 C with the following primary anti-human antibodies diluted in PBS at optimal working dilutions: mouse anti-human CD26 (1:100, Santa Cruz Biotechnology Inc), rabbit anti-human PPARD (1:100, ABclonal technology), and then washed three times in PBS and incubated in the dark with fluorescent conjugate secondary antibodies (donkey anti-mouse-FITC, donkey anti-rabbit-Tex-Red) diluted 1:250 in PBS. The slides were sequentially washed in PBS, and finally mounted in mounting medium with DAPI (Sigma Aldrich, USA). The samples were then observed with a confocal laser scanning microscope. 2.4. Cell transduction Healthy donor-derived HSCs were suspended in StemSpan™
SFEM II (StemCell Technologies, France) supplemented with SCF (100 ng/ml), FLT-3-L (100 ng/ml), IL-3 (20 ng/ml), and IL-6 (20 ng/ ml) (PeproTech, USA), in a 96-well plate coated with 5 mg/ml RetroNectin (Takara, Japan). BCR-ABL1 lentiviral vectors were added and incubated with cell suspensions for 12 h. 2.5. Quantitative reverse transcription PCR (qRT-PCR) Total RNA was extracted with TRIzol (Takara, Japan) to synthesize cDNA using the Prime Script TM RT Reagent Kit (Takara, Japan). RT-PCR was performed on a Fast 7500 Real-Time PCR system (Applied Biosystems, Foster, CA). The final reaction volume (10 ml) included 5 ml SYBR Premix Ex Taq II, 0.2 ml ROX Reference Dye (Takara, Japan), 0.4 ml forward primers, 0.4 ml reverse primers (tsingke, china), 1 ml cDNA and 3 ml RNase-free H2O. Relative expression was analyzed using the 2-△△Ct method. The primer sequences used for RT-PCR were listed as below: GAPDH-F: GAGAAGGCTGGGGCTCATTT, GAPDH-R: AGTGATGGCATGGACTGTGG; PPARD-F: CAAGAGCATCCCCAGCTTCA PPARD-R: GGCCAGGTCACTGTCATCAA; ABL-F: ACATCACGCCAGTCAACAG, ABL-R: GACGTAGAGCTTGCCATCAGA; BCR-ABL1-F: GATGCTGACCAACTCGTGTG, BCR-ABL-R: GTTGGGGTCATTTTCACTGG. 2.6. Western blot analysis The protein samples (40 mg) for each well were separated by sodium dodecylsulfate-polyacrylamide gel electrophoresis and transferred to nitrocellulose membranes. The membranes were blocked with 5% non-fat milk and incubated overnight with a rabbit anti-human antibody: ACTIN (Servicebio), PPARD (1:100, ABclonal technology) at 4 C and HRP conjugated goat anti-rabbit secondary antibody (1:500), and detected by the chemiluminescent detection kit (Amersham Biosciences, USA). 2.7. Statistical analysis Statistical analyses were performed using GraphPad Prism v5.04. Paired Student’s t tests were used to identify significant differences between two groups. Data were given as mean ± SEM. A P value of <0.05 was considered significant. 3. Results 3.1. Clinical characteristics of the patients enrolled into the study We previously monitored the CD34 þ CD38CD26 þ subset in CML patients, and discovered that the percentage of this subpopulation, especially in the patients under molecular remission, was extremely low [15]. Here, we chose the bone marrow samples derived from the patients with high leukocyte to isolate the CMLLSC (CD34þCD38CD26þ), HSC (CD34þCD38CD26) and CD34 þ CD38 þ cells. After isolating the cells, we measured the purity of LSCs (>90%, Fig. 1A). Because the number of cells from only one patient was not enough to perform proteomic analysis, we recruited 8 patients and accumulated the cells for late use. The median age of the patients was 33 years (range, 20e64 years) and male: female ratio was 5:3; of them, only one patient took TKI before but discontinued it for a period of time, and then relapsed, and the other patients were at diagnose; and all the patients were in chronic phase (Table 1). When acquiring enough cells, we extracted the protein of these three groups, digested trypsin, labeled peptide isobaric and then developed high-resolution LCMS/MS analysis (Fig. 1B).
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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Fig. 1. Schematic overview of the study (A) The picture of flow analysis showed the proportion of CD34 þ CD38CD26 þ cells after isolated by CD34 magnetic positive sorting (up) and that after magnetic sorting combined with flow sorting (down); (B) Schematic outline of proteomic analysis methodology.
Table 1 | Clinical characteristics on the patients enrolled into the study. Participants (n ¼ 8)
Clinical feature Patients Age (median/range) SEX M F Diagnosis CP AP BP Treatments None TKI
3.2. The dysregulated proteins in CD34 proteomic analysis
33 (20e64) 5 3 8 0 0
3.3. The verification of PPARD in CML samples and BCR-ABL1 overexpressed donor HSCs
7 1
þ
CD38CD26
CD34 þ CD38CD26 þ and CD34 þ CD38 þ subsets. Numerous differential expression proteins were discovered, including PPARD, S15A2, TOB1, PLD1, PCLO, MT2, RS29, SEBP2, CNBP, HPS6, etc. (Fig. 2D). Besides, IL1-RAP once confirmed to be a biomarker to distinguish LSCs with HSCs [22] was also demonstrated in our study. But no significant difference of IL1-RAP expression was found in the comparison between CD34 þ CD38CD26 þ and CD34 þ CD38 þ subsets.
þ
cells by
In total, 4102 proteins were identified, and a list of proteins that were significantly different among these three groups have been established (Fig. 2A and B). 141 proteins were upregulated and 136 proteins were downregulated in CD34 þ CD38CD26 þ cells when compared to CD34 þ CD38CD26cells (1.5 & 0.01). The category of molecular function of these dysregulated proteins mainly involved in cellular process, metabolic process and biological regulation (Fig. 2C). In addition, a lot of differentially expressed proteins were obtained in CD34 þ CD38CD26 þ cells/CD34 þ CD38 þ group with 207 proteins up-regulated and 241 down-regulated (1.5 & 0.01). The detailed data was shown in the supplementary table. Among these differentially expressed proteins, we chose the top-regulated proteins of interest listed in the way of heat-map (Fig. 2D and E). We found that the PPARD, M3K14, HNF6, VA0D1, S15A2, CKLF5, and LPH protein, some of which were associated with carbohydrate, amino acid, lipid metabolism, energy production or carcinogenesis [16e18], were extremely upregulated, while the MLH3 (DNA mismatch repair [19,20]), NOLC1 (cell senescence [21]), ELNE, CKS2, WDR46, PPIL2, RHG44, HMGA1 protein were downregulated in the CD34 þ CD38CD26 þ cells when compared with CD34 þ CD38CD26cells (Fig. 2E). In addition, we also compared the differences between
Out of these differentially expressed proteins, we selected PPARD for further investigations because it was extremely upregulated in CD34 þ CD38CD26 þ cells rather than in CD34 þ CD38CD26and CD34 þ CD38 þ subsets. To confirm the result, we isolated the CD34 þ CD38cells from CML patients, and incubated them with anti-CD26 and anti-PPARD antibody. As shown in Fig. 3A, which represents one of the CML cases, the PPARD protein was co-expressed with CD26, while the blue nuclear staining by DAPI that identified the presence of some CD26cells exhibited little PPARD expression. In addition, we isolated the HSCs (CD34 þ CD38subset) from heathy donors and transduced them with BCR-ABL1 gene. The transduction efficiency was 26.6% which was reflected by GFP; and among the GFP þ infected cells, the percentage of CD34 þ was 80.3% (Supplementary Fig. 1). In addition, the expression of BCR-ABL1 was identified by RT-PCR (Fig. 3B). Surprisingly, in contrast to negative control vectors transfected HSCs, the BCR-ABL1 overexpressed HSCs showed much more expression of PPARD which was verified by RT-PCR (1.441 vs. 2.383, p < 0.05) (Fig. 3C) and western blotting (Fig. 3D). The results further identified the reliability of patientderived proteomic analysis. 4. Discussion In TKI era, the bottleneck of curing CML may be focused on purging TKI-insensitive LSCs. Accumulating evidence has demonstrated that TKIs have great effects on CML cells but not LSCs due to the additional mechanism promoting the LSCs survival without BCR-ABL dependence [12]. Much of literature to date has presented
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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Fig. 2. The differentially expressed proteins in CD34 þ CD38¡CD26 þ cells (A) The Protein Ratio Vocano analysis in CD34 þ CD38CD26 þ cells vs. CD34 þ CD38 þ cells and (B) in CD34 þ CD38CD26 þ cells vs. CD34 þ CD38CD26cells; (C) All regulated GO classification; (D) Heat map analysis of the significantly dysregulated proteins of CD34 þ CD38CD26 þ cells compared to CD34 þ CD38 þ cells and (E) of CD34 þ CD38CD26 þ cells compared to CD34 þ CD38CD26cells.
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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Fig. 3. The verification of PPARD (A) The representative confocal laser scanning microscopy of a bone marrow smear from CML patient; Scale bars 20 mm; in green, the CD26 þ cells; in red, cells expressing PPARD; in blue, the nuclei. (B) 3 healthy donors derived HSCs were transduced with BCR-ABL1; the transduction was identified by RT-PCR; (C) The BCR-ABL1 overexpressed HSCs shown much more expression of PPARD verified by RT-PCR; (D) and western blotting, showing a high concordance to RT-PCR results. NT: Negative control transduced HSCs; BCR-ABL1: BCR-ABL1 overexpressed HSCs. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
various results related to additional mechanism contributing to LSCs survival which can be divided into two aspects: selfcharacteristics and the microenvironment support [23e27]. Ste’phane Prost et al. discovered that STAT5 expression levels were abnormally high in both total CP-CML CD34 þ cells and quiescent LSCs, and activation of PPARg by the glitazones decreased expression of STAT5 and its downstream targets HIF2 and CITED2, which promoted the purging of LSCs [28]. Puneet Agarwa et al. highlighted a critical role of CXCL12-expressing BMM cells in maintaining quiescence of TKI-resistant LSC populations [27]. These finds reveal the part of complexity of LSCs and bone marrow microenvironment and contribute to the LSCs eradication. Besides, emerging researches have focus on the discovery of unique biomarker to distinguish LSCs from HSCs. Harald Herrmann et al. firstly defined CD26 as a robust biomarker to distinguish LSCs from HSCs by comparing CML-derived stem cells with healthy donor-derived cord blood stem cells [14]. Next, Rebecca Warfvinge et al. revealed CML LSCs heterogeneity and changes imposed by TKI therapy utilizing single-cell gene expression analysis, and further confirmed that the subpopulation with primitive, quiescent signature and increased survival to therapy can be high-purity captured as CD45RA-cKIT-CD26þ [13]. We previously monitored the CD26 þ LSCs in CML patients, and revealed that LSCs could be detected in different disease status without the value of reflecting disease burden [15], which reminded us to analyze the biological characteristics of these subpopulation. CD26 is indeed a good biomarker to distinguish CML-LSCs and HSCs, which seems to be a potential therapy target to eradicate CML-LSCs. However, there is still a lot of concerns that CD26 is widely expressed on some heathy tissues such as T cells [29]. Targeting CD26þ CML-LSCs by CD26 antagonist may lead to much offtarget effect. Additionally, the reason why CD26 þ LSCs can persist
in CML patients was not elucidated. Therefore, we utilized CD26 as a biomarker to isolate these CD26 þ LSC cells, explored the distinct characteristic of them, and discovered new biomarkers. Due to the technical difficulties to study exceedingly small primary cell populations, we accumulated the samples from 8 CML patients. Compared with previous researches, our study was designed by comparing LSCs to self-derived normal cells which may reduce the deviation among samples. In the study, many differently expressed proteins have been discovered by the high-resolution LC-MS/MS analysis, some of which may take part in the specific mechanism to support the LSCs survival. Some proteins involved in energy metabolism and carcinogenesis, were extremely upregulated in the CD26 þ LSCs, while some majoring in DNA mismatch repair or related to cell senescence were downregulated. IL1RAP, once reported to be a biomarker of CML-LSCs and predict therapy outcome [22], was also demonstrated to elevate in CML-LSCs in our study. Besides, treatments to target IL1RAP, such as recombinant IL-1 receptor antagonist [30], IL1RAP antibodies [31], and IL1RAP targeting chimeric antigen receptor (CAR) T cells [32], have been proved to be applicable in eliminating quiescent CML-LSCs. From the top-regulated proteins, we selected PPARD for verification and further investigation. It has been reported that SNPs in PPARD are associated with CML predisposition [33], but the putative role in CML development was not clarified. PPARD, one of three members of the PPAR group in the nuclear receptor superfamily, has been confirmed to play an important pathogenetic and predictive role across multiple cancers [17]. Modulation of cellular energy consumption is a major function of PPARD. Studies have demonstrated that PPARD can promote the fatty acid b-oxidation to increase ATP production in harsh microenvironmental conditions, contributing to the survival of many cancer cells, such as chronic lymphocytic leukemia cells [16]. PPARD may account for an
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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important hallmark of drug-resistant cancer cells, namely survival in harsh metabolic conditions. In our study, we found that PPARD was upregulated in LSCs, which may take part in the LSCs persistence in TKI condition. Additionally, we isolated HSCs from health donor and transfected with BCR-ABL1 by lentivirus vector, and found that the PPARD was upregulated in BCR-ABL1 positive HSCs, which demonstrated that BCR-ABL1 promoted the expression of PPARD in LSCs, probably in turn involving in the persistence of them in TKI treated condition. In summary, this study uncovers the global proteome analysis of CD26þ CML-LSCs and discovered the dysregulated protein list contributing to the LSCs maintenance, and opens in turn new therapeutic avenues for eliminating TKI-insensitive LSCs. Declaration of competing interest
[12] [13]
[14]
[15]
[16]
[17]
[18]
The authors declare that they have no conflict of interest. [19]
Acknowledgement [20]
This study was funded by the National Natural Science Foundation of China (NSFC) [81500136 to XJZ, and 81670145, 81873440 to YY; 81873444 to Yi Xiao]. Appendix A. Supplementary data
[21]
[22]
Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbrc.2019.11.092.
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Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis Shu Zhou a, Xiaoying Zhu a, Wen Liu a, Fanjun Cheng a, **, Ping Zou a, Yong You a, Yi Xiao c, Anyuan Guo b, Xiaojian Zhu c, * a
Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China c Department of Hematology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 November 2019 Received in revised form 14 November 2019 Accepted 14 November 2019 Available online xxx
Tyrosine kinase inhibitors (TKIs) that target BCR-ABL are the standard first-line therapy for patients with chronic-phase CML. However, TKIs cannot eliminate quiescent leukemia stem cells (LSCs) which persist in all patients on long-term therapy and provides a reservoir for disease progression and recurrence. Many researches have confirmed that TKI-resistant LSCs compartment can be captured within CD26 þ fraction. In order to analyze distinctive biological characteristics of TKI-resistant LSCs, we isolated the CD34 þ CD38CD26þ, CD34 þ CD38CD26and CD34 þ CD38 þ cells from 8 CML patients utilizing magnetic and flow sorting, and analyzed the global proteomic expression through high-resolution LCMS/MS analysis. In the work, we discovered that a list of dysregulated proteins involved in energy metabolism and carcinogenesis, including PPARD, IL1-RAP, HNF, S15A2, PCLO, VA0D1, CKLF5, were extremely upregulated in the CD26 þ LSCs while some majoring in DNA mismatch repair or related to cell senescence, such as MLH3, NOLC1, were downregulated. Additionally, we verified the upregulation of PPARD in both CML patients-derived CD26 þ LSCs and donor-derived BCR-ABL1 overexpressed HSCs. These results open in turn new therapeutic avenues for targeting TKI-insensitive LSCs. © 2019 Elsevier Inc. All rights reserved.
Keywords: Chronic myeloid leukemia Leukemia stem cells CD26 Global proteome analysis
1. Introduction Chronic myeloid leukemia originates in a leukemia stem cell (LSC) caused by the acquisition of BCR-ABL in a hematopoietic stem cell (HSC) [1]. Tyrosine kinase inhibitor (TKI) that target BCR-ABL has revolutionized CML therapeutics, transforming CML into a chronic disease which can be well-controlled in the outpatient setting [2]. Under the proper treatment of TKI, the majority of cases achieve major molecular response (MMR), and approximately 10%e20% of all patients can develop even deeper molecular responses called complete molecular response (CMR) with
* Corresponding author. Department of Hematology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan 430030, China. ** Corresponding author. Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Road, Wuhan, 430022, China. E-mail addresses: [email protected] (F. Cheng), [email protected]. cn (X. Zhu).
undetectable BCR-ABL transcripts by qPCR [3]. Recently, treatmentfree remission (TFR) has been proposed as a goal for patients who achieved CMR [4]. However, in almost all TKI-discontinuation trials, approximate 40%e60% of patients relapsed within 12 months [5e8]. The main cause could be that quiescent CML-LSCs are resistant to TKIs and persist in all patients on long-term therapy, which provides a reservoir for disease progression and recurrence [1]. LSCs eradication has long been a challenge of great interest in a wide range of fields. Imatinib has antiproliferative effect on CML -LSCs but does not induce apoptosis [9]. Dasatinib, a second generation TKI, inhibits BCR-ABL activity more efficiently than Imatinib but still does not induce apoptosis of the quiescent LSCs subpopulation [10]. Further evidence has shown that LSCs survival is not dependent on BCR-ABL kinase activity [11]. Alternative mechanisms, including PI3K/AKT/mTOR and JAK-STAT signaling pathways, contribute to the maintenance of LSCs [12]. However, many pathways are also active in normal HSCs. Potential therapeutic targets must be validated to effectively eradicate CML-LSCs while
https://doi.org/10.1016/j.bbrc.2019.11.092 0006-291X/© 2019 Elsevier Inc. All rights reserved.
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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sparing normal counterparts. Researches have defined CD26 as a robust surface biomarker of CML-LSCs via analyzing CD34 þ CD38subpopulations separately derived from CML patients and healthy donors [13,14]. In the study, we isolated CD34 þ CD38CD26 þ subset from 8 CML patients, as well as CD34 þ CD38CD26, CD34 þ CD38 þ subsets, and applied a High-resolution LC-MS/MS analysis to identify proteomic expression difference among these three groups. 2. Materials and methods 2.1. Patients and isolation of cells After the informed consent was obtained from all individual participants, bone marrow samples from 8 CML patients and mobilized peripheral blood from 3 healthy donors were obtained. The CD34 þ cells were isolated from mononuclear cells (MNC) by positive selection using CD34 microbeads (Miltenyi Biotech, Germany). Furthermore, the three subpopulations were sorted by flow sorting after labeling with CD34-APC, CD38-PE-CY7, and CD26-PE (BD Biosciences, USA) according to the manufacturer’s instructions. After sorting the cells, we pooled the cells together; and measured the purity of isolation by flow analysis. All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Review Board of Tongji medical college and the Hubei committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. 2.2. Global proteomic analysis The cell deposit lysed in RIPA lysis buffer on ice. The protein concentrations were determined using a BCA protein assay kit (Pierce Biotechnology, USA). After trypsin digestion, peptide was desalted and reconstituted, and iTRAQ reagents (AB Sciex, USA) were added to peptide solution according to the manufacturer’s protocol. The dried and labeled peptide was reconstituted with HPLC solution A (2%ACN, pH 10) and then fractionated into fractions by high pH reverse-phase HPLC according to manufacturer’s instructions. The proteomic analysis was performed by NanoLC 1000 LC-MS/ MS using a Proxeon EASY-nLC 1000 coupled to Thermo Fisher Q Exactive. The raw data were searched against the reviewed Homo sapiens database downloaded from Uniprot database. Gene Ontology (GO) annotation proteome was derived from the UniProtGOA database (www. http://www.ebi.ac.uk/GOA/). 2.3. Confocal microscopy Cell smears were fixed in cold acetone/methanol (1:1 v/v) for 15 min, washed with PBS for 3 times, and treated with 0.5% TritonX100 (Beyotime, china) for 20 min, and incubated overnight at 4 C with the following primary anti-human antibodies diluted in PBS at optimal working dilutions: mouse anti-human CD26 (1:100, Santa Cruz Biotechnology Inc), rabbit anti-human PPARD (1:100, ABclonal technology), and then washed three times in PBS and incubated in the dark with fluorescent conjugate secondary antibodies (donkey anti-mouse-FITC, donkey anti-rabbit-Tex-Red) diluted 1:250 in PBS. The slides were sequentially washed in PBS, and finally mounted in mounting medium with DAPI (Sigma Aldrich, USA). The samples were then observed with a confocal laser scanning microscope. 2.4. Cell transduction Healthy donor-derived HSCs were suspended in StemSpan™
SFEM II (StemCell Technologies, France) supplemented with SCF (100 ng/ml), FLT-3-L (100 ng/ml), IL-3 (20 ng/ml), and IL-6 (20 ng/ ml) (PeproTech, USA), in a 96-well plate coated with 5 mg/ml RetroNectin (Takara, Japan). BCR-ABL1 lentiviral vectors were added and incubated with cell suspensions for 12 h. 2.5. Quantitative reverse transcription PCR (qRT-PCR) Total RNA was extracted with TRIzol (Takara, Japan) to synthesize cDNA using the Prime Script TM RT Reagent Kit (Takara, Japan). RT-PCR was performed on a Fast 7500 Real-Time PCR system (Applied Biosystems, Foster, CA). The final reaction volume (10 ml) included 5 ml SYBR Premix Ex Taq II, 0.2 ml ROX Reference Dye (Takara, Japan), 0.4 ml forward primers, 0.4 ml reverse primers (tsingke, china), 1 ml cDNA and 3 ml RNase-free H2O. Relative expression was analyzed using the 2-△△Ct method. The primer sequences used for RT-PCR were listed as below: GAPDH-F: GAGAAGGCTGGGGCTCATTT, GAPDH-R: AGTGATGGCATGGACTGTGG; PPARD-F: CAAGAGCATCCCCAGCTTCA PPARD-R: GGCCAGGTCACTGTCATCAA; ABL-F: ACATCACGCCAGTCAACAG, ABL-R: GACGTAGAGCTTGCCATCAGA; BCR-ABL1-F: GATGCTGACCAACTCGTGTG, BCR-ABL-R: GTTGGGGTCATTTTCACTGG. 2.6. Western blot analysis The protein samples (40 mg) for each well were separated by sodium dodecylsulfate-polyacrylamide gel electrophoresis and transferred to nitrocellulose membranes. The membranes were blocked with 5% non-fat milk and incubated overnight with a rabbit anti-human antibody: ACTIN (Servicebio), PPARD (1:100, ABclonal technology) at 4 C and HRP conjugated goat anti-rabbit secondary antibody (1:500), and detected by the chemiluminescent detection kit (Amersham Biosciences, USA). 2.7. Statistical analysis Statistical analyses were performed using GraphPad Prism v5.04. Paired Student’s t tests were used to identify significant differences between two groups. Data were given as mean ± SEM. A P value of <0.05 was considered significant. 3. Results 3.1. Clinical characteristics of the patients enrolled into the study We previously monitored the CD34 þ CD38CD26 þ subset in CML patients, and discovered that the percentage of this subpopulation, especially in the patients under molecular remission, was extremely low [15]. Here, we chose the bone marrow samples derived from the patients with high leukocyte to isolate the CMLLSC (CD34þCD38CD26þ), HSC (CD34þCD38CD26) and CD34 þ CD38 þ cells. After isolating the cells, we measured the purity of LSCs (>90%, Fig. 1A). Because the number of cells from only one patient was not enough to perform proteomic analysis, we recruited 8 patients and accumulated the cells for late use. The median age of the patients was 33 years (range, 20e64 years) and male: female ratio was 5:3; of them, only one patient took TKI before but discontinued it for a period of time, and then relapsed, and the other patients were at diagnose; and all the patients were in chronic phase (Table 1). When acquiring enough cells, we extracted the protein of these three groups, digested trypsin, labeled peptide isobaric and then developed high-resolution LCMS/MS analysis (Fig. 1B).
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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Fig. 1. Schematic overview of the study (A) The picture of flow analysis showed the proportion of CD34 þ CD38CD26 þ cells after isolated by CD34 magnetic positive sorting (up) and that after magnetic sorting combined with flow sorting (down); (B) Schematic outline of proteomic analysis methodology.
Table 1 | Clinical characteristics on the patients enrolled into the study. Participants (n ¼ 8)
Clinical feature Patients Age (median/range) SEX M F Diagnosis CP AP BP Treatments None TKI
3.2. The dysregulated proteins in CD34 proteomic analysis
33 (20e64) 5 3 8 0 0
3.3. The verification of PPARD in CML samples and BCR-ABL1 overexpressed donor HSCs
7 1
þ
CD38CD26
CD34 þ CD38CD26 þ and CD34 þ CD38 þ subsets. Numerous differential expression proteins were discovered, including PPARD, S15A2, TOB1, PLD1, PCLO, MT2, RS29, SEBP2, CNBP, HPS6, etc. (Fig. 2D). Besides, IL1-RAP once confirmed to be a biomarker to distinguish LSCs with HSCs [22] was also demonstrated in our study. But no significant difference of IL1-RAP expression was found in the comparison between CD34 þ CD38CD26 þ and CD34 þ CD38 þ subsets.
þ
cells by
In total, 4102 proteins were identified, and a list of proteins that were significantly different among these three groups have been established (Fig. 2A and B). 141 proteins were upregulated and 136 proteins were downregulated in CD34 þ CD38CD26 þ cells when compared to CD34 þ CD38CD26cells (1.5 & 0.01). The category of molecular function of these dysregulated proteins mainly involved in cellular process, metabolic process and biological regulation (Fig. 2C). In addition, a lot of differentially expressed proteins were obtained in CD34 þ CD38CD26 þ cells/CD34 þ CD38 þ group with 207 proteins up-regulated and 241 down-regulated (1.5 & 0.01). The detailed data was shown in the supplementary table. Among these differentially expressed proteins, we chose the top-regulated proteins of interest listed in the way of heat-map (Fig. 2D and E). We found that the PPARD, M3K14, HNF6, VA0D1, S15A2, CKLF5, and LPH protein, some of which were associated with carbohydrate, amino acid, lipid metabolism, energy production or carcinogenesis [16e18], were extremely upregulated, while the MLH3 (DNA mismatch repair [19,20]), NOLC1 (cell senescence [21]), ELNE, CKS2, WDR46, PPIL2, RHG44, HMGA1 protein were downregulated in the CD34 þ CD38CD26 þ cells when compared with CD34 þ CD38CD26cells (Fig. 2E). In addition, we also compared the differences between
Out of these differentially expressed proteins, we selected PPARD for further investigations because it was extremely upregulated in CD34 þ CD38CD26 þ cells rather than in CD34 þ CD38CD26and CD34 þ CD38 þ subsets. To confirm the result, we isolated the CD34 þ CD38cells from CML patients, and incubated them with anti-CD26 and anti-PPARD antibody. As shown in Fig. 3A, which represents one of the CML cases, the PPARD protein was co-expressed with CD26, while the blue nuclear staining by DAPI that identified the presence of some CD26cells exhibited little PPARD expression. In addition, we isolated the HSCs (CD34 þ CD38subset) from heathy donors and transduced them with BCR-ABL1 gene. The transduction efficiency was 26.6% which was reflected by GFP; and among the GFP þ infected cells, the percentage of CD34 þ was 80.3% (Supplementary Fig. 1). In addition, the expression of BCR-ABL1 was identified by RT-PCR (Fig. 3B). Surprisingly, in contrast to negative control vectors transfected HSCs, the BCR-ABL1 overexpressed HSCs showed much more expression of PPARD which was verified by RT-PCR (1.441 vs. 2.383, p < 0.05) (Fig. 3C) and western blotting (Fig. 3D). The results further identified the reliability of patientderived proteomic analysis. 4. Discussion In TKI era, the bottleneck of curing CML may be focused on purging TKI-insensitive LSCs. Accumulating evidence has demonstrated that TKIs have great effects on CML cells but not LSCs due to the additional mechanism promoting the LSCs survival without BCR-ABL dependence [12]. Much of literature to date has presented
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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Fig. 2. The differentially expressed proteins in CD34 þ CD38¡CD26 þ cells (A) The Protein Ratio Vocano analysis in CD34 þ CD38CD26 þ cells vs. CD34 þ CD38 þ cells and (B) in CD34 þ CD38CD26 þ cells vs. CD34 þ CD38CD26cells; (C) All regulated GO classification; (D) Heat map analysis of the significantly dysregulated proteins of CD34 þ CD38CD26 þ cells compared to CD34 þ CD38 þ cells and (E) of CD34 þ CD38CD26 þ cells compared to CD34 þ CD38CD26cells.
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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Fig. 3. The verification of PPARD (A) The representative confocal laser scanning microscopy of a bone marrow smear from CML patient; Scale bars 20 mm; in green, the CD26 þ cells; in red, cells expressing PPARD; in blue, the nuclei. (B) 3 healthy donors derived HSCs were transduced with BCR-ABL1; the transduction was identified by RT-PCR; (C) The BCR-ABL1 overexpressed HSCs shown much more expression of PPARD verified by RT-PCR; (D) and western blotting, showing a high concordance to RT-PCR results. NT: Negative control transduced HSCs; BCR-ABL1: BCR-ABL1 overexpressed HSCs. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
various results related to additional mechanism contributing to LSCs survival which can be divided into two aspects: selfcharacteristics and the microenvironment support [23e27]. Ste’phane Prost et al. discovered that STAT5 expression levels were abnormally high in both total CP-CML CD34 þ cells and quiescent LSCs, and activation of PPARg by the glitazones decreased expression of STAT5 and its downstream targets HIF2 and CITED2, which promoted the purging of LSCs [28]. Puneet Agarwa et al. highlighted a critical role of CXCL12-expressing BMM cells in maintaining quiescence of TKI-resistant LSC populations [27]. These finds reveal the part of complexity of LSCs and bone marrow microenvironment and contribute to the LSCs eradication. Besides, emerging researches have focus on the discovery of unique biomarker to distinguish LSCs from HSCs. Harald Herrmann et al. firstly defined CD26 as a robust biomarker to distinguish LSCs from HSCs by comparing CML-derived stem cells with healthy donor-derived cord blood stem cells [14]. Next, Rebecca Warfvinge et al. revealed CML LSCs heterogeneity and changes imposed by TKI therapy utilizing single-cell gene expression analysis, and further confirmed that the subpopulation with primitive, quiescent signature and increased survival to therapy can be high-purity captured as CD45RA-cKIT-CD26þ [13]. We previously monitored the CD26 þ LSCs in CML patients, and revealed that LSCs could be detected in different disease status without the value of reflecting disease burden [15], which reminded us to analyze the biological characteristics of these subpopulation. CD26 is indeed a good biomarker to distinguish CML-LSCs and HSCs, which seems to be a potential therapy target to eradicate CML-LSCs. However, there is still a lot of concerns that CD26 is widely expressed on some heathy tissues such as T cells [29]. Targeting CD26þ CML-LSCs by CD26 antagonist may lead to much offtarget effect. Additionally, the reason why CD26 þ LSCs can persist
in CML patients was not elucidated. Therefore, we utilized CD26 as a biomarker to isolate these CD26 þ LSC cells, explored the distinct characteristic of them, and discovered new biomarkers. Due to the technical difficulties to study exceedingly small primary cell populations, we accumulated the samples from 8 CML patients. Compared with previous researches, our study was designed by comparing LSCs to self-derived normal cells which may reduce the deviation among samples. In the study, many differently expressed proteins have been discovered by the high-resolution LC-MS/MS analysis, some of which may take part in the specific mechanism to support the LSCs survival. Some proteins involved in energy metabolism and carcinogenesis, were extremely upregulated in the CD26 þ LSCs, while some majoring in DNA mismatch repair or related to cell senescence were downregulated. IL1RAP, once reported to be a biomarker of CML-LSCs and predict therapy outcome [22], was also demonstrated to elevate in CML-LSCs in our study. Besides, treatments to target IL1RAP, such as recombinant IL-1 receptor antagonist [30], IL1RAP antibodies [31], and IL1RAP targeting chimeric antigen receptor (CAR) T cells [32], have been proved to be applicable in eliminating quiescent CML-LSCs. From the top-regulated proteins, we selected PPARD for verification and further investigation. It has been reported that SNPs in PPARD are associated with CML predisposition [33], but the putative role in CML development was not clarified. PPARD, one of three members of the PPAR group in the nuclear receptor superfamily, has been confirmed to play an important pathogenetic and predictive role across multiple cancers [17]. Modulation of cellular energy consumption is a major function of PPARD. Studies have demonstrated that PPARD can promote the fatty acid b-oxidation to increase ATP production in harsh microenvironmental conditions, contributing to the survival of many cancer cells, such as chronic lymphocytic leukemia cells [16]. PPARD may account for an
Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092
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important hallmark of drug-resistant cancer cells, namely survival in harsh metabolic conditions. In our study, we found that PPARD was upregulated in LSCs, which may take part in the LSCs persistence in TKI condition. Additionally, we isolated HSCs from health donor and transfected with BCR-ABL1 by lentivirus vector, and found that the PPARD was upregulated in BCR-ABL1 positive HSCs, which demonstrated that BCR-ABL1 promoted the expression of PPARD in LSCs, probably in turn involving in the persistence of them in TKI treated condition. In summary, this study uncovers the global proteome analysis of CD26þ CML-LSCs and discovered the dysregulated protein list contributing to the LSCs maintenance, and opens in turn new therapeutic avenues for eliminating TKI-insensitive LSCs. Declaration of competing interest
[12] [13]
[14]
[15]
[16]
[17]
[18]
The authors declare that they have no conflict of interest. [19]
Acknowledgement [20]
This study was funded by the National Natural Science Foundation of China (NSFC) [81500136 to XJZ, and 81670145, 81873440 to YY; 81873444 to Yi Xiao]. Appendix A. Supplementary data
[21]
[22]
Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbrc.2019.11.092.
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Please cite this article as: S. Zhou et al., Comparison of chronic myeloid leukemia stem cells and hematopoietic stem cells by global proteomic analysis, Biochemical and Biophysical Research Communications, https://doi.org/10.1016/j.bbrc.2019.11.092