Background
Suppressor of cytokine signaling (SOCS) is a protein family of eight members (SOCS1–7 and CIS) that form a classical negative feedback system to regulate cytokine signal transduction [
1]. By regulating the cytokine-driven STAT activation pathway, SOCS3 likely has an important role in development, allergic responses, and tumorigenesis [
2‐
4]. Methylation of the SOCS3 promoter and reduced gene expression of SOCS3 have been documented in numerous tumors such as breast cancer, lung cancer, and liver cancer [
5‐
7]. SOCS3 is highly conserved among vertebrates and has been considered to be a transcriptional regulator in the hematopoietic system. SOCS3
−/− mice die in utero because of fetal liver erythrocytosis, and over-expression of SOCS3 blocks fetal liver erythrocytosis, implying that SOCS3 plays a critical role in the negative regulation of hematopoiesis [
8,
9].
Evidence suggests a potential role of SOCS3 in the pathogenesis of leukemia. For example, Capello et al revealed that inactivation of SOCS3 was frequent in Ph-negative chronic myeloproliferative disorders (CMPD) [
10]. Al-Jamal et al. reported that down-regulation of SOCS3 was involved in the resistance of CML cells to imatinib [
11]. However, the exact function of SOCS3 in hematological malignancies remains unclear. A better understanding of the function and underlying molecular mechanisms of SOCS3 will contribute to the precision medicine in the field of CML.
In a previous study, we showed that SOCS3 was important for lineage commitment of hematopoietic stem cells to erythroid cells. SOCS3 knock-down increased the expression of multiple erythroid-specific genes and inhibited the expression of genes controlling lymphoid differentiation [
12]. In this study, we wanted to investigate the contribution of SOCS3 in pathogenesis of CML and further understand the potential underlying mechanisms of SOCS3. Previous studies suggested dysregulation of microRNA (miRNA) networks had been implicated in hematological malignancies, for example miR-29a/29b dysregulation played an important role in myeloid leukemogenesis [
13]. So, understanding of miRNA biology in carcinogenesis could possibly pave novel routes for anti-cancer therapy [
14,
15]. Here, we found that over-expression of SOCS3 in CML cells induced a transcriptional program enriched for leukemia suppression factors, including some miRNAs. For example, miR-124-3p was obviously up-regulated by SOCS3 over-expression. In turn, alterations of miR-124-3p expression levels influenced the effect of SOCS3 on CML cells. Furthermore, we confirmed that B4GALT1, a multidrug resistance gene, was the target gene of the SOCS3/miR-124-3p axis. These findings suggested the presence of a dysregulated molecular network involving SOCS3, miR-124-3p, and B4GALT1, which may provide novel insights into tumor biology and present a useful target for therapeutic interference of CML under certain circumstances.
Discussion
In this study, we explored the function and involved mechanisms of SOCS3 in the pathophysiology of CML. Firstly, we found that both mRNA and protein expression of SOCS3 were down-regulated in CML cell lines and most of samples from CML patients. Sakai et al. observed a large variation of SOCS3 expression in different patients [
16]; here, we also found the significant difference of SOCS3 expression in different patients which implied SOCS3 may be used as an index for CMLprecision diagnosis in the future.
Previous studies demonstrated that the expression of SOCS3 was associated with the response of CML cells to IFN-alpha [
16,
17], and down-regulation of SOCS3 was a possible reason for imatinib resistance of leukemia cells [
11]. Consistently, in our study, the expression of SOCS3 in CML cells was up-regulated after imatinib treatment. Although SOCS3 exerted no remarkable effect on apoptosis, SOCS3 over-expression could enhance imatinib-induced apoptosis in CML cells. Takeuchi et al. suggested increased expression of SOCS3 in bone marrow cells may result from the action of several cytokines secreted in the bone marrow environment [
17], so we speculated the bone marrow environment alteration caused by imatinib treatment may induce the up-regulation of SOCS3 in CML cells here. However, the in-depth mechanism needed to be clarified.
miRNAs play important roles in tumorigenesis [
18‐
23]. We then explored whether SOCS3 regulated the growth and chemo-sensitivity of CML cells by modulating miRNA. The gene expression bead array results indicated that miR-124-3p, a tumor suppressor [
24‐
26], was significantly affected by SOCS3. Fowler et al demonstrated that over-expression of miR-124 in GBM cells was associated with diminished tumor cell migration and invasion [
27]. Moreover, Shi et al. found that miR-124-3p could inhibit the proliferation of prostate cancer cells [
28]. In our study, we found that miR-124-3p expression in CML cell lines was regulated by SOCS3. A significant positive correlation between miR-124-3p and SOCS3 was observed. And, the inhibitory effect of SOCS3 on CML cell proliferation was attenuated in the absence of miR-124-3p. All these data indicated that miR-124-3p play an important role in SOCS3-mediated growth inhibition.
Recent study demonstrated that B4GALT1 gene family play an important role in the resistance of human leukemia cells to therapeutic drugs. In multidrug resistance leukemia patients, highly expressed B4GALT1 regulated the hedgehog pathway, and were associated with the expression of p-glycoprotein and multidrug resistance-associated protein, resulting in the specific drug-resistant phenotypes of leukemia cell lines [
29,
30]. Here, we first demonstrated that B4GALT1 was a target gene of miR-124-3p as predicted by bioinformatics, verified the conserved region in the B4GALT1 3‘UTR was binding to miR-124-3p. In addition, we found that B4GALT1 protein expression was significantly down-regulated by miR-124-3p over-expression in CML cells. So, we speculated that SOCS3 enhanced the chemo-sensitivity of CML cells by down-regulating B4GALT1, and that miR-124-3 was the link between them. Thus, we analyzed the effect of SOCS3 on the expression of B4GALT1 and proved that SOCS3 modulated the expression of B4GALT1 by miR-124-3p and, in turn, B4GALT1 could rescue SOCS3-induced chemo-sensitivity alterations in K562 cells. Finally, tumorigenicity assays in nude mice confirmed that over-expression of SOCS3 inhibited the proliferation of K562 cells and down-regulated the expression of B4GALT1 in vivo
. However, the in vivo function of SOCS-3 after imatinib treatment needs to be investigated in the further study.
Our results showed SOCS-3 regulated miR-124-3p/B4GALT1 pathway played an important role in the pathogenesis of CML. However, imatinib treatment still induced miR-124-3p increase in the absence of SOCS3 and SOCS3 could inhibit colony formation, regardless of the presence of miR-124-3p inhibitor, which implied other signal pathways may be involved. For example, previous studies demonstrated JAK/STAT pathway and cytokine signal pathways were involved in SOCS3-mediated effects in CML cells [
16,
17].
Resistance to targeted drugs remains a challenge for CML therapy. Accurate biomarkers are of great importance to antitumor therapeutics [
31]. In this study, there was an obvious correlation between SOCS3 expression and the sensitivity of CML cell lines to imatinib. Thus, SOCS3 may be used as a novel biomarker predicting the response to targeted drugs and it was of great value to further elucidate the role and mechanism underlying SOCS3 expression in CML cells. However, we did not explore the role of SOCS3 in primary cells from CML patients who are resistant to imatinib, and we acknowledge this is a limitation of this study.
Conclusions
In summary, our work revealed that an interesting signal pathway initiated by SOCS3 was involved in CML development. Down-regulated SOCS3 in CML cells was associated with low level of miR-124-3p, then could not exert enough repressive effect on B4GALT1, resulting in the proliferation of CML cells and targeted drugs resistance. In conclusion, SOCS3/miR-124-3p/B4GALT1 signaling pathway plays an important role in the pathophysiology of CML. SOCS3 may be used as an index for CML diagnosis, and a novel biomarker predicting the response of CML to targeted drugs, in clinical settings.
Methods
Patient samples
BMNCs were obtained from patients with confirmed diagnose of CML and from healthy donors with informed consent. BMNCs were enriched by Ficoll gradient centrifugation. The study was performed with the approval of the Ethics Committee of Chinese PLA General Hospital, Beijing, China.
Cell culture
K562, KU812, HL-60, and BV173 cells were cultured in RPMI-1640. HEK293 cells were cultured in DMEM. These mediums contained 10 % (v/v) fetal bovine serum (Gibco, Life technologies, USA) and 100 mg/mL penicillin/streptomycin. For imatinib treatment, cells were treated with 1 μmol/L imatinib for 48 h.
Lentiviral plasmid construct and transduction
Lentiviral expression and interference vectors targeting human SOCS3 were constructed as described previously [
12]. Empty expression vector (empty) or non-targeting siRNA (shControl) were used as controls of expression and interference vectors, respectively. Lentiviral particles were produced and cells were transduced. After transduction (48 h), positive cells were sorted by fluorescence-activated cell sorting (FACS), according to the expression of green fluorescent protein (GFP).
Quantitative RT-PCR
Total RNA isolation, reverse transcription, and the quantification of target gene expression were performed as previously described [
12]; β-Actin was used as an internal control. miR-124-3p expression levels were quantified using U6 as the internal control (GenePharm). The fold-change in expression was calculated using the following primer pairs for the amplification of target mRNAs: SOCS3 forward primer 5‘ATCCTGGTGACAT GCTCCTC’3 and reverse primer 5‘CAAATGTTGCTTCCCCCTTA’3; β-Actin forward primer 5‘ GATCCACATCTGCTGGAA GG’3 and reverse primer 5‘AAGTGTGACGTT GACATCCG’3; B4GALT1 forward primer 5‘AACCATGTGACTGAGTGC CC’3 and reverse primer 5‘TCAGTGTGTTGTGCCAAAGC’3; Micro124-3p forward primer 5‘TAAGGCACGCGGTGAATGCC’3 and reverse primer 5‘GATTGAATCGA GCACCAG TTAC’3; U6 forward primer 5‘CGCTTCGGCAG CAC ATATACTA’3 . Unified reverse primer 5‘GATTGAATCGA GCACCAG TTAC’3.
Western blot analysis
Cells were lysed directly in lysis buffer to collect whole cell extracts. Protein samples were separated on polyacrylamide gels, transferred onto nitrocellulose membrane by iblot (Invitrogen), detected using horseradish peroxidase-conjugated secondary antibodies, and exposed to BioMax film (Kodak) following chemiluminescence (Santa Cruz, CA, USA). The following primary antibodies were used: SOCS3, Actin, and B4GALT1 (Santa Cruz, CA, USA).
Cell proliferation assay
Cell proliferation was determined using CCK-8 (Dojindo, Japan) method. K562 cells (3000 cells/well) were plated in 96-well plates. At different time points, CCK-8 reagents were added to each well and further incubated at 37 °C for 2 h. The number of viable cells was assessed by measurement of absorbance at 450 nm using a Multiskan (Thermo Scientific, Asheville, NC, USA).
Clonogenic progenitor cell assay
Cells were seeded in a 6-well plate with methylcellulose medium (MethoCult H4435, STEMCELL Technologies, Canada) according to the manufacturer’s instructions. After 1 week of cultivation, colonies were counted.
Apoptosis assay
The apoptosis assays were performed using the Annexin V-PE kit (BioLegend, San Diego, CA, USA) according to the manufacturer’s protocol. The stained cells were immediately analyzed on a FACScalibur flow cytometer (Becton Dickinson). The data were expressed as the percentage of apoptosis cells.
Whole-genome expression analysis
Total RNA was extracted from K562 cells transduced with over-expression SOCS3 or empty vector (5 × 106 cells) using Trizol reagent (Invitrogen Life Technologies, Paisley, UK). Genome expression analysis was performed by Illumina Human HT-12 v4 BeadChip (Illumina, San Diego, CA, USA) at the Beijing Qian zhao xing ye Biological Technology Co., Ltd. (Beijing, China).
miR-124-3p mimic and inhibitor
The hsa-miR-124-3p mimic or control sequence, and hsa-miR-124-3p inhibitor and hsa-miR-124-3p inhibitor negative control were all purchased from GenePharma (Shanghai, China).
Luciferase assays
The human pre-miR-124 sequence was amplified and cloned into pcDNA3.1 constructs (Invitrogen) to generate the pcDNA3.1-miR-124 expression vector. The full-length 3‘UTR of B4GALT1 was amplified using cDNA from K562 cells and double-digested with XbaI/EcoRI and cloned downstream of the firefly luciferase coding region sites of a modified pGL3-control plasmid named Luci-B4GALT1. We also constructed mutated Luci-B4GALT1 reporter vectors bearing deletions of the UTR target regions and named them Luci-△B4GALT1. The vectors were co-transduced with control or pcDNA3.1-miR-124 expression vectors into K562 cells. Lysates were prepared 48 h after transduction. Luciferase activity was measured using a dual-luciferase reporter assay system (Promega). All experiments were performed in triplicate at least three independent times.
B4GALT1 expression plasmid construction and transduction
The full-length of the human B4GALT1 sequence was amplified and cloned into the pcDNA3.1 vector to generate the B4GALT1 expression vector. K562 cells were transduced with the B4GALT1 expression vector in 24-well plates using Lipofectamine 2000 (Invitrogen) according to the manufacturer’s protocol.
Tumorigenicity assays in nude mice
A total of 5 × 106 K562 cells that were stably transduced with SOCS3 over-expression or empty vectors were injected into male nude mice subcutaneously (n = 8). Mice were sacrificed at 28 days post-inoculation, and the tumors were excised and their weight was measured and photographed. Tumors from different groups were removed and fixed with formaldehyde, embedded in paraffin wax, and sectioned. The sections were cleared through xylene, graded ethanol, water and incubated with anti-B4GALT1 antibodies (Santa Cruz) at 4 °C overnight, stained with DAPI, washed with PBS three times, and observed by fluorescence microscopy.
Statistical analysis
All data were expressed as the mean ± standard deviation (SD). The differences between two groups were assessed by Student’s t test. Pearson’s correlation coefficient was calculated to analyze the correlation. P < 0.05 was considered to be statistically significant.
Abbreviations
3’-UTR, 3’-untranslated region; BMNCs, bone marrow mononuclear cells; CML, chronic myeloid leukemia; CMPD, chronic myeloproliferative disorders; FACS, fluorescence - activated cell sorting; GFP, green fluorescent protein; miR-124-3p, microRNA-124-3p; miRNAs, microRNAs; qPCR, quantitative real-time PCR; siRNA, small interfering RNA; SOCS3, suppressor of cytokine signaling 3; WB, Western blotting
Acknowledgements
Not applicable.
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