Single nucleotide polymorphism and promoter methylation analysis of protein tyrosine phosphatase 1B in patients with myeloproliferative neoplasms

Introduction

Background

Philadelphia chromosome-negative classic myeloproliferative neoplasms (cMPNs), which include polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF), are clonal disorders characterized by the hyperplasia of one or more myeloid cell lineages (1). A significant proportion of cMPN patients exhibited cytokine-independent activation of the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway due to recurrent somatic mutations in genes such as JAK2, calreticulin (CALR) and thrombopoietin receptor (MPL) (2). Additionally, other somatic mutations implicated in deoxyribonucleic acid (DNA) methylation, histone modification, messenger ribonucleic acid (mRNA) splicing, transcription, and signal transduction have been identified (3-5). Although the pathogenesis of cMPNs is multifactorial, the activation of the JAK/STAT pathway is of critical importance. This pathway is regulated by various inhibitors, including cytokine signaling (SOCS) (6), protein tyrosine phosphatase (PTP) (7) such as PTP1B, Src homology region 2 domain-containing phosphatase (SHP)-1, SHP-2, and cluster of differentiation 45 (CD45), and protein inhibitors of activated STAT (PIAS) (8). However, the specific roles of these negative feedback regulators in the pathogenesis of cMPNs remain poorly understood.

The tyrosine-protein phosphatase non-receptor type 1 gene (PTP1B, also known as PTPN1) functions as a negative feedback regulator within the PTP family. It encodes the PTPN1 protein (PTP1B), which is widely expressed across various tissues (9-11). The PTP1B gene has been implicated in both oncogenic and tumor suppressor activities (12). Huang et al. found that PTP1B inhibited cancer stemness and chemoresistance of triple negative breast cancer (13). Liu et al. found recurrent somatic mutations and splice variants of PTP1B in human B-cell and Hodgkin’s lymphoma (14). The PTP1B gene can suppress tumorigenesis through direct interactions between its encoded protein PTP1B, and oncoproteins, or by modulating downstream pathways (15).

The PTP1B gene is involved in hematopoiesis and plays a crucial role in regulating erythropoiesis. It downregulates the erythropoietin (EPO)-mediated JAK/STAT pathway (16), thereby influencing the production of red blood cells. Additionally, the PTP1B gene promotes the progression of monocyte-phagocytic cells into fully differentiated macrophages (17) by downregulating the colony-stimulating factor-1 receptor (CSF1R)-mediated signaling pathway. This gene is also associated with various myeloid neoplasms. Up-regulation of PTP1B gene expression prevents the transformation of Rat-1 cells induced by breakpoint cluster region (BCR)-breakpoints in the Abelson (ABL) and promotes the differentiation of BCR-ABL-expressing cells (18). Furthermore, the deficiency of PTP1B gene specifically in myeloid cells is sufficient to promote the development of acute myeloid leukemia (19).

Rationale and knowledge gap

Studies have shown that increased methylation of the PTP1B gene promoter is a risk factor for cancer. Hypermethylation of normally unmethylated CpG islands of tumor suppressor genes is associated with transcriptional silencing and plays a critical role in cancer development and progression (20). Mutations in the PTP1B gene result in a loss of phosphatase activity and increase in the phosphorylation of JAK and STAT family members. This leads to heightened cytokine sensitivity, elevated JAK-STAT signaling, and alterations in gene expression (21).

The PTP1B gene, located on human chromosome 20 within the region q13.1–q13.2, frequently undergoes deletion [del(20q)] in Philadelphia chromosome-negative cMPNs. This deletion affects the PTP1B gene locus, leading to loss of its expression and thereby disrupting its negative feedback regulation of the JAK/STAT signaling pathway (22). Despite its significance, research on the role of the PTP1B gene in cMPNs remains limited.

Objective

Building on this background, we propose that abnormalities in the PTP1B gene contribute to cMPNs by impairing its negative feedback regulation of the JAK/STAT pathway. This dysregulation may lead to increased activation of the JAK/STAT pathway, similar to the effects observed with the JAK2V617F mutation. To investigate this hypothesis, we conducted a study analyzing single nucleotide polymorphisms (SNPs) and methylation levels of PTP1B gene in cMPN patients, utilizing DNA sequencing and Methylation MassArray analysis to confirm the role of the PTP1B gene in the pathogenesis of cMPNs.

Methods

Patients and samples

Bone marrow (BM) biopsies were collected from a cohort comprising 96 patients diagnosed with chronic myeloproliferative neoplasms (cMPNs) and 50 healthy controls. Samples were obtained from the hematology departments of hospitals in Shanghai, including Tongji Hospital of Tongji University and Ruijin Hospital. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by both ethics committees of Tongji Hospital of Tongji University (No. 2021-KYSB-177) and Ruijin Hospital (No. SHDC2020CR5002-2021-105). Informed consent was obtained from all individual participants.

Diagnosis of cMPNs was based on the 2016 World Health Organization (WHO) diagnostic criterial (23). Mononuclear cells were isolated from BM samples, and genomic DNA was extracted using the Axygen Scientific DNA Extraction Kit. Subsequent analyses, including SNP genotyping and methylation Bisulfite amplicon sequencing (BSAS) analysis, were performed on the extracted DNA using the EZ DNA Methylation-Gold Kit (Zymo Research Corp., California, United States) and VAHTS Turbo DNA Library Prep Kit for Illumina^® (ND102-0102) (Vazyme, Nanjing, China), following the manufacturers’ protocol.

Identification the PTP1B gene SNPs

The PTP1B gene sequence was retrieved from GenBank and primers were designed using Primer Premier 5.0 software. The selected primers were subsequently compared on the National Center for Biotechnology Information (NCBI) website for sequence alignment using the Basic Local Alignment Search Tool (BLAST) tool. Primer specificity was confirmed through sequence alignment with the NCBI BLAST tool, ensuring that homology with non-target sequences was less than 70%. The synthesis of primers was carried out by Shenzhen Huada Gene Company, and their sequences are provided in Table 1. Polymerase chain reaction (PCR) amplification was conducted, and the resulting products were analyzed using 2% agarose gel electrophoresis. The purification of the PCR products involved treatment with shrimp alkaline phosphatase and exonuclease. SNP-specific extension primers were utilized to facilitate single base extension at the SNP site.

Sample preparation involved co-crystallization with chip matrices, followed by placing the crystal in the vacuum tube of the mass spectrometer. An intense nanosecond (10^-9 s) laser was used to excite the nucleic acid molecules, desorbing and transforming them into singly charged ions. Detection and analysis were then conducted using a MALDI-TOF mass spectrometer and MassARRAY Typer software.

Methylation BSAS analysis of PTP1B gene

Sequencing procedures targeting the promoter region of the PTP1B gene were detailed in Figure 1A,1B. The target fragment comprises two base sequences, denoted as pair 1 and pair 2, with primer sequences highlighted in yellow and green, respectively. The amplified fragment includes a CG site marked in red font. Relative positions of the CG site with respect to chromosome positions are summarized in Table 2.

Figure 1 Sequence characteristics, primer design and procedure of methylation detection by MassArray. (A,B) The two promoter region of PTP1B gene (the primers of target sequences were marked in yellow and green, respectively). And the CG marked in red were the detection sites. (C) Protocols of methylation detection by MassArray. PTP1B, protein tyrosine phosphatase 1B; DNA, deoxyribonucleic acid; PCR, polymerase chain reaction; CG, cytosine-guanine.

Methylation detection protocols employing BSAS are outlined in Figure 1C, with subsequent result descriptions referencing relative position annotations. The MethylKIT software (http://www.bioconductor.org/packages/release/bioc/html/methylKit.html) was utilized to perform methylation calling on the processed data, enabling the acquisition of site-specific methylation information. Methylation levels at each CpG site were calculated as the ratio of methylated reads to total reads (methylated plus unmethylated), yielding a value between 0 and 1. Additionally, the average methylation value for all sites in each sample was calculated. Visualization of data was facilitated using the Methylation Plotter software.

Statistical analysis

Statistical analysis of methylation at PTP1B gene sites was performed using the Kruskal-Wallis test due to non-normal distribution of the samples. Differences of methylation at PTP1B gene sites were compared and tested for statistical significance with the Kruskal-Wallis test. P values <0.05 were considered to be statistically significant.

Results

Characteristics of cMPN patients

Specimens were obtained from 96 patients diagnosed with cMPNs, comprising 50 male and 46 female patients, with a mean age of 47 years (range: 13 to 85 years). Diagnosis was established according to the WHO diagnostic criteria, with 40 cases of PV, 52 cases of ET, and 4 cases of PMF. The control group included 50 healthy volunteers. The average peripheral blood platelet count was 460×10⁹/L and the average white blood cell count was 16.7×10⁹/L.

SNPs of PTP1B gene detected in cMPN patients

Details of the identified SNPs within the PTP1B gene among cMPN patients and healthy controls are presented in Table 3 and Figure 2. A total of seven coding-region SNPs were identified in our study. Among these, one SNP (g.50579818 T>A) was novel, with a frequency of 1% in cMPN patients and was absent in healthy controls. The remaining six SNPs (rs75493894, rs1885177, rs2082849587, rs1364576352, rs2282147, rs2230604) had been previously reported. Their frequencies in cMPN patients were 1%, 31%, 3%, 5%, 15%, and 12%, respectively, compared to frequencies of 8%, 60%, 0%, 0%, 44%, and 36%, respectively, in healthy controls. Notably, some SNPs (rs2082849587, rs1364576352, and g.50579818 T>A) showed higher frequencies in cMPN patients than in healthy controls, whereas others (rs75493894, rs1885177, rs2282147, rs2230604) exhibited lower frequencies. Importantly, all identified SNPs were synonymous.

Figure 2 Different SNPs detected in cMPN patients. (A) rs75493894; (B) rs1885177; (C) rs2082849587; (D) rs1364576352; (E) rs2282147; (F) rs2230604; (G) newly discovered SNP. SNP, single nucleotide polymorphism; cMPN, classic myeloproliferative neoplasm.

Methylation level of each CpG site in the promoter region of PTP1B gene

To assess PTP1B promoter methylation, 33 samples (including 25 samples from healthy controls and 8 from cMPN patients) were successfully amplified, and BSAS methylation analysis was conducted. For PTP1B pair 1, average methylation levels of target fragments in each sample are depicted in Figure 3A, with blue representing normal controls and purple representing cMPN patient samples. Methylation profiles of all sites within pair 1 for normal controls and cMPN patients are illustrated in Figure 3B. A dendrogram displaying methylation levels across all sites of pair1 for normal control and cMPN samples is presented in Figure 3C. Box plots detailing methylation levels at all sites of pair1 for both groups are shown in Figure 3D. Schematic representation of methylation information across all sites of pair 1 is provided in Figure 3E and summarized in Table 4. Our analysis revealed statistically significant differences in methylation levels across multiple sites in PTP1B pair1 between normal control subjects and cMPN patients. Figure 3E and Table 4 provide a schematic representation and detailed data of methylation levels for all sites in pair1 across all samples. Specifically, cMPN patients exhibited significantly higher methylation levels in several sites of PTP1B pair 1 compared to normal controls.

Figure 3 Methylation level of each CpG site in the promoter region of PTP1B pair 1. (A) For PTP1B pair 1, average methylation levels of target fragments in each sample are depicted, with blue representing normal controls and purple representing cMPN patient samples; (B) methylation profiles of all sites within pair 1 for normal controls and cMPN patients are illustrated; (C) methylation levels across all sites of pair 1 for normal control and cMPN samples is presented in the dendrogram; (D) detailing methylation levels at all sites of pair 1 for both groups are shown in the box plots; (E) schematic representation of methylation information across all sites of pair 1 is provided. *, P<0.05. CpG, cytosine-phosphate-guanine; NA, not applicable; cMPN, classic myeloproliferative neoplasm.

For PTP1B pair2, average methylation levels of target fragments are shown in Figure 4A, distinguishing between normal controls (blue) and cMPN patients (purple). Methylation profiles across all sites of pair2 for both groups are shown in Figure 4B. A dendrogram illustrating methylation levels at all sites of pair2 is depicted in Figure 4C, followed by box plots in Figure 4D. Methylation information for all sites of pair2 in normal controls and cMPN samples is presented schematically in Figure 4E and detailed in Table 5. Our analysis revealed statistically significant differences in methylation levels at multiple sites in PTP1B pair2 between normal controls and cMPNs patients. Specifically, cMPN patients exhibited significantly higher methylation levels in several sites of PTP1B pair2 compared to normal controls.

Figure 4 Methylation level of each CpG site in the promoter region of PTP1B pair 2. (A) For PTP1B pair 2, average methylation levels of target fragments in each sample are depicted, with blue representing normal controls and purple representing cMPN patient samples; (B) methylation profiles of all sites within pair 2 for normal controls and cMPN patients are illustrated; (C) methylation levels across all sites of pair 2 for normal control and cMPN samples is presented in the dendrogram; (D) detailing methylation levels at all sites of pair 2 for both groups are shown in the box plots; (E) schematic representation of methylation information across all sites of pair 2 is provided. *, P<0.05. CpG, cytosine-phosphate-guanine; NA, not applicable; cMPN, classic myeloproliferative neoplasm.

Discussion

Key findings

Numerous studies have established the pivotal role of JAK-STAT pathway activation in the pathogenesis of cMPNs (24-26). While much attention has been directed towards positive regulators, the significance of negative feedback regulators within this pathway has been underexplored. A variety of negative feedback regulators are essential for maintaining balance in this regulatory network. In the present study, we conducted SNP and methylation analyses of the PTP1B gene in cMPN patients. We identified seven coding-region SNPs and aberrant hypermethylation of the PTP1B gene in cMPN patients for the first time.

Strengths and limitations

The discovery of a new SNP, differences in the frequency of seven SNPs between cMPN patients and normal controls and hypermethylation of PTP1B promoters collectively suggest that the PTP1B gene is disrupted in cMPNs and may contribute to the pathogenesis of these conditions. However, there are limitations in this study, including a limited sample size and lack of in vitro validation. Further research is warranted to fully elucidate these findings and their implications.

Comparison with similar researches and explanations of findings

The PTP1B gene, located on human chromosome 20q13.1-q13.2, is a critical negative feedback regulator of the JAK-STAT pathway. Chromosomal abnormalities, including deletions affecting chromosome 20q, are frequently associated with cMPNs. Abnormalities in the PTP1B gene have been implicated in various hematopoietic malignancies (20,27). Building upon this knowledge, we propose a novel hypothesis: abnormalities in the the PTP1B gene contribute to dysregulated negative feedback, thereby disrupting the balance and leading to enhanced JAK-STAT pathway activation in cMPNs. To test our hypothesis, we conducted SNP and methylation analyses of the PTP1B gene in cMPN patients. Our findings aim to elucidate the role of PTP1B gene alterations in the pathophysiology of cMPNs, potentially highlighting new avenues for therapeutic intervention.

In our study, we identified seven coding-region SNPs in the PTP1B gene (Figure 2). Among these, rs1885177 (exon 5), rs2282147 (exon 8) and rs2230604 (exon 8) were present in 31%, 15% and 12% of the 96 subjects, respectively. The occurrence of these SNPs in cMPN patients was lower compared to healthy volunteers. Additionally, the SNPs rs75493894 (exon 4) and rs1364576352 (exon 7) were detected in only one and five patients, respectively, with even lower occurrence in healthy volunteers. Furthermore, we identified a new SNP, g.50579818 T>A (exon 8), present in one case among cMPN patients, and absent in healthy volunteers. Despite their synonymous nature, these SNPs may still influence gene function (28). For instance, Möhlendick et al. demonstrated that the synonymous SNP rs7121 is associated with either tumor progression or prolonged survival in cancer patients (29), while Ovsyannikova et al. reported that the synonymous SNP rs2230604 in the PTP1B gene correlates with significantly lower T-cell receptor excision circle (TREC) level (30). Tan et al. provided an excellent example that a synonymous SNP can alter epidermal growth factor receptor (EGFR) dependency (31). Therefore, while synonymous coding SNPs do not directly alter the amino acid sequence of proteins, they can indirectly impact gene expression, regulation, and protein function through mechanisms including impact on mRNA splicing, alteration of mRNA stability, affect the ribosome’s translation speed, and impact microRNA binding.

Moreover, studies have indicated that abnormal PTP1B gene expression results in reduced phosphatase activity and increased phosphorylation of proteins in the JAK/STAT pathway (32,33). In Hodgkin’s lymphoma cell line KM-H2, silencing of the PTP1B gene via RNA interference leads to hyperphosphorylation and overexpression of downstream oncogenes (34). Taken together with our findings on the new SNPs and their frequency difference between cMPN patients and normal controls, our data support the hypothesis that PTP1B gene abnormalities in cMPN patients may disrupt negative feedback regulation.

For the methylation MassARRAY analysis, a total of 30 CpG sites were detected in the promoter region of PTP1B gene. Significant differences were observed in the methylation levels of several sites in PTP1B between the normal control group and the cMPN patient group. Abnormal methylation patterns have been widely associated with cancer development and progression. Our study represents the first report of hypermethylation in the PTP1B gene and its potential pathogenic implications in cMPNs. Hypermethylation of the PTP1B promoter region may lead to reduced expression of the PTP1B protein, thereby impairing its ability to dephosphorylate proteins in the JAK/STAT pathway. The reduction of PTP1B expression due to higher methylation of promoter region of PTP1B might attenuate the inhibition of the JAK/STAT pathway, thereby promote the cMPNs pathogenesis.

Conclusions

In summary, we have identified seven coding-region SNPs and aberrant hypermethylation of the PTP1B gene in cMPN patients for the first time. Notably, we discovered a new SNP and observed differences in the frequency of these seven SNPs between cMPN patients and normal controls. Additionally, we found hypermethylation of PTP1B promoters in cMPN patients compared to normal controls. These findings collectively suggest that the PTP1B gene is disrupted in cMPNs and may contribute to the pathogenesis of cMPNs. Further research is warranted to fully elucidate these findings.

Acknowledgments

None.

Footnote

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1338/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1338/prf

Funding: This work was supported by the National Natural Science Foundation of China (grant number 81372497), and Shanghai Pujiang Talents Plan (grant number 18PJD044). The role the funders had in our study is financial support.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1338/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by both ethics committees of Tongji Hospital of Tongji University (No. 2021-KYSB-177) and Ruijin Hospital (No. SHDC2020CR5002-2021-105). Informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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