SHP2 is involved in the occurrence, development and prognosis of cancer
- Authors:
- Published online on: July 27, 2023 https://doi.org/10.3892/ol.2023.13979
- Article Number: 393
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Copyright: © Li et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Src homology-domain-containing protein tyrosine phosphatase (SHP) is a protein tyrosine phosphatase (PTP) family member. SHP comprises SHP1, encoded by protein tyrosine phosphatase non-receptor type (PTPN) 6, and SHP2, encoded by PTPN11 (1,2). SHP2/PTPN11 is considered a signaling molecule that is involved in the regulation of a number of cellular processes, such as cell growth, differentiation, the mitotic cycle and oncogenic transformation. SHP2 is widely expressed in a variety of human tissues, such as breast and endometrial cancer (3,4).
SHP2 regulates cell proliferation, differentiation, apoptosis and survival, affecting multiple signaling pathways, such as the mitogen-activated protein kinase pathway. The abnormal expression and mutation of SHP2 are related to human developmental disorders, leukemia and solid tumors (such as lung, breast, ovarian and endometrial cancer) (3,4). In different cancer types, activation of SHP2 has been proposed as a disease cause. For example, Kim et al (5) indicated that SHP2 was not expressed in normal gastric mucosal cells, while it was found to be expressed at high levels in 87% of gastric cancer tissues, and was markedly related to the progression of gastric cancer. Patients with gastric cancer and high SHP2 expression demonstrate higher pathological grades, tumor stage (T stage) and lymph node stage. Elevated expression of SHP2 indicates a poor prognosis in patients with gastric cancer. SHP2 is widely upregulated in invasive ductal carcinoma of the breast, and is associated with HER2 expression, androgen receptor nuclear localization, T stage and lymph node metastasis (6,7). Inhibition of SHP2 expression can hinder the development of receptor tyrosine kinase (RTK)-driven malignant growth cells, such as those derived from KRAS-mutated breast carcinoma. In non-small cell lung cancer (NSCLC) with a KRAS mutation, the blockage of SHP2 expression is enough to induce tumor senescence, which triggers the clearance of cancer cells by the immune system (8). A limited number of studies have demonstrated that SHP2 expression is decreased in certain cancer types. For example, Jiang et al (9) observed that SHP2 expression was reduced in 70.6% of patients with liver cancer, and decreased SHP2 expression was associated with a poor prognosis in hepatocellular carcinoma. Therefore, given the close relationship between SHP2/PTPN11 and human diseases, and its wide expression in tumor tissues, as well as the dual function of SHP2/PTPN11 as a tumor suppressor and tumor-promoting gene in tumors, the comprehensive discussion of SHP2/PTPN11 has important clinical significance. The present study assessed the expression levels of SHP2 in different tumors, and its relationship with prognosis, immunity and the tumor microenvironment.
Materials and methods
Data acquisition and pre-processing
SHP2 expression levels of the 33 types of tumor with associated data in The Cancer Genome Atlas (TCGA) database and the corresponding tumor RNA-sequencing data were downloaded from the Genomic Data Commons data portal website (https://portal.gdc.cancer.gov/). Clinical information (SHP2 expression level, follow-up time and tumor type), tumor mutational burden and microsatellite instability of the corresponding patients were also downloaded. The 33 types of tumors included the following: Adrenocortical carcinoma (ACC), bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cervical and endocervical cancer (CESC), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), esophageal carcinoma (ESCA), glioblastoma multiforme (GBM), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), acute myeloid leukemia (LAML), brain lower grade glioma (LGG), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), mesothelioma (MESO), ovarian serous cystadenocarcinoma (OV), pancreatic adenocarcinoma (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate adenocarcinoma (PRAD), rectal adenocarcinoma (READ), sarcoma (SARC), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD), testicular germ cell tumors (TGCT), thyroid carcinoma (THCA), thymoma (THYM), uterine corpus endometrial carcinoma (UCEC), uterine carcinosarcoma (UCS) and uveal melanoma (UVM) (10).
Expression levels, prognostic evaluation and the tumor microenvironment
The R 4.2.2 software (R Core Team; www.r-project.org) was used for statistical analysis. Univariate Cox regression analysis was used to evaluate the association between SHP2 gene expression, overall survival (OS) and disease free survival (DFS); the use of forest plots through the ‘forest plot’ R package (version 3.1.1) aimed to display the P-value, hazard ratio (HR) and 95% confidence interval (CI) of every variable (11). According to the median value of the SHP2/PTPN11 gene expression, patients were divided into SHP2/PTPN11 high and SHP2/PTPN11 low expression groups. The Kaplan-Meier method was used to draw the survival curve of every tumor type, and the log-rank test was used to analyze survival status.
The matrix and immune scores of every patient were calculated using the ‘ESTIMATE’ software package (version 1.0.13) to evaluate the infiltration of immune cells in tumor tissue and tumor purity. For reliable immune score evaluation, the ‘CIBERSORT’ algorithm was used to evaluate tumor immune cell infiltration (12). Spearman's correlation analysis was used to evaluate the correlation between SHP2/PTPN11 gene expression and the target, including matrix and immune scores, immune cell infiltration, tumor mutation load and microsatellite instability (13). Student's unpaired t-test was used to evaluate the SHP2/PTPN11 gene expression levels between tumor and corresponding non-tumor normal tissues. P<0.05 was considered to indicate a statistically significant difference.
Patients and ELISA
A total of 42 breast cancer and 42 normal human serum specimens were collected. A total of 34 ovarian cancer and 36 normal human serum specimens were collected. A total of 29 endometrial cancer and 33 normal human serum specimens were collected. A total of 46 cervical cancer and 40 normal human serum specimens were collected. All samples were collected from the Chongqing Health Center for Women and Children (Chongqing, China) from February 2021 to December 2022. The patients' personal information was not collected. The patients provided written informed consent for the collection of blood samples. All specimens were stored at −80°C and tested by ELISA in January 2023. The present study was approved by the Ethics Association of Chongqing Health Center for Women and Children (approval no. cstc2020-jyk2.0).
The expression levels of SHP2/PTPN11 in serum were detected by double antibody one-step sandwich ELISA. The PTPN11 ELISA kit (cat. no. P20220809; Shanghai Enzyme-linked Biotechnology Co., Ltd.) was used at room temperature. A total of 50 µl standard at different concentrations was used, and 50 µl sample was added into the sample well. A total of 100 µl horseradish peroxidase-labeled antibody was added to the standard and sample wells, and incubated in a water bath at 37°C for 60 min. Following washing, 50 µl substrates A and B was added to the plate wells and incubated at 37°C for 15 min. A total of 50 µl stop solution was added to each well, and the optical density (OD) value was measured at a wavelength of 450 nm within 15 min. The test was repeated three times.
Statistical analysis
SPSS version 25.0 (IBM Corp.) was used to analyze the experimental data. The Shapiro-Wilk test was used to evaluate whether experimental data conformed to a normal distribution. Unpaired Student's t-test was used to evaluate the expression levels of the SHP2/PTPN11 gene between tumor and normal tissues. Spearman's correlation analysis was used to evaluate the correlation between the SHP2/PTPN11 gene expression and the target (matrix score, immune score, immune cell infiltration, tumor mutation load and microsatellite instability) (13). The χ2 test was used to analyze the difference in SHP2 expression level in the peripheral blood of patients with breast, ovarian, endometrial and cervical cancer. P<0.05 was considered to indicate a statistically significant difference.
Results
Expression levels of the PTPN11 gene in tumors
Among the 33 types of tumors that exhibit PTPN11 in TCGA, 30 types of tumors could be compared with their corresponding normal tissues as controls (LAML, MESO and UVM had no controls). For a total of 26 out of the 30 types of tumors, statistically significant differences were noted in the expression levels of the PTPN11 gene compared with those of the normal tissues (P<0.05). Among them, PTPN11 was expressed at higher levels in ACC, BRCA, CHOL, COAD, DLBC, ESCA, GBM, HNSC, KICH, KIRC, KIRP, LGG, LIHC, LUAD, LUSC, OV, PAAD, PRAD, READ, SKCM, STAD, TGCT and THCA, while the expression levels of PTPN11 were decreased in THYM, UCEC and UCS (Fig. 1).
Expression levels of the PTPN11 gene are associated with patient prognosis
According to the median value of the PTPN11 gene expression, patients with 33 types of tumors were divided into PTPN11 high and low expression groups. Survival analysis demonstrated that the OS of patients in the PTPN11 high and low expression groups was significantly different among the BRCA (HR, 1.70; 95% CI, 1.01–2.21; P=0.001), CESC (HR, 1.70; 95% CI, 1.23–1.98; P=0.023), MESO (HR, 1.80; 95% CI, 1.23–2.22; P=0.027), BLCA (HR, 1.40; 95% CI, 1.12–1.68; P=0.031) and LIHC (HR, 1.40; 95% CI, 1.23–1.87; P=0.049) tumor types. Patients in the PTPN11 high expression group exhibited shorter OS times than those in the control group (P<0.05). However, high expression levels of PTPN11 improved the OS time of patients with the KIRC tumor type (HR, 0.60; 95% CI, 0.54–0.89; P=0.001) (Fig. 2A). Considering that OS may be affected by non-tumor-associated deaths, the relationship between PTPN11 gene expression and DFS was evaluated further. High expression of the PTPN11 gene reduced the DFS time of patients with the BLCA (HR, 1.50; 95% CI; 1.22–1.76; P=0.021) and CESC (HR, 1.90; 95% CI, 1.65–2.22; P=0.043) tumor types. This phenomenon was not observed in patients with other tumor types. However, high expression levels of PTPN11 improved the DFS time of patients with KIRC (HR, 0.65; 95% CI, 0.61–0.76; P=0.022) (Fig. 2B).
PTPN11 gene expression correlates with immune checkpoints and immune scores
By using Spearman's correlation analysis, it was found that the expression levels of the PTPN11 gene were significantly correlated with cancer types in the presence of immune cells. In BLCA, BRCA, CESC, CHOL, COAD, HNSC, KIRC, KIRP, LGG, PRAD, READ, SKCM, STAD, THCA, THYM and UCEC, the expression levels of the PTPN11 gene were significantly negatively correlated with regulatory, follicular helper and cluster of differentiation (CD)8+ T cells (P<0.05). In BRCA, CESC, COAD, ESCA, HNSC, KICH, KIRC, LAML, LGG, LUAD, LUSC, OV, PCPG, PRAD, READ, SARC, TGCT, THCA, THYM and UCEC, the expression levels of the PTPN11 gene were significantly and positively correlated with the number of CD4+ T cells (P<0.05). In BLCA, BRCA, HNSC, LIHC, LUAD, PRAD and THCA, the expression levels of the PTPN11 gene were significantly and positively correlated with the number of neutrophils (P<0.05). In BRCA, KIRC, SKCM, STAD, TGCT, THCA, THYM and UCEC, the expression levels of the PTPN11 gene were significantly and positively correlated with the number of macrophages M2 (P<0.05; Fig. 3).
Sialic acid binding Ig like lectin 15, indoleamine 2,3-dioxygenase 1, CD274, hepatitis A virus cellular receptor 2, programmed cell death (PDCD) 1, cytotoxic T-lymphocyte associated protein 4, lymphocyte activating 3 (LAG3) and PDCD 1 ligand 2 are transcripts related to immune checkpoints. The expression levels of these eight immune checkpoint-related genes were obtained and assessed. Spearman's correlation analysis was used to analyze the immune checkpoints genes related to PTPN11. Results were found in the DLBC, PCPG, PAAD, PRAD, LIHC, UVM and READ tumor types, where the expression levels of the PTPN11 gene were significantly and positively correlated with CD274, which had a large number of associations (P<0.05). However, in UCS, THCA and MESO (correlation coefficient >±0.3), the expression levels of the PTPN11 gene were significantly and negatively correlated with LAG3 (P<0.05; Fig. 4; Table I).
Expression levels of the PTPN11 gene are related to microsatellite instability and tumor mutational burden
The expression levels of the PTPN11 gene in LAML, LUAD, SKCM and THYM were significantly and positively correlated with microsatellite instability. However, in UVM and LGG, the expression levels of the PTPN11 gene were significantly and negatively correlated with microsatellite instability. Among them, the correlation coefficient between the expression levels of the PTPN11 gene and microsatellite instability was the highest in UVM (ρ=−0.313), THYM (ρ=0.212) and LAML (ρ=0.203) (Fig. 5A).
The expression levels of the PTPN11 gene were significantly and positively correlated with the tumor mutation burden in ACC, COAD, LUAD, LUSC, MESO, OV, READ, TGCT and UCEC. However, the expression levels of the PTPN11 gene in DLBC and SARC were significantly and negatively correlated with the tumor mutational burden. Among them, the correlation coefficient between the expression levels of the PTPN11 gene and the tumor mutational burden was the highest in DLBC (ρ=−0.561), SARC (ρ=−0.400), ACC (ρ=0.449), MESO (ρ=0.315), LUSC (ρ=0.289) and READ (ρ=0.281) (Fig. 5B).
SHP2 is associated with the risk of breast, ovarian, endometrial and cervical cancer
The peripheral blood samples from patients with 4 different tumor types were collected. ELISA was used to assess the expression levels of SHP2. The standard OD value was 0.143. If the OD value of the sample was higher than that of the standard OD value, it was considered positive for SHP2, otherwise it was considered negative. By using the χ2 test, it was found that SHP2 was expressed at higher levels in breast cancer (71.43%; P<0.001) and ovarian cancer (58.82%; P<0.001) than in the control group; however, it was expressed at lower percentages in endometrial cancer (31.03%; P<0.001) and cervical cancer (41.30%; P=0.001) than in the control group (Table II; Fig. 6). This finding is consistent with the results of the pan-cancer analysis in the present study.
Discussion
SHP2 consists of the N-SH2 and C-SH2 domains, a protein tyrosine phosphatase (PTP) domain and a C-terminal tail with two tyrosine phosphorylation sites (14). The deviations in its biological function can cause various disorders in the regulation of normal body functions (such as normal development of the body, cardiovascular production and immune response), and lead to the formation of cancer, diabetes and autoimmune diseases, among others (15). SHP2 serves a number of roles in the formation and progression of tumors (4). SHP2 can regulate the proliferation and metastasis of tumor cells by participating in numerous signaling pathways such as the PI3K/AKT and RAS/ERK pathways (16–18). Mutations or changes in the expression levels of PTPN11 can lead to the formation of leukemia and various other tumors, such as liver, cervical, ovarian and endometrial cancer (4,17). Therefore, SHP2/PTPN11 may be an ideal target for cancer intervention (4).
In the present study, the expression levels of SHP2/PTPN11 were analyzed in tumors, and the data indicated that SHP2/PTPN11 was expressed at high levels in KIRC. Concomitantly, the prognostic analysis indicated that high expression of SHP2/PTPN11 resulted in increased OS (HR, 0.60; P=0.001) and DFS (HR, 0.65; P=0.022) times of patients with KIRC. Therefore, SHP2/PTPN11 may be a tumor suppressor gene in KIRC, and its elevated expression can improve patient prognosis. Increased SHP2/PTPN11 expression decreased the OS (BLCA: HR, 1.40; P=0.031; CESC: HR, 1.70; P=0.023) and DFS (BLCA: HR, 1.50; P=0.021; CESC: HR, 1.90; P=0.043) times of patients with BLCA and CESC; moreover, the high expression levels of SHP2/PTPN11 decreased the OS times of patients with BRCA, MESO and LIHC, thereby worsening patient prognosis, suggesting that SHP2/PTPN11 may act as an oncogene in BLCA, CESC, BRCA, MESO and LIHC.
In a number of solid tumors, excessive SHP2 activation has been stated to serve an essential pathogenic role. For example, Feng et al (19) indicated that SHP2 was expressed at high levels in 94.1% of patients with NSCLC; its expression was higher in the intratumoral area than in the stromal area. Moreover, high expression of SHP2 is associated with an improved prognosis in patients with NSCLC, and can increase OS and PFS time. Lei et al (20) indicated that high expression of SHP2 could promote the occurrence of breast cancer and reduce lymph node metastasis. Hu et al (21) observed that the positive rate of SHP2 in ovarian cancer tissues reached 81.67%, while the positive rate of SHP2 in normal ovarian tissues was 0.00%. Moreover, SHP2 expression was associated with lymph node metastasis, clinical stage and histological grade. The current study indicated that SHP2 was expressed in various tumor types. The expression levels of SHP2 were increased in the majority of tumors, with the exception of THYM, UCEC and UCS. By using peripheral blood samples of patients with cancer, it was found that SHP2 was not expressed at high levels in all tumors; by contrast, it indicated tumor-promoting or -suppressing functions in different tumors. The expression levels of SHP2 were increased in breast and ovarian cancer, whereas they were expressed at low levels in endometrial and cervical cancer. Therefore, the role of SHP2 in the remaining tumors requires additional investigation.
SHP2 is involved in the regulation of various signaling pathways in organisms. SHP2 binding sites are present in RTKs and backbone adaptors, such as growth factor receptor bound (GRB)2-associated binding protein (GAB), insulin receptor substrate, FAR1-related sequence and other proteins. Therefore, this ‘molecular switch’ ensures that SHP2 is only activated in the appropriate cellular regions (N-SH2 and PTP domain) (22). During the signal transduction process of several growth factors and cytokines, SHP2 acts upstream of RAS, and enables the full activation of the ERK/MAPK pathway (6). The C-terminal tyrosine of SHP2 is phosphorylated in response to the majority of the agonists, and the tyrosine-phosphorylated SHP2 recruits the adaptor protein GRB2 and the guanine nucleotide exchange factor son of sevenless, which contribute to RAS activation (23). Certain studies (14,16,20) have shown that SHP2, which is expressed at high levels in breast cancer, can activate PI3K/AKT signaling to phosphorylate GSK3-β, thereby promoting the proliferation of breast cancer cells. However, SHP2 can also inhibit the PI3K/AKT signaling pathway. In the EGFR signaling pathway, SHP2 can dephosphorylate the PI3K binding site on GAB1 and decrease the GAB1-mediated activation of the PI3K/AKT proteins. In addition, SHP2 can also bind to p85 to form GAB2/SHP2/p85 complexes, thereby inhibiting the PI3K/AKT pathway (24). SHP2 can inhibit the gp130 pathway mediated by IL-6 and promote STAT3 dephosphorylation, thereby negatively regulating the Janus kinase/STAT3 pathway and eventually leading to juvenile bone marrow monocyte leukemia (25,26). In addition, SHP2 is involved in regulating T-cell activity by binding to the phosphotyrosine motif of the immune checkpoint protein PDC1 through its N-SH2 domain (27). Inhibitors that can block the protein-protein interactions between PD-1 and SHP2 are expected to be used as new tumor immunotherapy agents. Therefore, SHP2 has also become a potential drug target in tumor immunotherapy (28).
SHP2/PTPN11 may play an important role in promoting tumor immune escape (29). As important players in shaping the tumor microenvironment, tumor-associated macrophages (TAMs) mediate tumor angiogenesis and immune escape (30). TAMs are a subset of macrophages with M2-like aggregate properties, which play a major role in tumorigenesis, angiogenesis, grid renovation and metastasis (31). For example, the deletion of SHP2 in TAMs can significantly inhibit the growth of melanoma. In response to IFN-γ or cytokine stimulation, the deletion of SHP2 can notably enhance the ability of macrophages to produce chemokine ligand (CXCL) 9, thereby recruiting additional T cells, promoting the production of CXCL9 in the tumor microenvironment, and forming a macrophage/CXCL9-T cell/IFN-γ feedback loop to facilitate the antitumor immune function of T cells (32,33). The aforementioned studies have demonstrated that SHP2/PTPN11 is an expected target for managing TAM function in immunotherapy. By inhibiting SHP2 expression, a direct inhibition of tumor formation is facilitated by inhibiting downstream pathways, such as that of RAS/ERK, PI3K/AKT and JAK/STAT. By contrast, SHP2 inhibitors can also inhibit tumors by activating T cells and promoting macrophage phagocytosis. Therefore, SHP2 is a target for both immune and targeted therapies.
In conclusion, the findings of the present study showed that SHP2/PTPN11 was widely expressed in the majority of tumors assessed, and that its expression was related to tumorigenesis, tumor development and disease prognosis. SHP2/PTPN11 upregulation could improve OS and DFS time in patients with KIRC. However, SHP2/PTPN11 upregulation could reduce OS time in patients with BLCA, CESC, BRCA, MESO and LIHC. Moreover, the elevated expression of SHP2 could also reduce patient DFS time in BLCA and CESC. SHP2 serves an important role in maintaining the immunosuppressive microenvironment via the inhibition of T-cell activation and the promotion of M2 macrophage activation. Inhibition of SHP2 may be a novel therapeutic approach with the following dual applications: It can directly inhibit the growth of cancer cells in specific tumors and it can change the tumor microenvironment to promote antitumor immunity. Based on the function of SHP2 in tumor cells, novel and effective antitumor drugs targeting it can be developed.
Acknowledgements
Not applicable.
Funding
The present study was supported by the Chongqing Science and Technology Commission (grant nos. cstc2020jcyj-msxmX0588 and cstc2019jcyj-msxmX0371).
Authors' contributions
SL conceptualized the study, visualized the data, developed the methodology used, applied the software, performed the statistical analysis, wrote the original draft, and reviewed and edited the manuscript. JQ applied the software and developed the methodology used. XW developed the methodology used, applied the software and performed the statistical analysis. QZ developed the methodology and performed the statistical analysis. CL conceptualized the study, visualized the data, developed the methodology, and wrote, reviewed and edited the manuscript. SL and CL confirm the authenticity of all the raw data. All authors have read and approved the final version of the manuscript.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Ethics approval and consent to participate
The present study was approved by the Ethics Association of Chongqing Health Center for Women and Children (approval no. cstc2020-jyk2.0). The patients provided written informed consent for the collection of blood samples and their use in the present study.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Glossary
Abbreviations
Abbreviations:
|
ACC |
adrenocortical carcinoma |
|
BLCA |
bladder urothelial carcinoma |
|
BRCA |
breast invasive carcinoma |
|
CESC |
cervical and endocervical cancer |
|
CHOL |
cholangiocarcinoma |
|
COAD |
colon adenocarcinoma |
|
DFS |
disease-free survival |
|
DLBC |
lymphoid neoplasm diffuse large B-cell lymphoma |
|
ESCA |
esophageal carcinoma |
|
GBM |
glioblastoma multiforme |
|
HNSC |
head and neck squamous cell carcinoma |
|
KICH |
kidney chromophobe |
|
KIRC |
kidney renal clear cell carcinoma |
|
KIRP |
kidney renal papillary cell carcinoma |
|
LAML |
acute myeloid leukemia |
|
LGG |
brain lower grade glioma |
|
LIHC |
liver hepatocellular carcinoma |
|
LUAD |
lung adenocarcinoma |
|
LUSC |
lung squamous cell carcinoma |
|
MESO |
mesothelioma |
|
NSCLC |
non-small cell lung cancer |
|
OS |
overall survival |
|
OV |
ovarian serous cystadenocarcinoma |
|
PAAD |
pancreatic adenocarcinoma |
|
PCPG |
pheochromocytoma and paraganglioma |
|
PRAD |
prostate adenocarcinoma |
|
READ |
rectal adenocarcinoma |
|
SARC |
sarcoma |
|
SKCM |
skin cutaneous melanoma |
|
STAD |
stomach adenocarcinoma |
|
TAMs |
tumor-associated macrophages |
|
TGCT |
testicular germ cell tumors |
|
THCA |
thyroid carcinoma |
|
THYM |
thymoma |
|
UCEC |
uterine corpus endometrial carcinoma |
|
UCS |
uterine carcinosarcoma |
|
UVM |
uveal melanoma |
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