|
| |
 |
|
| ORIGINAL ARTICLE |
|
| Year : 2022 | Volume
: 65
| Issue : 2 | Page : 93-102 |
|
Prostaglandin F2 receptor inhibitor overexpression predicts advanced who grades and adverse prognosis in human glioma tissue
Ho-Wen Chen1, Meng-Chi Lin2, Pei-Ru Wu3, Yu-Chan Chang4, Sung-Shun Weng5, Wen-Chiuan Tsai6
1 Ph.D. Program of College of Management, National Taipei University of Technology, Taipei, Taiwan
2 Department of Neurological Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei; Department of Surgery, Zuoying Branch of Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan
3 Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
4 Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
5 Department of Information and Finance Management, National Taipei University of Technology, Taipei, Taiwan
6 Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| Date of Submission | 04-Nov-2021 |
| Date of Decision | 06-Feb-2022 |
| Date of Acceptance | 11-Feb-2022 |
| Date of Web Publication | 28-Apr-2022 |
Correspondence Address:
Prof. Sung-Shun Weng
Department of Information and Finance Management, National Taipei University of Technology, Taipei 10608
Taiwan
Prof. Wen-Chiuan Tsai
Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490
Taiwan
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/cjp.cjp_97_21
Prostaglandin F2 receptor inhibitor (PTGFRN) promotes neoplastic cell migration and metastasis in some human cancers. However, the role of PTGFRN in human gliomas is still undetermined. First of all, PTGFRN messenger ribonucleic acid (mRNA) overexpression correlated with some poor prognostic factors of glioma after analyzing The Cancer Genome Atlas and Chinese Glioma Genome Atlas database. In order to detect the effect of PTGFRN expression on tumor characteristics of gliomas, U87MG, LN229, and glioblastoma 8401 glioma cell lines were cultured and prepared for western blot analysis and real-time polymerase chain reaction, respectively. The results revealed the overexpression of PTGFRN in all glioma cell lines as compared to normal brain cells. In addition, PTGFRN immunohistochemical (IHC) staining was performed on two sets of glioma tissue microarrays. Consistent with the results of in vitro studies, cytoplasmic PTGFRN immunostaining scores positively correlated with tumor grades and poor prognosis of gliomas. Therefore, PTGFRN IHC staining may be useful for the evaluation of tumor grades and overall survival time to facilitate the tailoring of appropriate treatment strategy. PTGFRN may serve as a potential pharmacologic target for the suppression of gliomagenesis.
Keywords: Glioma, immunostaining scores, prognosis, prostaglandin F2 receptor inhibitor
How to cite this article:
Chen HW, Lin MC, Wu PR, Chang YC, Weng SS, Tsai WC. Prostaglandin F2 receptor inhibitor overexpression predicts advanced who grades and adverse prognosis in human glioma tissue. Chin J Physiol 2022;65:93-102 |
How to cite this URL:
Chen HW, Lin MC, Wu PR, Chang YC, Weng SS, Tsai WC. Prostaglandin F2 receptor inhibitor overexpression predicts advanced who grades and adverse prognosis in human glioma tissue. Chin J Physiol [serial online] 2022 [cited 2023 Dec 9];65:93-102. Available from: https://www.cjphysiology.org/text.asp?2022/65/2/93/344171 |
Ho-Wen Chen, Meng-Chi Lin, Pei-Ru Wu: These authors contributed equally to the research
| Introduction | |  |
More than half of the central nervous system neoplasms are gliomas, which are classified as astrocytic, oligodendroglial, oligoastrocytic, ependymal, and choroid plexus, and other neuroepithelial types according to the World Health Organization (WHO) classification.[1] In the USA, the incidence of glioblastoma (GBM) was more than 3 in 100,000 populations and belonged to the highest mortality rate between gliomas during 2013–2017.[2] Mutated isocitrate dehydrogenase-1 (IDH1) and 1p/19q co-deletion have been well-known as the potential factors associated with chemosensitivity and prognosis in gliomas.[3],[4] Up to now, grossly tumor resection with radiotherapy and associated chemotherapeutic drugs, such as temozolomide (TMZ) and bevacizumab, is the main therapeutic regimen.[5],[6] The tumor inhibitory effects of the above therapeutic regimens depend on promoting tumor apoptosis and suppressing microvascularization.[7],[8] However, O6-methylguanine-DNA methyltransferase promoter methylation status, tumor stemness character, and tumor-associated macrophages are important factors to interfere the success of treatment.[9],[10] Recently, carmustine wafer (Gliadel) is newly developed to treat recurrent GBM, but the cerebral edema maybe an adverse effect.[11] Similarly, chemoresistance and severe neurogenic deficit limit certain drugs' efficacy.
The induction of cellular apoptosis was shown to be stimulated by caspase activators, which are regulated by the loss of mitochondrial transmembrane electric potential.[12] The change in the electron transport depends on the existence of prostanoids that are composed of prostaglandins (PGs) and thromboxane.[13] The activity of PGs depends on the connection with G protein-coupled receptors.[14] PGF2 receptor inhibitor (PTGFRN), also known as CD9-partner 1 (CD9P-1), is a transmembrane protein that belongs to the tetraspanin protein family.[15],[16] The expression of CD9P-1 is downregulated by CD9 and CD81,[17] while CD9P-1 overexpression is correlated with neoplastic angiogenesis, cell migration, and metastatic ability in some human cancers.[18],[19] Aguila et al.[20] had proved PTGFRN could inhibit GBM tumor growth and predict poor prognosis by activating phosphatidylinositol-3-kinase (PI3K)/Akt signaling pathway. However, up to now, no in vivo study could support evidence to confirm the relationship between PTGFRN and human glioma tissue.
In this study, we successfully demonstrated the significantly higher expression levels of PTGFRN protein and messenger ribonucleic acid (mRNA) in glioma cell lines as compared to the normal brain cell lysates. Furthermore, immunohistochemical (IHC) staining showed the positive correlation between PTGFRN expression and WHO tumor grades of human glioma tissues. In addition, poor prognosis seemed to be associated with extensive PTGFRN IHC expression. Therefore, our results first proved PTGFRN could be viewed as a poor prognostic factor in human glioma tissue not just GBM. Besides, we explored the possible risk factors with PTGFRN IHC overexpression by univariant and multivariant analysis. Finally, we also confirmed PTGFRN overexpression, patient's age, IDH1, and ATRX loss expression are poor prognostic factors of the included gliomas.
| Materials and Methods | | |
In silico study
The PTGFRN mRNA information was obtained from the profile of GDS1962/224950_s_at in the National Center for Biotechnology Information Gene Expression Omnibus database. Additionally, of all The Cancer Genome Atlas More Details (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases, we explored all clinical parameters and genomic data, including PTGFRN, epidermal growth factor receptor (EGFR), phosphatase and tensin homolog (PTEN), chromosome 1, 7, 10, 19 from the following website: https://xenabrowser.net/heatmap/. Furthermore, the associated relations between PTGFRN and IDH1 mutation and 1p/19q co-deletion were analyzed from the CGGA database.
Cell culture, cell lysates preparation, and western blot analysis
The human glioma cell lines, U87MG, LN229, and GBM8401 were maintained in Dulbecco's modified Eagle's medium (DMEM; Invitrogen) supplemented with 10% fetal bovine serum (FBS), 100 units/mL penicillin, and 100 mg/mL streptomycin in 25 cm2 flasks. All cells were incubated at 37°C in a humidified atmosphere with 5% CO2. Cells were lysed with radioimmunoprecipitation assay buffer (100 mM Tris-HCl, 150 mM sodium chloride (NaCl), 0.1% sodium dodecyl sulfate (SDS), and 1% Triton-X 100) at 4°C for 10 min and the cell lysates were harvested by centrifugation at 15,000 rpm for 10 min to obtain supernatants. Lysates from normal brain tissues were purchased from Origene Technologies. A total of 30 μg of cell lysate from each group was separated by 10% SDS polyacrylamide gel electrophoresis and protein bands were transferred onto polyvinyl difluoride membranes (Millipore, MA, USA). The membranes were blocked with 5% skim milk in TBS buffer containing 0.05% Tween 20 (TBST buffer) (12.5 mM Tris/HCl, pH 7.6, 137 mM NaCl, and 0.1% Tween-20) for 1 h at room temperature. After blocking with 5% nonfat milk in TBST, blots were incubated overnight at 4°C with a polyclonal rabbit anti-human PTGFRN antibody (Santa Cruz Biotechnology, Santa Cruz, CA, USA). Blots were incubated with horseradish peroxidase-labeled secondary antibody for 30 min at room temperature, rewashed, and developed using a Western Lightning Plus chemiluminescence reagent kit (PerkinElmer, Wellesley, MA, USA) as per the manufacturer's instructions. A monoclonal mouse anti-β-actin antibody (Sigma-Aldrich, St. Louis, MO, USA) served as the internal control.
Total ribonucleic acid extraction and quantitative real-time polymerase chain reaction
LN229, U87MG, and GBM8401 cells were maintained in DMEM supplemented with 10% FBS, penicillin, and streptomycin. Total RNA was extracted using the EasyPure Total RNA reagent (Bioman, Taipei, Taiwan) according to the manufacturer's protocol. For cDNA synthesis, 1 μg RNA was reverse transcribed into cDNA using Oligo dT primer with MMLV Reverse Transcriptase (Epicentre Biotechnologies, Madison, WI, USA). The normal brain cDNA was purchased from Origene Technologies (Rockville, MD, USA). Polymerase chain reaction (PCR) reactions were performed on a LightCyclerTM instrument using the Fast-StartTM DNA Master SYBR Green I real-time PCR kit (Roche Molecular Biochemicals). Thermocycling was performed in a final volume of 20 μL containing 3 mM magnesium chloride, 0.5 μM of each primer, and 10 μL of the appropriate cDNA. PCR was performed at an initial denaturation step of 10 min at 95°C, followed by 40 cycles of a touch-down PCR protocol (10 s at 95°C, 10 s annealing at 68°–58°C, and 16 s extension at 72°C). Specific primers for glyceraldehyde-3-phosphate (GAPDH) and PTGFRN were purchased from Search-LC (Heidelberg, Germany). To confirm the specificity of amplification, thermal cycling conditions were 95°C for 5 min, followed by 40 cycles of 95°C for 30 s and 60°C for 5 min. The relative quantity of PTGFRN mRNA level was determined using the standard 2−ΔΔCt method.
- Mouse GAPDH (forward): 5'-GCACCGTCAAGGCT GAGAAC-3'
- Mouse GAPDH (reverse): 5'-ATGGTGGTGAAGACGCC AGT-3'
- Mouse PTGFRN (forward): 5'-CACAGCTCGCCTCATG TTG-3'
- Mouse PTGFRN (reverse): 5'-GTCTGGTTCTAGCCAGG TCAC-3'.
Tissue microarray slide preparation and immunohistochemistry
This study was approved by Institutional Review Board of Tri-Service General Hospital (approval number: 1-108-05-154). Two tissue microarray slides (No. GL2083a and GL2083b) were purchased from GenDiscovery Biotechnology Inc. The primary antibody was a polyclonal rabbit anti-human PTGFRN antibody (1:50, Santa Cruz Biotechnology, Santa Cruz, CA, USA), which was detected using an avidin-biotin-peroxidase complex detection kit (DakoCytomation, Glostrup, Denmark). Sections were dewaxed in xylene and dehydrated in alcohol; the sections were pressure-cooked in 10 mM citrate buffer (pH 6.0) for 30 min for antigen retrieval and incubated with 3% hydrogen peroxide and nonimmune goat serum to block the endogenous peroxidase activity and nonspecific binding, respectively. Slides were sequentially treated with the primary antibody for 60 min, biotinylated secondary antibody for 10 min, peroxidase-conjugated streptavidin for 10 min, and 3-amino-9-ethylcarbazole to visualize the immunoreaction at room temperature. Sections were counterstained with hematoxylin and covered with a coverslip. Control sections were stained following the same procedure, but the primary antibody was replaced either with a buffer (negative control) or normal rabbit immunoglobulin G (Santa Cruz Biotechnology, Inc., Santa Cruz, CA, USA) at the same dilution (nonspecific binding control). PTGFRN expression detected in samples from an endometrial adenocarcinoma was used as a positive control. Membrane and cytoplasmic staining was evaluated in all tumor cells. All experiments were repeated thrice and the slides were examined and scored by at least one qualified pathologist.
Assessment of immunohistochemical scores in gliomas
To score PTGFRN expression in each sample, we assessed both the number of tumor cells that expressed PTGFRN and the intensity of staining. Any samples with more than 5% tumor cells displaying cytoplasmic and membrane staining were considered positive. The intensity of PTGFRN staining in tumor cells was scored on a scale of 0–3, with 0 being the absence of staining; 1, weak staining; 2, moderate staining, and 3, strong staining. Cytoplasmic and nuclear staining was classified as weak, moderate, or strong using microscopy at a magnification of 40×, 20×, 10×, and 4×. The percentage of positive cells (from 5 to 100) was multiplied by the corresponding average immunostaining intensity (from 0 to 3) to obtain PTGFRN expression score, which ranged from 0 to 300. In addition, we evaluated the percentage of cytoplasmic and membranous protein expression in nonneoplastic brain tissue and various grades of gliomas by IHC staining method.
Statistics
To detect the correlation between PTGFRN immunoscores and WHO grades of gliomas, statistical analysis was performed using the Pearson Product Moment method. The correlation between WHO grades and PTGFRN immunoscores was established at P < 0.05. In addition, survival times were calculated from the date of surgery to the date of death. These cases were divided into two groups to compare the survival time with PTGFRN immunostaining scores. Statistical analysis of survival time was performed with the Kaplan–Meier survival test.
| Results | | |
Prostaglandin F2 receptor inhibitor mRNA expression associated with WHO grades of gliomas from gene expression omnibus database
From the GDS1962 profile, WHO Grade III and IV gliomas revealed higher PTGFRN mRNA expressions than nonneoplastic brain tissue [Figure 1]a (P = 0.043 and P < 0.001). In addition, compared to Grade III tumors, Grade IV gliomas also had significantly higher PTGFRN expression (P = 0.013). Therefore, PTGFRN mRNA expression showed positively correlated with advanced WHO grades in gliomas. | Figure 1: (a) Prostaglandin F2 receptor inhibitor mRNA expression in non-tumor brain tissue, Grade II, Grade III and Grade IV gliomas from National Center for Biotechnology Information gene expression omnibus database. (b) Heatmap of glioma tumor grades with copy number of epidermal growth factor receptor, phosphatase and tensin homolog, chromosome 1, 7, 10, 19. (c) Higher prostaglandin F2 receptor inhibitor mRNA expression correlated with the status of epidermal growth factor receptor amplification, phosphatase and tensin homolog loss, isocitrate dehydrogenase-1-wild type, 1p/19q non-codeletion, gain on chromosome 7 and loss on chromosome 10 function.
Click here to view |
Advanced tumor grades associated with prostaglandin F2 receptor inhibitor and EGFR overexpression, PTEN suppression, chromosome 1p/19q noncodeletion, and isocitrate dehydrogenase-1 wild-type gliomas in the cancer genome atlas and Chinese glioma genome atlas database
Compared to low-grade gliomas, we observed GBMs had more cases of high PTGFRN expression from the TCGA database [Figure 1]b. Similarly, EGFR overexpression, PTEN suppression, IDH1 wild-type, chromosome 1p/19q non-codeletion, loss of chromosome 10 and gain of chromosome 7 function [Figure 1]c. Besides, our data from CCGA database revealed PTGFRN expression significantly had a shorter overall survival time of gliomas [Figure 2]a. Furthermore, gliomas with IDH wild-type or non-codeleted chromosome 1p/19q had higher PTGFRN expression than IDH mutant or chromosome 1p/19q codeletion tumors respectively [Figure 2]b. | Figure 2: (a) From Chinese Glioma Genome Atlas database, prostaglandin F2 receptor inhibitor mRNA expression correlated with poor prognosis in human gliomas. (b) Compared to isocitrate dehydrogenase-mutant gliomas, isocitrate dehydrogenase-wild type glioblastoma and low grade gliomas had higher prostaglandin F2 receptor inhibitor mRNA expression.
Click here to view |
Higher prostaglandin F2 receptor inhibitor mRNA and protein expression may indicate gliomas
In this study, western blot analysis and quantitative reverse transcription-PCR were performed to detect PTGFRN protein and mRNA expression, respectively, in glioma cells. Normal brain cell lysates only showed a low level of PTGFRN protein and mRNA expression. In comparison with the normal brain lysates, those obtained from glioma cell lines showed a significantly higher expression level of PTGFRN [Figure 3]a. LN229, GBM8401, and U87MG also showed higher PTGFRN mRNA expression level as compared to normal brain tissue [Figure 3]b. Thus, PTGFRN overexpression was common in most glioma cells but not in normal brain tissues. | Figure 3: (a) Expression of prostaglandin F2 receptor inhibitor protein in U87MG, LN229 and glioblastoma 8401 human glioma cell lines and normal brain tissue lysates. β-actin served as a loading control. (b) Quantitative real-time quantitative reverse transcription was performed to examine prostaglandin F2 receptor inhibitor mRNA expression in U87MG, LN229 and glioblastoma 8401 human glioma cell lines and normal brain tissue. The relative expression was normalized with that reported in normal brain tissue. Bars, means ± SEM; **P < 0.01, ***P < 0.001. Data are representative of three independent experiments.
Click here to view |
Prostaglandin F2 receptor inhibitor overexpression tended to high-grade gliomas in human glioma tissue
To detect the relationship between PTGFRN expression and tumor grades in human glioma tissues, we performed PTGFRN IHC staining for two slides of tissue microarrays. Of all cases on tissue microarrays, 5 normal brain tissues and 84 glioma samples of various grades were included in this study under the criteria of intact tissue and consistent staining. The astrocytic tumors comprised 1 pilocytic astrocytoma, 11 diffuse astrocytomas, 9 anaplastic astrocytomas, and 53 GBMs. In addition, 5 oligodendrogliomas, 7 anaplastic oligodendrogliomas, 2 ependymomas, and 1 anaplastic ependymoma were tested by PTGFRN IHC staining. Only a small portion of normal brain tissue showed weak positive staining for PTGFRN. On the other hand, most glioma cells showed significantly higher PTGFRN immunostaining scores than normal brain tissues. Of all included glioma cases, the average immunostaining scores of PTGFRN were as follows: 5 for WHO Grade I, 48.93 for WHO Grade II, 50.71 for Grade III, and 101.63 for Grade IV tumors [Table 1]. Therefore, our results showed the positive correlation between higher immunostaining scores and advanced tumor grades in gliomas (P = 0.001). Stronger intensities and more extensively stained area of PTGFRN were similarly associated with higher grade astrocytic tumors [Figure 4]. Although both oligodendrogliomas and ependymomas revealed higher PTGFRN IHC expression as compared to the nonneoplastic brain tissue, their immunostaining scores showed no correlation with WHO grades. It is critical to discriminate between high-grade (WHO Grade III and IV) and low-grade (WHO Grade I and II) gliomas, owing to the differences in the therapeutic strategies employed for their treatment. However, the limited surgical specimens with disorientation are difficult to decide tumor grades precisely. In the current study, PTGFRN immunostaining scores were higher in high-grade gliomas than in low-grade gliomas and non-neoplastic brain tissues [Figure 5]a (P = 0.001 and P = 0.003). Therefore, PTGFRN IHC expression may serve as an important evidence for the proper diagnosis and optimal treatment of gliomas. In order to detect the associated risk factors of PTGFRN in gliomas, we performed univariate and multivariate analysis and the results showed female, H3K27M, EGFRvIII, mutated p53, neurofibromatosis type 1 (NF1) are related to PTGFRN overexpression in gliomas [Table 2]. | Figure 4: Hematoxylin and eosin staining of nonneoplastic brain tissue (a), pilocytic astrocytoma (b), diffuse astrocytoma (c), anaplastic astrocytoma (d), glioblastoma (e). Immunohistochemical analysis of prostaglandin F2 receptor inhibitor expression in non-neoplastic brain tissue (f), pilocytic astrocytoma (g), diffuse astrocytoma (h), anaplastic astrocytoma (i), glioblastoma (j) (original magnification, ×400).
Click here to view |
 | Figure 5: (a) The comparison of prostaglandin F2 receptor inhibitor immunostaining scores between non-neoplastic brain tissue, low-grade glioma, and high-grade glioma.(b) Relationship between overall survival rate and prostaglandin F2 receptor inhibitor immunostaining scores in gliomas. Survival rates were analyzed using the Kaplan–Meier survival test.
Click here to view |
 | Table 1: The correlation of prostaglandin F2 receptor inhibitor immunostain score and World Health Organization grades of gliomas
Click here to view |
 | Table 2: Univariate and multivariate analysis of risk factors associated with a positive prostaglandin F2 receptor inhibitor expression
Click here to view |
Prostaglandin F2 receptor inhibitor implied poor prognosis in human gliomas
To evaluate the association between PTGFRN IHC expression and prognosis of patients with glioma, we divided all glioma cases into two groups based on PTGFRN immunostaining scores. A total of 60 glioma cases were included in the evaluation of prognosis, owing to the availability of their overall survival time. For relatively even number of cases in each group, the cut-off value of PTGFRN immunostaining score was set as 60. We found that the group with high PTGFRN expression (immunostaining scores >60) had longer overall survival than that with low PTGFRN expression (immunostaining scores ≤60) [Figure 5]b (P = 0.022). Thus, PTGFRN expression may be a prognostic factor of gliomas. In addition, since GBM is a multifactorial neoplasms, we performed multivariate analysis to evaluate the possible factors to influence glioma prognosis. Our results revealed glioma patient's prognosis were associated with age, IDH1 R132H, and ATRX mutation, as well as PTGFRN overexpression [Table 3].
| Discussion | | |
The cell surface acts as a physiological barrier and prevents the cell from environmental injury. The interactions between cells or between the cell and matrix rely on the stimulation received from several types of transmembrane proteins, including ion channels, G-protein, enzyme-linked receptors, and cell adhesion factors.[21] The effects of cell surface oncoproteins on tumor migration and metastasis have been well studied.[22] The activation of signaling cascade by these oncoproteins plays an important role in tumor overgrowth and distant spreading.[23] PTGFRN is a transmembrane protein involved in the tetraspanin web.[15],[24] The function of tetraspanin web proteins in the induction or suppression of cancer development relies on tetraspanin-enriched microdomains.[25],[26] Although the detailed mechanism is still unclear, PTGFRN expression may promote tumor metastasis in human lung cancers.[27] Chambrion et al.[17] showed that other tetraspanins such as CD9 and CD81 may downregulate PTGFRN expression and inhibit tumor migration. In the current study, we demonstrated PTGFRN overexpression in all glioma cell lines and revealed the correlation between PTGFRN IHC staining and tumor grades as well as survival rates of human glioma tissues. In the previous study, EGFR amplification and PTEN loss were related to Akt/JNK signaling pathway activation in GBM.[28] Besides, 1p/19q co-deletion or IDH1 mutation had a better prognosis in gliomas.[29] In addition, the combination of gain of chromosome 7 and loss of chromosome 10 seemed to be associated with IDH-wild type GBM.[30] Therefore, PTGFRN overexpression might be a poor prognostic factor of GBM from our in silico data. Furthermore, our results revealed that PTGFRN IHC expression might discriminate high-grade from low-grade gliomas and predict tumor aggressiveness. Although PTGFRN expression correlated with tumor grades in gliomas, we failed to observe any statistical significance with IDH1 mutation. On the other hand, gliosis is a nonspecific reactive change in glial cell proliferation and results in histology similar to that observed in low-grade gliomas.[31] It is difficult to distinguish between glioma and gliosis based on histology alone, especially in small biopsies. The size of gliomas in our tissue microarray slides seemed too small to evaluate if PTGFRN IHC expression could differentiate between glioma and nonneoplastic components. We observed that nonneoplastic brain tissues were negative for PTGFRN expression or showed only focal expression of PTGFRN. On the contrary, most glioma tissues presented strong and diffuse PTGFRN expression. Therefore, the combination of histology analysis and PTGFRN IHC staining may help clinicians and pathologists accurately discriminate between low-grade gliomas and gliosis.
Of all risk factors related to PTGFRN in gliomas, H3K27M mutation is classified as a new entity of gliomas in 2016, often presents as a diffuse midline glial cell neoplasm with young age predominance and poor prognosis.[1] A previous study proved H3K27M mutated gliomas had aggressive clinical behavior and were refractory to TMZ treatment.[32] Besides, EGFRvIII mutation-induced tumor proliferation and angiogenesis in GBMs. A recent clinical trial revealed the possible mechanism of anti-EGFRvIII vaccine failure since EGFRvIII amplicons can hide during therapy.[33] In our study, since PTGFRN overexpression might be associated with H3K27M and EGFRvIII mutation, the inference of the enhancement of PTGFRN might be a possible chemo-resistance factor, but still needed more evidence to confirm. In addition, since p53 is a cell cycle regulator, mutated p53 overexpression could induce cell proliferation. Similarly, PTGFRN had been proved to play a critical role of increase GBM proliferative ability by activating G1 phase.[20] The association of PTGFRN and mutated p53 expression needs further study to explore. Finally, NF1 and PTGFRN induced glioma development through PI3K-Akt-mTOR pathway activation might raise the possibility to detect the connection between each other.[20],[34] Otherwise, of all prognostic factors related to glioma, IDH1 R132H had the highest hazard ratio from the data of multivariate analysis of overall survival time. Most of WHO grade II and III cases revealed IDH1 mutation and R132H comprises more than 90% mutation of IDH1.[35] Cui et al.[36] presented R132H mutation in IDH1 inhibited tumor proliferation and invasion by down-regulating Wnt/β-catenin signaling pathway. The cascade of Wnt/β-catenin signaling is also related to several common pathways of glioma development, including TNF/NFκB, PI3K/Akt/mTOR signaling, and HIF-1 mediated mitochondrial reactive oxygen species.[37] Therefore, IDH1 R132H mutation might be considered as the most critical factor to improve glioma prognosis.
| Conclusion | | |
We successfully proved the association between PTGFRN overexpression and glioma progression. Furthermore, PTGFRN IHC staining could predict tumor grades and overall survival time. The pharmacologic events that inhibit PTGFRN expression may effectively suppress the GBM overgrowth and improve patient prognosis in the future.
Financial support and sponsorship
This study was supported by grants from the Tri-Service General Hospital, TSGH-E-110229, TSGH-D-109091, and National Defense Medical Center, MND-MAB-110-003, and Ministry of Science and Technology, MOST 110-2320-B-016-008-MY3, Taiwan, R. O. C.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Louis DN, Ohgaki H, Weistler OD, Cavenee WK. World Health Organization Classification of Tumours of the Central Nervous System. Lyon: IARC Press; 2016. p. 16-122.  |
| 2. | Ostrom QT, Patil N, Cioffi G, Waite K, Kruchko C, Barnholtz-Sloan JS. CBTRUS Statistical report: Primary brain and other central nervous system tumors diagnosed in the United States in 2013-2017. Neuro Oncol 2020;22:1-96. |
| 3. | Wakimoto H, Tanaka S, Curry WT, Loebel F, Zhao D, Tateishi K, et al. Targetable signaling pathway mutations are associated with malignant phenotype in IDH-mutant gliomas. Clin Cancer Res 2014;20:2898-909. |
| 4. | Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, et al. The 2016 World Health Organization classification of tumors of the central nervous system: A summary. Acta Neuropathol 2016;131:803-20. |
| 5. | Giladi M, Munster M, Schneiderman RS, Voloshin T, Porat Y, Blat R, et al. Tumor treating fields (TTFields) delay DNA damage repair following radiation treatment of glioma cells. Radiat Oncol 2017;12:206. |
| 6. | Gil-Gil MJ, Mesia C, Rey M, Bruna J. Bevacizumab for the treatment of glioblastoma. Clin Med Insights Oncol 2013;7:123-35. |
| 7. | Carter TC, Medina-Flores R, Lawler BE. Glioblastoma treatment with temozolomide and bevacizumab and overall survival in a rural tertiary healthcare practice. Biomed Res Int 2018;2018:6204676. |
| 8. | Seystahl K, Hentschel B, Loew S, Gramatzki D, Felsberg J, Herrlinger U, et al. Bevacizumab versus alkylating chemotherapy in recurrent glioblastoma. J Cancer Res Clin Oncol 2020;146:659-70. |
| 9. | Le Rhun E, Preusser M, Roth P, Reardon DA, van den Bent M, Wen P, et al. Molecular targeted therapy of glioblastoma. Cancer Treat Rev 2019;80:101896. |
| 10. | Fabian D, Guillermo Prieto Eibl MD, Alnahhas I, Sebastian N, Giglio P, Puduvalli V, et al. Treatment of glioblastoma (GBM) with the addition of tumor-treating fields (TTF): A review. Cancers (Basel) 2019;11:174. |
| 11. | Weber EL, Goebel EA. Cerebral edema associated with gliadel wafers: Two case studies. Neuro Oncol 2005;7:84-9. |
| 12. | Green DR, Reed JC. Mitochondria and apoptosis. Science 1998;281:1309-12. |
| 13. | Fang KM, Shu WH, Chang HC, Wang JJ, Mak OT. Study of prostaglandin receptors in mitochondria on apoptosis of human lung carcinoma cell line A549. Biochem Soc Trans 2004;32:1078-80. |
| 14. | Tsuboi K, Sugimoto Y, Ichikawa A. Prostanoid receptor subtypes. Prostaglandins Other Lipid Mediat 2002;68-69:535-56. |
| 15. | Charrin S, Manié S, Billard M, Ashman L, Gerlier D, Boucheix C, et al. Multiple levels of interactions within the tetraspanin web. Biochem Biophys Res Commun 2003;304:107-12. |
| 16. | Charrin S, Le Naour F, Oualid M, Billard M, Faure G, Hanash SM, et al. The major CD9 and CD81 molecular partner. Identification and characterization of the complexes. J Biol Chem 2001;276:14329-37. |
| 17. | Chambrion C, Le Naour F. The tetraspanins CD9 and CD81 regulate CD9P1-induced effects on cell migration. PLoS One 2010;5:e11219. |
| 18. | Guilmain W, Colin S, Legrand E, Vannier JP, Steverlynck C, Bongaerts M, et al. CD9P-1 expression correlates with the metastatic status of lung cancer, and a truncated form of CD9P-1, GS-168AT2, inhibits in vivo tumour growth. Br J Cancer 2011;104:496-504. |
| 19. | Colin S, Guilmain W, Creoff E, Schneider C, Steverlynck C, Bongaerts M, et al. A truncated form of CD9-partner 1 (CD9P-1), GS-168AT2, potently inhibits in vivo tumour-induced angiogenesis and tumour growth. Br J Cancer 2011;105:1002-11. |
| 20. | Aguila B, Morris AB, Spina R, Bar E, Schraner J, Vinkler R, et al. The Ig superfamily protein PTGFRN coordinates survival signaling in glioblastoma multiforme. Cancer Lett 2019;462:33-42. |
| 21. | Kabbani N. Proteomics of membrane receptors and signaling. Proteomics 2008;8:4146-55. |
| 22. | Kawaguchi T. Cancer metastasis: Characterization and identification of the behavior of metastatic tumor cells and the cell adhesion molecules, including carbohydrates. Curr Drug Targets Cardiovasc Haematol Disord 2005;5:39-64. |
| 23. | Dowling P, Walsh N, Clynes M. Membrane and membrane-associated proteins involved in the aggressive phenotype displayed by highly invasive cancer cells. Proteomics 2008;8:4054-65. |
| 24. | Yáñez-Mó M, Barreiro O, Gordon-Alonso M, Sala-Valdés M, Sánchez-Madrid F. Tetraspanin-enriched microdomains: A functional unit in cell plasma membranes. Trends Cell Biol 2009;19:434-46. |
| 25. | Stipp CS, Kolesnikova TV, Hemler ME. EWI-2 is a major CD9 and CD81 partner and member of a novel Ig protein subfamily. J Biol Chem 2001;276:40545-54. |
| 26. | Hemler ME. Tetraspanin functions and associated microdomains. Nat Rev Mol Cell Biol 2005;6:801-11. |
| 27. | Saito Y, Tachibana I, Takeda Y, Yamane H, He P, Suzuki M, et al. Absence of CD9 enhances adhesion-dependent morphologic differentiation, survival, and matrix metalloproteinase-2 production in small cell lung cancer cells. Cancer Res 2006;66:9557-65. |
| 28. | Rong Y, Belozerov VE, Tucker-Burden C, Chen G, Durden DL, Olson JJ, et al. Epidermal growth factor receptor and PTEN modulate tissue factor expression in glioblastoma through JunD/activator protein-1 transcriptional activity. Cancer Res 2009;69:2540-9. |
| 29. | Boots-Sprenger SH, Sijben A, Rijntjes J, Tops BB, Idema AJ, Rivera AL, et al. Significance of complete 1p/19q co-deletion, IDH1 mutation and MGMT promoter methylation in gliomas: Use with caution. Mod Pathol 2013;26:922-9. |
| 30. | Stichel D, Ebrahimi A, Reuss D, Schrimpf D, Ono T, Shirahata M, et al. Distribution of EGFR amplification, combined chromosome 7 gain and chromosome 10 loss, and TERT promoter mutation in brain tumors and their potential for the reclassification of IDHwt astrocytoma to glioblastoma. Acta Neuropathol 2018;136:793-803. |
| 31. | Brat DJ, Prayson RA, Ryken TC, Olson JJ. Diagnosis of malignant glioma: Role of neuropathology. J Neurooncol 2008;89:287-311. |
| 32. | Wierzbicki K, Ravi K, Franson A, Bruzek A, Cantor E, Harris M, et al. Targeting and therapeutic monitoring of H3K27M-mutant glioma. Curr Oncol Rep 2020;22:19. |
| 33. | Nathanson DA, Gini B, Mottahedeh J, Visnyei K, Koga T, Gomez G, et al. Targeted therapy resistance mediated by dynamic regulation of extrachromosomal mutant EGFR DNA. Science 2014;343:72-6. |
| 34. | Lobbous M, Bernstock JD, Coffee E, Friedman GK, Metrock LK, Chagoya G, et al. An update on neurofibromatosis type 1-associated gliomas. Cancers (Basel) 2020;12:114. |
| 35. | Parsons DW, Jones S, Zhang X, Lin JC, Leary RJ, Angenendt P, et al. Anintegrated genomic analysis of human glioblastoma multiforme. Science 2008;321:1807-12. |
| 36. | Cui D, Ren J, Shi J, Feng L, Wang K, Zeng T, et al. R132H mutation in IDH1 gene reduces proliferation, cell survival and invasion of human glioma by downregulating Wnt/β-catenin signaling. Int J Biochem Cell Biol 2016;73:72-81. |
| 37. | Mo Y, Wang Y, Zhang L, Yang L, Zhou M, Li X, et al. The role of Wnt signaling pathway in tumor metabolic reprogramming. J Cancer 2019;10:3789-97. |
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2], [Table 3]
|
Search Pubmed for