MTMR14 is a potential independent prognostic factor in glioma patients and induces glioma cell apoptosis through the Akt/mTOR pathway

doi:10.21203/rs.3.rs-1611941/v1

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MTMR14 is a potential independent prognostic factor in glioma patients and induces glioma cell apoptosis through the Akt/mTOR pathway

https://doi.org/10.21203/rs.3.rs-1611941/v1

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Purpose: Novel phosphoinositide phosphatase MTMR14 is responsible for regulating inflammatory metabolism, stable aging, and autophagy. This study investigated the clinicopathological significance of MTMR14 expression in glioma.

Methods: mRNA expression profiles and clinical information of 703 glioma patients were downloaded from The Cancer Genome Atlas database. Wilcoxon signed-rank test and logistic regression were used to evaluate the relationship between clinical factors and MTMR14 expression. Cox regression and the Kaplan–Meier method were used to determine the clinical factors associated with overall survival of patients with glioma. Using the STRING database and the TIMER2.0 database, proteins and tumor immune infiltrating cells interacting with MTMR14 were identified. MTMR14 of U87 and U251 cells was knocked out by transfection. Interference efficiency was determined by a real-time fluorescence quantitative nucleic acid amplification test; the CCK-8 experimental wound healing test was performed, and a flow cytometry apoptosis assay was used to observe the effect of MTMR14 knockout on glioma cells.

Results:MTMR14 expression levels were highly correlated with grade, age, and survival time of glioma patients. The expression level of MTMR14 was correlated with overall survival.The proliferation and migration of U87 and U251 cells were weakened and apoptosis was promoted after knocking MTMR14.

Conclusions: MTMR14 was a potential independent prognostic factor for glioma patients, participating in the regulation of various signaling pathways and influencing tumor immune microenvironment. In cell experiments, deletion of MTMR14 resulted in decreased proliferation and migration ability of glioma cells, and activation of the Akt/ mTOR pathway led to glioma cell apoptosis.

MTMR14

glioma

glioma cell apoptosis

Akt/ mTOR pathway

Glioma is the most common malignant primary brain tumor, accounting for 81% of all malignant brain tumors^[1]. Among them, glioblastoma is the most malignant and relapses easily, leading to significant mortality and morbidity^[2]. Glioma is the most common brain tumor in children and adolescents^[3]. Glioblastoma multiforme is the most common malignant primary brain tumor, with an incidence of 3.19 cases per 100,000 person years and remarkably poor prognosis showing a 5-year survival rate of 4–5%, and only a 26–33% survival rate at 2 years in clinical trials^[4]. The standard treatment for glioma is surgical resection of the tumor followed by radiotherapy and chemotherapy with temozolomide^{[5, 6]}; however, the outcome is unsatisfactory, and the recurrence rate is high. Studies have found that the Akt-mediated molecular pathway plays an important role in the development of glioma cells^[7].

Myotubularin related protein 14 (MTMR14) is a member of the myotubularin-related protein family^[8]. As a novel phosphoinositide phosphatase, MTMR14 mutation was first identified in human central nuclear myopathy^[9]. Recent studies have shown that MTMR14 plays an important role in the regulation of muscle performance, inflammation, metabolic homeostasis, aging, and autophagy^[10–13]. MTMR14 deficiency leads to the disruption of calcium homeostasis, tissue dysfunction, late-onset inflammatory responses, and metabolic dysfunction induced by a high-fat diet in mice^{[14, 15]}. Knockout of MTMR14 can cause severe developmental abnormalities in zebrafish and Drosophila^{[8, 16, 17]}. Inhibition of MTMR14 can promote apoptosis and migration of hepatocellular carcinoma cells and affect the prognosis of stroke patients through PTEN^[18–20]. MTMR14 alleviates myocardial hypertrophy, which is closely related to the regulation of Akt activation^[14]. Recent studies have also shown that MTMR14 is a biological marker of autophagy-related prognosis, diagnosis, and treatment of liver cancer and cervical cancer^{[20, 21]}.

2 − 1 Data processing

We downloaded clinical information of patients with glioma mRNA expression patterns from The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov/repository), including five cases of normal samples and 698 cases of tumor samples^[22].

2–2 Statistical analysis

The Wilcoxon signed-rank test and logistic regression were used to evaluate the relationship between clinical factors and MTMR14 expression. Cox regression and Kaplan–Meier methods were used to determine the clinical factors associated with overall survival in patients with glioma. Multivariate Cox regression analysis was used to investigate the role of MTMR14 expression in survival and other clinical characteristics (age and stage). High and low expression of MTMR14 were determined according to the median value, based on which all patients were divided into low-and high-expression groups. All statistical analyses were performed using R software (version 4.1.1).

2–3 Functional enrichment analysis

Gene Set Enrichment Analysis is a calculation used to determine whether a predefined set of genes exhibits significant differences between two biological states^{[23, 24]}. To investigate the potential mechanism by which MTMR14 expression affects LGG progression, we used R software (V.4.1.1) to screen for biological pathways with significant differences between the MTMR14-high and MTMR14-low groups. For each analysis, the genome was sequenced 5,000 times. Genomes with a false discovery rate < 0.05 and adjusted P value < 0.05, were considered significantly enriched, and significantly enriched gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified.

2–4 Construction of protein-protein interaction (PPI) network and selection of hub genes

MTMR14 was imported into the STRING database (version 11.5B, https://string-db.org) to identify physically and functionally interacting genes and proteins^[25]. The PPI network was constructed with a comprehensive score > 0.4 and further visualized using Cytoscape version 3.9.1. The CytoHubba plugin selected (http://www.cytoscape.org/) the neutral (MCC) algorithm through the largest group PPI network degree of interaction in the top five hub genes^{[26, 27]}.

2–5 Immune cell infiltration

The expressions of MTMR14 and myeloid dendritic cells (DCs), CD + T cells, macrophages, and neutrophils were analyzed with the TIMER2.0 (http://timer.cistrome.org/) database^[28]. The threshold for MTMR14 was significantly associated with immune cell infiltration (P < 0.001).

2–6 Reagents and Antibodies

Culture medium (DMEM), fetal bovine serum (FBS), Cell Counting Kit (CCK8) kit, and a cell cycle and apoptosis detection kit were purchased from Servicebio (Wuhan, China). Akt, P-Akt, Bax, P-mTOR, caspase-3, caspase-9,Bcl-2, and β-actin antibodies were purchased from Servicebio (Wuhan, China) .

2–7 Cell culture

Glioma cell lines (U87 and U251) were purchased from the Chinese Academy of Medical Sciences (Beijing, China) and cultured in DMEM containing 10% FBS in an incubator at 5% CO2 and 37°C.

2–8 Transfection

To verify and screen for better interference fragments, cells were divided into a group with interference fragment 1 (S1), a group with interference fragment 2 (S2), and a group with no load (NC). The interference fragment and riboFECTTMCP were mixed at a ratio of 1:2 and inoculated at a concentration of 50 nm on a six-well plate with a growth density of approximately 50%. The interference efficiency was analyzed using real-time polymerase chain reaction (PCR) after 24 h of interference.

2–9 Real-time fluorescence quantitative nucleic acid amplification detection experiment

Total RNA was isolated using TRIzol (Servicebio) and then reverse-transcribed into complementary DNA using the Green qPCR Master Mix Kit (Servicebio). The primer sequences are listed in Supplementary Table S1. A two-step quantitative RT-PCR (Servicebio) was used for quantitative PCR. To verify the efficiency of the interference fragment, an interference fragment with a better interference effect was selected for subsequent experiments.

2–10 Experimental grouping

The cells were divided into a control group without any treatment, an S group with interfering fragment, and an NC group without interfering fragment vector.

2–11 Cell viability assay

Cells (2 × 10³) were cultured evenly on 96-well plates for 2, 24, and 48 h, after which 10 µL CCK8 reagent was added and cultured at 37°C for 30 min. The absorbance of the solution was measured at 490 nm using a microplate reader.

2–12 Wound healing assay

U87 and U251 cells were cultured in 6-well plates. When they reached approximately 85% confluence, they were scraped with a new 200 µL pipette tip and washed twice with cold phosphate buffer solution (PBS). Photographs were taken at 0, 24, and 48 h for the S, NC, and CON groups, respectively. The ImageJ software was used to collect images and quantify the gap distance.

2–13 Flow cytometry apoptosis assay

ServiceBio cell cycle and apoptosis assay kits were used. Glioma cells were inoculated in 6-well plates, and the S, NC, and CON groups were treated for 48 h. Cells were collected after trypsin digestion, washed twice with PBS, centrifuged for 5 min (1000 × g), and the supernatant was collected. Centrifugation was conducted at 5–10 × 10⁴ cells for 5 min (1000 × g) and suspended in 480 µL of combined buffer. Add RNase A (10 µL) and Propidium Iodide (PI, 10 µL) were added and incubated at 37°C in the dark for 30–60 min. Fluorescence was detected and analyzed using flow cytometry at an excitation wavelength of 488 nm.

2–14 Immunofluorescence assay

The cells were cultured in a 12-well plate, transfected 24 h later, and fixed in a 12-well plate, after which properly diluted fluorescent-labeled antibody solution was added to completely cover the specimen, and they were incubated overnight at 4°C. The following day, excess water was absorbed with filter paper, and the specimens were immediately observed under a fluorescence microscope (Leica China).

2–15 Western blotting analysis

U87 and U251 cells were cultured and treated in 6-well plates. They were then cut in an ice bath in radioimmunoprecipitation assay buffer for 30 min and centrifuged at 4°C and 12,000 × g for 15 min. The extracted supernatant was stored at -80°C for analysis. Protein concentration was determined using the BCA method (Beyotime). Equal quantities of proteins were loaded onto a 10% sodium dodecyl sulfate-polyacrylamide gel for electrophoresis and then transferred by electrophoresis to a polyvinylidene fluoride membrane (Millipore, Boston, MA, USA). For blocking, 5% bovine serum albumin was used at room temperature for 2 h, and the primary antibody was incubated overnight at 4°C. Tris buffer brine and Tween-20 washing solution were mixed three times (5 min/time), dual fluorescence antibody at 1:20,000 dilution was added, and the broth was incubated at room temperature for 1 h. SPECTRA MAX SoftMax Pro analysis software was used to detect the optical density (OD) signal intensity of each band on the film. β-actin was used as a loading control and for standardization.

2–16 Statistical analysis

All data are expressed as mean standard deviation (SD). The experiments were repeated at least three times, and two groups were compared using an independent t-test. Univariate ANOVA was used among multiple groups, and GraphPad Prism8 software was used for comparative analysis. P < 0.05 was considered statistically significant.

3 − 1 We analyzed the mRNA expression profiles of 703 glioma patients in TCGA database, and the results showed that MTMR14 expression levels were different between the normal and tumor samples(Fig. 1a). MTMR14 expression levels were highly correlated with grade, age, and survival time of glioma patients but had no correlation with gender, as shown in Figure.1 (Fig. 1b-d). The expression of MTMR14 in glioma and normal tissues were compared, and the expression of MTMR14 in glioma increased (P = 0.012). MTMR14 expression was significantly correlated with tissue score (P = 4.839E 06) and grade distribution (P = 1.41E 06), but there was no correlation with sex (P = 0.878).

3 − 2 The expression level of MTMR14 was closely related to the overall survival rate, and the overall survival time of the group with low MTMR14 expression was significantly longer than that of the group with high MTMR14 expression(Fig. 1e,f). In TCGA database, MTMR14 was closely correlated with overall survival (P = 2.124 E-11. MTMR14 was also strongly associated with overall survival in the Chinese Glioma Genome Atlas(CGGA) database (P < 0.0001)^[29].

3–3 Univariate Cox regression analysis showed that age, grade, and MTMR14 expression levels were significantly correlated with overall survival (P < 0.05); however, sex was not associated with overall survival (P = 0.802). Multivariate Cox regression analysis showed the same pattern; age, grade, and MTMR14 expression levels were correlated with overall survival (P < 0.05) while sex was not (P = 0.957). In both univariate and multivariate Cox regression analysis, the expression level of MTMR14 was correlated with overall survival (P = 0.007 and P = 0.07, respectively), suggesting that MTMR14 expression is a potential independent prognostic factor for glioma patients(table.1).

Table 1

Univariate and multivariate analysis of the relationship between MTMR14 expression and overall survival among gastric cancer patients.
Parameter		univariate analysis			multivariate analysis
	HR	95%CL	pvalue	HR	95%CL	pvalue
age	1.065	1.049–1.082	1.21E-15	1.061	1.045–1.0785	1.75E-13
gender	1.050	0.719–1.532	0.802043	1.010	0.691–1.479	0.957
grade	3.087	2.040–4.673	9.9E-08	2.616	1.716–3.988	7.82E-06
MTMR14	1.684	1.152–2.463	0.007197	1.428	0.970–2.103	0.071

3–4 Five KEGG pathways were closely related to MTMR14 overexpression: spliceosome, DNA replication, primary immune deficiency, cell cycle, and RNA degradation. Five KEGG pathways were also closely associated with MTMR14 underexpression: the calcium signaling pathway, neuroactive ligand receptor interactions, phosphatidylinositol signaling system, gap junctions, and glutamate metabolism (Fig. 2a). Five GO pathways were closely related to MTMR14 overexpression: negative regulation of mitotic cell cycle, regulation of cysteine-type endopeptidase activity involved in apoptotic signaling pathways, granulocyte differentiation, DNA decomposition process, and transcription-coupled nucleotide excision repair. Five GO pathways were closely related to MTMR14 underexpression: regulation of the glutamate receptor signaling pathway, astrocyte projection, postsynaptic membrane, regulation of neurotransmitter receptor activity, and regulation of cation channel activity (Fig. 2b). The GO and KEGG items are summarized in Table 2.

Table.2 Gene enrichment analysis based on high and low MTMR14 expression phenotype.

NAME	NES	NOM p-val	FDR q-val
KEGG_SPLICEOSOME	2.523	0	0
KEGG_DNA_REPLICATION	2.281	0	0
KEGG_PRIMARY_IMMUNODEFICIENCY	2.167	0	0
KEGG_CELL_CYCLE	2.082	0	0
KEGG_RNA_DEGRADATION	2.043	0	0
GO_NEGATIVE_REGULATION_OF_MITOTIC_CELL_CYCLE	0.610	2.160	0
GO_REGULATION_OF_CYSTEINE_TYPE_ENDOPEPTIDASE_ACTIVITY_INVOLVED_IN_APOPTOTIC_SIGNALING_PATHWAY	0.770	2.140	0
GO_GRANULOCYTE_DIFFERENTIATION	0.690	2.130	0
GO_DNA_CATABOLIC_PROCESS	0.670	2.120	0
GO_TRANSCRIPTION_COUPLED_NUCLEOTIDE_EXCISION_REPAIR	0.710	2.110	0
KEGG_CALCIUM_SIGNALING_PATHWAY	-2.695	0	0
KEGG_NEUROACTIVE_LIGAND_RECEPTOR_INTERACTION	-2.525	0	0
KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM	-2.000	0	9.34E-04
KEGG_GAP_JUNCTION	-1.927	0	0.003
KEGG_ALANINE_ASPARTATE_AND_GLUTAMATE_METABOLISM	-1.796	0	0.008
GO_REGULATION_OF_GLUTAMATE_RECEPTOR_SIGNALING_PATHWAY	-0.790	-2.220	0
GO_ASTROCYTE_PROJECTION	-0.860	-2.190	0
GO_POSTSYNAPTIC_MEMBRANE	-0.680	-2.190	0
GO_REGULATION_OF_NEUROTRANSMITTER_RECEPTOR_ACTIVITY	-0.760	-2.170	0
GO_REGULATION_OF_CATION_CHANNEL_ACTIVITY	-0.630	-2.160	0
NES: normalized enrichment score; P.adjust: adjust P value; FDR: false discovery rate

Gene sets with adjust p-value < 0.05 and FDR q-value < 0.05 are considered as significant

3–5 The PPI network of MTMR14 was established using Cytoscape (Fig. 3a), and the top five hub genes determined by the CytoHubba plug-in were sorted according to the MCC score. The most closely connected modules were identified (Fig. 3b, d). TIMER2.0 showed that MTMR14 expression was significantly different from that of B cells, CD + T cells, macrophages, neutrophils, and myeloid DCs (Fig. 3e).

3–6 Real-time PCR analysis showed that the expression of MTMR14 in U87 cells was approximately 27% after MTMR14 S1 knockdown. After S2 interference, the MTMR14 expression was approximately 55% (Fig. 4a). In the U251 cell line, the expression of MTMR14 after MTMR14 S1 knockdown was approximately 42%, while that after MTMR14 S2 interference was approximately 54% (Fig. 4b). The MTMR14 S1 interference fragment was selected for transfection in the subsequent experiments.

3–7 Knockout of MTMR14 significantly inhibited the growth and migration of glioma cells (U87 and U251).A CCK-8 assay was performed, and digestive cells of the S, NC, and CON groups were treated accordingly. After 24 h, 2000 cell species were placed in a 96-well plate, and the absorbance value after adding CCK-8 was measured at 2, 24, and 48 h. The absorbance value (OD value) of S group was significantly lower than those of the NC and CON groups (P < 0.05). MTMR14 deletion significantly inhibited the proliferation of U87 and U251 cells(Fig. 4c-d). In the wound healing experiment, cell images of the S, NC, and CON groups were obtained at 0, 24, and 48 h after the corresponding treatment(Fig. 4e-h). The migration ability of cells in the S group was significantly weaker than that of cells in the NC and CON groups (P < 0.05). The wound healing experiment showed that MTMR14 inhibited the migration of U87 and U251 cells.

3–8 Cell apoptosis was detected using flow cytometry. The results showed that the apoptosis ratio of cells in the S group was significantly higher than those in the NC and CON groups(Fig. 5a-b). MTMR14 knockout significantly promoted the apoptosis of tumor cells. In the immunofluorescence assay, the expression of caspase-3 protein labeled with green fluorescence was significantly higher in the S group than that in the NC and CON groups(Fig. 5c-d). In contrast, the expression of the Bcl-2 protein labeled with red fluorescence in the S group was significantly lower than that in the NC and CON groups(Fig. 5e-f). In conclusion, MTMR14 knockout significantly promoted the apoptosis of tumor cells.

3–9 Western blot results showed that MTMR14 inhibited the activation of Akt, and the expression of P-Akt, p-mTOR, Bax and caspase-9 was significantly increased in the S group. Akt expression did not change, but the expression of Bcl-2 decreased.

As the most common primary brain tumor, glioma mostly shows diffuse growth, is difficult to treat, and is prone to recurrence and poor prognosis, making it a significant burden for most patients and society^[1]. Currently, the widely accepted standard treatment for glioma includes maximum surgical resection combined with radiotherapy and chemotherapy, but the prognosis of patients remains poor ^{[5, 6]}. This urges experts to continue to study how genes and molecular pathways play a role in the development of glioma^[30]. Currently, it has been recognized that the Akt mediated molecular pathway plays an important role in the development of glioma cells^[31]. In this study, through the statistical analysis of the sequencing and clinical data of glioma patients in TCGA database, MTMR14 was found to be a potential independent prognostic factor of glioma patients. The relationship between MTMR14 and cellular DNA and RNA was recognized by enrichment analysis, protein network construction, and immune correlation analysis. Neuronal synaptic regulation and the phosphatidylinositol 3-kinase (PI3K)/Akt pathway are closely related and can affect the immune level and change the immune microenvironment of glioma cells. Therefore, MTMR14 may help clinicians improve the diagnosis of glioma patients to develop a more beneficial personalized treatment regimen. MTMR14, a new phosphoinositide phosphatase is a member of the tubulin-related protein family and is mainly expressed in the myocardium and skeletal muscles^{[32, 33]}. MTMR14 was first discovered in human central nuclear myopathy and binds to MTM1 to maintain myocyte homeostasis, which is essential for normal embryos^[9]. MTMR14 can also negatively regulate autophagy levels^{[34, 35]}.

Studies have shown that MTMR14 is significantly overexpressed in liver cancer, which is positively correlated with clinical stage and promotes hepatocyte apoptosis through the mitochondrial pathway^[20]. In cervical cancer, MTMR14 is considered to be a prognostic marker related to autophagy^[21]. MTMR14, one of the biomarkers for diagnosis and treatment, affects the injury degree of hepatic cells after ischemia-reperfusion and the injury level of cerebral ischemia-reperfusion by regulating the level of autophagy^{[18, 19]}. Studies have shown that MTMR14 can be homologous with Phosphatase and Tensin Homolog (PTEN) interact with each other to regulate autophagy levels of nerve cells, thereby affecting the cells^[36]. Recent studies have shown that improving mitochondrial function and mitochondrial autophagy homeostasis may be one of the mechanisms by which MTMR14 alleviates Chronic Obstructive Pulmonary Disease (COPD) and may become a new therapeutic target for COPD^[37]. PTEN is an important tumor suppressor protein and one of the most frequently mutated genes in human cancer, usually negatively regulating the PI3K/Akt pathway ^[38]. Studies have shown that PTEN inhibits tumor cell growth and proliferation by inhibiting the PI3K/Akt oncogenic signaling pathway in liver cancer cells^[38]. MTMR14 can interact with Akt to regulate the Akt pathway, affecting the degree of cardiac hypertrophy and the level of metabolic function and inflammation^[15]. In this study, we used two glioma cell lines, U87 and U251, through wound healing and CCK-8 experiments, and showed that MTMR14 can significantly inhibit the migration and proliferation of glioma cells. Flow cytometry showed that MTMR14 can significantly promote the apoptosis of glioma cells, and an immunofluorescence assay was performed to label the caspase-3 and Bcl-2 genes. In MTMR14 knockout cells, caspase-3 expression was significantly increased, while Bcl-2 expression significantly decreased MTMR14 and inhibited the activation of Akt. In MTMR14 knockout cells, the expressions of P-Akt, p-mTOR, Bax, and caspase-9 were significantly increased, but there was no change in the NC and CON groups; therefore, we believe that the experimental conclusion that MTMR14 affects tumor cells by inhibiting Akt/mTOR pathway is consistent with the conclusion of statistical analysis of biological information, that is, the prognosis of glioma patients with low MTMR14 expression is significantly better than that of glioma patients with high MTMR14 expression.

Conflict of interest The authors declare that they have no conflict of interest.

Author contributions All authors actively contributed to the article.

Funding The study was supported by National Natural Science Foundation of China (Project No. 82074174)

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MTMR14 is a potential independent prognostic factor in glioma patients and induces glioma cell apoptosis through the Akt/mTOR pathway

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