TMEM71 is crucial for cell proliferation in lower-grade glioma and is linked to unfavorable prognosis

Abstract

Objective

Transmembrane protein 71 (TMEM71) is implicated in multiple cellular physiological functions and has been demonstrated to be crucial in the advancement of different cancerous growths. However, its specific function in low-grade glioma (LGG) remains unclear.

Methods

We examined the expression patterns and prognostic importance of TMEM71 in various types of cancer by using pan-cancer analysis. The analyses of the correlations between TMEM71 expression and clinicopathological characteristics, prognosis, biological functions, immune characteristics, and genomic variations in LGG were conducted based on its expression patterns. Finally, the expression level and biological function of TMEM71 in LGG were verified by executing in vitro studies.

Results

Abnormal elevation of TMEM71 expression level was associated with poor prognosis of many tumors including LGG. Both multivariate and univariate Cox regression analyses indicated that the expression of TMEM71 served as a standalone prognostic biomarker for LGG. The levels of TMEM71 expression were associated with immune-related characteristics, infiltration of immune cells, immune checkpoint genes (ICPGs) expression, and tumor mutation burden (TMB) in patients with LGG. In laboratory studies, elevated levels of TMEM71 were found to be involved in activating the JAK2/STAT3 pathway, promoting CCAAT/Enhancer Binding Protein D (CEBPD) expression, and ultimately affecting the growth and motility of LGG cells.

Conclusion

TMEM71 is an independent prognostic indicator for LGG and is strongly associated with the growth of LGG cells, positioning it as a potential novel target for treatment.

Introduction

Cancer has always been one of the major health challenges on a global scale. Glioma, the most prevalent malignant tumor of the central nervous system, has garnered significant interest in its treatment and prognosis [1]. Per the classification by the World Health Organization (WHO), gliomas can be categorized into grades I-IV, with Grade II and III gliomas being classified as low-grade glioma (LGG). LGG is a relatively slow-developing tumor subtype, despite its lower malignancy, its poor prognosis and high heterogeneity are still deeply worrying for the medical community [2]. LGG remains a challenge in clinical treatment. With the continuous advancement of molecular biology and genomics technology, more and more research has focused on discovering and explaining the molecular mechanisms related to the development, progression and prognosis of gliomas. In this context, the role of key molecular markers in the development and progression of gliomas is highly anticipated.

Members of the transmembrane (TMEM) protein family play a role in various physiological and pathological processes, including regulating genes associated with epithelial-mesenchymal transition (EMT), controlling calcium levels, activating signaling pathways, facilitating cell movement, attachment, programmed cell death, and self-degradation [3,4,5]. Over the past few years, scientists have slowly uncovered the role of the TMEM group in the advancement of different types of cancers. TMEM97 enhances breast cancer metastasis through the activation of EMT-associated signaling pathways [6]. TMEM14A plays a role in the progression and spread of ovarian cancer [7]. TMEM45B enhances the proliferation, movement, and infiltration of stomach cancer cells through the activation of the JAK2/STAT3 signaling pathway [8]. TMEM71 could potentially suppress the growth and movement of breast cancer cells [9]. Nevertheless, there have been few reports on the role and features of TMEM71 in glioma. Therefore, we investigated the specific function of TMEM71 in LGG patients through bioinformatics analysis and in vitro experiments.

Initially, we discovered a notable rise in TMEM71 expression in LGG through a pan-cancer analysis across different types of cancer. Subsequently, we evaluated the predictive significance of TMEM71 in LGG utilizing datasets from TCGA and Chinese Glioma Genome Atlas (CGGA). The LGG specimens were categorized into high and low TMEM71 expression subgroups using the median TMEM71 expression level, and further survival analysis revealed that the high TMEM71 group had a worse prognosis compared to the low TMEM71 group. Clinical pathological data was analysed, incorporating key clinical factors such as gender, age, WHO grade, isocitrate dehydrogenase (IDH) level, 1p/19q status, and O6-methylguanine-DNA methyltransferase (MGMT) status. And detected TMEM71 was an independent prognostic biomarker for LGG by using cox regression analysis.

Functional enrichment analyses were conducted to explore the biological role of TMEM71 in LGG. Subsequently, Gene set variation analysis (GSVA) was performed to identify the molecular pathways affected by TMEM71. A single sample GSEA (ssGSEA) algorithm was conducted to evaluate the association of TMEM71 expression with immunological features, genomic changes, and reactions to chemotherapy. Finally, the abnormal expression and malignant biological function of TMEM71 in LGG were demonstrated by in vitro experiments, and the possible molecular mechanism of TMEM71 mediating the occurrence and development of LGG was also revealed. Collectively, these results indicated that TMEM71 could independently predict outcomes in patients with LGG and could serve as a promising target for treatment in this population.

Materials and methods

Data Availability

The data analyzed in this research can be acquired in the TCGA (https://portal.gdc.cancer.gov/) and CGGA (http://www.cgga.org.cn/) databases.

Data collection and processing

Data on gene expression, survival, clinicopathological information, and TMB for TMEM71 in 33 tumors were gathered from the TCGA database for comprehensive cancer analysis. Expression data of TMEM71 in normal tissue was obtained from the Genotype-Tissue Expression (GTEx) database.

The LGG samples’ gene expression data from the TCGA and CGGA (CGGA_325 and CGGA_693) databases were initially in fragments per kilobase million (FPKM) format, then converted to transcripts per kilobase million (TPM) values, and finally transformed to log2 TPM values. The genome variation data of LGG samples were obtained from the TCGA database.

Sample inclusion criteria

Patients with LGG who met the following criteria were included in our study: (1) those who were classified as Grade II or III; (2) Patients with OS > 30 days; (3) Patients with availability of mRNA expression data. According to the above criteria, a total of 529 and 447 LGG patients were screened from the TCGA and CGGA databases. For maintaining uniformity in survival data among 33 different types of cancer, the TMEM71 pan-cancer analysis included LGG patients who had an overall survival of less than 30 days.

Prognostic value of TMEM71 and validation

According to the median expression of TMEM71 in the TCGA and CGGA cohorts, LGG patients were divided into low TMEM71 and high TMEM71 subgroups. Kaplan-Meier analysis was used to determine the prognosis of patients with two subtypes of LGG. The formula for the risk score is as follows: Risk score = gene A expression level * coefficient A + gene B expression level * coefficient B +… + gene N expression level * coefficient N. Cox regression was utilized to assess the predictive significance of TMEM71 levels as a standalone biomarker in patients with LGG.

Functional enrichment analysis

Utilize the R package “limma” within the TCGA and CGGA cohorts to identify DEGs in each subgroup (|log2 [fold change] > 0.5, false discovery rate (FDR) < 0.05). GO-BP and KEGG enrichment analyses were performed for these DEGs using the R package “clusterProfiler”. GSVA was used to evaluate molecular pathways that were significantly enriched in both low and high TMEM71 subgroups. The most prevalent molecular pathways between the two subgroups were identified using KEGG analysis (c2.cp.kegg.v7.2.symbols). Significance was determined based on|log2 FC| > 0.1, p < 0.05, and FDR < 0.05.

Immunological features of LGGs

Using 29 immune-related characteristics identified in prior research, we applied the ssGSEA method to assess the levels of immune-related features in two subgroups within the TCGA and CGGA datasets. The ESTIMATE algorithm was used to analyze the abundance of immune cells, stromal cells, and tumor purity. Following that, we assessed four different types of scores which consisted of tumor purity, an ESTIMATE score indicating non-tumor structures, a stromal score reflecting the abundance of stromal cells, and an immune score indicating the abundance of immune cells. CIBERSORT algorithm was utilized to assess the infiltration level of TIICs based on the median expression of TMEM71 in LGG. 25 ICPGs with potential therapeutic value were chosen for investigation of their correlation with TMEM71 expression, based on prior research.

Genomic mutation analysis

The RCircos tool was used to detect significant deletions and amplification in the whole genome of two expression subtypes. Maftools and GenVisR were used to assess the variety and occurrence of mutations in various genes within the low and high TMEM71 groups. The software package “fmsb” was utilized to evaluate the correlation between TMEM71 expression and TMB levels in 33 tumors, whereas the software package “ggplot2” was utilized to evaluate the correlation between TMEM71 expression and TMB levels in LGG patients within the TCGA dataset.

Cell culture and transfection

Human LGG lines, SW1783, SW1088, purchased from the American Type Culture Collection (ATCC). NHA cell line was sourced from the Culture Collection of the Chinese Academy of Sciences (Shanghai, China). SW1783 and SW1088 cells were grown in Leibovitz’s L-15 medium (ATCC) supplemented with 10% fetal bovine serum (Gibco) and 1% penicillin-streptomycin solution (Solarbio, China) at 37℃ with 5% CO2, whereas NHA cells were cultivated in Dulbecco’s modified Eagle’s medium/F12 medium (ATCC). Lentiviruses expressing TMEM71 shRNA were obtained from Obio Technology (Shanghai, China), in which the TMEM71 shRNA target sequences were 5’-CATTGATGATAACTGTAGCTT-3’ and 5’-CTCTTCAACCTCAGTACCTCC-3’. SW1783 and SW1088 cell lines were transfected with lentiviruses containing TMEM71 shRNA and negative control (NC) vectors. The multiplicities of infection (MOIs) were 10. Polystyrene improves transfection efficiency and puromycin screening positive cells.

Western blot analysis and quantitative real-time PCR

The harvested cells lysates were lytically denatured in RIPA lysis buffer (Solarbio, China). 4 µg of protein lysates were loaded onto a 10% SDS-PAGE gel and separated, followed by transfer of the proteins to PVDF membranes. Following this, the primary antibody TMEM71 (1:1000, ab235788, abcam, China), CEBPD (1:800, A15261, ABclonal, China), JAK2 (1:1000, A19629, ABclonal, China), Phospho-JAK2 (1:800, AP0531, ABclonal, China), STAT3 (1:1000, A1192, ABclonal, China) and Phospho-STAT3 (1:800, AP0705, ABclonal, China) were introduced and left to incubate at 4 °C. Next, the membranes were exposed to the appropriate secondary antibody during incubation. Finally, protein bands on the membrane were observed using the GV6000M imaging system (GelView6000pro). We utilized the Simple P Total RNA Extraction Kit (Biolux, China) for RNA extraction from cells, and subsequently employed the M5 Sprint qPCR RT kit with gDNA remover (Mei5bio, China) to reverse transcribe the RNA into complementary DNA. The 2-ΔΔCT method was used to process the results. The primers used were as follows: TMEM71: forward, TCTCTCTTCAACCTCAGTACCTC, and reverse, TGCAACAACCTGGTTTCATTTCC; β-actin: forward, TGACGTGGACATCCGCAAAG, and reverse, CTGGAAGGTGGACAGCGAGG.

CCK-8 assay

SW1783 or SW1088 cells that were transfected were placed in 96-well dishes and left to incubate for 24, 48, 72, or 96 h. 10µL of CCK-8 solution was added to each well, followed by incubation at 37 °C for 1 h. The absorbance at a wavelength of 450 nm was then measured using an enzyme labeling device.

Colony formation assay

SW1783 or SW1088 cells that had been transfected were placed in 6-well dishes and left to incubate for a period of 14 days. Next, it was treated with 4% paraformaldehyde for half an hour, then dyed with a 2.5% crystal violet solution for 15 min, and the quantity of colonies was determined using ImageJ.

Transwell invasion assay

Transfected SW1783 or SW1088 cells were added to the top chamber of serum-free medium. The membranes in the upper chambers were pre-coated with Matrigel at a dilution of 1:8 (Yeasen, China). Pour 500 µl of DMEM containing 10% FBS into the lower chamber. Following a 24–48-hour incubation period, the cells in the apical chamber were eliminated using a cotton swab, then preserved in 4% paraformaldehyde for 15 min, and finally colored with a 2.5% crystal violet solution for 15 min. The region of the adherent cells in each hole is photographed.

Wound-healing assay

SW1783 or SW1088 cells that were transfected were placed in 6-well plates and incubated for 24 h until reaching 90–100% confluence. Using a 200 µl pipette tip, the cells were scraped and then washed twice with phosphate-buffered saline (PBS) to eliminate any cell debris. The cells were further cultured in DMEM medium supplemented with 1% FBS. The wounds were imaged every 12 h.

Statistical analysis

The outcomes of the high and low TMEM71 subgroups were differentiated using Kaplan-Meier analysis along with a bilateral logarithmic rank test. Prognosis assessment using TMEM71 expression was conducted by analyzing ROC curves and area under the curve (AUC) values. Student’s test was used to compare immune-related factors, including 29 immune-related features, TIIC, 25 ICPGs, and TMB load, between the two subtypes. Pearson’s or Spearman’s correlation tests are used to determine correlations between distributed variables. The statistical analysis was conducted using R version 4.2.1, SPSS Statistics, and GraphPad Prism 8 software. A significance level of p < 0.05 was applied.

Results

Analysis of TMEM71 across multiple types of cancer

Pan-cancer analyses obtained from the TCGA database indicated that TMEM71 was abnormally expressed in a variety of cancers (Fig. 1A). The findings indicated that TMEM71 expression was significantly increased in GBM, KIRC, KIRP, LGG, THCA, COAD and LUAD. In contrast, TMEM71 was decreased in 9 types of cancers including BLCA, BRCA, HNSC, KICH, LIHC, LUSC, PRAD, STAD, UCEC, and READ. In 33 different types of cancer, we utilized univariate Cox regression analysis to assess the prognostic significance of TMEM71 expression. As shown in the forest plots (Fig. 1B), we discovered the expression of TMEM71 was negatively correlated with the overall survival (OS) of LGG, ACC, BRCA, HNSC, KIRP, THYM, UCEC, UCS, and UVM. Survival analysis supported the finding that higher TMEM71 expression was linked to lower survival rates in LGG patients (Fig. 1C). Subsequently, we investigated the connection between TMEM71 levels and tumor mutation burden (TMB) across 33 cancer types. Our findings revealed a positive association between TMEM71 expression and TMB in LGG and SARC, while a negative correlation was observed in LIHC, LUAD, LUSC, PAAD, PCPG, PRAD, STAD, TGCT, THYM, BLCA, CESC, and DLBC (Fig. 1D). Additionally, we assessed the relationship between TMEM71 levels and immune checkpoint genes (ICPGs) levels in 33 different types of cancer. The findings indicated a positive correlation between the expression of TMEM71 in ACC, BLCA, BRCA, CHOL, HNSC, KICH, KIRC, KIRP, LGG, LIHC, LUAD, PAAD, PRAD, and THCA and the expression of most ICPGs (Fig. 1E). The above analysis suggested that TMEM71 exhibited abnormal expression and poor prognosis in LGG.

Fig. 1

Pan-cancer analysis of TMEM71. (A) Differential expressions of TMEM71 in normal and cancer tissues. (B) Univariate Cox regression analysis of TMEM71 expression in a variety of tumors. (C) Kaplan-Meier analysis of TMEM71 in pan-LGG. (D) Differential TMB in various cancers. (E) Co-expressions of TMEM71 and ICPGs in multifarious cancers. P < 0.05, P < 0.01, P < 0.001

TMEM71 and clinicopathological characteristics in LGG

According to the median expression of TMEM71, LGG patients were divided into low and high TMEM71 subgroups. The relationship between TMEM71 expression and clinicopathological characteristics was investigated. As shown in Fig. 2A and B. In the TCGA dataset, higher TMEM71 expression was significantly associated with high WHO classification, older age, IDH wild-type status, 1p/19q non-coding status, and MGMT promoter unmethylated status, simultaneously, the similar results also were observed in CGGA database (Supplementary Fig. 1A, B). These findings indicated a significant correlation between TMEM71 expression and the clinical characteristics of individuals with LGG.

TMEM71 was a dependable predictor in LGG

In the TCGA and CGGA databases, Kaplan-Meier analysis showed that the low-TMEM71 subgroup had better OS than high-TMEM71 subgroup (Fig. 2C and Supplementary Fig. 1C). Later, we discovered that increased TMEM71 levels in individuals with LGG were linked to poorer OS and elevated risk scores (Fig. 2D, Supplementary Fig. 1D, and Supplementary Table 1). Additionally, we analysed the proportion of LGG patients with different TMEM71 expression levels within the selected survival period (Fig. 2E and Supplementary Fig. 1E), which showed that the survival rate of patients with high TMEM71 expression was consistently lower than that of patients with low expression. Importantly, we performed multivariate and univariate Cox regression analyses, the results showed that TMEM71 expression, age, WHO grade, IDH status, 1p/19q status, and MGMT status were independent prognostic biomarkers for LGG in the TCGA and CGGA datasets (Fig. 2F-G and Supplementary Fig. 1F-G). These findings indicated that TMEM71 could serve as an independent prognostic biomarker for LGG.

Fig. 2

Clinical correlation analysis of TMEM71 in TCGA. (A) Relationship between TMEM71 expression in TCGA and clinical features of LGG. (B) To analyze the relationship between TMEM71 expression and different clinical characteristics (gender, age, tumor grade, 1p/19q, IDH status and MGMT status). (C) Prognostic analysis of high and low subtypes of TMEM71 in LGG patients. (D) Risk scores and OS status for high and low TMEM71 subtypes. (E) OS distribution in patients with high and low TMEM71 subtypes LGG. (F, G) Univariate and multivariate Cox regression analysis of TMEM71 expression and clinicopathological features in TCGA. P < 0.05, P < 0.01, P < 0.001

Functional annotations of TMEM71 in LGG

Differential expression genes (DEGs) were discovered in LGG patients based on the average expression of TMEM71 (log2 (fold change)| > 0.5, P < 0.05 was significant) to assess TMEM71’s impact on the differential prognosis of OS in LGG patients. In the TCGA dataset (Supplementary Table 2), we selected 923 down-regulated and 475 up-regulated DEGs. In the CGGA database (Supplementary Table 3), a total of 6,340 down-regulated and 809 up-regulated DEGs were selected. The heat map showed the obvious DEGs in the TCGA (Fig. 3A) and CGGA (Supplementary Fig. 2A) cohorts. Next, we utilized Gene Ontology Biological Processes (GO-BP) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to examine these DEGs. The DEGs showed strong associations with immune responses mediated by leukocyte mediated immunity, positive regulation of cell activation, collagen − containing extracellular matrix based on the GO analysis findings from the TCGA dataset (Fig. 3B). In the CGGA database (Supplementary Fig. 2B), DEGs were shown to be closely related to synapse organization, axon development, and neuronal cell body. KEGG pathway analysis in the TCGA (Fig. 3C) and CGGA (Supplementary Fig. 2C) datasets displayed that DEGs were enriched in phagosome, focal adhesion, human T − cell leukemia virus 1 infection, synapse organization, axond evelopment and modulationof chemica. In addition, GSVA analysis showed that the high TMEM71 subtype was mainly associated with extracellular matrix–receptor (ECM-receptor), focal adhesion, pantothenate, coa biosynthesis, antigen processing and presentation and jak-stat signaling pathway (Fig. 3D, Supplementary Tables 4, and Supplementary Fig. 2D). These functional annotation analyses indicated that TMEM71 was involved in regulating multiple key signaling pathways of the immune microenvironment in LGG.

Fig. 3

Biological function of TMEM71 in LGG patients in the TCGA database. (A) DEGs in low and high expression groups of TMEM71. (B-C) GO-BP (B), KEGG (C). (D) GSVA analysis of TMEM71

Association between TMEM71 expression and immune characteristics

The above GO-BP and KEGG results revealed an association between TMEM71 and LGG immune regulation. Hence, we employed a single-sample GSEA (ssGSEA) algorithm to identify the abundance of 29 factors related to the immune system to examine the correlation between TMEM71 expression and immune cell infiltration. In the TCGA (Fig. 4A) and CGGA (Supplementary Fig. 3A) datasets, immune-related characteristics were decreased in the low TMEM71 subgroup compared to the high TMEM71 subgroup. According to the ESTIMATE algorithm, in the TCGA (Fig. 4B) and CGGA (Supplementary Fig. 3B) cohorts, TMEM71 expression showed a positive correlation with estimation scores, immune scores, and stromal scores, while exhibiting a negative correlation with tumor purity. In two TMEM71 subgroups, the CIBERSORT algorithm was utilized to forecast the quantities of immune cells infiltrating tumors (TIICs). Within the TCGA (Fig. 4C, D) (Supplementary Table 5) and CGGA (Supplementary Fig. 3 C, D) groups, TMEM71 expression was positively correlated to Macrophages M1, T cells CD4 memory resting, Macrophages M0, Activated Dendritic cells, Neutrophils, and positively associated with T cells CD8 infiltration but negatively correlated with activated Mast cells, Monocytes, resting NK cells, and memory B cells. Subsequently, difference correlation analyses were used to further explore the differential expression of ICPGs and TMEM71 in LGG patients. In the TCGA (Fig. 4E) and CGGA (Supplementary Fig. 3E) datasets, we discovered TMEM71 expression had a positive correlation with the majority of ICPGs. Correlation analysis was utilized to predict the relationship between TMEM71 and key ICPGs (including PD1, PD-L1, CD80, and CD86) in the TCGA (Fig. 4F) and CGGA (Supplementary Fig. 3F) datasets. As expected, TMEM71 was positively correlated with all these genes. The above results indicated that TMEM71 might be closely associated with the immune environment.

Fig. 4

TME and immunological characteristics of low and high TMEM71 subtypes in the TCGA cohort. (A, B) The relationship between TMEM71 expression and 29 immune-related features, ESTIMATE score, immune score, stromal score, and tumor purity. (C) Comparison of infiltration of 22 types of immune cells in the subgroup with low and high expression of TMEM71 in LGG. (D) The lollipop plot shows the association between TMEM71 expression and TIICs. (E, F) Co-expression analysis of TMEM71 and 25 ICPGs. P < 0.05, P < 0.01, P < 0.001

Relationship between TMEM71 and genomic variation

Research indicates that genetic differences could be crucial in controlling the immune response to tumors and the infiltration of immune cells [10,11,12]. Establishing a “waterfall” map of somatic variation showed the specific mutated genes present in both high and low TMEM71 subgroups. The figure demonstrated that the frequencies of mutations in IDH1 (isocitrate dehydrogenase 1) and CIC (capicua) were reduced in the high TMEM71 subtype compared to the low TMEM71 subtype, whereas the frequencies of mutations in TP53 (tumor protein 53) and ATRX (alpha-thalassemia mental retardation X-linked) were similar between the two subtypes (Fig. 5A-B). The level of TMEM71 expression showed a positive correlation with TMB in patients with LGG (Fig. 5 C-D). Patients with LGG who had elevated levels of both TMEM71 expression and TMB experienced worse overall survival outcomes (Fig. 5E-F). The findings indicated that individuals with high levels of TMEM71 expression among LGG patients may exhibit unique immune traits.

Fig. 5

Comparison of genomic mutations between low and high TMEM71 subgroups in the TCGA dataset. (A, B) Waterfall map shows mutated genes in high TMEM71 subgroup (A) and low TMEM71 subgroup (B). (C, D) Relationship between TMEM71 expression and TMB level. (E) Relationship between TMB level and prognosis of LGG patients. (F) The differential prognostic value of TMB levels in patients with low and high TMEM71 subtype LGG. P < 0.05, P < 0.01, P < 0.001

In vitro experiment of TMEM71 in patients with LGG

A set of functional experiments were carried out to assess the relationship between TMEM71 expression and glioma cells in a laboratory setting. First, we performed qRT-PCR and western blotting to detect the mRNA expression and protein levels of TMEM71 in the LGG cell lines (SW1088, SW1783 cells) and the Normal human astrocyte (NHA) cell line. And the results showed that the expression of TMEM71 in the LGG cell lines was notably elevated in comparison to the NHA cell line (Fig. 6A and B). Cell scratch healing experiments showed that transfection of sh-TMEM71 into SW1783 and SW1088 cells decreased their migration ability compared with transfection of sh-NC (Fig. 6C). The results of the CCK-8 assay (Fig. 6D) and colony formation assay (Fig. 6E) demonstrated that depletion of TMEM71 led to a significant decrease in the proliferation ability of SW1783 and SW1088 cells. Through transwell assay, we confirmed that depletion of TMEM71 significantly weakened the invasive ability of LGG cells (Fig. 6F). These in vitro experiments indicated that TMEM71 had an impact on the growth, movement, and infiltration of glioma cells.

Next, we explored the underlying molecular mechanisms. Analysis of Gene Set Enrichment Analysis (GSEA) revealed that TMEM71 exhibited elevated expression within the JAK/STAT signaling pathway (Fig. 6G). Previous studies have demonstrated that STAT3 activates the expression of the transcription factor C/EBP-δ (which is encoded by the CEBPD gene) in response to inflammatory signals [13–14]. CEBPD is significantly upregulated in gliomas, and high levels of CEBPD have been shown to promote glioma cell invasion and growth [15]. In this study, we examined whether the alteration in TMEM71 levels would impact the JAK/STAT pathway and CEBPD through western blot analysis. The results showed that inhibiting the expression of TMEM71 could decrease the expression level of CEBPD. Conversely, the expression of CEBPD increased after overexpression of TMEM71 (Fig. 6H and I). In comparison to the sh-NC group, the reduced TMEM71 expression suppressed the levels of p-JAK2 and p-STAT3, with no impact on total JAK2 and total STAT3 protein levels. However, overexpression of TMEM71 produced the opposite result (Fig. 6J, K). WP1066, a derivative of AG 490, is a JAK2 and STAT3 inhibitor of cell permeability [8]. As shown in Fig. 6L, in overexpressed TMEM71 cell lines, WP1006 weakened the promoting effect of TMEM71 on p-JAK2, p-STAT3, and CEBPD expression. Overall, the above results indicated that TMEM71 played a key role in the activation of JAK2/STAT3/CEBPD signaling pathway and tumor progression in LGG.

Fig. 6

The expression and biological function of TMEM71 in LGG were verified in vitro. (A) Western blot and (B) qRT-PCR analysis of TMEM71 expression in NHA and LGG cell lines. (C) Wound healing assay to detect the migration and healing ability of sh-TMEM71 transfected and sh-NC transfected SW1783 and SW1088 cells. (D) The effect of sh-TMEM71 transfection on the cell viability of SW1783 and SW1088 cells was measured by CCK-8. (E) Effect of TMEM71 knockout on colony formation of SW1783 and SW1088 cells. (F) The invasive ability of SW1783 and SW1088 cells after sh-TMEM71 transfection and sh-NC transfection was detected by Transwell invasion assay. (G) TMEM71 gene set enrichment analysis (GSEA). (H, I) Western blot analysis of the effects of knockdown (H) and overexpression (I) of TMEM71 on CEBPD expression in SW1783 and SW1088 cells. (J, K) Western blot analysis of the effects of knockdown (J) and overexpression (K) of TMEM71 on the expression of JAK2/STAT3 pathway marker protein in SW1783 and SW1088 cells. (L) Changes in JAK2/STAT3/CEBPD protein levels after adding WP1006 to TMEM71 overexpressing cell lines

Discussion

Although there have been advancements in treating LGG cancer through surgery, radiotherapy, and chemotherapy, the impact of these conventional methods on LGG patients remains restricted, resulting in a bleak clinical outlook for these patients [16,17,18]. Therefore, new therapeutic methods and prognostic factors are urgently needed. TMEM71, a membrane-bound protein, plays a role in various cellular functions, including programmed cell death and self-degradation. Recent research has shown that the increased presence of TMEM71 is linked to the advancement of gastric cancer, ovarian cancer, and other tumors [6,7,8,9], however, its impact on LGG is still poorly understood. Wang et al.reported that TMEM71 acted as an oncogene in GBM, was associated with GSC, TMZ resistance, and immune response, and was considered a potential target for clinical treatment of GBM [19]. However, the study lacked further validation of the expression characteristics and functions of TMEM71. Consequently, we conducted a further examination of the correlation between TMEM71 levels and clinicopathological characteristics, survival rate, biological role, immune response to tumors, and genetic changes in individuals with LGG. Our objective was to offer a possible treatment option for individuals diagnosed with LGG.

Pan-cancer analysis of TMEM71 in 33 cancers showed that high expression of TMEM71 was associated with shorter survival time, high ICPG expression, and high TMB load in pan-LGG patients. Survival analysis on LGG samples from the TCGA and CGGA cohorts indicated that high TMEM71 subtype had a poorer prognosis compared to low TMEM71 subtype. The Kaplan-Meier analysis indicated a strong correlation between increased TMEM71 expression and decreased overall survival. The presence of TMEM71 was linked to the clinicopathological characteristics of patients with LGG. Subsequent multivariate Cox regression analysis found that TMEM71 could be an independent prognostic biomarker for LGG.

Enrichment analysis using KEGG and GO-BP was conducted to examine the DEGs in the TCGA and CGGA cohorts. The analysis revealed a connection between the levels of TMEM71 and immune response by leukocytes, synapse organization, as well as the activation of cells. Additionally, it was also related to processes such as Phagosome, Focal adhesion, synapse organization, axond evelopment and infection by Human T-cell leukemia virus 1. GSVA analysis confirmed that high TMEM71 expression was associated with immune response and cancer-related signaling pathways.

Analysis of GO-BP, KEGG, and GSVA results indicated a correlation between TMEM71 and immune response in LGG. Additionally, analyses with ssGSEA, ESTIMATE, and CIBERSORT algorithms were conducted to compare immune-related characteristics between two TMEM71 subgroups in the TCGA and CGGA cohorts, and to identify the makeup of the tumor microenvironment and tumor-infiltrating immune cells. The findings indicated a correlation between immune infiltration and the presence of TMEM71 in LGG. We evaluated the relationship between TMEM71 and ICPGs expression in patients with LGG. In the TCGA and CGGA datasets, it was discovered that the levels of certain typical ICPGs, such as PD1, PD-L1, CD80, and CD86, were directly related to the levels of TMEM71 expression. Then, analysis of somatic mutations revealed that the TMB was greater in the group with high TMEM71 expression compared to the group with low TMEM71 expression. In summary, based on the above research results, it is anticipated that TMEM71 will have a effective impact on the immunotherapy of patients with LGG.

Western blot and qRT-PCR analyses of LGG and NHA cells confirmed the upregulation of TMEM71 expression in gliomas. We studied the impact of TMEM71 on cell proliferation, migration, and invasion in individuals with LGG by reducing TMEM71 levels in the LGG cell line to determine its role in the progression of LGG. TMEM71 knockdown led to a notable decrease in the proliferation and invasion capabilities of tumor cells when compared to the control group. Cytokine signaling leads to the activation of the JAK/STAT signaling pathway, and its abnormal activation is associated with the occurrence and development of glioma [20], lung cancer [21], colorectal cancer [22], breast cancer [23] and other cancers. GSEA enrichment analysis indicated that the TMEM71 gene was highly present in the JAK/STAT signaling pathway. Shen et al. have previously confirmed in their research that TMEM45B from the TMEM family can promote the proliferation, migration, and invasion of gastric cancer cells through the JAK2/STAT3 signaling pathway [8]. In our study, we attempted to explore the specific mechanism of action of the TMEM71 and JAK2/STAT3 signaling pathway in LGG. CEBPD controls numerous biological functions, such as cellular differentiation, growth, and apoptosis, and has strong connections to cancer. Some earlier research demonstrated that STAT3 triggers the production of the transcription factor CEBPD [13, 24]. Therefore, we performed western blot and the results showed that reducing TMEM71 levels suppressed the expression of CEBPD, p-JAK2, and p-STAT3, with the opposite effect seen with overexpression. We also further utilized WP1006, a JAK inhibitor that can block the JAK/STAT signaling pathway [8]. WP1006 was found to suppress the activation of p-JAK2, p-STAT3, and CEBPD in cell lines with overexpressed TMEM71. This suggested a possible mechanistic relationship between TMEM71 and glioma development through JAK2/STAT3/CEBPD signaling pathway.

Conclusion

In conclusion, this study demonstrated that TMEM71 was a reliable prognostic biomarker, closely related to the proliferation, migration and invasion of LGG cells, and participated in the activation of the JAK2/STAT3/CEBPD signaling pathway. Therefore, TMEM71 may be an effective therapeutic target for patients with LGG.

Limitations of the study

Our study had certain limitations. Future in vitro and in vivo experiments should be adopted to further verify the specific molecular mechanisms by which TMEM71 drives malignant progression of LGG through the JAK2/STAT3/CEBPD signaling pathway in LGG.