Analysis and Validation of TMED3 correlates with poor prognosis and tumor immune infiltration of glioma

doi:10.21203/rs.3.rs-1632245/v1

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Analysis and Validation of TMED3 correlates with poor prognosis and tumor immune infiltration of glioma

https://doi.org/10.21203/rs.3.rs-1632245/v1

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Background:Glioma is the most common primary intracranial tumor. It is notorious for its high degree of malignancy, strong invasion, and poor prognosis. The transmembrane emp24 trafficking protein 3 (TMED3) belongs to the TMED family, which is responsible for intracellular protein transport and innate immune signal transmission. More and more evidence shows that TMED3 plays a key role in the tumor progression of human cancer. However, the role and potential molecular mechanism of TMED3 in glioma have not been clarified.

Methods: TMED3 expression levels, clinical data, survival prognosis, prediction of upstream miRNA, and immune-related analyses were all analyzed utilizing relevant databases. Finally, a molecular cell experiment confirmed TMED3 expression in glioma.

Results: We discovered that TMED3 is overexpressed in most tumors, including gliomas, and is associated with tumor staging and prognosis. Subsequently, a combination of a series of bioinformatics analyses, including correlation and survival analyses, identified miR-1296-5p as the most potent upstream miRNA of TMED3 in gliomas.Additionally, we analyzed the relationship between TMED3 level and tumor immune cell infiltration and immune checkpoint expression.

Conclusion

TMED3 is highly expressed in gliomas and is associated with tumor staging and affects the prognosis of patients. Therefore, the TMED3 gene may be a potential immunotherapy target and prognostic marker for gliomas.

TMED3

pan-cancer

prognosis

immune infiltration

Glioma is the most common tumor in the central nervous system (80%), with the highest degree of malignancy and the strongest invasion. At present, there are various methods to treat glioma, which are generally combined with surgery, radiotherapy, or chemotherapy. However, the 5-year relative survival rate is about 5%. In addition, the recurrence rate of glioma is high, so it is necessary to explore a new method to treat glioma.¹

Transmembrane emp24 domain containing (TMED) proteins constitute a highly conserved family of proteins that exist as monomers or dimers of various compositions.² TMED family consists of type I single-pass transmembrane proteins that are found in all eukaryotes.TMED family members have emerged as key protein transport regulators.³ TMED3 has been definitively linked to the occurrence and progression of several human cancers, including osteosarcoma⁴, squamous cell carcinoma of the lung⁵, breast cancer⁶, and colorectal cancer⁷. However, there is currently a paucity of thorough studies on TMED3 expression, prognosis, and mechanism in glioblastoma. Furthermore, no link between TMED3 and tumor immune infiltration in glioma has been established.

In this study, we first analyzed the expression and survival of TMED3 in various types of human cancers. Next, we also explored the regulation of non-coding RNA (ncRNA) related to TMED3 in glioma. Finally, we determined the relationship between TMED3 expression and immune cell infiltration, immune cell biomarkers, or immune checkpoints. Finally, we verified the expression level of TMED3 in glioma by cell experiment.

UCSC database analysis

We downloaded the unified and standardized pan-cancer data set: TCGA Target GTEX (PANCAN, n = 19131, g = 60499) from the UCSC (https://xenaburowser.net/) database, and further extracted the expression data of ENSG00000166557(TMED3) gene in each sample. Further, we screened the sample sources as follows: Solid Tissue Normal, Primary Solid Tumor, Primary Tumor, Normal Tissue, primary blood derived cancer-bone marrow, The samples of primary blood derived cancer-peripheral blood, in addition, we filtered the samples with expression level of 0, and further carried out log2(x+0.001) transformation on each expression value. Finally, we eliminated the cancer species with less than 3 samples in a single cancer species, and finally obtained the expression data of 34 cancer species.We used R software (version 4.1.3) to calculate the expression difference between normal samples and tumor samples in each tumor, and used unpaired Wilcoxon rank sum and signed rank tests to analyze the significance of the difference. Next, the authenticity of the data is verified using the TIMER database(https://cistrome.shinyapps.io/timer/)and the UCSC database. Survival and clinical phenotype data were extracted from each sample downloaded from the USCS and the R-package was used for correlation analysis of clinical phenotype and prognosis.The selection criteria for classifying as statistically significant were set at p value <0.05.

Candidate miRNA prediction

Upstream binding miRNAs of TMED3 are predicted by five target gene prediction programs, including ENCORI (https://starbase.sysu.edu.cn), miRDB (http://mirdb.org/), mirDIP (http://ophid.utoronto.ca/mirDIP/), miRWalk (http://mirwalk.umm.uni-heidelberg.de/), and TarBase (http://carolina.imis.athena-innovation.gr/diana_tools/web/index.php?r=tarbasev8%2Findex). Only miRNAs that were present in more than two procedures had the opportunity for subsequent correlation analysis.

Immunoinfiltration analysis

The correlation between TMED3 and immune infiltration degree and immune checkpoint of CD4 T lymphocytes, CD8 T lymphocytes, B cells, macrophages, and dendritic cells was carried out in the sangerbox (http://vip.sangerbox.com/home.html).

RNA extraction and quantitative real-time polymerase chain reaction (qRT-PCR)

The Total RNA Small Amount Extraction Kit (Axygen, Corning, USA) was used to extract total RNA from cell lines according to the manufacturer's instructions. Sangon Biotech developed primers for the amplification of TMED3 and the endogenous control actin (Shanghai, China). The SYBR Green master mix kit (Tiangen Biotech, Beijing, China) was used for qRT-PCR according to the manufacturer's instructions. The 2-ΔΔCt method was used to calculate fold changes in target gene expression.

Western blot and antibodies

SDS-PAGE (Solar Bio, Beijing, China) was used to separate the protein, which was then transferred to a polyvinylidene fluoride membrane (Millipore, Billerica, MA, USA) and mixed with TMED3(1: 2000), GAPDH (1: 10000; Proteintech, USA) was incubated at 4℃for 12 hours. The HRP-bound anti-mouse or rabbit IgG antibody (1:10000, affinity) was incubated for 2 hours at 25°C. ECL chemiluminescence reagent(UE,Suzhou,China) was used to detect the target protein band. The strip density was measured and compared to the internal control using a gel imaging technique.

Statistical analysis

The statistical analysis in this study was automatically calculated by the online database mentioned above. Statistical significance was defined as p value 0.05 or log rank p value 0.05.

Expression Levels of TMED3 in Pan-Cancer

From the UCSC dataset, we observed significant upregulation of TMED3 in 30 tumors, such as Glioblastoma multiforme (GBM), Brain Lower Grade Glioma (LGG), GBMLGG (GBM+LGG), Uterine Corpus Endometrial Carcinoma (UCEC), Breast invasive carcinoma (BRCA), Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), Lung adenocarcinoma (LUAD), Esophageal carcinoma (ESCA), Stomach and Esophageal carcinoma (STES), Kidney renal papillary cell carcinoma (KIRP), Pan-kidney cohort (KIPAN), Colon adenocarcinoma (COAD), Colon adenocarcinoma/Rectum adenocarcinoma Esophageal carcinoma (COADREAD), Prostate adenocarcinoma (PRAD), Prostate adenocarcinoma (STAD), Kidney renal clear cell carcinoma (KIRC), Lung squamous cell carcinoma (LUSC), Liver hepatocellular carcinoma (LIHC), Skin Cutaneous Melanoma (SKCM), Bladder Urothelial Carcinoma (BLCA), Thyroid carcinoma (THCA), Ovarian serous cystadenocarcinoma (OV), Pancreatic adenocarcinoma (PAAD), Testicular Germ Cell Tumors (TGCT), Uterine Carcinosarcoma (UCS), Acute Lymphoblastic Leukemia (ALL), Acute Myeloid Leukemia (LAML), Pheochromocytoma and Paraganglioma (PCPG), Adrenocortical Carcinoma (ACC), Cholangiocarcinoma (CHOL), and significant down-regulation in 2 kinds of tumors, such as Head and Neck squamous cell carcinoma (HNSC), High-Risk Wilms Tumor (WT).(Figure 1A)We further verified the expression of TMED3 in these cancer types by using the TIMER database. Except for those cancers whose normal tissue samples are less than 3 instances, substantial changes in TMED3 expression between tumors and normal tissues were observed in 19 malignancies, as shown in Figure 1B, when compared to the matching normal control.Among them, TMED3 is in BLCA, BRCA, Chol, COAD, ESCA, HNSC-HPVneg, KIRC, KIRP, LIHC, LUAD, LUSC, PRAD, Rectum adenocarcinoma (READ), SKCM, STAD, THCA, UCEC. On the contrary, compared with the normal tissues in HNSC and Kidney Chromophobe (KICH), the level of TREM2 in tumors is down-regulated. In addition, the results from the Xena database showed that the expression of TMED3 was significantly increased in some cancers, including ACC, BLCA, BRCA, CHOL, COAD, DLBC, ESCA, GBM, KIRC, KIRP, LIHC, LUAD, LUSC, OV, PAAD, PCPG, PRAD, READ, SKCM, STAD, TGCT, THCA, THYM, UCEC, UCS, but low TMED3 expression in HNSC compared with non-tumor tissue (Figure 1C). The results from three different databases are basically consistent, which indicates that TMED3 may play a key regulatory role in the carcinogenesis of cancer.

Clinical correlation analysis of TMED3 in Pan-Cancer

We downloaded a unified and standardized pan-cancer data set, TCGA PAN-Cancer (PANCAN, n = 10535, g = 60499) from the UCSC database, and extracted the expression data of the ENSG0000166557 (TMED3) gene in each sample. Further, the samples from primary blood-derived cancer (peripheral blood and primary tumor) were selected. In addition, we also filtered the samples with an expression level of 0, and further carried out a log2 (x+0.001) transformation on each expression value. Finally, we eliminated cancer species with fewer than 3 samples in a single cancer species. Finally, the expression data of 37 cancer species was obtained. We used R software (version 4.1.3) to calculate the gene expression difference of each tumor in different clinical stage samples, used an unpaired Student's t-Test to analyze the difference significance between pairs, and used ANOVA to test the difference between multiple groups of samples. The results are shown in the following figures 2A-F.

The prognostic values of TMED3 in Pan-Cancer

In order to study the relationship between TMED3 expression level and prognosis, we analyzed the survival associations of each cancer, including Overall Survival (OS), Disease-specific Survival (DSS), Disease-specific Survival (DFI), and Progression-free Interval (PFI). We established the Cox proportional hazards regression model by using the coxph function of the R software package survival (version 4.1.3) to analyze the relationship between gene expression and the prognosis of each tumor, and we statistically tested it with the Logrank test to obtain the significance of prognosis. With regard to OS (Figure 3A), we observed that the high expression of TMED3 had poor prognosis in these 15 tumor types (GBMLGG, LGG, LAML, BRCA, LUAD, KIRP, KIPAN, KIRC, LIHC, SKCM, BLCA, UVM, LAML, ALL, and KICH). Furthermore, we analyzed the relationship between TMED3 expression and disease-specific survival in pan-cancer. The results suggested that increased expression of TMED3 was associated with poor DSS in GBMLGG, LGG, BRCA, KIRP, KIPAN, KIRC, SKCM, SKCM-M, UVM, and KIRC. (Figure 3B). The increased expression of TMED3 indicates that the DFI rate of KIPAN is worse. However, it shows very poor clinical results in THCA patients with low expression of TMED3.(Figure 3C). Meanwhile, the results of COX regression analysis showed that TMED3 expression was associated with PFI in GBMLGG, LGG, CESC, KIRP, KIPAN, HNSC, GBM, KIRC, SKCM, SKCM-M, MESO, UVM, PCPG PRAD, and OV. (Figure 3D) Combining OS, DSS and PFI, we can clearly find that the prognosis of glioma patients with high expression of TMED3 is worse.

Prediction and analysis of upstream miRNAs of TMED3

MicroRNA (miRNA) is a kind of endogenous small RNA with a length of about 20–24 nucleotides that is responsible for regulating gene expression in cells. To determine whether TMED3 is regulated by some mirnas, we used the intersection method of five databases (ENCORI, miRDB, mirDIP, miRWalk, and TarBase) to predict the upstream mirnas that might bind to TMED3. In order to visualize the results, we made a venn diagram using a website. In order to visualize the results, we made a venn diagram using a website (http://bioinformatics.psb.ugent.be). Under the premise that the disease is glioma, we analyzed the correlation between TMED3 expression and miRNA using the starbase database (https://starbase.sysu.edu.cn/panCancer.php). Two miRNAs not recorded in the database were discarded. We found a significant negative correlation between TMED3 and five predicted miRNAs and a positive correlation with seven predicted miRNAs. There were no statistical expression relationships between TMED3 and the other 29 predicted miRNAs. (Figure 4 A-C) Based on the mechanism of miRNA controlling target gene expression, there should be a negative association between miRNA and SEMA3F. Finally, we focused on miRNAs that were adversely associated with TMED3 and their prognostic value in glioma. (Figure 4 D-H)The up-regulation of hsa-miR-1296-5p was positively correlated with the prognosis of the patient. All of these data points to miR-1296-5p as the most likely TMED3 regulating miRNA in glioma.

Relationship between TMED3 and immune cell infiltration in glioma

Immune cell infiltration has been identified as a prognostic biomarker in several cancers. ⁸We observed significant changes in immunocyte infiltration levels in gliomas at different TMED3 copies through the SCNA module of the TIMER database, comparing the infiltration levels of each SCNA category to normal using a two-sided Wilcoxon rank sum test. Following that, we investigate the relationship between TMED3 expression and different amounts of immune cell infiltration in glioma. As shown in figures 5, in glioblastoma, the expression level of TMED3 is significantly positively correlated with CD4+ T cells and dendritic cells. Furthermore, the expression level of TMED3 and the levels of CD8+ T cells was positively correlated in low-grade glioma. Moreover, tumor purity is linked to clinical characteristics, genomic expression, and biological properties of tumor patients. We discovered that the purity values of LGG and GBM are diametrically opposed, which might explain why their biological properties are so dissimilar.

Relationship between TMED3 and immune checkpoints in glioma

Checkpoint therapy (ICT) is a novel treatment for malignant tumors that improves the anti-tumor immune response of T cells and hence has a high curative efficacy. ⁹To further understand the potential carcinogenic effects of TMED3 in gliomas, we evaluated the relationship of TMED3 to immune checkpoints. As shown in Figure 6, TMED3 was found to be positively correlated with most immune checkpoints, with CD276, VEGFB, ARG1, HMGB1, CX3CL1, and ICOSLG all showing significant differences in low-grade gliomas and glioblastomas. All these have provided new ideas for the development of glioma immune checkpoint inhibitors.

Molecular experimental verification

For protein blotting and PCR investigations, we utilized this kit to extract protein and RNA from normal brain tissue cells (HEB) and glioma cell lines (T98G, U118, and U251). After that, PS software was used to process the western blot data, and Graphpad prism8 was used to analyze the RT-PCR results. As shown in Fingure 7, TMED3 is overexpressed in gliomas as compared to normal brain tissue.

Glioma is an internal brain tumor that originates from glial cell progenitor cells, accounting for 81% of malignant brain tumors. Conventional therapies, including surgery, chemotherapy, and radiotherapy, have limited improvement in the prognosis of patients with glioma. ¹Secondly, immunotherapy is a cancer treatment revolution that has emerged as a viable technique for penetrating the blood-brain barrier. As a result, improved indicators for immunotherapy and glioma diagnosis are required from a biological standpoint.⁹

TMED3 is involved in the onset and progression of a variety of human malignancies. However, there is currently inadequate data on TMED3 in glioma, which requires additional research. This research is unique because it focuses on p24/transmembrane emp24 domain family proteins, which are rarely studied in immunotherapy.

In this study, the expression of TMED3 in glioma was explored for the first time. First, we downloaded the unified and standardized pan-cancer data set from the UCSC database to conduct pan-cancer analysis on the expression of TMED3, and then further used the TIMER database and Xena Shiny database to verify the expression of TMED3. Secondly, the staging and prognosis of TMED3 and glioma were analyzed. Finally, the results were verified again by cell experiments. We found that TMED3 was highly expressed in gliomas, and it was closely related to tumor stage and prognosis.

MicroRNA is a kind of short non-coding RNA that plays a function in the post-transcriptional control of gene expression and is a potent regulator of numerous cellular processes.¹⁰ To explore the upstream regulatory miRNA of TMED3, we introduced five prediction programs, including Encori, Mirdb, Mirdip, Mirwalk, and Tarbase, to predict miRNA that may bind to TMED3. The relationship between miRNA and TMED3 on the prognosis of glioma was also analyzed, and finally a statistically significant miRNA was obtained. The up-regulation of miR-1296-5p was positively correlated with the prognosis of patients and negatively correlated with the expression of TMED3. MiR-1296-5p has been found to act as a tumor suppressor miRNA in gastric cancer, breast cancer, and osteosarcoma. At present, studies have found that miR-1296-5p can inhibit the proliferation, migration, and invasion of tumors by reducing the expression of target genes.^11–13

Immune cell infiltration can affect the efficacy of chemotherapy, radiotherapy, or immunotherapy as well as the prognosis of cancer patients.¹⁴ Immunotherapy has changed the traditional cancer treatment and revitalized the field of tumor immunology. We hope to explore the mechanism of immune escape from cancer through the analysis of glioma-infiltrating immune cells, thereby providing an opportunity to develop new therapeutic strategies. The results showed that the expression of TMED3 was positively correlated with CD4 T lymphocytes, CD8 T lymphocytes, macrophages, and other different immune cells, indicating that the expression level of TMED3 could reflect the immune state of glioma. On the other hand, we searched into the association between TMED3 and immunological checkpoints, and found that high TMED3 expression was linked to CD276, VEGFB, ARG1, HMGB1, CX3CL1, and ICOSLG in glioma, demonstrating that targeting TMED3 might improve immunotherapy's therapeutic impact in glioblastoma.

The transmembrane emp24 trafficking protein (TMED)

Glioblastoma multiforme (GBM)

Brain Lower Grade Glioma (LGG)

Uterine Corpus Endometrial Carcinoma (UCEC)

Breast invasive carcinoma (BRCA)

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC)

Lung adenocarcinoma (LUAD)

Esophageal carcinoma (ESCA)

Stomach and Esophageal carcinoma (STES)

Kidney renal papillary cell carcinoma (KIRP)

Pan-kidney cohort (KIPAN)

Colon adenocarcinoma (COAD)

Colon adenocarcinoma/Rectum adenocarcinoma Esophageal carcinoma (COADREAD)

Prostate adenocarcinoma (PRAD)

Prostate adenocarcinoma (STAD)

Kidney renal clear cell carcinoma (KIRC)

Lung squamous cell carcinoma (LUSC)

Liver hepatocellular carcinoma (LIHC)

Skin Cutaneous Melanoma (SKCM)

Bladder Urothelial Carcinoma (BLCA)

Thyroid carcinoma (THCA)

Ovarian serous cystadenocarcinoma (OV)

Pancreatic adenocarcinoma (PAAD)

Testicular Germ Cell Tumors (TGCT)

Uterine Carcinosarcoma (UCS)

Acute Lymphoblastic Leukemia (ALL)

Acute Myeloid Leukemia （LAML）

Pheochromocytoma and Paraganglioma (PCPG)

Adrenocortical Carcinoma (ACC)

Cholangiocarcinoma (CHOL)

a Head and Neck squamous cell carcinoma （HNSC）

High-Risk Wilms Tumor (WT).

Rectum adenocarcinoma (READ)

Kidney Chromophobe (KICH)

Overall Survival (OS)

Disease-specific Survival (DSS)

Disease-specific Survival (DFI)

Progression-free Interval (PFI)

MicroRNA (miRNA)

Checkpoint therapy (ICT)

Conflict of interest.

All authors certify that ther have no conflicts of interest.

Ethical approval:

This article does not include any research on human participants conducted by any author.

Credit Author Statement：

Chunliang-Wang conceived the study. Gang-Liao and Meimei-Zhang performed database search and analysis, and experimental verification. Chunliang-Wang wrote the manuscript. All authors participated in the biological analysis, interpretation of the results, reading and approval of the final version of the manuscript.

Funding

This work was supported by the scientific program of Science and Technology Plan of Jiangxi Provincial Health Department (202130174), National Natural Science Foundation (81760448).

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No competing interests reported.

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Analysis and Validation of TMED3 correlates with poor prognosis and tumor immune infiltration of glioma

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