Home The expression of ASAP3 and NOTCH3 and the clinicopathological characteristics of adult glioma patients
Article Open Access

The expression of ASAP3 and NOTCH3 and the clinicopathological characteristics of adult glioma patients

  • Li-ping Su , Min Ji , Li Liu , Wei Sang , Jing Xue , Bo Wang , Hong-Wei Pu EMAIL logo and Wei Zhang EMAIL logo
Published/Copyright: October 31, 2022

Abstract

ASAP3 is involved in a variety of biological activities, including cancer progression in humans. In adult glioma, we explore the effects of ASAP3 and NOTCH3 and their relationships on prognosis. The Oncomine, TIMER, and Gene Expression Profiling Interactive Analysis databases were used to investigate ASAP3 expression. Immunohistochemistry was used to assess the levels of ASAP3 and NOTCH3 expressions. The effects of ASAP3 and NOTCH3 on prognosis were assessed using survival analysis. The results revealed that the amount of ASAP3 mRNA in gliomas was much higher than in normal tissue (P < 0.01). Glioma patients with high ASAP3 mRNA expression had a worse overall survival and progression-free survival. ASAP3 overexpression is directly associated with the NOTCH signaling system. Immunohistochemistry revealed that ASAP3 and NOTCH3 were overexpressed in glioblastomas (GBMs). ASAP3 expression was associated with age, recurrence, tumor resection, postoperative chemoradiotherapy, World Health Organization (WHO) grade, and Ki-67 expression. ASAP3 expression was related to the isocitrate dehydrogenase-1 mutation in low-grade glioma. Gender, local recurrence, tumor resection, postoperative radio-chemotherapy, WHO grade, recurrence, and ATRX expression were all associated with NOTCH3 expression. ASAP3 was shown to be positively associated with NOTCH3 (r = 0.337, P = 0.000). Therefore, ASAP3 and NOTCH3 as oncogene factors have the potential to be prognostic biomarkers and therapeutic targets in adult glioma.

1 Introduction

Adult diffuse glioma is the most prevalent malignant brain tumor, accounting for over 80% of all malignant brain and central nervous system (CNS) cancers. Glioma is an aggressive and lethal solid tumor generated by glial cells and among the most prevalent malignant tumors in the brain [1]. According to epidemiological statistics, glioblastomas (GBMs) are malignant tumors, which account for 30% of CNS tumors and 80% of malignant brain tumors in the whole world [2]. Glioma is a refractory solid tumor that is resistant to chemo and radiotherapy. Although combination therapy has improved the prognosis of adult glioma, the prognosis of adult glioma remains dismal, with a median survival of 14–16 months. Following the World Health Organization's (WHO) reclassification of CNS tumors in 2021, a new diagnostic concept was adopted, combining tumor histology and molecular genetics, such as isocitrate dehydrogenase (IDH) mutations and 1P/19Q co-deletion states, TRET, Alpha Thalassemia/Mental Retardation Syndrome X-Linked (ATRX), and morphologic changes, to form a more accurate diagnosis [3]. Patients who were graded as 2–3 low-grade glioma (LGG) survived for more than 10 years before developing highly invasive grade glioma due to aberrant activation of several oncogenes and signaling pathways [4]. With the advancement of genomics and bioinformatics databases, the cancer genome atlas (TCGA), Oncomine, and TIMER data sites have been promoted to deeply understand the genomes of glioma occurrence and progression, and targeted gene therapy is emerging as a promising glioma-accurate drug treatment strategy. However, the intricacy of the signaling pathways involved in gliomagenesis raises confusion regarding the optimal target and limits the utility of targeted treatment in glioma. The processes that cause glioma cell invasion are mostly unknown. Further understanding the mechanism of the malignant invasion and molecular targeted therapy of glioma can lay a theoretical foundation for finding effective biomarkers and potential carcinogenic pathways to fight against this invasive tumor.

ASAP3, also known as ACAP4, is a GTPase-activating protein (GAP) for the ADP-ribosylation factor 6 (ARF6) and possesses the BAR, PH, ankyrin repeat, and GAP domains. Okabe et al. initially identified it as a development and differentiation enhancing factor (called DDEFL1) and demonstrated that it promoted the proliferation of hepatocellular carcinoma cells [5]. Given that DDEFL1 and ACAPs family proteins share a similar domain structure organization and substrate, DDEFL1 was renamed ACAP4 and found to be a particular GAP protein for ARF6 and a critical participant in cell migration [6]. ASAP3 expression is minimal or nonexistent in normal epithelia, but it has been reported to be significantly increased in a variety of human carcinomas, including lung carcinomas, colon cancers, and breast cancers, and ASAP3 expression may contribute to a poor clinical outcome in non-small cell lung carcinoma and colon cancer [7,8,9]. These effects may be attributable to the role of ASAP3 in regulating cell migration and, by extension, cancer cell invasion. Epidermal growth factor (EGF) activation causes EGF receptor (EGFR) kinase to phosphorylate ASAP3 at Tyr34, and CCL18 therapy causes ASAP3 Lys311 to be acetylated. These post-translational changes play a vital role in regulating the localization of ASAP3 at focal adhesions during cell migration [10]. However, the molecular processes underlying ASAP3 overexpression and the role of ASAP3 in glioma progression remain largely unknown. This study is intended to evaluate the potential biological function of ASAP3 in the progression of adult glioma.

The NOTCH signaling pathway is an evolutionarily conserved pathway that is crucial for both normal embryonic development and malignancy. The pathway is also frequently implicated in neoplasia and promotes neoplastic growth in most situations [11]. Notch3 is a component of the signaling cascade, including NOTCH ligands, NOTCH receptors, and transcription factors. The oncogenic function of NOTCH3 has been documented in esophageal cancer [12], ovarian cancer [13], hepatocellular carcinoma [14], and so on. Furthermore, it has been proven that cross-regulation between EGFR and NOTCH3 has long been detected in genetic studies and that, depending on the cellular context, it can be both cooperative and antagonistic [15]. NOTCH3 promotes glioma cell invasion and proliferation through activation of cell cycle protein D1 (CCND1) and EGFR gene expression. Studies have shown that NOTCH3 gene polymorphisms have the potential to be diagnostic and therapeutic biomarkers for gliomas.

Our team has been investigating the glioma molecular mechanism. In our early studies, Ingenuity Pathway Analysis was used to confirm that Notch signaling was activated in GBM with a Z score of 1.342 and P-value of 0.029, and that ASAP3 was activated with a fold change of 1.54 and a P-value of 0.0009. Gene Expression Profiling Interactive Analysis (GEPIA) was used to validate the expression of ASAP3 as well as the correlation of NOTCH signaling pathway proteins in gliomas. Although it has been reported that the expression of ASAP3 is elevated in glioma, its prognostic value and relationship with the expression of the cooperative protein NOTCH3 remain unclear. We intend to investigate the biological function of ASAP3 and its closely related protein NOTCH3, as well as provide new hints for molecularly targeted glioma therapy, by elucidating the expression and clinical significance of ASAP3 in adult glioma.

2 Materials and methods

2.1 Analysis of the expression of ASAP3 in tumors and normal tissues

2.1.1 Tissues in human cancers

The Oncomine database (https://www.oncomine.org/resource/login.html), the TIMER database (https://cistrome.shinyapps.io/timer/), and the GEPIA database (http://gepia2.cancer-pku.cn/#analysis) were utilized to evaluate ASAP3 expression between human tumor and paired normal tissue. The data on tumors and normal tissues are analyzed by the GEPIA database, which is a website. This database looks at the data from the TCGA database.

2.2 The prognostic relevance of ASAP3 in glioma

Using the GEPIA database (http://gepia2.cancer-pku.cn/#analysis), the prognostic significance of ASAP3 expression in glioma was investigated. We examined the relationship between ASAP3 expression and overall survival (OS) and disease-free survival (DFS) in glioma using the GEPIA database. In the GEPIA database, the median ASAP3 expression was applied to classify groups as the cutoff value.

2.3 GSEA identifies ASAP3-associated signaling pathways in glioma

The glioma data, mRNA expression profiles, and survival information for 169 glioma patients were downloaded from the TCGA Genomic Data Commons data portal (https://portal.gc.cancer.gov/repository). GSEA is a computer program that determines if a priori-defined collection of genes exhibits statistically significant differential expression between high expression and low expression groups. Generated datasets and phenotype label files were submitted to the GSEA software. The phenotypes were labeled as ASAP3-high and ASAP3-low. For each analysis, 1,000 permutations of the gene set were performed. Generally regarded as enriched were gene sets with a normal P-value <0.05 and a false discovery rate <0.25.

2.4 Analysis of ASAP3’s interaction network with the NOTCH signaling pathway

The GEPIA database was used to generate a scatter plot and related genes. The GeneMANIA database was used to analyze protein–protein interactions, genetic pathways, and protein co-expression networks in the ASAP3 gene with the NOTCH signaling pathway.

2.5 The function of the ASAP3 gene

WebGestalt is a website that analyses gene function enrichment. WebGestalt analyzed the key genes of the NOTCH signaling pathway that interact with ASAP3 to investigate the involved cell components, biological processes, and biological functions.

2.6 Immunohistochemistry and assessment of the intensity of immunostaining

The Department of Pathology at the First Affiliated Hospital of Xinjiang Medical University constructed tissue microarrays (TMAs), while Shanghai Outdo Biotech Company provided technical support (Shanghai, China). The TMA was built from formalin-fixed paraffin-embedded blocks of 211 adult glioma surgical resections, which were reviewed in each case to confirm the original diagnosis and select the most representative sections using Hematoxylin and Eosin (HE) stained slides. All the surgical resections came from the First Affiliated Hospital of Xinjiang Medical University between July 2010 and November 2020. All glioma biopsies were reviewed by two professional pathologists, and any inconsistent diagnosis was further reviewed by a third professional pathologist in order to reach a final determination.

The gliomas of grades 2 and 3 were classified as LGG, whereas the glioblastoma was classified as GBM. Among all the 211 cases of gliomas, 138 were LGG and 73 were GBM. The detection kit was used for immunostaining (ZSGB-BIO, SP-9001, China). Anti-ASAP3 (SC-365840, 1:100, Santa) and anti-NOTCH3 (ab23426, 1:100, Abcam) antibodies were incubated overnight at 4°C on the sections. All slides were dehydrated and counterstained with diaminobenzidine solution (ZSGB-BIO, ZLI-9017, China) for 2 min and hematoxylin (Solarbio, G1140, China). The intensity of the IHC staining was graded as 0 (no), 1 (weak), 2 (medium), and 3 (strong). The staining extent was graded from 0 to 3 based on the percentage of immune-reactive tumor cells (0–10%, 21–75%, and 76–100%). For each example, a score ranging from 0 to 9 was calculated by multiplying the staining extent score by the staining intensity score, resulting in low (0–4) or high (5–9) staining. ASAP3 staining expresses cytoplasm. NOTCH3 staining revealed the cell membrane and nucleus.

  1. Ethics approval and consent to participate: This study was approved by the ethics committee of the First Affiliated Hospital of Xinjiang Medical University. A Signed written informed consent was obtained from all participants before the study.

2.7 Statistical methods

Statistical analysis was performed using SPSS 26.0 Software (SPSS Inc., Chicago, IL, USA) and GraphPad Prism 8.0 Software (GraphPad Software Inc., San Diego, CA, USA). The χ 2 test and Pearson correlation coefficient were used to examine the expression of ASAP3 and NOTCH3 in adult gliomas. The OS and PFS were analyzed by the Kaplan–Meier method and the log-rank method. The cox proportional risk regression model was used for multivariate analysis. Statistical analysis results with P < 0.05 were considered statistically significant, offering credibility for the above data analysis.

3 Results

3.1 ASAP3 expression levels in different types of human cancers

We determined the expression difference of ASAP3 between tumor tissues and normal tissues through multiple databases. According to the Oncomine database, ASAP3 expression was higher in cervical cancer, colorectal cancer, gastric cancer, kidney cancer, melanoma, and lymphoma tumors in cancer histology. It is also higher in multicancer with Brain and CNS cancer, kidney, melanoma, and breast cancer in some datasets (Figure 1a). The results of the TIMER database analysis showed that ASAP3 expression was significantly higher in GBM (Glioblastoma multiforme), kidney chromophobe (KICH), and liver hepatocellular carcinoma (LIHC) compared with adjacent normal tissues. However, ASAP3 expression was significantly lower in bladder urothelial carcinoma (BLCA), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), head and neck cancer (HNSC), kidney renal clear cell carcinoma (KIRC), lung adenocarcinoma (LUAD), Kidney renal papillary cell carcinoma (KIRP), lung squamous cell carcinoma (LUSC), Pheochromocytoma and Paraganglioma (PCPG), rectum adenocarcinoma (READ), stomach adenocarcinoma (STAD), thyroid carcinoma (THCA), and uterine corpus endometrial carcinoma (UCEC) when compared with adjacent normal tissues (Figure 1b). The results of the GEPIA database analysis were used as supplementary results for cancers without paired normal tissues in the TIMER database. Meanwhile, the results showed that the expression of ASAP3 mRNA was also significantly higher in other cancer types: Lymphoid Neoplasm Diffuse Large B-Cell Lymphoma (DLBC), Brain LGG, and Thymoma (THYM) (Figure 1c). These results suggest that the expression levels of ASAP3 are inconsistent in different tumor tissues, which may be related to the different pathogenesis processes of tumors. However, ASAP3 may be involved in the process of glioma regulation.

Figure 1 
                  ASAP3 expression levels in different types of human cancer. (a) The expression of ASAP3 in different cancers by the Oncomine database; the P-value threshold is set to 0.05, and the fold change requirement is set to 2. (b) The expression of ASAP3 in different cancer types by the TIMER database; *P < 0.05, **P < 0.01, ***P < 0.001. (c) The expression of ASAP3 in several cancers and paired normal tissue by the GEPIA database; *P < 0.05.
Figure 1

ASAP3 expression levels in different types of human cancer. (a) The expression of ASAP3 in different cancers by the Oncomine database; the P-value threshold is set to 0.05, and the fold change requirement is set to 2. (b) The expression of ASAP3 in different cancer types by the TIMER database; *P < 0.05, **P < 0.01, ***P < 0.001. (c) The expression of ASAP3 in several cancers and paired normal tissue by the GEPIA database; *P < 0.05.

3.2 ASAP3 is a prognostic glioma biomarker

We used the GEPIA database to analyze the prognostic value of ASAP3 expression in glioma. We analyzed the correlation between ASAP3 expression levels and the OS and PFS of 676 glioma patients. According to the median expression, the 676 glioma patients were split into the ASAP3 high expression group (n = 338) and the ASAP3 low expression group (n = 338). These results of the GEPIA database showed that higher ASAP3 expression was associated with OS and DFS in gliomas (n = 338, OS: Hazard Ratio (HR) = 1.4, P = 0.018; n = 338, DFS: HR = 1.5, P = 0.0023). This was determined by HR, which is a statistical measure of the likelihood of an event occurring. There was a statistical significance to the results (Figure 2a and b).

Figure 2 
                  Analysis of the expression of ASAP3 in the survival of glioma patients. (a) The expression of ASAP3 in the OS of glioma patients. (b) The expression of ASAP3 in the DFS of glioma patients.
Figure 2

Analysis of the expression of ASAP3 in the survival of glioma patients. (a) The expression of ASAP3 in the OS of glioma patients. (b) The expression of ASAP3 in the DFS of glioma patients.

3.3 GSEA identified signaling pathways associated with ASAP3

On the basis of the TCGA-STAD dataset, we used GSEA to identify biological pathways that may be influenced by ASAP3 in the tumors. Using GSEA (h.all.v6.2.symbols.gmt), significant differences in the enrichment of the MSigDB dataset were discovered. The analysis result displayed that the ASAP3 high expression phenotype was associated with the Rig like receptor signaling pathway (Figure 3a), Inositol phosphate metabolism (Figure 3b), NOTCH signaling pathway (Figure 3c), Adherens junction, Alpha linolenic acid metabolism, Phosphatidylinositol signaling system, ABC transporters, Acute myeloid leukemia, Basal cell carcinoma, Pancreatic cancer, etc. The Ribosome (Figure 3d), Oxidative Phosphorylation (Figure 3e), Parkinson disease (Figure 3f), Alzheimer’s disease, Huntington disease, and Proteasome were differentially associated with the ASAP3 low expression phenotype (Table 1).

Figure 3 
                  Potential downstream signal pathways of ASAP3 are revealed through GSEA analysis. Based on GSEA data results, Rig like receptor signaling pathway (a), Inositol phosphate metabolism (b), and NOTCH signaling pathway (c) were enriched in the high ASAP3 expression group. Ribosome (d), oxidative phosphorylation (e), and Parkinson's disease (f) were enriched in the low ASAP3 expression group. The scores for each gene's enrichment are displayed in the top panels. The lower panels display the ranking metrics for each gene. X-axis: rankings for all genes; Y-axis: values of ranking metrics. NES stands for normalized enrichment score.
Figure 3

Potential downstream signal pathways of ASAP3 are revealed through GSEA analysis. Based on GSEA data results, Rig like receptor signaling pathway (a), Inositol phosphate metabolism (b), and NOTCH signaling pathway (c) were enriched in the high ASAP3 expression group. Ribosome (d), oxidative phosphorylation (e), and Parkinson's disease (f) were enriched in the low ASAP3 expression group. The scores for each gene's enrichment are displayed in the top panels. The lower panels display the ranking metrics for each gene. X-axis: rankings for all genes; Y-axis: values of ranking metrics. NES stands for normalized enrichment score.

Table 1

Results of GSEA analysis based on the expression level of ASAP3 gene

Group Term ES NES NOM P-val
High ASAP3 KEGG_RIG_I_LIKE_RECEPTOR_SIGNALING_PATHWAY 0.46 1.94 0.000
KEGG_INOSITOL_PHOSPHATE_METABOLISM 0.48 1.93 0.000
KEGG_NOTCH_SIGNALING_PATHWAY 0.48 1.89 0.002
KEGG_ADHERENS_JUNCTION 0.44 1.84 0.000
KEGG_ALPHA_LINOLENIC_ACID_METABOLISM 0.58 1.79 0.006
KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 0.4 1.71 0.000
KEGG_ABC_TRANSPORTERS 0.44 1.66 0.004
KEGG_ACUTE_MYELOID_LEUKEMIA 0.41 1.66 0.006
KEGG_BASAL_CELL_CARCINOMA 0.41 1.64 0.002
KEGG_PANCREATIC_CANCER 0.39 1.62 0.009
Low ASAP3 KEGG_RIBOSOME −0.8 −3.44 0.000
KEGG_OXIDATIVE_PHOSPHORYLATION −0.72 −3.26 0.000
KEGG_PARKINSON’S_DISEASE −0.66 −3.02 0.000
KEGG_ALZHEIMER’S_DISEASE −0.58 −2.73 0.000
KEGG_HUNTINGTON_DISEASE −0.57 −2.73 0.000
KEGG_PROTEASOME −0.69 −2.59 0.000
KEGG_CARDIAC_MUSCLE_CONTRACTION −0.56 −2.34 0.000
KEGG_OOCYTE_MEIOSIS −0.43 −1.92 0.000
KEGG_DNA_REPLICATION −0.52 −1.9 0.000
KEGG_CELL_CYCLE −0.41 −1.84 0.000

3.4 Prediction and functional analysis of the ASAP3 protein interaction NOTCH signaling pathway network and GO analysis

Using GeneMANIA analysis, we screened a total of 21 genes interacting with ASAP3 (The core enrichment of GSEA was yes in the NOTCH signaling pathway): DTX3L, NUMBL, NOTCH2, ADAM17, PSEN2, CREBBP, DVL1, EP300, CTBP1, LFNG, MAML2, NCSTN, NUMB, NOTCH1, DVL2, NOTCH3, DVL3, DTX1, DTX4, MAML1, and DTX2. We focused on analyzing the interaction relationship between ASAP3 and NOTCH signaling pathway proteins, where the main components are physical interactions, co-expression, shared protein domains, and co-localization. The results showed the correlation scatter plots for ASAP3 and each gene individually in Figure 4. The interaction network showed that these proteins were found to be mainly engaged in biological regulation, metabolic processes, cellular communication, etc. (Figure 5). Genes associated with ASAP3 may be found in many different parts of the cell, such as the nucleus, membrane-enclosed lumens, and membranes. Among the several molecular roles are protein binding, ion binding, and transferase activity (Figure 6).

Figure 4 
                  Analysis of the correlation between ASAP3 and each gene in the NOTCH signaling pathway.
Figure 4

Analysis of the correlation between ASAP3 and each gene in the NOTCH signaling pathway.

Figure 5 
                  Analysis of ASAP3-interacting proteins by GeneMANIA.
Figure 5

Analysis of ASAP3-interacting proteins by GeneMANIA.

Figure 6 
                  Analysis of ASAP3-related biological processes, cell components, and molecular activities.
Figure 6

Analysis of ASAP3-related biological processes, cell components, and molecular activities.

3.5 Clinicopathologic characteristics of 211 cases of adult glioma

The clinicopathologic characteristics of 211 patients with adult glioma are shown in supplement Table A1. We mainly analyzed the composition of LGG (65.4%; 138/211) and GBM (34.6%; 73/211) in this cohort. The overall cohort's clinical information included tumor size ≥ 3 cm (82.46%; 174/211), total tumor resection (67.3%; 142/211), and no local recurrence (65.4%; 138/211). There were significant differences in age, tumor location, local recurrence, tumor resection, Ki-67 expression, and p53 expression between LGG and GBM patients.

3.6 The protein expression of ASAP3 and NOTCH3 in adult glioma and their relationship with clinicopathological parameters

Immunohistochemistry was used to detect the protein expression of ASAP3, NOTCH3, and their relationship with clinicopathological features in all cohorts in order to study the potential function of ASAP3 and NOTCH3 in the progression of adult glioma (Figure 7). In this cohort, the expression of ASAP3 was found to be high in 123 tumors (58.29%), whereas it was low in 88 tumors (41.71%). The high expression of ASAP3 in GBM (80.82%) suggested that ASAP3 is activated more frequently in the most aggressive and malignant tumors (in Table 2). The results of the statistical analysis showed that ASAP3 expression was related to age, recurrence, tumor resection, postoperative radio-chemotherapy, WHO grade, and Ki-67 expression; however, its expression was not related to gender, ethnicity, tumor size, tumor location, p53 expression, and ATRX expression (Table 3). Meanwhile, the relationship between ASAP3 and 1p19q codeletion in LGG had no statistical significance (P = 0.798). We analyzed the IDH1 mutation status of LGG and found 113 cases of IDH1 mutation (termed IDH1mut) and 25 cases of IDH1 wild type (termed IDH1wt). We detected high ASAP3 expression in 40.71% of IDH1mut (46/113) and 72.00% of IDH1wt (18/25), indicating that ASAP3 was expressed significantly differently between IDH1mut and IDH1wt (P = 0.004). Spearman results revealed the negative relationship between IDH1 mutation and ASAP3 expression (P = 0.004, r = −0.242) (Table 4).

Figure 7 
                  The expressions of ASAP3 and NOTCH3 were detected by immunohistochemistry. (a) Low expression of ASAP3 in LGG. (b) High expression of ASAP3 in LGG. (c) Low expression of ASAP3 in GBM. (d) High expression of ASAP3 in GBM. (e) Low expression of NOTCH3 in LGG. (f) High expression of NOTCH3 in LGG. (g) Low expression of NOTCH3 in GBM. (h) High expression of NOTCH3 in GBM. Magnification ×200.
Figure 7

The expressions of ASAP3 and NOTCH3 were detected by immunohistochemistry. (a) Low expression of ASAP3 in LGG. (b) High expression of ASAP3 in LGG. (c) Low expression of ASAP3 in GBM. (d) High expression of ASAP3 in GBM. (e) Low expression of NOTCH3 in LGG. (f) High expression of NOTCH3 in LGG. (g) Low expression of NOTCH3 in GBM. (h) High expression of NOTCH3 in GBM. Magnification ×200.

Table 2

Staining results of ASAP3 and NOTCH3 on the adult glioma specimens (n = 211)

Antibody Grade Low expression High expression P value
ASAP3 [n (%)] LGG 74 (74/138, 53.62%) 64 (64/138, 46.38%) <0.0001
GBM 14 (14/73, 19.18%) 59 (59/73, 80.82%)
NOTCH3 [n (%)] LGG 83 (83/138, 60.14%) 55 (55/138, 39.86%) <0.0001
GBM 19 (19/73, 26.03%) 54 (58/73, 73.97%)

P values were calculated by Pearson’s χ 2 test (two sided). P < 0.05 indicates statistical significance. LGG, low-grade gliomas; GBM, glioblastoma.

Table 3

Clinicopathological characteristics according to protein expressions of ASAP3 and NOTCH3 in all glioma patients (n = 211)

Clinicopathologic characteristics ASAP3 expression [n (%)] NOTCH3 expression [n (%)]
Low High P-value Low High P-value
Age 0.030* 0.070
 ≤50 59 (50.9%) 57 (49.1%) 55 (47.4%) 61 (52.6%)
 >50 29 (30.5%) 66 (69.5%) 33 (34.7%) 62 (65.3%)
Gender 0.672 0.048*
 Male 53 (43.1%) 70 (56.9%) 44 (35.8%) 79 (64.2%)
 Female 35 (39.8%) 53 (60.2%) 44 (50%) 44 (50%)
Ethnic 0.674 0.532
 Han 51 (43.2%) 67 (56.8%) 49 (41.5%) 69 (58.5%)
 Other 37 (39.8%) 56 (60.2%) 39 (41.9%) 54 (58.1%)
Size of the main lesion 0.513 0.364
 <3 cm 15 (40.5%) 22 (59.5%) 18 (48.6%) 19 (51.4%)
 ≥3 cm 73 (42%) 101 (58%) 70 (40.2%) 104 (59.8%)
Tumor location 0.485 0.889
 Frontal 48 (44.4%) 60 (55.6%) 46 (42.6%) 62 (57.4%)
 Other 40 (38.8%) 63 (61.2%) 42 (40.8%) 61 (59.2%)
Local recurrence 0.000* 0.000*
 No 72 (52.2%) 66 (47.8%) 76 (55.1%) 62 (44.9%)
 Yes 16 (21.9%) 57 (78.1%) 12 (16.4%) 61 (83.6%)
Tumor resection 0.002* 0.025*
 Total resection 70 (49.3%) 72 (50.7%) 67 (47.2%) 75 (52.8%)
 Partial resection 18 (26.1%) 51 (73.9%) 21 (30.4%) 48 (69.6%)
Postoperative radio-chemotherapy 0.026* 0.012*
 No 56 (48.7%) 59 (51.3%) 57 (49.6%) 58 (50.4%)
 Yes 32 (33.3%) 64 (66.7%) 31 (32.3%) 65 (67.7%)
WHO grade 0.000* 0.000*
 II 60 (65.9%) 31 (34.1%) 56 (61.5%) 35 (38.5%)
 III 14 (29.8%) 33 (70.2%) 17 (36.2%) 30 (63.8%)
 IV 14 (19.2%) 59 (80.8%) 15 (20.5%) 58 (79.5%)
Ki-67 expression 0.002* 0.051
 ≤5% 55 (52.4%) 50 (47.6%) 51 (48.6%) 54 (51.4%)
 >5% 33 (31.1%) 73 (68.9%) 37 (34.9%) 69 (65.1%)
P53 expression 0.513 0.516
 ≤5% 53 (41.4%) 75 (58.6%) 50 (39.1%) 78 (60.9%)
 >5% 35 (42.2%) 48 (57.8%) 33 (39.8%) 50 (60.2%)
ATRX expression 0.073 0.003*
 wt 27 (52.9%) 24 (47.1%) 30 (58.8%) 21 (41.2%)
 mut 61 (38.1%) 99 (61.9%) 56 (35%) 104 (65%)

Statistical analyses were performed by the Pearson χ 2 test (two sided). *P < 0.05 was considered statistically significant.

Table 4

The expression of ASAP3 and NOTCH3 in LGG according to the IDH1 gene and 1p19q state

Molecular Profiles ASAP3 r P-value NOTCH3 r P-value
Low High Low High
IDH1 wt 7 (28.00%) 18 (72.00%) −0.242 0.004 11 (44.00%) 14 (56.00%) −0.084 0.328
mut 67 (59.29%) 46 (40.71%) 62 (54.87%) 51 (45.13%)
1p9q codel 27 (55.10%) 22 (44.90%) 0.022 0.798 29 (59.18%) 20 (40.82%) 0.093 0.276
non-codel 47 (52.81%) 42 (47.19%) 44 (49.44%) 45 (50.56%)

P < 0.05 was considered statistically significant. IDH1 indicates isocitrate dehydrogenase 1.

According to the results, there may be a correlation between ASAP3 expression and the molecular subtypes of adult glioma. Meanwhile, NOTCH3 was found to be expressed low in 102 tumors (48.14%) and high in 109 tumors (51.66%). High expression of NOTCH3 was predominant in GBM (73.97%) (Table 2). Statistical analysis showed that NOTCH3 expression was associated with gender, local recurrence, tumor resection, postoperative radiotherapy, WHO classification, and ATRX (P < 0.05). But there was no relationship with age, ethnicity, tumor size, tumor location, P53 expression, and Ki-67 expression in glioma (P > 0.05). There was no statistically significant relationship between NOTCH3 expression and 1p19q codeletion in LGG (P = 0.276). In addition, there was no significant difference in the expression of NOTCH3 between IDH1mut and IDH1wt (P = 0.328) (in Table 4). The above results suggested that the expression of NOTCH3 is not closely related to the molecular subtype of glioma. The correlation between the ASAP3 and NOTCH3 protein markers was clarified by Spearman correlation analysis. The ASAP3 expression was found to be associated with the NOTCH3 expression (r = 0.337; P = 0.000) (in Table 5). In adult glioma, the high expression of NOTCH3 is related to the overexpression of ASAP3. Therefore, ASAP3 and NOTCH3 are interconnected with each other and associated with the development of adult glioma.

Table 5

Relationship between ASAP3 and NOTCH3 expression

Protein Expression ASAP3 [n (%)] r P-value
Low High
NOTCH3 [n (%)] Low 54 (61.36%) 34 (27.64%) 0.337 0.000
High 34 (38.64%) 89 (72.36%)

P values were calculated by Pearson’s correlation test. P < 0.05 indicates statistical significance.

3.7 Prognostic factors for OS and PFS

We constructed univariate and multivariate analyses of OS and PFS in adult glioma patients so that we could evaluate the clinical characteristics of these patients and the prognostic significance of the expression of the ASAP3 and NOTCH3 proteins. Two were lost to follow-up in the 211 cases. The Kaplan–Meier method was used to perform a univariate survival analysis. The following prognostic factors influence the OS in adult glioma (Figure 8a–j): Age, tumor location, local recurrence, tumor resection, WHO grade, Ki-67 expression, ATRX expression, ASAP3 expression, and NOTCH3 expression. Multivariate analysis (Cox’s proportional hazards regression model) showed that the possible independent prognostic factors for OS were as follows: Age, tumor location, local recurrence, tumor resection, WHO grade, Ki-67 expression, and ATRX expression, ASAP3 expression, and NOTCH3 expression (in Table 6).

Figure 8 
                  Kaplan–Meier survival analysis for OS and PFS in adult glioma patients. (a–j) The OS of patients in adult glioma with age (a), tumor location (b), local recurrence (c), tumor resection (d), WHO grade (e), Ki-67 expression (f), ATRX expression (g), ASAP3 expression (h), NOTCH3 expression (i), ASAP3 and Notch3 co-expression (j); P < 0.05. (k–t) The PFS of patients in adult glioma with age (k), tumor location (l), local recurrence (m), tumor resection (n), WHO grade (o), Ki-67 expression (p), ATRX expression (q), ASAP3 expression (r), NOTCH3 expression (s), ASAP3 and Notch3 co-expression (t); P < 0.05.
Figure 8

Kaplan–Meier survival analysis for OS and PFS in adult glioma patients. (a–j) The OS of patients in adult glioma with age (a), tumor location (b), local recurrence (c), tumor resection (d), WHO grade (e), Ki-67 expression (f), ATRX expression (g), ASAP3 expression (h), NOTCH3 expression (i), ASAP3 and Notch3 co-expression (j); P < 0.05. (k–t) The PFS of patients in adult glioma with age (k), tumor location (l), local recurrence (m), tumor resection (n), WHO grade (o), Ki-67 expression (p), ATRX expression (q), ASAP3 expression (r), NOTCH3 expression (s), ASAP3 and Notch3 co-expression (t); P < 0.05.

Table 6

Univariable and multivariable analysis for OS and PFS

Clinicopathologic characteristics OS PFS
Univariate Multivariate Univariate Multivariate
P-value P-value HR (95 % CI) P-value P-value HR (95% CI)
Age <0.0001 <0.0001 3.037 (2.100–4.390) <0.0001 <0.0001 3.132 (2.135–4.596)
≤50 vs >50
Gender 0.276 0.192 0.142
Male vs female
Ethnic 0.556 0.889 0.206
Han vs other
Size of the main lesion 0.899 0.737 0.941
<3 cm vs ≥3 cm
Tumor location 0.016 0.007 1.481 (1.039–2.110) 0.011 0.0046 1.575 (1.084–2.290)
Frontal vs other
Local recurrence <0.0001 <0.0001 3.542 (2.342–5.359) 0.000 <0.0001 3.68 (2.371–5.712)
No vs Yes
Tumor resection 0.000 <0.0001 2.221 (1.486–3.318) 0.000 <0.0001 2.307 (1.514– 3.516)
Total vs partial
Postoperative radio-chemotherapy 0.588 0.655
No vs Yes
WHO grade 0.000 <0.0001 6.28 (3.920–10.06) 0.000 <0.0001 7.046 (4.256–11.66)
LGG vs GBM
Ki-67 expression 0.000 <0.0001 2.541 (1.789–3.609) 0.000 <0.0001 2.702 (1.881–3.880)
≤5% vs >5%
P53 expression 0.328 0.466
≤5% vs >5%
ATRX expression 0.011 0.014 1.739 (1.177–2.567) 0.014 0.0176 1.725 (1.154–2.579)
Wt vs Mut
IDH1 expression <0.0001 <0.0001 5.916 (4.002–8.745) <0.0001 <0.0001 6.438 (4.278–9.688)
Wt vs Mut
ASAP3 expression 0.000 <0.0001 2.065 (1.418–3.007) 0.000 <0.0001 2.044 (1.383–3.021)
Low vs high
NOTCH3 expression 0.000 <0.0001 2.377 (1.666–3.392) 0.000 0.002 1.857 (1.299–2.657)
Low vs high
ASAP3 and NOTCH3 co-expression 0.000 <0.0001 <0.0001
(ASAP3 low + NOTCH3 low vsASAP3 low + Notch3 High vs ASAP3 High + NOTCH3 Low vs ASAP3 High + NOTCH3 High)

P < 0.05 was considered statistically significant.

In univariate survival analysis, Age, tumor location, local recurrence, tumor resection, WHO grade, Ki-67 expression, ATRX expression, ASAP3 expression, and NOTCH3 expression were the significant prognostic factors for PFS in adult gliomas (Figure 8k–t). In multivariate analysis, the prognostic factors were the same as those of OS and ASAP3 expression. Also, NOTCH3 expression was independent of prognostic factors for PFS in adult glioma (in Table 6). In conclusion, we analyzed that the independent factors which can predict short OS and PFS in the adult glioma cohort were >50 years old, frontal location, recurrence, tumor total resection, WHO grade IV, Ki-67 expression >5%, IDH1 expression, and ATRX expression. The high expression of ASAP3 and NOTCH3 could predict the short OS in adult glioma. Therefore, ASAP3 and NOTCH3 may be the potential biomarkers of poor prognosis in adult glioma. According to the results of our study, further analysis of ASAP3 and NOTCH3 co-expression in survival analysis in adult gliomas (in Table 7). In the LGG group, the results showed that patients with high ASAP3 and NOTCH3 co-expression had shorter OS and PFS. For the GBM group, the expression levels of ASAP3 and NOTCH3 were not statistically significant with OS and PFS. In conclusion, there was an inverse relationship between the expression of ASAP3, NOTCH3 as well as ASAP3 and NOTCH3 co-expression with poor OS and DFS in the whole cohort. Cox regression analysis showed that ASAP3 and NOTCH3 could be independent prognostic factors for OS in the LGG group (Figure 9).

Table 7

Kaplan–Meier survival curves of LGG and GBM patients according to the co-expression of ASAP3 and NOTCH3

Protein expression OS PFS
LGG (P-value) GBM (P-value) LGG (P-value) GBM (P-value)
ASAP3 expression
Low expression vs high expression <0.0001 0.2717 <0.0001 0.4321
NOTCH 3 expression
Low expression vs high expression 0.0009 0.7815 0.0023 0.1001
ASAP3 and NOTCH3 co-expression
ASAP3 low NOTCH3 low vs ASAP3 low NOTCH3 high vs ASAP3 high NOTCH3 low vs ASAP3 high NOTCH3 high <0.0001 0.7276 <0.0001 0.519

P values were calculated by Pearson’s correlation test. P < 0.05 indicates statistical significance.

Figure 9 
                  The expression of ASAP3 and NOTCH3 in LGG and their relationship with prognosis. (a) Patients with high ASAP3 expression have a significantly shorter survival time (P < 0.0001). (b) Patients with high NOTCH3 expression have a significantly shorter survival time (P = 0.0009). (c) Patients with high co-expressions of ASAP3 and NOTCH3 have a shorter OS time (P < 0.0001).
Figure 9

The expression of ASAP3 and NOTCH3 in LGG and their relationship with prognosis. (a) Patients with high ASAP3 expression have a significantly shorter survival time (P < 0.0001). (b) Patients with high NOTCH3 expression have a significantly shorter survival time (P = 0.0009). (c) Patients with high co-expressions of ASAP3 and NOTCH3 have a shorter OS time (P < 0.0001).

4 Discussion

Glioma in adults remains a disease for which there are no specific therapy targets or prognostic biomarkers. Studying the special biology of glioma through molecular profiling might contribute to new diagnoses that improve therapeutic efficacy. High-throughput sequencing and microarray hybridization technologies have resulted in the development of a variety of gene databases, which have been widely utilized in gene expression quantitative analysis, giving a strong platform for cancer research. The TCGA database was used to derive ASAP3 expression levels in glioma from the TMA data in the library. The function of ASAP3 in glioma has not been deeply comprehended in recent years, despite a number of studies on the abnormal expression of RNA and proteins in malignancies.

ASAP3 was initially found as a widely upregulated gene that leads to cell proliferation in hepatocellular carcinoma. Then, it was identified as a member of the ArfGAP family, which may be involved in the functional role of cell migration in the invasion of normal tissues by cancer cells [6,7]. Subsequently, Ha et al. revealed that ASAP3 may regulate the filamentous actin of NIH 3T3 cells and perform essential functions in cell migration [16]. ASAP3 is increased in lung and colorectal cancers with metastasis, which promotes the course of malignant disease and indicates poor patient survival [9]. It is possible that ASAP3 is involved in the regulation of cell migration and, as a result, the invasion of cancer cells. In response to EGF stimulation, CrkII recruited ASAP3 to the plasma membrane, where it cooperated with Grb2 and guanine nucleotide exchange factors to promote the recycling of integrin β1 [17]. In addition to regulating EGF-stimulated membrane and cytoskeleton remodeling and the formation of actin-containing stress fibers, ASAP3 plays an essential role in the process of EGF-elicited cell migration and invasion. ASAP3 is phosphorylated at Tyr34 in the BAR domain by EGFR receptor kinase in response to EGF stimulation, and CCL18 therapy induces acetylation of Lys311 in ASAP3. The location of ASAP3 at the focal adhesion during cell migration is determined by these post-translational modifications [10]. The interaction between ASAP3 and EZRIN was thought to be important for acid secretion in gastric parietal cells because it controls the movement of K-ATPase-containing tubulovesicles to the apical plasma membrane [18]. On the contrary, upregulation of ASAP3 also showed a negative effect on the cell adhesion, spreading, and migration on fibronectin. It has been revealed that ASAP3 was unable to bind to invadopodia in breast cancer cells or podosomes in NIH3T3 mouse fibroblasts. In breast cancer cells transfected with plasmids overexpressing active or inactive ASAP3, cellular vinculin or paxillin in focal adhesion and the distribution of invadopodia were not affected. Ha et al. demonstrated that overexpression of ASAP3 or GAP-inactive mutant ASAP3, or ASAP3 knockdown did not affect vinculin or paxillin distribution, suggesting that ASAP3 does not affect focal adhesions in cancerous tissues [16]. MST4 is activated by histamine stimulation, which enhances MST4-ASAP3 interaction. Furthermore, MST4 causes a conformational change in ASAP3, allowing ASAP3 to associate with PKA-phosphorylated EZRIN at the apical membrane of gastric parietal cells [18].

Previous studies have shown that ASAP3 is associated with glioma biology [19]. However, there is scarcely any research that investigates whether or not there is a correlation between the expression of ASAP3 and the prognosis of glioma patients. Through the bioinformatics database, we found that ASAP3 is closely related to the NOTCH signaling pathway. We analyzed the relationship between the expression of ASAP3 and NOTCH3 and the clinicopathological parameters of 211 adult gliomas using TMA. When we compared the expression of ASAP3 in GBM and LGG, we found that the expression of ASAP3 in GBM was much higher. This result indicated a favorable connection between the ASAP3 marker and the glioma grade. Our study demonstrated that the high expression of ASAP3 in gliomas was closely related to age, high WHO grade, recurrence, resection, postoperative radio-chemotherapy, and Ki-67 expression ≥10%, suggesting that ASAP3 was strongly associated with cell proliferation and migration. The high expression rate of ASAP3 in the IDH1 mutant in LGG was greater than that of the IDH1 wild-type patients. According to the findings of a multivariable study of prognosis, patients whose ASAP3 expression was high had a considerably worse probability of PFS and OS than patients whose ASAP3 expression was low. Multivariate prognostic analysis showed that age, tumor site, WHO grade, recurrence, Ki-67 expression, IDH1 mutant, ATRX, ASAP3, and NOTCH3 expression were shown to be independent predictive determinants of overall survival in gliomas. The high expression of ASAP3 was positively correlated with the Ki-67 expression rate ≥10% and the high WHO grade. Ki-67 is a marker of cell proliferation. IDH1 mutation is associated with a good prognosis and can be used as a predictor of survival. ASAP3 expression was found to be different in the IDH1 mutant and wild-type. ASAP3 expression is negatively correlated with IDH1 mutation. Therefore, we speculated that ASAP3 is related to the proliferation and invasion of adult gliomas, and the effect of ASAP3 expression on the prognosis of gliomas may be realized by promoting the proliferation of glioma cells and thus changing the tissue grading to achieve the malignant characteristics of tumors. So, there was no connection between ASAP3 expression and poor OS and PFS in the GBM cohort. Finally, in multivariate analyses between OS and PFS, we determined that ASAP3 expression was an independent predictive factor for OS. Our findings showed that ASAP3 may play a significant role in the aggressiveness and progression of gliomas. Accordingly, ASAP3 may serve as a prognostic indicator and a potential treatment target in adult glioma.

Based on database comparison and literature assessment, the role of the relationship between ASAP3 and NOTCH3 in glioma has attracted the research group's interest among the 21 ASAP3 interacting proteins evaluated in the NOTCH signaling pathway. According to a wide range of studies, NOTCH signaling is involved in regulating biological activity, such as tumor cell adhesion and migration. A wide variety of hematological and solid tumors are associated with the NOTCH signal pathway, which often promotes tumor growth, but it can serve as a tumor suppressor in some cell types [20]. It is still not entirely clear how different NOTCH receptors play a role in the growth of tumors in organisms. The fourmammalian NOTCH paralogs (Notch1–4) are not functionally comparable under all conditions, despite their structural similarities. Studies have shown that binding sites on the promoters of target genes can be linked to different Notch receptors in different ways [20]. The molecular basis for these variances is currently under investigation. Because selectively targeting individual Notch receptors in tumors could reduce treatment side effects, it is important to know which receptor paralogs play key roles in the initial stage and growth of different types of cancer.

Increasing evidence suggests that the NOTCH receptor may be responsible for the development of gliomas. However, the majority of research has focused on the importance of how Notch1-mediated signaling pathways contribute to the development, invasion, and recurrence of glioma tumors. NOTCH3 was recently verified as a prognostic factor in the regulation of biological activity, including tumor cell adhesion, migration, invasion, and survival [21]. NOTCH3 belongs to a family of proteins essential for cellular differentiation in a variety of developing tissues. In tumorigenesis, NOTCH3 has been shown to induce T cell leukemia through the activation of NF-kB. NOTCH3 amplified is associated with worse survival compared to tumors with non-amplified locus for gliomas in Chinese patients [22]. Rutten et al. also found that EGFR and NOTCH signaling have vital functions throughout normal development, and they regularly interact in cooperative and antagonistic manners depending on the cellular context [15]. EGFR opposes NOTCH signaling in various developmental stages, and the NOTCH system can also compensate for hypomorphic alleles of EGFR loss of function mutations in Drosophila. Genetic studies demonstrate that EGFR and NOTCH signaling pathways interact complexly. For instance, blocking the epidermal growth factor receptor leads to an increase in the number of lung cancer stem cells that are dependent on NOTCH signaling [23]. EGFR and LIN-12/NOTCH have conflicting impacts on cell fate determination in C. elegans vulva development. The combination of Notch inhibitors with EGFR inhibitors, gefitinib or osimertinib, was found to be effective in EGFR tyrosine kinase inhibitor-resistant lung cancer [24]. NOTCH1 and EGFR have been demonstrated to have antagonistic effects in skin cancer, where suppression of EGFR results in enhanced differentiation of squamous cell carcinoma cells and increased resistance to apoptosis. These results provide additional support for the combined targeting of EGFR and NOTCH3 signaling to inhibit tumor development. Using bioinformatics and functional tests, it was revealed that the NOTCH pathway is significantly associated with increased ASAP3 expression in the TCGA GBM cohort (NES = 1.89; P = 0.002).

NOTCH3 is a NOTCH family member that promotes glioma proliferation and invasion [21]. Our studies showed that high NOTCH3 expression in adult gliomas was related to several factors, including gender, recurrence, tumor resection by surgery or resection, postoperative radio-chemotherapy, higher WHO grade, Ki-67 expression ≥10%, and ATRX expression. Patients with high NOTCH3 expression showed substantially shorter PFS and OS than patients with low NOTCH3 expression, indicating that it may emerge as a crucial driver for the malignant development of glioma in a univariate prognostic analysis. Glioma treatment research is now focused on trying to gain a better understanding of the precise processes that are involved in the NOTCH3 pathway. The chromatin remodeler protein ATRX is frequently mutated in H3F3A-mutant pediatric glioblastoma and IDH-mutant grade 2/3 adult glioma [25]. ATRX mutation affects DNA damage repair to render these cells more amenable to therapy, which may contribute to the survival advantage of glioma patients with ATRX mutations. NOTCH3 expression was also detected in the majority of vascular endothelial cells associated with tumors, which may facilitate tumor angiogenesis.

ASAP3 may be combined with EGFR to arouse NOTCH3 expression to promote adult glioma proliferation and invasion. We demonstrated for the first time that ASAP3 and NOTCH3 are substantially associated in human glioma samples. The expression of ASAP3 was an independent prognostic factor for the OS of glioma, and the expression of ASAP3 was positively correlated with that of NOTCH3 and Ki-67 expression rate. We speculated that ASAP3, as an upstream factor of the NOTCH3 signaling pathway, may promote glioma proliferation by regulating the expression of NOTCH3, thus affecting the development and prognosis of glioma. Meanwhile, ASAP3 and NOTCH3 co-expression correlated with poorer OS and PFS in glioma patients. These results suggest that ASAP3 may cooperate with NOTCH3 in the malignant progression of glioma. ASAP3 and NOTCH3 co-expression may be a reliable prognostic biomarker. Inhibiting ASAP3 and NOTCH3 co-expression may improve the prognosis of glioma patients. However, due to the single experimental method in this study, the mechanism of ASAP3 in glioma through regulation of the NOTCH3 signaling pathway needs to be further verified at the cellular level and in animal models so as to further confirm the mechanism of ASAP3 in glioma. Future studies on the molecular interaction of ASAP3 and its potential role in the development of glioma will be helpful for a better understanding of the development of this malignant tumor and the clinical tactics of therapy.


# Equal contributors and co-first authors.


Acknowledgments

Not applicable.

  1. Funding information: The present study was supported by State Key Laboratory of Pathogenesis, Prevention and Treatment of Central Asian High Incidence Diseases Fund (Grant no. SKL-HIDCA-2022-JZ7 and SKL-HIDCA-2018-28) and the Natural Science Foundation of Xinjiang Uyghur Autonomous Region (Grant no. 2020D01C135 and 2020D01C257).

  2. Author contributions: All authors participated in the preparation of the manuscript. W.Z. and H.W.P. conceived and designed the study. L.P.S. and W.S. conducted the research. L.L. and J.J. standardized the procedure for sequence search. J.X. contributed to data analysis and revised the manuscript. L.P.S. wrote the first draft of the manuscript. All authors read and approved the final version of the manuscript.

  3. Conflict of interest: The authors declare no competing interest.

  4. Data availability statement: The datasets used during the current study are available from the corresponding author on reasonable request.

Appendix

Table A1

Clinicopathological characteristics in 211 patients with adult glioma

Clinicopathologic characteristics Total (N = 211) LGG (n = 138) GBM (n = 73) P-value
n (%)
Age
 ≤50 116 (116/211, 54.98%) 95 (68.84%) 21 (28.77%) <0.0001*
 >50 95 (95/211, 45.02%) 43 (31.16%) 52 (71.23%)
Gender
 Male 123 (123/211, 58.29%) 59 (42.75%) 44 (60.27%) 0.0154
 Female 88 (88/211, 41.71%) 79 (57.25%) 29 (39.73%)
Ethnic
 Han 118 (118/211, 55.92%) 76 (55.07%) 42 (57.53%) 0.7319
 Other 93 (93/211, 44.08%) 62 (44.93%) 31 (42.47%)
Size of the main lesion
 <3 cm 37 (37/211, 17.05%) 24 (17.39%) 13 (17.81%) 0.9396
 ≥3 cm 174 (174/211, 82.46%) 114 (82.61%) 60 (43.48%)
Tumor location
 Frontal 108 (108/211, 51.18%) 84 (60.87%) 24 (32.88%) 0.0001*
 Other 103 (103/211, 48.82%) 54 (39.13%) 49 (67.12%)
Local recurrence
 No 138 (138/211, 65.41%) 118 (85.51%) 20 (27.40%) <0.0001*
 Yes 73 (73/211, 34.59%) 20 (14.49%) 53 (72.60%)
Tumor resection
 Total resection 142 (142/211, 67.30%) 114 (82.61%) 28 (38.36%) <0.0001*
 Partial resection 69 (69/211, 32.70%) 24 (17.39%) 45 (61.64%)
Postoperative radio-chemotherapy
 No 115 (115/211, 54.50%) 78 (56.52%) 37 (50.68%) 0.418
 Yes 96 (96/211, 45.50%) 60 (43.48%) 36 (49.32%)
Ki-67 expression
 ≤5% 105 (105/211, 49.76%) 80 (57.97%) 25 (34.25%) 0.001*
 >5% 106 (106/211, 50.24%) 58 (42.03%) 48 (65.75%)
P53 expression
 ≤5% 128 (128/211, 60.66%) 92 (66.67%) 36 (49.32%) 0.0141*
 >5% 83 (83/211, 39.34%) 46 (33.33%) 37 (50.68%)
ATRX expression
 wt 51 (51/211, 24.17%) 39 (28.26%) 12 (16.44%)
 mut 160 (160/211, 75.83%) 99 (71.74%) 61 (83.56%) 0.0564

Statistical analyses were performed by the Pearson χ 2 test. *P < 0.05 was considered statistically significant. GBM indicates glioblastoma; LGG, indicates lower grade glioma.

References

[1] Hu T, Xi J. Identification of COX5B as a novel biomarker in high-grade glioma patients. Onco Targets Ther. 2017;10:5463–70. 10.2147/OTT.S139243.Search in Google Scholar PubMed PubMed Central

[2] Song X, Zhang N, Han P, Moon BS, Lai RK, Wang K, et al. Circular RNA profile in gliomas revealed by identification tool UROBORUS. Nucleic Acids Res. 2016;44(9):e87. 10.1093/nar/gkw075.Search in Google Scholar PubMed PubMed Central

[3] Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol. 2021;23(8):1231–51. 10.1093/neuonc/noab106.Search in Google Scholar PubMed PubMed Central

[4] Gusyatiner O, Hegi ME. Glioma epigenetics: From subclassification to novel treatment options. Semin Cancer Biol. 2018;51:50–8. 10.1016/j.semcancer.Search in Google Scholar

[5] Okabe H, Furukawa Y, Kato T, Hasegawa S, Yamaoka Y, Nakamura Y. Isolation of development and differentiation enhancing factor-like 1 (DDEFL1) as a drug target for hepatocellular carcinomas. Int J Oncol. 2004;24(1):43–8. 10.3892/ijo.24.1.43.Search in Google Scholar

[6] Fang Z, Miao Y, Ding X, Deng H, Liu S, Wang F, et al. Proteomic identification and functional characterization of a novel ARF6 GTPase-activating protein, ACAP4. Mol Cell Proteom. 2006;5(8):1437–49. 10.1074/mcp.M600050-MCP200.Search in Google Scholar PubMed

[7] Fan C, Tian Y, Miao Y, Lin X, Zhang X, Jiang G, et al. ASAP3 expression in non-small cell lung cancer: association with cancer development and patients' clinical outcome. Tumour Biol. 2014;35(2):1489–94. 10.1007/s13277-013-1205-1.Search in Google Scholar PubMed

[8] Song X, Liu W, Yuan X, Jiang J, Wang W, Mullen M, et al. Acetylation of ACAP4 regulates CCL18-elicited breast cancer cell migration and invasion. J Mol Cell Biol. 2018;10(6):559–72. 10.1093/jmcb/mjy058.Search in Google Scholar PubMed PubMed Central

[9] Tian H, Qian J, Ai L, Li Y, Su W, Kong XM, et al. Upregulation of ASAP3 contributes to colorectal carcinogenesis and indicates poor survival outcome. Cancer Sci. 2017;108(8):1544–55. 10.1111/cas.13281.Search in Google Scholar PubMed PubMed Central

[10] Zhao X, Wang D, Liu X, Liu L, Song Z, Zhu T, et al. Phosphorylation of the Bin, Amphiphysin, and RSV161/167 (BAR) domain of ACAP4 regulates membrane tubulation. Proc Natl Acad Sci U S A. 2013;110(27):11023–8. 10.1073/pnas.1217727110.Search in Google Scholar PubMed PubMed Central

[11] Monticone G, Miele L. Notch pathway: a journey from notching phenotypes to cancer immunotherapy. Adv Exp Med Biol. 2021;1287:201–22. 10.1007/978-3-030-55031-8_13.Search in Google Scholar PubMed

[12] Matsuura N, Tanaka K, Yamasaki M, Yamashita K, Saito T, Makino T, et al. NOTCH3 limits the epithelial-mesenchymal transition and predicts a favorable clinical outcome in esophageal cancer. Cancer Med. 2021;10(12):3986–96. 10.1002/cam4.3933.Search in Google Scholar PubMed PubMed Central

[13] Pei Y, Li K, Lou X, Wu Y, Dong X, Wang W, et al. miR-1299/NOTCH3/TUG1 feedback loop contributes to the malignant proliferation of ovarian cancer. Oncol Rep. 2020;44(2):438–48. 10.3892/or.2020.7623.Search in Google Scholar PubMed PubMed Central

[14] Bao L, Wang M, Fan Q. Hsa_circ_NOTCH3 regulates ZNF146 through sponge adsorption of miR-875-5p to promote tumorigenesis of hepatocellular carcinoma. J Gastrointest Oncol. 2021;12(5):2388–402. 10.21037/jgo-21-567.Search in Google Scholar PubMed PubMed Central

[15] Rutten JW, Van Eijsden BJ, Duering M, Jouvent E, Opherk C, Pantoni L, et al. Correction: The effect of NOTCH3 pathogenic variant position on CADASIL disease severity: NOTCH3 EGFr 1-6 pathogenic variants are associated with a more severe phenotype and lower survival compared with EGFr 7-34 pathogenic variant. Genet Med. 2019;21(8):1895. 10.1038/s41436-018-0306-z.Search in Google Scholar PubMed PubMed Central

[16] Ha VL, Bharti S, Inoue H, Vass WC, Campa F, Nie Z, et al. ASAP3 is a focal adhesion-associated Arf GAP that functions in cell migration and invasion. J Biol Chem. 2008;283(22):14915–26. 10.1074/jbc.M709717200.Search in Google Scholar PubMed PubMed Central

[17] Song X, Xu W, Xu G, Kong S, Ding L, Xiao J, et al. ACAP4 interacts with CrkII to promote the recycling of integrin β1. Biochem Biophys Res Commun. 2019;516(1):8–14. 10.1016/j.bbrc.2019.05.173.Search in Google Scholar PubMed

[18] Yuan X, Yao PY, Jiang J, Zhang Y, Su Z, Yao W, et al. MST4 kinase phosphorylates ACAP4 protein to orchestrate apical membrane remodeling during gastric acid secretion. J Biol Chem. 2017;292(39):16174–87. 10.1074/jbc.M117.808212.Search in Google Scholar PubMed PubMed Central

[19] Song Y, Shao L, Xue Y, Ruan X, Liu X, Yang C, et al. Inhibition of the aberrant A1CF-FAM224A-miR-590-3p-ZNF143 positive feedback loop attenuated malignant biological behaviors of glioma cells. J Exp Clin Cancer Res. 2019;38(1):248. 10.1186/s13046-019-1200-5.Search in Google Scholar PubMed PubMed Central

[20] Aster JC, Pear WS, Blacklow SC. The varied roles of notch in cancer. Annu Rev Pathol. 2017;12:245–75. 10.1146/annurev-pathol-052016-100127.Search in Google Scholar PubMed PubMed Central

[21] Ulasov IV, Mijanovic O, Savchuk S, Gonzalez-Buendia E, Sonabend A, Xiao T, et al. TMZ regulates GBM stemness via MMP14-DLL4-Notch3 pathway. Int J Cancer. 2020;146(8):2218–28. 10.1002/ijc.32636.Search in Google Scholar PubMed

[22] Shen Z, Hou X, Chen B, Chen P, Zhang Q. NOTCH3 gene polymorphism is associated with the prognosis of gliomas in Chinese patients. Med (Baltim). 2015;94(9):e482. 10.1097/MD.0000000000000482.Search in Google Scholar PubMed PubMed Central

[23] Arasada RR, Amann JM, Rahman MA, Huppert SS, Carbone DP. EGFR blockade enriches for lung cancer stem-like cells through Notch3-dependent signaling. Cancer Res. 2014;74(19):5572–84. 10.1158/0008-5472.CAN-13-3724.Search in Google Scholar PubMed PubMed Central

[24] Bousquet Mur E, Bernardo S, Papon L, Mancini M, Fabbrizio E, Goussard M, et al. Notch inhibition overcomes resistance to tyrosine kinase inhibitors in EGFR-driven lung adenocarcinoma. J Clin Invest. 2020;130(2):612–24. 10.1172/JCI126896.Search in Google Scholar PubMed PubMed Central

[25] Qin T, Mullan B, Ravindran R, Messinger D, Siada R, Cummings JR, et al. ATRX loss in glioma results in dysregulation of cell-cycle phase transition and ATM inhibitor radio-sensitization. Cell Rep. 2022;38(2):110216. 10.1016/j.celrep.2021.110216.Search in Google Scholar PubMed PubMed Central

Received: 2022-06-17
Revised: 2022-09-28
Accepted: 2022-09-28
Published Online: 2022-10-31

© 2022 Li-ping Su et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Research Articles
  2. AMBRA1 attenuates the proliferation of uveal melanoma cells
  3. A ceRNA network mediated by LINC00475 in papillary thyroid carcinoma
  4. Differences in complications between hepatitis B-related cirrhosis and alcohol-related cirrhosis
  5. Effect of gestational diabetes mellitus on lipid profile: A systematic review and meta-analysis
  6. Long noncoding RNA NR2F1-AS1 stimulates the tumorigenic behavior of non-small cell lung cancer cells by sponging miR-363-3p to increase SOX4
  7. Promising novel biomarkers and candidate small-molecule drugs for lung adenocarcinoma: Evidence from bioinformatics analysis of high-throughput data
  8. Plasmapheresis: Is it a potential alternative treatment for chronic urticaria?
  9. The biomarkers of key miRNAs and gene targets associated with extranodal NK/T-cell lymphoma
  10. Gene signature to predict prognostic survival of hepatocellular carcinoma
  11. Effects of miRNA-199a-5p on cell proliferation and apoptosis of uterine leiomyoma by targeting MED12
  12. Does diabetes affect paraneoplastic thrombocytosis in colorectal cancer?
  13. Is there any effect on imprinted genes H19, PEG3, and SNRPN during AOA?
  14. Leptin and PCSK9 concentrations are associated with vascular endothelial cytokines in patients with stable coronary heart disease
  15. Pericentric inversion of chromosome 6 and male fertility problems
  16. Staple line reinforcement with nebulized cyanoacrylate glue in laparoscopic sleeve gastrectomy: A propensity score-matched study
  17. Retrospective analysis of crescent score in clinical prognosis of IgA nephropathy
  18. Expression of DNM3 is associated with good outcome in colorectal cancer
  19. Activation of SphK2 contributes to adipocyte-induced EOC cell proliferation
  20. CRRT influences PICCO measurements in febrile critically ill patients
  21. SLCO4A1-AS1 mediates pancreatic cancer development via miR-4673/KIF21B axis
  22. lncRNA ACTA2-AS1 inhibits malignant phenotypes of gastric cancer cells
  23. circ_AKT3 knockdown suppresses cisplatin resistance in gastric cancer
  24. Prognostic value of nicotinamide N-methyltransferase in human cancers: Evidence from a meta-analysis and database validation
  25. GPC2 deficiency inhibits cell growth and metastasis in colon adenocarcinoma
  26. A pan-cancer analysis of the oncogenic role of Holliday junction recognition protein in human tumors
  27. Radiation increases COL1A1, COL3A1, and COL1A2 expression in breast cancer
  28. Association between preventable risk factors and metabolic syndrome
  29. miR-29c-5p knockdown reduces inflammation and blood–brain barrier disruption by upregulating LRP6
  30. Cardiac contractility modulation ameliorates myocardial metabolic remodeling in a rabbit model of chronic heart failure through activation of AMPK and PPAR-α pathway
  31. Quercitrin protects human bronchial epithelial cells from oxidative damage
  32. Smurf2 suppresses the metastasis of hepatocellular carcinoma via ubiquitin degradation of Smad2
  33. circRNA_0001679/miR-338-3p/DUSP16 axis aggravates acute lung injury
  34. Sonoclot’s usefulness in prediction of cardiopulmonary arrest prognosis: A proof of concept study
  35. Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation
  36. Decreased expression of miR-195 mediated by hypermethylation promotes osteosarcoma
  37. LMO3 promotes proliferation and metastasis of papillary thyroid carcinoma cells by regulating LIMK1-mediated cofilin and the β-catenin pathway
  38. Cx43 upregulation in HUVECs under stretch via TGF-β1 and cytoskeletal network
  39. Evaluation of menstrual irregularities after COVID-19 vaccination: Results of the MECOVAC survey
  40. Histopathologic findings on removed stomach after sleeve gastrectomy. Do they influence the outcome?
  41. Analysis of the expression and prognostic value of MT1-MMP, β1-integrin and YAP1 in glioma
  42. Optimal diagnosis of the skin cancer using a hybrid deep neural network and grasshopper optimization algorithm
  43. miR-223-3p alleviates TGF-β-induced epithelial-mesenchymal transition and extracellular matrix deposition by targeting SP3 in endometrial epithelial cells
  44. Clinical value of SIRT1 as a prognostic biomarker in esophageal squamous cell carcinoma, a systematic meta-analysis
  45. circ_0020123 promotes cell proliferation and migration in lung adenocarcinoma via PDZD8
  46. miR-22-5p regulates the self-renewal of spermatogonial stem cells by targeting EZH2
  47. hsa-miR-340-5p inhibits epithelial–mesenchymal transition in endometriosis by targeting MAP3K2 and inactivating MAPK/ERK signaling
  48. circ_0085296 inhibits the biological functions of trophoblast cells to promote the progression of preeclampsia via the miR-942-5p/THBS2 network
  49. TCD hemodynamics findings in the subacute phase of anterior circulation stroke patients treated with mechanical thrombectomy
  50. Development of a risk-stratification scoring system for predicting risk of breast cancer based on non-alcoholic fatty liver disease, non-alcoholic fatty pancreas disease, and uric acid
  51. Tollip promotes hepatocellular carcinoma progression via PI3K/AKT pathway
  52. circ_0062491 alleviates periodontitis via the miR-142-5p/IGF1 axis
  53. Human amniotic fluid as a source of stem cells
  54. lncRNA NONRATT013819.2 promotes transforming growth factor-β1-induced myofibroblastic transition of hepatic stellate cells by miR24-3p/lox
  55. NORAD modulates miR-30c-5p-LDHA to protect lung endothelial cells damage
  56. Idiopathic pulmonary fibrosis telemedicine management during COVID-19 outbreak
  57. Risk factors for adverse drug reactions associated with clopidogrel therapy
  58. Serum zinc associated with immunity and inflammatory markers in Covid-19
  59. The relationship between night shift work and breast cancer incidence: A systematic review and meta-analysis of observational studies
  60. LncRNA expression in idiopathic achalasia: New insight and preliminary exploration into pathogenesis
  61. Notoginsenoside R1 alleviates spinal cord injury through the miR-301a/KLF7 axis to activate Wnt/β-catenin pathway
  62. Moscatilin suppresses the inflammation from macrophages and T cells
  63. Zoledronate promotes ECM degradation and apoptosis via Wnt/β-catenin
  64. Epithelial-mesenchymal transition-related genes in coronary artery disease
  65. The effect evaluation of traditional vaginal surgery and transvaginal mesh surgery for severe pelvic organ prolapse: 5 years follow-up
  66. Repeated partial splenic artery embolization for hypersplenism improves platelet count
  67. Low expression of miR-27b in serum exosomes of non-small cell lung cancer facilitates its progression by affecting EGFR
  68. Exosomal hsa_circ_0000519 modulates the NSCLC cell growth and metastasis via miR-1258/RHOV axis
  69. miR-455-5p enhances 5-fluorouracil sensitivity in colorectal cancer cells by targeting PIK3R1 and DEPDC1
  70. The effect of tranexamic acid on the reduction of intraoperative and postoperative blood loss and thromboembolic risk in patients with hip fracture
  71. Isocitrate dehydrogenase 1 mutation in cholangiocarcinoma impairs tumor progression by sensitizing cells to ferroptosis
  72. Artemisinin protects against cerebral ischemia and reperfusion injury via inhibiting the NF-κB pathway
  73. A 16-gene signature associated with homologous recombination deficiency for prognosis prediction in patients with triple-negative breast cancer
  74. Lidocaine ameliorates chronic constriction injury-induced neuropathic pain through regulating M1/M2 microglia polarization
  75. MicroRNA 322-5p reduced neuronal inflammation via the TLR4/TRAF6/NF-κB axis in a rat epilepsy model
  76. miR-1273h-5p suppresses CXCL12 expression and inhibits gastric cancer cell invasion and metastasis
  77. Clinical characteristics of pneumonia patients of long course of illness infected with SARS-CoV-2
  78. circRNF20 aggravates the malignancy of retinoblastoma depending on the regulation of miR-132-3p/PAX6 axis
  79. Linezolid for resistant Gram-positive bacterial infections in children under 12 years: A meta-analysis
  80. Rack1 regulates pro-inflammatory cytokines by NF-κB in diabetic nephropathy
  81. Comprehensive analysis of molecular mechanism and a novel prognostic signature based on small nuclear RNA biomarkers in gastric cancer patients
  82. Smog and risk of maternal and fetal birth outcomes: A retrospective study in Baoding, China
  83. Let-7i-3p inhibits the cell cycle, proliferation, invasion, and migration of colorectal cancer cells via downregulating CCND1
  84. β2-Adrenergic receptor expression in subchondral bone of patients with varus knee osteoarthritis
  85. Possible impact of COVID-19 pandemic and lockdown on suicide behavior among patients in Southeast Serbia
  86. In vitro antimicrobial activity of ozonated oil in liposome eyedrop against multidrug-resistant bacteria
  87. Potential biomarkers for inflammatory response in acute lung injury
  88. A low serum uric acid concentration predicts a poor prognosis in adult patients with candidemia
  89. Antitumor activity of recombinant oncolytic vaccinia virus with human IL2
  90. ALKBH5 inhibits TNF-α-induced apoptosis of HUVECs through Bcl-2 pathway
  91. Risk prediction of cardiovascular disease using machine learning classifiers
  92. Value of ultrasonography parameters in diagnosing polycystic ovary syndrome
  93. Bioinformatics analysis reveals three key genes and four survival genes associated with youth-onset NSCLC
  94. Identification of autophagy-related biomarkers in patients with pulmonary arterial hypertension based on bioinformatics analysis
  95. Protective effects of glaucocalyxin A on the airway of asthmatic mice
  96. Overexpression of miR-100-5p inhibits papillary thyroid cancer progression via targeting FZD8
  97. Bioinformatics-based analysis of SUMOylation-related genes in hepatocellular carcinoma reveals a role of upregulated SAE1 in promoting cell proliferation
  98. Effectiveness and clinical benefits of new anti-diabetic drugs: A real life experience
  99. Identification of osteoporosis based on gene biomarkers using support vector machine
  100. Tanshinone IIA reverses oxaliplatin resistance in colorectal cancer through microRNA-30b-5p/AVEN axis
  101. miR-212-5p inhibits nasopharyngeal carcinoma progression by targeting METTL3
  102. Association of ST-T changes with all-cause mortality among patients with peripheral T-cell lymphomas
  103. LINC00665/miRNAs axis-mediated collagen type XI alpha 1 correlates with immune infiltration and malignant phenotypes in lung adenocarcinoma
  104. The perinatal factors that influence the excretion of fecal calprotectin in premature-born children
  105. Effect of femoral head necrosis cystic area on femoral head collapse and stress distribution in femoral head: A clinical and finite element study
  106. Does the use of 3D-printed cones give a chance to postpone the use of megaprostheses in patients with large bone defects in the knee joint?
  107. lncRNA HAGLR modulates myocardial ischemia–reperfusion injury in mice through regulating miR-133a-3p/MAPK1 axis
  108. Protective effect of ghrelin on intestinal I/R injury in rats
  109. In vivo knee kinematics of an innovative prosthesis design
  110. Relationship between the height of fibular head and the incidence and severity of knee osteoarthritis
  111. lncRNA WT1-AS attenuates hypoxia/ischemia-induced neuronal injury during cerebral ischemic stroke via miR-186-5p/XIAP axis
  112. Correlation of cardiac troponin T and APACHE III score with all-cause in-hospital mortality in critically ill patients with acute pulmonary embolism
  113. LncRNA LINC01857 reduces metastasis and angiogenesis in breast cancer cells via regulating miR-2052/CENPQ axis
  114. Endothelial cell-specific molecule 1 (ESM1) promoted by transcription factor SPI1 acts as an oncogene to modulate the malignant phenotype of endometrial cancer
  115. SELENBP1 inhibits progression of colorectal cancer by suppressing epithelial–mesenchymal transition
  116. Visfatin is negatively associated with coronary artery lesions in subjects with impaired fasting glucose
  117. Treatment and outcomes of mechanical complications of acute myocardial infarction during the Covid-19 era: A comparison with the pre-Covid-19 period. A systematic review and meta-analysis
  118. Neonatal stroke surveillance study protocol in the United Kingdom and Republic of Ireland
  119. Oncogenic role of TWF2 in human tumors: A pan-cancer analysis
  120. Mean corpuscular hemoglobin predicts the length of hospital stay independent of severity classification in patients with acute pancreatitis
  121. Association of gallstone and polymorphisms of UGT1A1*27 and UGT1A1*28 in patients with hepatitis B virus-related liver failure
  122. TGF-β1 upregulates Sar1a expression and induces procollagen-I secretion in hypertrophic scarring fibroblasts
  123. Antisense lncRNA PCNA-AS1 promotes esophageal squamous cell carcinoma progression through the miR-2467-3p/PCNA axis
  124. NK-cell dysfunction of acute myeloid leukemia in relation to the renin–angiotensin system and neurotransmitter genes
  125. The effect of dilution with glucose and prolonged injection time on dexamethasone-induced perineal irritation – A randomized controlled trial
  126. miR-146-5p restrains calcification of vascular smooth muscle cells by suppressing TRAF6
  127. Role of lncRNA MIAT/miR-361-3p/CCAR2 in prostate cancer cells
  128. lncRNA NORAD promotes lung cancer progression by competitively binding to miR-28-3p with E2F2
  129. Noninvasive diagnosis of AIH/PBC overlap syndrome based on prediction models
  130. lncRNA FAM230B is highly expressed in colorectal cancer and suppresses the maturation of miR-1182 to increase cell proliferation
  131. circ-LIMK1 regulates cisplatin resistance in lung adenocarcinoma by targeting miR-512-5p/HMGA1 axis
  132. LncRNA SNHG3 promoted cell proliferation, migration, and metastasis of esophageal squamous cell carcinoma via regulating miR-151a-3p/PFN2 axis
  133. Risk perception and affective state on work exhaustion in obstetrics during the COVID-19 pandemic
  134. lncRNA-AC130710/miR-129-5p/mGluR1 axis promote migration and invasion by activating PKCα-MAPK signal pathway in melanoma
  135. SNRPB promotes cell cycle progression in thyroid carcinoma via inhibiting p53
  136. Xylooligosaccharides and aerobic training regulate metabolism and behavior in rats with streptozotocin-induced type 1 diabetes
  137. Serpin family A member 1 is an oncogene in glioma and its translation is enhanced by NAD(P)H quinone dehydrogenase 1 through RNA-binding activity
  138. Silencing of CPSF7 inhibits the proliferation, migration, and invasion of lung adenocarcinoma cells by blocking the AKT/mTOR signaling pathway
  139. Ultrasound-guided lumbar plexus block versus transversus abdominis plane block for analgesia in children with hip dislocation: A double-blind, randomized trial
  140. Relationship of plasma MBP and 8-oxo-dG with brain damage in preterm
  141. Identification of a novel necroptosis-associated miRNA signature for predicting the prognosis in head and neck squamous cell carcinoma
  142. Delayed femoral vein ligation reduces operative time and blood loss during hip disarticulation in patients with extremity tumors
  143. The expression of ASAP3 and NOTCH3 and the clinicopathological characteristics of adult glioma patients
  144. Longitudinal analysis of factors related to Helicobacter pylori infection in Chinese adults
  145. HOXA10 enhances cell proliferation and suppresses apoptosis in esophageal cancer via activating p38/ERK signaling pathway
  146. Meta-analysis of early-life antibiotic use and allergic rhinitis
  147. Marital status and its correlation with age, race, and gender in prognosis of tonsil squamous cell carcinomas
  148. HPV16 E6E7 up-regulates KIF2A expression by activating JNK/c-Jun signal, is beneficial to migration and invasion of cervical cancer cells
  149. Amino acid profiles in the tissue and serum of patients with liver cancer
  150. Pain in critically ill COVID-19 patients: An Italian retrospective study
  151. Immunohistochemical distribution of Bcl-2 and p53 apoptotic markers in acetamiprid-induced nephrotoxicity
  152. Estradiol pretreatment in GnRH antagonist protocol for IVF/ICSI treatment
  153. Long non-coding RNAs LINC00689 inhibits the apoptosis of human nucleus pulposus cells via miR-3127-5p/ATG7 axis-mediated autophagy
  154. The relationship between oxygen therapy, drug therapy, and COVID-19 mortality
  155. Monitoring hypertensive disorders in pregnancy to prevent preeclampsia in pregnant women of advanced maternal age: Trial mimicking with retrospective data
  156. SETD1A promotes the proliferation and glycolysis of nasopharyngeal carcinoma cells by activating the PI3K/Akt pathway
  157. The role of Shunaoxin pills in the treatment of chronic cerebral hypoperfusion and its main pharmacodynamic components
  158. TET3 governs malignant behaviors and unfavorable prognosis of esophageal squamous cell carcinoma by activating the PI3K/AKT/GSK3β/β-catenin pathway
  159. Associations between morphokinetic parameters of temporary-arrest embryos and the clinical prognosis in FET cycles
  160. Long noncoding RNA WT1-AS regulates trophoblast proliferation, migration, and invasion via the microRNA-186-5p/CADM2 axis
  161. The incidence of bronchiectasis in chronic obstructive pulmonary disease
  162. Integrated bioinformatics analysis shows integrin alpha 3 is a prognostic biomarker for pancreatic cancer
  163. Inhibition of miR-21 improves pulmonary vascular responses in bronchopulmonary dysplasia by targeting the DDAH1/ADMA/NO pathway
  164. Comparison of hospitalized patients with severe pneumonia caused by COVID-19 and influenza A (H7N9 and H1N1): A retrospective study from a designated hospital
  165. lncRNA ZFAS1 promotes intervertebral disc degeneration by upregulating AAK1
  166. Pathological characteristics of liver injury induced by N,N-dimethylformamide: From humans to animal models
  167. lncRNA ELFN1-AS1 enhances the progression of colon cancer by targeting miR-4270 to upregulate AURKB
  168. DARS-AS1 modulates cell proliferation and migration of gastric cancer cells by regulating miR-330-3p/NAT10 axis
  169. Dezocine inhibits cell proliferation, migration, and invasion by targeting CRABP2 in ovarian cancer
  170. MGST1 alleviates the oxidative stress of trophoblast cells induced by hypoxia/reoxygenation and promotes cell proliferation, migration, and invasion by activating the PI3K/AKT/mTOR pathway
  171. Bifidobacterium lactis Probio-M8 ameliorated the symptoms of type 2 diabetes mellitus mice by changing ileum FXR-CYP7A1
  172. circRNA DENND1B inhibits tumorigenicity of clear cell renal cell carcinoma via miR-122-5p/TIMP2 axis
  173. EphA3 targeted by miR-3666 contributes to melanoma malignancy via activating ERK1/2 and p38 MAPK pathways
  174. Pacemakers and methylprednisolone pulse therapy in immune-related myocarditis concomitant with complete heart block
  175. miRNA-130a-3p targets sphingosine-1-phosphate receptor 1 to activate the microglial and astrocytes and to promote neural injury under the high glucose condition
  176. Review Articles
  177. Current management of cancer pain in Italy: Expert opinion paper
  178. Hearing loss and brain disorders: A review of multiple pathologies
  179. The rationale for using low-molecular weight heparin in the therapy of symptomatic COVID-19 patients
  180. Amyotrophic lateral sclerosis and delayed onset muscle soreness in light of the impaired blink and stretch reflexes – watch out for Piezo2
  181. Interleukin-35 in autoimmune dermatoses: Current concepts
  182. Recent discoveries in microbiota dysbiosis, cholangiocytic factors, and models for studying the pathogenesis of primary sclerosing cholangitis
  183. Advantages of ketamine in pediatric anesthesia
  184. Congenital adrenal hyperplasia. Role of dentist in early diagnosis
  185. Migraine management: Non-pharmacological points for patients and health care professionals
  186. Atherogenic index of plasma and coronary artery disease: A systematic review
  187. Physiological and modulatory role of thioredoxins in the cellular function
  188. Case Reports
  189. Intrauterine Bakri balloon tamponade plus cervical cerclage for the prevention and treatment of postpartum haemorrhage in late pregnancy complicated with acute aortic dissection: Case series
  190. A case of successful pembrolizumab monotherapy in a patient with advanced lung adenocarcinoma: Use of multiple biomarkers in combination for clinical practice
  191. Unusual neurological manifestations of bilateral medial medullary infarction: A case report
  192. Atypical symptoms of malignant hyperthermia: A rare causative mutation in the RYR1 gene
  193. A case report of dermatomyositis with the missed diagnosis of non-small cell lung cancer and concurrence of pulmonary tuberculosis
  194. A rare case of endometrial polyp complicated with uterine inversion: A case report and clinical management
  195. Spontaneous rupturing of splenic artery aneurysm: Another reason for fatal syncope and shock (Case report and literature review)
  196. Fungal infection mimicking COVID-19 infection – A case report
  197. Concurrent aspergillosis and cystic pulmonary metastases in a patient with tongue squamous cell carcinoma
  198. Paraganglioma-induced inverted takotsubo-like cardiomyopathy leading to cardiogenic shock successfully treated with extracorporeal membrane oxygenation
  199. Lineage switch from lymphoma to myeloid neoplasms: First case series from a single institution
  200. Trismus during tracheal extubation as a complication of general anaesthesia – A case report
  201. Simultaneous treatment of a pubovesical fistula and lymph node metastasis secondary to multimodal treatment for prostate cancer: Case report and review of the literature
  202. Two case reports of skin vasculitis following the COVID-19 immunization
  203. Ureteroiliac fistula after oncological surgery: Case report and review of the literature
  204. Synchronous triple primary malignant tumours in the bladder, prostate, and lung harbouring TP53 and MEK1 mutations accompanied with severe cardiovascular diseases: A case report
  205. Huge mucinous cystic neoplasms with adhesion to the left colon: A case report and literature review
  206. Commentary
  207. Commentary on “Clinicopathological features of programmed cell death-ligand 1 expression in patients with oral squamous cell carcinoma”
  208. Rapid Communication
  209. COVID-19 fear, post-traumatic stress, growth, and the role of resilience
  210. Erratum
  211. Erratum to “Tollip promotes hepatocellular carcinoma progression via PI3K/AKT pathway”
  212. Erratum to “Effect of femoral head necrosis cystic area on femoral head collapse and stress distribution in femoral head: A clinical and finite element study”
  213. Erratum to “lncRNA NORAD promotes lung cancer progression by competitively binding to miR-28-3p with E2F2”
  214. Retraction
  215. Expression and role of ABIN1 in sepsis: In vitro and in vivo studies
  216. Retraction to “miR-519d downregulates LEP expression to inhibit preeclampsia development”
  217. Special Issue Computational Intelligence Methodologies Meets Recurrent Cancers - Part II
  218. Usefulness of close surveillance for rectal cancer patients after neoadjuvant chemoradiotherapy
Downloaded on 9.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/med-2022-0585/html
Scroll to top button