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The expression of SERPINE1 in colon cancer and its regulatory network and prognostic value

BMC Gastroenterology volume 23, Article number: 33 (2023) Cite this article

Abstract

Background

Serpin Peptidase Inhibitor 1 (SERPINE1) promotes cancer progression by making it easier for cancer cells to spread to surrounding normal tissue. We expect to understand the prognostic value and regulatory network of SERPINE1 in colon cancer using bioinformatics methods.

Methods

The expression of target gene SERPINE1 in varying cancers was analyzed by the Tumor Immune Estimation Resource (TIMER) database. SERPINE1 expression in Colon Adenocarcinoma and normal tissue samples was assessed by starBase and UALCAN databases. SERPINE1 expression in clinical tissues was assayed using quantitative reverse transcription Polymerase Chain Reaction (qRT-PCR). SERPINE1 expression was detected in colon cancer patients with various clinical features (age, gender, nodal metastasis status, race, stages, and subtype) using analysis of variance. Survival curve was used to analyze the effect of high and low expression of SERPINE1 on the survival time of patients with different clinical phenotypes. Gene Set Enrichment Analysis (GSEA) was conducted on the results of LinkFinder calculation using LinkInterpreter module, which was combined with Pearson correlation analysis to obtain the kinase targets and miRNA targets, transcription factor targets, and corresponding signaling pathways associated with SERPINE1. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on GSEA result. Finally, Gene Multiple Association Network Integration Algorithm (GeneMANIA) was utilized to establish a network of genes related to the kinases MAPK1, miR-18a, and SRF_Q, and biological functions were analyzed.

Results

Based on TIMER, starBase, and UALCAN databases, SERPINE1 was found to be remarkably highly expressed in colon cancer patients, which was further verified by clinical tissue. It was also associated with different clinical features (nodal metastasis status, stages, subtypes). Additionally, survival analysis showed that patients with low expression of SERPINE1 had a longer survival time, suggesting that SERPINE1 was a prognostic risk factor for colon cancer. Pearson correlation analysis revealed that the expression of Integrin Alpha 5 (ITGA5), Matrix Metallopeptidase 19 (MMP19), and ADAM Metallopeptidase with Thrombospondin Type 1 Motif, 4 (ADAMTS4) had the highest correlation with that of SERPINE1. The GSEA results indicated that these genes were mainly enriched in the pathways of RNA expression and kinases. Finally, GeneMANIA analysis was introduced to construct the molecular network of SERPINE1.

Conclusion

Overall, our bioinformatics analyses comprehensively described the networks involved SERPINE1 in colon cancer and the potentially associated molecular mechanisms.

Peer Review reports

Introduction

Colon cancer is a common malignancy that occurs in the gastrointestinal tract. According to statistics from the National Cancer Institute, as of the first three quarters of 2022, there were about 150,000 cases in the United States, and it caused about 50,000 deaths. Many risk factors lead to the onset of colon cancer: family history, gene mutations, disease history, excessive drinking, smoking, and obesity [1]. Existing studies found that gene mutation is a major risk factor for colon cancer. For instance, mutations in K-RAS can stimulate colon cancer, and mutations in TP53 can promote early colon cancer deterioration and transformation into metastatic colon cancer [2]. Change in gene expression levels is also a key factor affecting the onset and prognosis of colon cancer. Numerous studies analyzed the gene transcriptional levels of colon cancer patients and found key genes such as GLUT1, MUC2, Cyclooxygenase-2, etc. that are related to the prognosis of colon cancer [3, 4]. Recent studies on colon cancer-related gene regulatory pathways found that MAPK signaling pathway, JAK/STAT, AKT/NF-κB and other signaling pathways can modulate the occurrence of colon cancer [5,6,7]. Therefore, we believed that the analysis and mining of colon cancer-related genes would deepen our understanding of colon cancer and improve colon cancer treatment.

Serpin Peptidase Inhibitor 1 (SERPINE1), also known as plasminogen activator inhibitor-1 (PAI-1), is an encoding gene of serine protease inhibitors that can suppress fibrinolysis in vivo [8]. SERPINE1 is closely correlated with the morbidity of multiple cancers. Studies illustrated that SERPINE1 can stimulate the progression of triple-negative breast cancer by promoting cytoskeletal reorganization and glycometabolism and can also accelerate the progression of pancreatic cancer by up-regulating the secretion and expression of IL-8 [9, 10]. The role of SERPINE1 in the pathogenesis of colon cancer was studied previously, and a current study found that SERPINE1 can promote the progression of colon cancer through the P38-MAPK pathway [11]. Since the expression of SERPINE1 is closely related to cancer, it is vital to understand the regulatory mechanism of SERPINE1 expression in vivo. Current research believed that miR-143 can reduce the expression of SERPINE1, thereby preventing the progression of bladder cancer [12]. It was also found that SERPINE1 interacts with the membrane receptor LDL receptor-related protein 1 to enhance proliferation and migration of esophageal squamous carcinoma cells, and activate AKT and ERK signaling pathways [13]. Due to its complex regulatory effect in vivo, the study of SERPINE1 and its regulatory mechanism will shed light on further understanding of pathogenesis and the early screening of colon cancer.

In this study, multiple databases (including Tumor Immune Estimation Resource (TIMER), starBase, UALCAN, and The Human Protein Atlas) were used to find that SERPINE1 was markedly overexpressed in colon cancer, and SERPINE1 expression was correlated with clinical features of colon cancer patients. Survival curve was used to analyze patient survival rate. In this study, survival curve was utilized to analyze the prognostic effect of SERPINE1 on colon cancer, and it was found that patients with high SERPINE1 expression had poor prognoses. LinkedOmics is a multi-omics analysis tool based on The Cancer Genome Atlas (TCGA) database. The highly correlated genes (Integrin Alpha 5 (ITGA5), Matrix Metallopeptidase 19 (MMP19), and ADAM Metallopeptidase with Thrombospondin Type 1 Motif, 4 (ADAMTS4)) of SERPINE1 were obtained by Pearson correlation analysis. Gene set enrichment analysis (GSEA) was used to identify SERPINE1-associated kinases, miRNAs and transcription factors. Gene Multiple Association Network Integration Algorithm (GeneMANIA) is a simple co-expression gene analysis software that can be used to establish gene regulatory networks and analyze the biological functions of genes. In this study, GeneMANIA was utilized to obtain network based on MAPK1, miR-18a and SRF-Q6 and the biological functions of these 3 genes. The results of our research might reveal novel targets and strategies for the diagnosis and treatment of colon cancer, as well as provide a deeper insight into the pathogenesis of colon cancer, which would inform further research.

Materials and methods

Analysis of SERPINE1 expression among different cancers and clinical features of colon cancer

Expression of the target gene SERPINE1 in various cancers was analyzed through the TIMER database (http://cistrome.dfci.harvard.edu/TIMER/). The expression differences were examined by Wilcoxon method. Based on the starBase database (http://starbase.sysu.edu.cn/index.php) and the UALCAN database (http://ualcan.path.uab.edu/analysis.html), SERPINE1 gene expression in Colon Adenocarcinoma (COAD) and normal tissue samples was detected. Detection of SERPINE1 expression in colon cancer patients with various clinical features (age, gender, nodal metastasis status, race, stages, subtypes and weight) was performed using analysis of variance. All database parameters were set by default.

Clinical samples

This study included 15 patients with colon cancer who underwent one-stage operation in Tangshan Central Hospital from May, 2020, to March, 2021. All patients included in the study had not received chemotherapy or radiotherapy before resection, and adjacent tissue and tumor tissue samples were immediately frozen at -80 ℃ until analysis. The study was approved by the Medical Ethics Committee of Tangshan Central Hospital, and participants proffered written informed consent for research purposes and publication.

qRT-PCR detection

Total RNA was extracted from adjacent and tumor tissues utilizing Trizol (Invitrogen, USA). RNA was reversely transcribed into cDNA by PrimeScript RT kit (Takara, Japan). Gene expression in adjacent and tumor tissues was assessed utilizing miScript SYBR Green PCR Kit (Qiagen, Germany), and qRT-PCR analysis was done on 7500 Real-time PCR System (Applied Biosystems, USA). Beta-actin was utilized as an internal reference for mRNA. Relative expression levels of mRNA were calculated using the 2−ΔΔCT method. Primers were as follows:

SERPINE1: Forward primer5’-GCAAGGCACCTCTGAGAACT-3’.

Reverse primer5’-GGGTGAGAAAACCACGTTGC-3’.

Beta-actin: Forward: 5’-ACAGAGCCTCGCCTTTGCC-3’.

Reverse: 5’-TGGCCATCTCTTGCTCGAAG-3’.

Evaluation of the relationship between SERPINE1 expression and patient survival

To assess prognostic value of SERPINE1 for colon cancer, we used R package “survival” [14] for survival analysis to explore the impact of SERPINE1 expression on the survival time of patients with different clinical phenotypes. First, patients were divided into high and low expression groups according to SERPINE1 expression. Then the survival curve was plotted by Kaplan Meier (K–M) method, and compared by log-rank test. P value < 0.05 was regarded as significant.

GSEA analysis

The LinkFinder module of the LinkedOmics (http://www.linkedomics.org/login.php) was utilized to analyze the co-expressed genes of SERPINE1 based on TCGA-COAD cohort (n = 533), and Pearson correlation coefficient was calculated to evaluate the correlation between gene expression (false discovery rate [FDR < 0.01]). Then, the LinkInterpreter module was used to perform GSEA on the LinkFinder calculation results: First, the obtained LinkFinder data were labeled and sorted, and then GSEA was performed for Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, kinase target enrichment, miRNA target enrichment and transcription factor target enrichment. Finally, the kinase targets, miRNA targets, transcription factor targets and corresponding signaling pathways related to SERPINE1 were obtained. 500 simulations were performed. The top 10 genes with the most prominent FDR were selected for GO and KEGG analyses.

GeneMANIA analysis

GeneMANIA (http://www.genemania.org) is a simple analysis software that can be used to establish gene regulatory networks and analyze the biological function of genes. gene regulatory networks with Kinase MAPK1, miR-18a and SRF_Q related genes were constructed, and relevant biological functions were analyzed based on GeneMANIA (http://www.genemania.org) database.

Results

Differential expression of SERPINE1 in various cancers

To understand the expression status of SERPINE1 among various cancers, TIMER database was employed to analyze the expression of SERPINE1 in various cancer tissues and the corresponding normal tissues. The results demonstrated that SERPINE1 was dramatically highly expressed in breast cancer, colon cancer, esophageal cancer, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, gastric cancer, and thyroid cancer tissue, while prominently lowly expressed in renal chromophobe cell carcinoma, renal papillary cell carcinoma, hepatocellular carcinoma, and endometrial cancer tissue (Fig. 1). Based on the analysis above, we selected colon cancer in which SERPINE1 was highly expressed.

Fig. 1
figure 1

Expression of SERPINE1 mRNA in different cancer types. SERPINE1 levels in varying cancer tissues and normal tissues were analyzed through TIMER database. Red box: tumor sample; blue box: normal sample; purple box: metastasis sample; expression data of SERPINE1 were normalized to log2 (TPM). Statistical analysis was conducted using Wilcoxon method. * p < 0.05, ** p < 0.01, *** p < 0.001

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SERPINE1 expression in colon cancer

To comprehensively examine the expression condition of SERPINE1 in colon cancer, gene expression of SERPINE1 was further verified in the starBase and UALCAN databases. Consistently, the results of the expression analyses illustrated that SERPINE1 was highly expressed in colon cancer tissue (n = 471/286) in contrast with the normal tissue (n = 41) (Fig. 2A–B). To validate SERPINE1 level in clinical tissues, 15 pairs of tumor tissues and adjacent tissues were excised from colorectal cancer patients and compared SERPINE1 expression. The findings presented that SERPINE1 was highly expressed in cancer tissues in contrast with adjacent tissues (Fig. 3). Afterwards, the relationship analyses between the expression of SERPINE1 and clinical phenotypes in colon cancer were subsequently conducted. As shown in Fig. 4A–F, the results illustrated that SERPINE1 expression was associated with the malignant degree and clinical features (nodal metastasis status, stages, subtypes) of the colon cancer patients.

Fig. 2
figure 2

Expression of SERPINE1 mRNA in colon cancer. A Analysis results of SERPINE1 expression in starBase database; orange box represents tumor tissue (n = 471); purple box represents normal tissue (n = 41); expression data were normalized to log2 (FPKM + 0.01); B Analysis results of SERPINE1 expression in UALCAN database (normal: n = 41; tumor: n = 286); expression data were normalized to TPM. Statistical analysis was conducted using Student’s t-test (p < 0.05 indicates a significant difference)

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Fig. 3
figure 3

SERPINE1 level in clinical tissues. Analysis of SERPINE1 expression in 15 pairs of tumor tissues and adjacent tissues from patients with colon cancer. Statistical analysis was conducted using Student’s t-test. * p < 0.05

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Fig. 4
figure 4

Association between SERPINE1 expression and clinical characteristic. A Association between SERPINE1 expression and patient’s age as analyzed by analysis of variance (21–40 Yrs: n = 12; 41–60 Yrs: n = 90; 61–80 Yrs: n = 149; 81–100 Yrs: n = 32); B Association between SERPINE1 expression and patient’s gender as analyzed by analysis of variance (male: n = 156; female: n = 127); C Association between SERPINE1 expression and patient’s race as analyzed by analysis of variance (Caucasian: n = 193; African-American: n = 55; Asian: n = 11); D Association between SERPINE1 expression and patient’s nodal metastasis status as analyzed by analysis of variance (N0: n = 166; N1: n = 70; N2: n = 47); E Association between SERPINE1 expression and patient’s cancer stage as analyzed by analysis of variance (stage1: n = 45; stage2: n = 110; stage3: n = 80; stage4: n = 39); F Association between SERPINE1 expression and patient’s histological subtype as analyzed by analysis of variance (adenocarcinoma: n = 243; mucinous adenocarcinoma: n = 37) (p < 0.05 indicates a significant difference)

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To further explore the impact of clinical phenotypes and SERPINE1 expression on the prognosis of colon cancer patients, survival curves of various clinical phenotypes were plotted. The results presented that survival time of patients in stage1 and those in stage2 was longer in the low expression group of SERPINE1. But other clinical phenotypes in the high and low SERPINE1 expression groups were not strongly associated with patient’s survival (Fig. 5A–F). All of these illustrated that SERPINE1 expression was associated with specific stages of cancer and prognoses of colon cancer patients.

Fig. 5
figure 5

Association between SERPINE1 level and colon cancer patients’ prognoses. A Survival curves of patients in N0 stage with high/low SERPINE1 expression; B Survival curves of patients in N1 stage and N2 stage with high/low SERPINE1 expression; C Survival curves of patients in stage1 and stage2 with high/low SERPINE1 expression; D Survival curves of patients in stage3 and stage4 with high/low SERPINE1 expression; E Survival curves of Adenocarcinoma patients with high/low SERPINE1 expression; F Survival curves of Mucinous Adenocarcinoma patients with high/low SERPINE1 expression. K–M method was used for survival analysis and drawing the survival curves, and difference among patients’ subgroups was calculated by log-rank test (p value < 0.05 indicates a significant difference)

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Functional enrichment analysis of SERPINE1 co-expressed genes

The LinkFinder module of the LinkedOmics database was utilized to perform correlation analysis based on the 106 colon cancer patients in TCGA database. The results of correlation analysis exhibited that a total of 5,407 genes were markedly correlated with SERPINE1, with 2,377 substantially positively correlated and 3,030 substantially negatively correlated (Fig. 6A). The Top 50 genes that were conspicuously positively/negatively correlated with SERPINE1 were shown in heat maps in Fig. 6B–C. As can be seen from Fig. 6D–F, the three genes most significantly correlated to SERPINE1 expression were ITGA5, MMP19, and ADAMTS4.

Fig. 6
figure 6

Relationship between SERPINE1 and associated genes. A Correlation analysis of SERPINE1 in TCGA-COAD (TCGA-Colon Adenocarcinoma); green dots represent downregulated genes; red dots represent upregulated genes; B–C Heatmap of the top 50 genes substantially positively/negatively associated with SERPINE1; Z-score value gradually decreases from red to blue; D–F ITGA5, MMP19 and ADAMTS4 with the highest correlation coefficient with key co-expressed genes of SERPINE1 as calculated by Pearson correlation analysis (p value < 0.05 indicates a significant difference)

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Based on the top 10 genes significantly associated with SERPINE1, GO and KEGG analyses were employed to predict the potentially involved biofunctions and signaling pathways. GO enrichment analysis uncovered that changes in the expression of SERPINE1 mainly affected biological processes such as translational initiation, protein targeting, ncRNA processing, which was mainly correlated with cellular components including ribosome, cell structures related to mitochondria and cell adhesion, as well as relevant molecular functions such as receptor ligand activity, protein tyrosine kinase activity (Fig. 7A–C). The results of KEGG enrichment analysis indicated that changes in SERPINE1 expression mainly affected Rap1\PI3K-Akt and MAPK signaling pathways (Fig. 7D).

Fig. 7
figure 7

GSEA enrichment results for SERPINE1 associated genes. A–C GO enrichment analysis of 10 SERPINE1-associated genes; D KEGG enrichment analysis of 10 SERPINE1-associated genes

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Constructing co-expression networks based on SERPINE1-associated kinase, miRNA, and transcription factor

To further explore the potential targets of SERPINE1 in colon cancer, SERPINE1 networks for kinase, miRNA and transcription factor targets were analyzed by GSEA. The results signified that kinase targets were mainly related to MAPK1, SRC, AKT1, FYN and MAPK8 kinase-related signaling pathways. The miRNA-target network was mainly related to miR-18a, miR-29a, miR-29b, miR-29c, miR-24, miR-138 and miR-9. The transcription factor-target regulatory network was mainly related to several transcription factors such as SRF-Q6, ZIC1, ZIC3, NF-κB and SRF-C (Table 1).

Table 1 Constructing SERPINE1 regulatory networks for kinase, miRNA, and transcription factor targets in colon cancer
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In the GeneMANIA database, genes associated with kinase MAPK1, miR-18a and SRF-Q6 were used to construct a regulatory network. The results revealed that MAPK1 was mainly involved in neurotrophin signaling pathway, Fc receptor signaling pathway, and toll-like receptor 10 signaling pathway, etc. (Fig. 8A). MiR-18a mainly participated in 3’-5’-exoribonuclease activity, positive regulation of proteolysis, exoribonuclease activity, producing 5’-phosphomonoesters, RNA phosphodiester bond hydrolysis, exonucleolytic and other biological processes (Fig. 8B). The transcription factor SRF-Q6 was mainly involved in the modulation of actin cytoskeleton, actin-binding, MAP kinase tyrosine/serine/threonine phosphatase activity (Fig. 8C). Together, these findings suggested that in colon cancer, SERPINE1 may be involved in signaling pathways or cell functions of MAPK1, MiR-18a and SRF-Q6. Changes in expression of these genes may also cause alternation in specific cell functions.

Fig. 8
figure 8

Analysis results of GeneMANIA. A A gene regulatory network with kinase MAPK1 related genes constructed based on the GeneMANIA database; B A gene regulatory network with miR-18a related genes constructed based on the GeneMANIA database; C A gene regulatory network with SRF-Q6 related genes constructed based on the GeneMANIA database

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Discussion

SERPINE1 (PAI-1) is proven by numerous studies to be a pivotal gene influencing the occurrence and progression of cancer. Current research believes that SERPINE1 can catalyze the degradation of basement membrane and ECM, making it easier for cancer cells to invade surrounding normal tissue and promote the progression of cancer [15]. In this study, through the analysis of TIMER database, it was found that SERPINE1 had obvious differential expression in various cancers, and the most significant differential expression was present in colon cancer. Colon cancer as a common type of cancer attracted a large number of studies on changes in its gene expression. For example, changes in FGFRL1 gene can promote the occurrence and progression of colon cancer [16]. WISP can extend the survival time of patients through the WISP2/β-catenin pathway [17]. Based on the analysis of the relevant data from The Human Protein Atlas and the UALCAN database, this study found that the expression of SERPINE1 in colon cancer tissue was significantly up-regulated, demonstrating that SERPINE1 may be a key gene involved in development and progression of colon cancer. This study also explored the expression of SERPINE1 in patients with various clinical characteristics in the UALCAN database. The findings indicated that the expression of SERPINE1 was generally higher in patients with various clinical characteristics than that in healthy individuals. By comparing SERPINE1 with tumor-associated factors, it was revealed that SERPINE1 level in stage1 of colorectal cancer substantially varied from other 3 stages, and SERPINE1 was related to TMN stages of CRC [18]. Furthermore, the differences in survival time of patients with high/low SERPINE1 expression were also analyzed in combination with clinical characteristics, and the results showed that the survival time of patients with high SERPINE1 expression was dramatically shorter. Li et al. [19] reported that SERPINE1 is highly expressed in gastric adenocarcinoma and is dramatically implicated in patients’ prognoses. Forced expression of SERPINE1 (PAI-1) is noticeably related to shorter survival of glioblastoma patients [20]. Another study indicated that gastric cancer patients with high SERPINE1 expression have shorter OS than those with low SERPINE1 expression [21].

The top 10 genes significantly associated with SERPINE1 were assessed by GO and KEGG to predict the potential biological functions and signaling pathways involved. GO enrichment analysis reported that changes in SERPINE1 expression mainly affected cellular components related to ribosomes, cell structure and cell adhesion, receptor ligand activity, and protein tyrosine kinase activity. KEGG enrichment analysis presented that alternations in SERPINE1 expression mainly affected Rap1\PI3K-Akt and MAPK signaling pathways. Zhang et al. [22] reported that protein tyrosine kinase is poorly expressed in breast cancer cells and represses invasion and metastasis of breast cancer cells. Xiong et al. [23] found that 6 differentially expressed miRNA target genes in osteosarcoma involved in the PI3K-Akt signaling pathway. Forced expression of ART3 stimulates proliferation of triple-negative breast cancer cells and modulates triple-negative breast carcinogenesis via activation of Akt and ERK pathways [24].

Subsequently, it was found through the LinkedOmics database that there were a great number of genes associated with the expression of SERPINE1, wherein the expression of ITGA5, MMP19 and ADAMTS4 was the most pronouncedly related to the expression of SERPINE1. ITGA5 is integrin subunit α5, and there are little published data on proving that relationship between SERPINE1 and the expression of ITGA5, while it is reported that overexpression of ITGA5 can promote the metastasis and spread of colon cancer [25]. MMP19 (matrix metallopeptidase 19) is related to epithelial cell proliferation, enterocyte migration and poor prognosis [26, 27]. ADAMTS4 is highly expressed in colon cancer cells, and research suggested that ADAMTS4 can promote cancer progression through macrophages [28, 29]. SERPINE1 is notably positively correlated with these three genes, that is, SERPINE1 and these three genes may jointly played important roles in the progression of colon cancer.

Exploring biological pathways is an important method for cancer research. Studies found that biological pathways such as MAPK pathway and NF-κB pathway can affect the pathogenesis of colon cancer [30, 31]. Our research found that SERPINE1 might affect the pathogenesis of colon cancer by influencing cell adhesion, kinase activation and other pathways, and thus we further studied the kinases, miRNAs and transcription factors related to SERPINE1. Kinases play a pivotal role in the pathogenesis of cancer and research suggested that the activation of the tyrosine kinase pathway can stimulate the pathogenesis of colon cancer [32]. This study found that the MAPK1 kinase pathway and SRC kinase were important causes of colon cancer, while MAPK1 is a common cancer-promoting pathway that is believed to promote the progression of prostate cancer and breast cancer [33, 34]. In addition, SRC is also a common cancer-promoting pathway, and it can promote the occurrence of breast cancer by inducing mitochondrial dysfunction [35]. Besides, miRNAs are also common cancer-related regulatory factors. MiRNAs such as miR-770‑5p and miR-200 family are found to be related to the risk of colon cancer [36, 37]. Here, miR-18a and miR-29a were found in the SERPINE1-miRNA regulatory network. MiR-18a can affect the onset of colon cancer through the Cdc42/filopodia pathway, and miR-29a can affect the onset of colon cancer by regulating b-3p-COL5A1 [38, 39]. In addition to miRNA, transcription factors are also important regulators that affect pathogenesis. Research suggested that the aberrant expression of transcription factors such as KLF14 and SOX2 in colon cancer can affect the occurrence and progression of colon cancer by affecting the expression of downstream genes [40, 41]. This study found that SERPINE1 was associated with SRF-Q6 and ZIC, which are serum response factor and zinc finger protein, respectively. Research suggested that SRF-Q6 can affect the occurrence of cancer through the SRF/MRTF pathway while ZIC can induce colon cancer by influencing the expression of GLUT142, 43. After conducting the above research, GeneMINIA was used to establish regulatory networks. The results demonstrated that MAPK1 was mainly involved in immune-related pathways, miR-18a was mainly involved in serotonin methylation-related pathways, and SRF-Q6 was mainly involved in actin-related pathways.

In summary, this study dived into SERPINE1 (PAI-1) through bioinformatics methods and explored the genes and pathways related to SERPINE1 expression. SERPINE1 expression was found dramatically related to the expression of ITGA5, MMP19, and ADAMTS4, and affected biological pathways such as RNA transcription, cell adhesion, and kinase activation. This study also identified regulatory networks of SERPINE1 with kinases, miRNAs, and transcription factors through GSEA, such as MAPK1 kinase, miR-18a, and transcription factor SRF-Q6, etc. The contribution of this study is to fully explore the genes and pathways that might interact with SERPINE1. However, this study has the following two limitations. First, this paper is mainly based on bioinformatics methods for analysis, lacking of cell or clinical experiments for verification. Additionally, we conducted bioinformatics analysis directly based on the databases without special treatment, and there may be differences in sample quality, leading to some deviations in the results. We will design relevant experiments in the follow-up study to verify the clinical significance of SERPINE1, and will look for more sample data for optimization to reduce the deviation of results.

Availability of data and materials

The data used to support the findings of this study are included within the article. The data and materials in the current study are available from the corresponding author on reasonable request.

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  1. Yigang Wang and Jinyan Wang contributed equally

Authors and Affiliations

  1. Anus and Intestine Surgery, Tangshan Central Hospital, Tangshan, 063000, Hebei, China

    Yigang Wang, Jinyan Wang, Jianchao Gao & Mei Ding

  2. Department of Gastrointestinal Surgery, Tangshan Central Hospital, Tangshan Youyi Road and Changning Road Interchange Westbound 300 Meters, Tangshan, 063000, China

    Hua Li

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Contributions

YW participated in the design and interpretation of the data and revising the manuscript. JW and JG conceived of the study, and participated in its design and interpretation and helped to draft the manuscript. MD performed the statistical analysis and revised the manuscript critically. YW, JW, JG and Hua Li participated in its design and interpretation and helped to revise the manuscript critically. All authors read and approved by the final manuscript.

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Correspondence to Hua Li.

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Wang, Y., Wang, J., Gao, J. et al. The expression of SERPINE1 in colon cancer and its regulatory network and prognostic value. BMC Gastroenterol 23, 33 (2023). https://doi.org/10.1186/s12876-022-02625-y

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Keywords

BMC Gastroenterology

ISSN: 1471-230X

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