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. 2025 Oct 28;22(6):1061–1068. doi: 10.21873/cgp.20555

Strong Association Between Higher Expression of Anillin Actin-Binding Protein in Pancreatic Adenocarcinoma Tissues and Patient Survival Analyzed With the UALCAN and GEPIA Platforms Using the TCGA Database

SHIN-NOSUKE YAMASHITA 1,2,#, YOSHIATSU TANAKA 1,2,#, SHAJEDUL ISLAM 1,3, TAKAO KITAGAWA 1, KAZUHIRO TOKUDA 4, DURGA PAUDEL 1, SARITA GIRI 1, TOHRU OHTA 1, FUMIYA HARADA 2, HIROKI NAGAYASU 2, YASUHIRO KURAMITSU 1,5
PMCID: PMC12577607  PMID: 41151864

Abstract

Background/Aim

Pancreatic adenocarcinoma (PAAD) is one of the most lethal cancers worldwide, with more than 95% of PAAD patients not surviving beyond 5 years. Due to its rapid progression, in most cases there is no time for treatment by the time the disease is diagnosed, and metastases have developed in many organs. Therefore, there is currently a need to discover prognostic markers. Anillin actin-binding protein (ANLN) is an actin-binding protein involved in cell division. Its increased expression has been reported in many types of cancer, suggesting that it may be strongly involved in the progression of cancer malignancy, such as invasion and metastasis. The purpose of this study was to use bioinformatics to examine the possibility that ANLN may be a useful prognostic marker for PAAD.

Materials and Methods

The Gene Expression Profiling Interactive Analysis (GEPIA) and the University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) bioinformatics platforms were used to analyze ANLN mRNA expression, protein revel, and survival in patients with PAAD from The Cancer Genome Atlas (TCGA) database.

Results

ANLN mRNA and protein levels were found to be significantly higher in PAAD tissues compared to normal pancreatic tissues, and this elevation correlated with poor prognosis in PAAD patients.

Conclusion

Increased expression of ANLN mRNA and protein was detected in PAAD tissues compared to normal pancreatic tissues by the GEPIA and UALCAN platforms of the TCGA database. Increased ANLN expression correlated with poor patient prognosis. These results suggest that ANLN may be a promising prognostic biomarker in PAAD.

Keywords: ANLN, pancreatic adenocarcinoma, TCGA, UALCAN, GEPIA

Introduction

Pancreatic adenocarcinoma (PAAD) has an extremely poor prognosis, with a 5-year survival rate of less than 5% (1). Currently, surgical resection is the only potentially curative treatment, but 85-90% of patients have metastatic disease at the time of diagnosis. Because the disease progresses quickly, most patients are only diagnosed when the disease is in its late stages. PAAD can spread to the abdomen, liver, lungs, bones, and brain, and once spread, it cannot be removed surgically or treated with radiation therapy alone. It is therefore hoped that the biological characteristics that cause aggressiveness in PAAD will be elucidated. Recent intensive research has identified genetic abnormalities including K-ras and p53 that are frequently expressed in human malignancies, including pancreatic cancer (2-4). Currently, many researchers are working to identify the factors that determine the aggressiveness of PAAD (5,6).

Launched in 2006 as a collaboration between the National Cancer Institute and the National Human Genome Research Institute, the Cancer Genome Atlas (TCGA) is a database of molecular analyses of more than 20,000 primary cancer and matched normal tumor samples across 33 cancer types. This database is structured to aid in cancer diagnosis, treatment, and other research. The University of Alabama at Birmingham Cancer Data Analytics Portal (UALCAN) is a comprehensive interactive web resource for analyzing cancer OMICS data, enabling users to identify biomarkers and perform in silico validation of genes of interest (7). The Gene Expression Profiling Interactive Analysis (GEPIA) is a web-based tool that provides fast and customizable functionality based on TCGA and GTEx database. It also enables users to identify biomarkers and perform in silico validation of genes of interest (8). Using the UALCAN and GEPIA platforms, the authors have previously identified several molecules from the TCGA database that are significantly associated with the prognosis of patients with adrenocortical carcinoma and uveal melanoma (9-12). The authors used UALCAN and GEPIA from the TCGA database to identify mRNAs that are more strongly expressed in tissues of pancreatic cancer patients than in normal pancreatic tissues and that significantly worsen the prognosis of pancreatic cancer patients, i.e., significantly shorten their survival time.

Anillin actin-binding protein (ANLN) is an actin-binding protein involved in cytokinesis (13). Overexpression of ANLN mRNA has been reported in various types of cancer, including pancreatic cancer, and is also widely involved in the progression and metastasis of many types of cancer, including prostate cancer, and may be closely related to the progression of cancer malignancy (14-20).

This study aimed to clarify the clinical significance of ANLN expression in patients with PAAD using bioinformatics of the TCGA dataset.

Materials and Methods

Analysis for mRNA expression of ANLN in pancreatic adenocarcinoma tissues. To investigate ANLN mRNA expression levels in PAAD tissues, the GEPIA (8) and the UALCAN (22) web servers for cancer and normal gene expression profiling were used. ANLN mRNA expression levels in cancer tissues of PAAD patients were investigated from TCGA database using GEPIA and UALCAN platforms. In the TCGA database, the gene name “ANLN” was entered. A p-value <0.05 was considered statistically significant (Figure 1).

Figure 1.

Figure 1

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Flow chart for bioinformatics from TCGA database using GEPIA (A) and UALCAN (B) platform. TCGA: The Cancer Genome Atlas; GEPIA: Gene Expression Profiling Interactive Analysis; UALCAN: University of Alabama at Birmingham Cancer Data Analytics Portal.

Analysis for protein expression of ANLN in pancreatic adenocarcinoma tissues. To investigate protein levels of ANLN in PAAD tissues, UALCAN (21) was used. Protein levels of ANLN in cancer tissues of PAAD patients were investigated from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) PAAD dataset using UALCAN platforms. In the CPTAC database, the protein name “ANLN” was entered. A p-value <0.05 was considered statistically significant.

Survival analysis according to mRNA expression levels of ANLN in pancreatic adenocarcinoma tissues. Survival analysis was performed to examine ANLN expression in PAAD tissues using UALCAN and GEPIA platforms. The gene name “ANLN” was entered into the TCGA database, and a median cutoff was selected to generate Kaplan-Meier curves for PAAD patients. A p-value <0.05 was considered statistically significant.

Results

ANLN mRNA expression was increased in pancreatic adenocarcinoma tissues. To assess whether ANLN mRNA expression is increased in PAAD tissues, we analyzed the TCGA dataset using the GEPIA platform. The results showed that the expression of ANLN mRNA was increased in PAAD tissues (n=179) compared with normal tissues (n=171) (p<0.05) (Figure 2). We then analyzed the mRNA expression of ANLN in PAAD tissues using UALCAN. The result was similar to those from analysis using GEPIA. The mRNA expression of ANLN in PAAD tissues (n=178) was significantly higher than that in normal pancreatic tissues (n=4) (p<1E-12) (Figure 3A).

Figure 2.

Figure 2

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ANLN mRNA expression analysis for pancreatic adenocarcinoma tissues from TCGA database using GEPIA platform. The boxplots were downloaded from the GEPIA based on TCGA PAAD dataset. The right box represents normal pancreatic tissues (n=171), wherein the left box represents PAAD tissues (n=179). p<0.05 was regarded as statistically significant. ANLN: Anillin actin-binding protein; TCGA: The Cancer Genome Atlas; GEPIA: Gene Expression Profiling Interactive Analysis; PAAD: pancreatic adenocarcinoma.

Figure 3.

Figure 3

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ANLN mRNA and protein expression analysis for pancreatic adenocarcinoma tissues from TCGA and CPTAC databases using the UALCAN platform. (A) The boxplots were downloaded from the UALCAN based on TCGA PAAD dataset. The left box represents ANLN mRNA expression in normal pancreatic tissues (n=4), wherein the right box represents ANLN mRNA expression in pancreatic adenocarcinoma tissues (n=178) (p<1E-12). p<0.05 was regarded as statistically significant. (B) The boxplots were downloaded from UALCAN based on CPTAC PAAD dataset. The left box represents ANLN protein expression in normal pancreatic tissues (n=74), wherein the right box represents ANLN protein expression in pancreatic adenocarcinoma tissues (n=137) (p=4.26941959587804E-172). p<0.05 was regarded as statistically significant. ANLN: Anillin actin-binding protein; CPTAC: Clinical Proteomic Tumor Analysis Consortium; TCGA: The Cancer Genome Atlas; GEPIA: Gene Expression Profiling Interactive Analysis; PAAD: pancreatic adenocarcinoma; UALCAN: University of Alabama at Birmingham Cancer Data Analytics Portal.

The protein expression levels of ANLN were increased in pancreatic adenocarcinoma tissues. To assess whether the protein expression level of ANLN is increased in PAAD tissues, we analyzed the CPTAC dataset using UALCAN platform. The results showed that the protein levels of ANLN were increased in PAAD tissues (n=137) compared to normal tissues (n=74) (p=4.26941959587804E-172) (Figure 3B).

High levels of ANLN expression in pancreatic adenocarcinoma tissues are correlated with poor patient prognosis. Kaplan-Meier survival plots of patients with high and low/medium ANLN expression levels in PAAD tissues were generated using UALCAN platform. The results showed that higher ANLN expression levels in PAAD tissues were correlated with poor patient survival with PAAD (p=0.00019) (Figure 4). We then used GEPIA platform to analyze Kaplan-Meier overall survival and disease-free survival plots for patients with high and low ANLN expression levels in PAAD tissues. The results showed that higher ANLN expression levels in PAAD tissues were correlated with both poor PAAD patient overall survival (p=0.013) and poor disease-free survival (p=0.0003) (Figure 5).

Figure 4.

Figure 4

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Kaplan–Meier survival plots of patients with pancreatic adenocarcinoma with higher ANLN levels. The overall survival analysis of patients with PAAD according to ANLN expression was performed by using the UALCAN platform. The overall survival curve of patients with PAAD was compared between a high ANLN expression group (▲, n=45) and a low/medium DDX39 expression group (n=132). p<0.05 was regarded as statistically significant. ANLN: Anillin actin-binding protein; PAAD: pancreatic adenocarcinoma; UALCAN: University of Alabama at Birmingham Cancer Data Analytics Portal.

Figure 5.

Figure 5

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Kaplan–Meier survival plots of patients with pancreatic adenocarcinoma with higher ANLN levels. (A) Overall survival analysis and (B) disease-free survival analysis based on ANLN expression were performed by using the GEPIA platform. Overall survival and disease-free survival curves of PAAD patients were compared between the high ANLN expression group (▲, n=89) and the low ANLN expression group (n=89). p<0.05 was regarded as statistically significant. ANLN: Anillin actin-binding protein; GEPIA: Gene Expression Profiling Interactive Analysis; PAAD: pancreatic adenocarcinoma.

Discussion

In this study, the TCGA database was analyzed by using the UALCAN and GEPIA bioinformatics platforms to analyze ANLN mRNA expression, ANLN protein expression, and Kaplan-Meier survival in patients with PAAD. The results showed that the expression levels of ANLN mRNA and protein were significantly higher in PAAD tissues compared with normal tissues. Furthermore, PAAD patients with high ANLN mRNA expression showed shorter overall survival and disease-free survival compared to patients without high ANLN mRNA expression. These results suggest that ANLN is highly expressed in PAAD tissues, both in terms of mRNA and its translation product, the protein, and that this expression has a negative impact on the prognosis of patients.

ANLN is an actin-binding protein involved in cytokinesis. Thus, ANLN is required for correct cell division. There is no doubt that it is an essential molecule for cancer cells to continue dividing and growing. It has been reported that ANLN expression is increased in cancer tissues such as prostate cancer, oral squamous cell carcinoma, hepatocellular carcinoma (HCC), bladder urothelial carcinoma, gastric cancer, pancreatic cancer, and colorectal cancer. Furthermore, high expression of ANLN in these cancer tissues was closely correlated with poor prognosis of cancer patients and the progression of malignant transformation of cancer cells (14-20,22,23). However, our analysis of the TCGA database using the UALCAN and GEPIA platforms revealed that increased expression of ANLN mRNA in cancer tissues was associated with significantly worse patient prognosis in five cancer types: PAAD, HCC, lung adenocarcinoma, renal clear cell carcinoma, and adrenocortical carcinoma. In prostate cancer, GEPIA analysis showed no significant increase in mRNA expression of ANLN in cancer tissues and no worsening of prognosis due to increased ANLN mRNA expression was observed. In bladder urothelial carcinoma, although increased ANLN mRNA expression was significantly associated with worsening of prognosis, UALCAN analysis showed no significant increase in ANLN mRNA expression. In gastric cancer and colorectal cancer, although significant increase in expression was observed in cancer tissues, no worsening of prognosis due to increased ANLN mRNA expression was observed. This difference is likely due to the database.

What is the mechanism by which anillin actin-binding protein is involved in the progression of malignant transformation of cancer cells? Shan et al. reported that knockdown of ANLN in clear cell renal cell carcinoma cells reduced proliferation, migration, invasion, and EMT, and the use of a PI3K/AKT pathway inhibitor suppressed the invasive behavior of clear cell renal cell carcinoma cells. This suggests that anillin actin-binding protein may activate the PI3K/AKT pathway to enhance proliferation, migration, and invasion (24). Furthermore, Yu et al. reported that anillin actin-binding protein directly interacted with RhoA, facilitating its activation and subsequent stimulation of the PI3K/AKT signaling pathway (25). Su et al. reported that a long non-coding RNA HOXC-AS1 promotes the malignancy by sponging miR-195-5p with anillin actin-binding protein in esophageal cancer (26). Liu et al. also showed that anillin actin-binding protein can stabilize the proto-oncogene c-Myc and activate the MAPK signaling pathway via IGF2BP1 in prostate cancer cells (27). Hao et al. reported that E2F7 promotes the proliferation of HCC cells by suppressing the transcription of miR-383-5p, which in turn promotes the SP1/SOX4/Anillin axis (28). On the other hand, Chen et al. showed that ANLN functions as an oncogene in bladder urothelial carcinoma cells by activating the JNK signaling pathway (17). In any case, it has been suggested that anillin actin-binding protein may be involved in the progression of malignant transformation of cancer cells by activating several pathways.

Now, we know that anillin actin-binding protein is highly expressed in PAAD tissues, is involved in the malignant transformation of PAAD cells, and worsens the patient’s prognosis, but is it possible to detect highly expressed anillin actin-binding protein in blood and other samples and use it as a prognostic factor for patients? Kim et al. applied triple quadrupole mass spectrometry-based multiple reaction monitoring (MRM) to identify anillin actin-binding protein in individual serum samples from HCC patients (29). If anillin actin-binding protein could be quantitatively detected in the serum of patients with PAAD, it may be possible to predict prognosis without invasive clinical testing, which would be extremely convenient for patients.

Further studies are needed to clarify the exact mechanism by which anillin-actin-binding protein promotes the progression of PAAD and explore the possibility that anillin-actin-binding protein in the serum of PAAD patients can serve as a prognostic biomarker for PAAD.

Conflicts of Interest

The Authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Authors' Contributions

All Authors contributed to the conception and design of the study. Data collection and analysis were performed by Shin-nosuke Yamashita, Yoshiatsu Tanaka, Shajedul Islam and Yasuhiro Kuramitsu. Shin-nosuke Yamashita and Yoshiatsu Tanaka wrote the first draft of the manuscript, Takao Kitagawa and Yasuhiro Kuramitsu commented on an earlier version of the manuscript. All Authors read and approved the final manuscript.

Artificial Intelligence (AI) Disclosure

No artificial intelligence (AI) tools, including large language models or machine learning software, were used in the preparation, analysis, or presentation of this manuscript.

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