Research ArticleExperimental Studies
Open Access

Integrated Bioinformatics and Experimental Analysis of Argonaute Family Members in Pancreatic Adenocarcinoma

OZCAN GULBEY and TUGCE DURAN
In Vivo January 2026, 40 (1) 123-135; DOI: https://doi.org/10.21873/invivo.14178

Abstract

Background/Aim: Pancreatic adenocarcinoma (PAAD) is an aggressive cancer type with high mortality rates. The Argonaute (AGO) gene/protein family is an evolutionary conserved family, which is responsible for post-transcriptional regulation of gene expression. Despite the fact that this family members (AGO1-4) have been linked to prognosis in some cancers, they have not been comprehensively investigated in PAAD. Therefore, this study investigates the role of AGO family members on PAAD.

Materials and Methods: In our research, bioinformatics analyses were performed to study gene, protein and methylation levels, prognostic importance, gene-gene and protein-protein interactions, enrichment analysis, and immune infiltration analysis, using online and publicly available platforms. Additionally, real-time PCR was used to check mRNA levels in the pancreatic cell line BxPC-3.

Results: mRNA (p<0.05), protein (p<0.001) and methylation (p<0.001) levels of AGO2 were statistically different between normal and tumor samples in the in silico and laboratory analyses, and high AGO2 levels were found to be linked to poor prognosis (p=0.037). Additionally, immune infiltration analysis demonstrated a close relationship between AGO2 mRNA expression and immune cells. In contrast to the consistent results of AGO2, other AGO family members (AGO1, AGO3, or AGO4) differed at the protein or methylation levels but had non-significant prognostic values.

Conclusion: The findings of this study indicate the potential importance of AGO2 in terms of biological functions and prognostication in PAAD.

Keywords:

Introduction

Pancreatic adenocarcinoma (PAAD) is a solid cancer type and is the most common form of pancreatic cancer (1). The incidence of PAAD has increased over the last decades (2), and it is expected that PAAD will be one of the most fatal cancer types by 2030 in the US (3). Although surgical resection, chemotherapy, radiotherapy, and targeted therapy exist for patients with PAAD, they still have very poor clinical outcomes due to late diagnosis (4, 5). Therefore, it is vital to identify biological and clinical biomarkers for early detection, prognostication, and treatment stratification in PAAD.

Argonaute (AGO, previously EIF2C) gene family expresses four different proteins in humans: AGO1, AGO2, AGO3, and AGO4. They are highly conserved and play important roles in post-transcriptional regulation of gene expression via gene-silencing mechanisms. Members of the AGO protein family are an essential element of RNA-induced silencing complex (RISC), which is a multi-protein complex functioning for gene silencing (6), and dysregulation of AGO family members has been associated with poor prognosis in some cancers. For example, high expression of AGO2 was related to an increased relapse rate and lower recurrence-free survival in estrogen receptor alpha-positive breast cancer (7). Also, increased expression levels of AGO2, AGO3 and AGO4 were correlated with metastasis in colon cancer, and a positive correlation was found between high expression of AGO1 and occurrence of colon cancer (8).

Radiotherapy and immunotherapy have not shown satisfactory results, so surgery is currently the only potentially curative treatment option in PAAD. Therefore, there is an urgent need to identify biomarkers for more effective therapies and treatment strategies. In our study, we investigated the gene and protein expression of the AGO family members in PAAD to examine their potential biological and/or prognostic impacts.

Materials and Methods

Gene expression levels in PAAD data. The GEPIA2 web tool (9) (http://gepia2.cancer-pku.cn) was used to compare gene expression levels of AGO1, AGO2, AGO3, and AGO4 between normal and tumor tissues. On this platform, box plots were generated using TCGA normal and GTEx data via the “Expression DIY” module in the PAAD cohort (normal sample n=171 vs. tumor sample n=179). The following settings were used on the online tool: |log2FC| cutoff:1 and p-value (p) cutoff: 0.05. log2(TPM+1) transformed values were used for differential analysis, and the difference of median (Tumor) – median (Normal) was defined as log2FC. The comparison results were statistically evaluated using one-way ANOVA followed by Tukey’s test on the GEPIA2 tool.

Gene expression levels in pancreatic adenocarcinoma cell line (BxPC-3). BxPC-3 pancreatic adenocarcinoma (CRL-1687™) and HEK293 human embryonic kidney cells were obtained from ATCC and cultured in DMEM with 10% FBS (Biochrome, Germany) and 1% penicillin/streptomycin (Sigma-Aldrich, St. Louis, MO, USA) at 37 °C in 5% CO2. At ~80-90% confluency, cells were detached with 0.05% (w/v) trypsin-EDTA, and total RNA was isolated using TRIzol™ reagent (Invitrogen, Carlsbad, CA, USA). All RNA concentrations were adjusted (0.1 ng-5 μg), and cDNA was synthesized with the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, Waltham, MA, USA). Expression of AGO1-4 genes was measured by QuantStudio3™ qPCR system (Thermo Fisher Scientific) using SYBR Green I Master Mix (Roche Diagnostics, Rotkreuz, Switzerland) and specific primers: AGO1 F: AGAGTGACTTTCCCAGGCTC, R: AATCCTCTCACATGGGC CAA; AGO2 F: CGCCCCAATTTCTCCATGAG, R: CATCGAAA CCCCAAACAGCA; AGO3 F: TCCCAGTTCCTAGTCAAGCG, R: CGAATTGCCTAAGGACACGG; AGO4 F: GCTCACGCCTGTAA TTCCAG, R: ATTACAGGCATCCACCACCA; GAPDH F: CCG TCTAGAAAAACCTGCC, R: GGAGGAGTGGGTGTCGCTGT. GAPDH was used as a housekeeping gene. Reactions were run for 40 cycles (95 °C, 5 min; 57-60 °C, 30 s; 72 °C, 1 min), and relative expression was calculated using the ∆∆Ct method (10), with all reactions performed in triplicate.

Levels of protein expression and methylation in PAAD data. Jitter plots were generated using the UALCAN (11) web tool (https://ualcan.path.uab.edu/) for the comparison of protein expression levels of the AGO protein family members between normal (n=74) and primary tumor (n =137) samples in PAAD cohort. “Proteomics” and “total-protein” modules were selected for the analysis on this platform, using Clinical Proteomic Tumor Analysis Consortium (CPTAC) data. Z-values in the jitter plots indicate standard deviations from the median across samples. Additionally, the protein expression levels were compared to tumor grades on this platform.

Comparison of promoter DNA methylation levels between normal (n=10) and primary tumor (n=184) samples was done using “TCGA” and “methylation” modules on the UALCAN platform, and beta values indicate the estimation of methylation degree (higher beta values correspond to higher methylation levels). The independent t-test was automatically performed for comparisons on the platform.

Survival analysis. Disease-free survival and overall survival analyses were performed on the GEPIA2 platform (9). Patients with PAAD were categorized into two groups based on gene expression levels: Low expression groups (tercile ≤33.3%) and high expression groups (tercile ≥66.6%). The log-rank test was used to compare survival differences.

Gene-gene and protein-protein interaction networks. Gene-gene interaction network was constructed using the GeneMANIA web tool (12) (https://genemania.org/). The STRING tool (13) (https://string-db.org/) was used to construct a protein-protein interaction network, limited to the organism of Homo sapiens and 20 interactors. The setting of interaction score was adjusted to the highest level (0.900) for the network confidence.

Gene Ontology (GO) enrichment analysis. GO analysis was performed using the “Functional analysis” module on the TNMplot platform (14) (https://tnmplot.com/analysis/). Common interactors between the gene-gene and protein-protein interaction networks were included in enrichment analysis for the identification of biological processes, molecular functions, and cellular components.

Immune infiltration analysis. The Guolab web tool (15) (https://guolab.wchscu.cn/GSCA/#/) was used to estimate the interaction between the expression level of AGO2 and immune cells, using Spearman’s correlation test, which generates a coefficient that is an indicator for correlation level/direction.

Statistical analysis. Comparison and correlation tests (one-way ANOVA followed by Tukey’s test, independent t-test, Spearman’s correlation) were used on the online bioinformatics tools of interest, and the log-rank test was performed to check significance level of survival analyses. p<0.05 was considered to be statistically significant in all analyses performed in our research.

Results

AGO gene and protein expression levels. PAAD data derived from GTEx and TCGA samples were used to compare mRNA expression levels of the AGO gene family in pancreatic adenocarcinoma. Only AGO2 was highly expressed in patients with PAAD (p<0.05), but not AGO1, AGO3 or AGO4 (Figure 1A). The laboratory results confirmed that mRNA expression levels in BxPC-3 cells were upregulated in AGO1 [log2 fold change (log2FC)=4.9, p=0.005], AGO2 (log2FC=4.0, p=0.042), and AGO3 (log2FC=6.4, p<0.001), compared to the control cell line (HEK293). In contrast, AGO4 was downregulated in BxPC-3 cell line (log2FC=−2.6, p=0.004) (Figure 1B). On the other hand, data from CPTAC showed that expression levels of AGO protein family significantly differed between tumor and normal samples (p<0.001 for all members). AGO1 protein expression level decreased in PAAD samples, while the protein expression levels of other members increased in those with PAAD, compared to normal samples (Figure 2A). In addition, the protein expression levels of AGO family members were associated with tumor grades compared to normal stage; however, there was no statistically significant difference among the tumor grades (Figure 2B). Although the sample size is small (n=10) in The Cancer Genome Atlas (TCGA) control data for the comparison of DNA methylation levels using the UALCAN tool, promoter methylation levels of AGO1-3 were statistically higher in PAAD samples than in healthy individuals (Figure 3).

Figure 1.
Figure 1.

AGO gene family in pancreatic adenocarcinoma (PAAD). (A) The levels of mRNA expression of AGO family members were compared between normal (N) and tumor (T) samples using the GEPIA2 platform, evaluated with one-way ANOVA followed by Tukey’s test. (B) The log2 fold change at expression levels of AGO gene family in BxPC-3 were compared to the HEK293 (control) group. The ∆∆Ct method was used for the calculation of expression levels and comparison in qPCR experiments. (*p<0.05; num, number).

Figure 2.
Figure 2.
Figure 2.

Protein levels of AGO family members in PAAD using the UALCAN platform. (A) The expressed protein levels of AGO family members were compared between normal and tumor samples. (B) The protein levels are shown among tumor grades, compared with normal samples. Z-value shows the level of protein expression. The independent t-test was performed for evaluation of statistical significance. PAAD, Pancreatic adenocarcinoma; CPTAC, Clinical Proteomic Tumor Analysis Consortium.

Figure 3.
Figure 3.

DNA promoter methylation levels of AGO family members. Beta value reflects the methylation level (higher scores correspond to higher methylation levels). The graphs were generated on the UALCAN platform by using the independent t-test (The Cancer Genome Atlas).

Survival analysis of AGO expression levels. After demonstrating gene/protein expression levels of AGO family members in PAAD, survival analysis was performed using Kaplan-Meier curve to check the prognostic value of transcriptional levels. Patients with PAAD were categorized to the following two groups based on terciles: low-expression group (≤33.3) and high-expression group (≥66.6). High expression of AGO2 was statistically associated with poor prognosis in overall survival [low (n=59) vs. high (n=60), p=0.037], but not in disease-free survival [low (n=59) vs. high (n=60), p=0.37] (Figure 4). Expression levels of other AGO family members (AGO1, AGO3, and AGO4) were not significantly correlated with either disease-free survival (Figure 4A) or overall survival (Figure 4B).

Figure 4.
Figure 4.

Prognosis of patients with low and high mRNA expression levels of AGO family members. The cut-off of patient groups with PAAD was defined based on terciles [low group (≤33.3%) vs. high group (≥66.6%)] in disease-free (A) and overall survival (B) analyses. Kaplan-Meier graphs were generated using GEPIA2 platform and the significance of difference was evaluated using the log-rank test. PAAD, Pancreatic adenocarcinoma; n, number.

Gene-gene and protein-protein interaction networks of AGO2. The previous analyses showed that AGO2 exhibited both differential expression and prognostic significance in PAAD; therefore, we further investigated the gene-gene and protein-protein interactions of AGO2, using the GeneMANIA and STRING platforms, respectively. Analysis of the gene-gene interaction network of AGO2 revealed the following 20 genes: DICER1, TARBP2, AGO1, AGO3, TNRC6C, AGO4, TNRC6B, PIWIL4, TNRC6A, PIWIL1, PRKRA, UBC, NLK, MOV10, GMPS, FXR1, APOBEC3A, APOBEC3C, TNF, and DDX6 (Figure 5A). Analysis of the protein-protein interaction network also reported 20 proteins, which interacted with the AGO2 protein: TARBP2, GEMIN4, DHX9, DDX20, AGO1, TNRC6A, DICER1, DDX6, FMR1, TNRC6B, HSP90AA1, AGO3, ELAVL1, MOV10, FXR1, DROSHA, NPM1, TNRC6C, HSP90AB1, and EIF4E (Figure 5B). The common interactors obtained by comparing the gene-gene and protein-protein networks were DICER1, TARBP2, AGO1, AGO3, TNRC6A, TNRC6B, TNRC6C, MOV10, FXR1, which were investigated for enrichment analysis below.

Figure 5.
Figure 5.
Figure 5.

Gene-gene and protein-protein interactions of AGO2 and the predicted functions of common interactors between the gene-gene and protein-protein interaction networks of AGO2. AGO2 interacted with 20 genes (A) and 20 proteins (B), predicted by the GeneMANIA and STRING platforms. Nine common interactors overlapping between gene-gene (A) and protein-protein (B) interactions of AGO2 were included in GO enrichment analysis performed by TNMplot platform for the information about biological process, molecular functions and cellular component of the interactors (C). GO, Gene Ontology.

GO enrichment analysis of the common interactors. GO enrichment analysis was used to detect biological processes, molecular functions, and cellular components of the nine common interactors identified by the comparison result of the interaction networks. The TNMplot platform demonstrated that the common interactors were mainly correlated with gene silencing, negative and positive regulations, and RISC complex. They were also involved in RNA binding and endonuclease activities. Additionally, these common interactors were associated with the following cellular components: intracellular membrane, nucleus, RISC, and endoribonuclease complexes (Figure 5C).

Correlation between AGO2 expression and immune infiltration. The Guolab platform was used to investigate the correlation between AGO2 expression level and immune cell infiltration. The mRNA expression level of AGO2 was significantly and positively associated with natural T regulatory (nTreg) cells [correlation (cor)=0.39, p<0.001]; monocyte (cor=0.33, p<0.001), induced T regulatory (iTreg) cells (cor=0.30, p<0.001), dendritic cell (DC) (cor=0.22, p=0.003), central memory cells (cor=0.19, p=0.012), and Type 1 regulatory (Tr1) cells (cor=0.16, p=0.03) (Figure 6). On the other hand, the following immune cells were significantly and negatively correlated with AGO2 mRNA expression: gamma-delta cells (cor=−0.34, p<0.001), mucosal-associated invariant T (MAIT) cells (cor=−0.29, p<0.001), CD4+ T cells (cor=−0.28, p<0.001), CD8+ T cells (cor=−0.27, p<0.001), and natural killer (NK) cells (cor=−0.25, p=0.001) (Figure 6).

Figure 6.
Figure 6.

Correlation between mRNA expression levels of AGO2 and immune cells in PAAD. Correlation graphs and scores were generated using the Guolab platform. PAAD, Pancreatic adenocarcinoma; cor, correlation; FDR, false discovery rate; nTreg, natural T regulatory; iTreg, induced T regulatory; DC, dendritic cell; Tr1, Type 1 regulatory; MAIT, mucosal-associated invariant T; CD, cluster of differentiation; NK, natural killer.

Discussion

PAAD has a high mortality rate because of tumor-related deaths (4, 16). Despite the achievements in the detection techniques and therapy, patients with PAAD still have very poor prognosis with a 5-year overall survival rate of around 10% (17). Effective diagnostic and prognostic biomarkers are urgently required for the improvement of prognosis of these patients (18).

Argonaute (AGO, previously EIF2C) gene family is highly conserved in humans and has four members: AGO1, AGO2, AGO3, and AGO4, which play vital roles in mRNA gene-silencing mechanism via the RISC complex (19). In the literature, some studies found that aberrant expression of these family members was associated with poor prognosis and occurrence in some cancers (7, 8). Unfortunately, functions of AGO family members are not comprehensively investigated in PAAD. Therefore, our research aimed to study the biological and clinical effects of AGO family members in PAAD in terms of four different perspectives: (a) mRNA, protein, and promoter DNA methylation levels, (b) correlation of tumor grades and survival analysis, (c) gene-gene and protein-protein interactions and pathway analysis, and (d) immune infiltration. Overall, we showed that AGO2 had the most consistent levels of mRNA, protein, and promoter DNA methylation in PAAD samples when compared to normal samples, using bioinformatics and experimental analyses (Figure 1, Figure 2, Figure 3). However, the rest of the family members (AGO1, AGO3, or AGO4) differed at mRNA, protein, and methylation levels (Figure 1, Figure 2, Figure 3). These expression and methylation results suggest that dysregulation of AGO family members can be due to post-transcriptional or epigenetic regulations other than typical transcriptional regulations in PAAD.

In context of clinical perspective, there was a statistically significant difference at the protein expression levels between normal samples and tumor grades of PAAD samples, but no significant difference among tumor grades (Figure 2B). Yang and co-workers reported that high expression levels of AGO2 were significantly correlated with histological grade in urothelial carcinoma of the bladder (20). Also, high AGO2 expression was statistically higher in high-grade tumor samples compared to low-grade tumor samples in glioma cancer (21). On the other hand, disease-free survival analysis revealed non-significant results for all members of the AGO family (Figure 4A). However, PAAD patients with high mRNA expression levels of AGO2 had lower overall survival compared to those with low mRNA expression levels (Figure 4B). Low and high mRNA expression levels of AGO1, AGO3 and AGO4 did not show statistically significant differences in overall survival (Figure 4B). These results show that only AGO2 might have clinical importance rather than other family members in PAAD. Other studies support the evidence that AGO2 can be prognostic in some cancers. For instance, Sunnetci-Akkoyunlu and co-workers identified AGO2 among the top dysregulated transcription factors, which were common between periodontitis and pancreatic cancer (22). Asai et al. reported in vitro results indicating that AGO2 can directly regulate angiogenesis in carcinomas (23). Zhang and co-workers reported that lung cancer patients who had a high expression level of AGO2 experienced a lower survival rate compared to those with low AGO2 expression (24). Additionally, patients with high AGO2 expression had lower survival rates than those with low AGO2 expression in urothelial carcinoma of the bladder (20) and gliomas (21).

Among AGO family members, only AGO2 was both differentially expressed and prognostically significant in PAAD data; therefore, we further investigated the gene-gene and protein-protein interactions of AGO2 for the identification of common interactors between these interaction networks (Figure 5A, B). Nine common interactors (DICER1, TARBP2, AGO1, AGO3, TNRC6A, TNRC6B, TNRC6C, MOV10, and FXR1) were identified and then involved in GO enrichment analysis for the investigation of functions in the cells (Figure 5C). The most enriched biological processes, molecular functions and cellular components were RNA binding (GO: 0003723), RNA-mediated gene silencing (GO: 0031047), and intracellular membrane (GO: 0043231), respectively. It is well-known that these common interactors are associated with AGO proteins in RNA-related processes, as reported in the literature (25, 26). Ikeda and colleagues developed a monoclonal antibody 4F9 to capture AGO2-related miRNAs (27), so the possible interactions and activities of the AGO2 protein in PAAD might be further investigated for potential drug development using this antibody.

Immune infiltration analysis demonstrated that immune cells were correlated with the mRNA expression levels of AGO2 (Figure 6). Monocytes, nTreg, and iTreg cells were significantly and positively correlated, with a correlation score of ≥0.30 while gamma-delta, MAIT, CD4+, CD8+, and NK cells were significantly and negatively correlated with a correlation score of ≥−25. Our findings might suggest that AGO2 expression might be an indicator of immunological response in PAAD. A study reported by Wang et al. confirmed that AGO2 suppressed CD8+ cytotoxicity, and its overexpression was related to immunotherapy failure (28).

Study limitations. The main limitation of this study is that the data used for the bioinformatics analyses were collected from online databases. Another limitation is the lack of control pancreatic cell line as HEK293 human embryonic kidney cell line was used to compare expression levels of the AGO family members in the real-time PCR analysis. Additionally, mRNA levels of the family members were assessed using real-time PCR; however, in vitro and in vivo methods could not be performed in our study to determine protein levels. To validate our research for the verification of the biological and clinical roles of AGO family members, additional in vitro and in vivo experiments are needed in PAAD.

Conclusion

The bioinformatics analyses and laboratory results revealed that AGO2 is both differentially expressed and prognostically significant in PAAD. AGO1, AGO3, and AGO4 differed only at mRNA expression levels (measured by real-time PCR), protein levels, and methylation status, but did not show prognostic significance. AGO2 and its interacting partners might offer new insights into the mechanisms of RNA silencing in PAAD and can serve as targets for the development of potential treatments. Consequently, further research is required for the investigation of AGO2 and its related interactions in pancreatic cancer, specifically pancreatic adenocarcinoma.

Acknowledgements

This study was supported by the Ministry of National Education, Republic of Türkiye [International Graduate Education Scholarship (YLSY)].

Footnotes

  • Authors’ Contributions

    Conceptualization: OG. Formal analysis: OG & TD. Methodology: OG & TD. Writing - original draft: OG & TD. Writing - review & editing: OG and TD.

  • Conflicts of Interest

    The Authors declare that they have no conflicts of interest.

  • 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.

  • Received September 26, 2025.
  • Revision received October 22, 2025.
  • Accepted October 29, 2025.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

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Integrated Bioinformatics and Experimental Analysis of Argonaute Family Members in Pancreatic Adenocarcinoma
OZCAN GULBEY, TUGCE DURAN
In Vivo Jan 2026, 40 (1) 123-135; DOI: 10.21873/invivo.14178
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