CAPG serves as a prognostic biomarker and promotes proliferation and migration in pancreatic ductal adenocarcinoma

Figures

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  Fig 1. CAPG is highly expressed in clinical samples from PDAC patients. A–B: The gene expression levels of CAPG across various tissues were analyzed using the GEPIA2 and GENT2 platforms, comparing tumor tissues with adjacent non-tumor tissues. P-values below 0.05 indicate statistical significance. C: Differential expression of CAPG between PDAC tumor tissues and adjacent non-tumor tissues was assessed using data from the GEPIA2 and GSE183795 databases. The GEPIA2 expression data were obtained from the TCGA dataset. D: A differential gene expression analysis was performed using GEO2R on the GSE183795 dataset, and the results were visualized as a volcano plot. The location of CAPG is indicated on the plot. E–F: A dot plot illustrates CAPG expression under different T-stages (data sourced from TCGA; ANOVA summary: F = 1.644, P = 0.1813). The violin plot, generated via GEPIA2, displays CAPG expression across various pathological stages. G: The promoter methylation status of CAPG across different stages of pancreatic cancer was analyzed using the UALCAN platform, with p-values shown in the accompanying table. H: CAPG promoter methylation levels were compared between pancreatic cancer cells…

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  Fig 2. Correlation Between CAPG Expression and Functional Enrichment Scores in Cancer Cells. A–B: The biological processes (BP) and molecular functions (MF) most strongly associated with CAPG expression were identified using the GEO (A) and TCGA (B) datasets. C: A heatmap displays the correlations between CAPG expression and enrichment scores of various cellular functions in the GEO and TCGA datasets, as determined by Gene Set Variation Analysis (GSVA).

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  Fig 3. High CAPG Expression Is Associated with Shorter Overall Survival in Pancreatic Cancer (PDAC). A–C: Kaplan-Meier survival analysis was performed to assess the impact of CAPG expression on disease-free survival (A) and overall survival (B) in PDAC patients, using data from the TCGA database, as well as the GEO database (C). Red: high CAPG expression; Blue: low CAPG expression. D: Univariate analysis was conducted to evaluate prognostic factors, including age, lymph node metastasis, tumor stage, and treatment modalities, using the TCGA database. E: Immunohistochemistry (IHC) staining was used to detect CAPG expression in PDAC tumors and adjacent normal tissues. Representative images are shown. Quantitative analysis summarizes data from 5 paired samples; three fields of view were selected for each sample, resulting in a total of 15 paired images analyzed. Statistical significance was calculated using a t-test (***p < 0.001).

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  Fig 4. Inhibition of Pancreatic Cancer (PDAC) Cell Proliferation by CAPG Knockdown. A: Western blot analysis was performed to examine CAPG expression levels in HPNE, PANC-1, and AsPC-1 cell lines. B: Western blot analysis was conducted to evaluate CAPG protein levels, with β-actin used as a loading control. The results were quantified and presented in a bar plot. C: Quantitative RT-PCR was used to measure CAPG mRNA expression. D: Cell proliferation was assessed at various time points using the CCK-8 assay. E: Flow cytometry analysis was performed to evaluate cell proliferation via Ki67 staining. Representative images and corresponding bar plots depict the Mean Fluorescence Intensity (MFI) of Ki67 expression in each cell line. Statistical analyses were performed using one-way ANOVA for panels B, C, and E, and a t-test for panel D. Significance is indicated as follows: *p < 0.01; ***p < 0.001.

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  Fig 5. CAPG Promotes Migration and Its Knockdown Sensitizes Pancreatic Cancer Cells to Gemcitabine-induced apoptosis. A–B: A wound healing assay was performed to assess the migratory capacity of PANC-1 and AsPC-1 cells following CAPG knockdown. Images were captured at 0 and 12 hours to visualize wound closure, and the migration rates were quantified and shown in bar plots. C–D: After 24-hour treatment with gemcitabine (GEM, 10 nM), apoptotic cells in PANC-1 and AsPC-1 lines were detected using an Annexin V/PI staining kit. Representative flow cytometry plots and corresponding bar graphs display the percentage of apoptotic cells in each group. Data are presented as mean ± SD. Statistical analyses were performed using one-way ANOVA, with significance indicated as *p < 0.01, ***p < 0.001.

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  Fig 6. CAPG Knockdown Reduces ERK1/2 Phosphorylation and Cyclin D1 Expression. A: GSEA enrichment plots show that MAPK3-related gene sets are significantly enriched in the CAPG high- and low-expression groups within the GEO dataset. B: Western blot analysis was used to assess the expression of phosphorylated ERK (p-ERK) and Cyclin D in PANC-1 and AsPC-1 cells following CAPG knockout, with β-actin as a loading control. Representative blot images and quantification data are provided. C: Cell proliferation was measured at various time points using the CCK-8 assay. D: The ERK1/2 inhibitor PD98059 (20 μM) was administered to PANC-1 and AsPC-1 cells, either alone or in combination with gemcitabine (GEM, 10 nM), for 24 hours. Apoptotic cells were analyzed by flow cytometry. Representative images and bar plots illustrate the percentage of apoptotic cells. Statistical analysis was performed using two-way ANOVA. Significance levels are indicated as *p < 0.01, ***p < 0.001.