Abstract
Objective: To explore the effects of baicalein on immune cell infiltration and tumor progression in pancreatic cancer by modulating DDX60 expression. Methods: RNA-seq data of pancreatic cancer and normal tissues were obtained from the UCSC XENA database. DDX60 expression differences and their associations with patient prognosis and immune infiltration were analyzed. Panc02 pancreatic cancer cells were treated with baicalein (0, 20, 40, 60 μmol/L) for 24, 48, and 72 hours. Cell viability was assessed by MTT assay, while apoptosis and DDX60 expression were evaluated by flow cytometry and RT-qPCR, respectively. In vivo, tumor-bearing mice received baicalein, and tumor volume, immune cell infiltration, and DDX60 expression in tumor tissues were assessed. Results: DDX60 expression was significantly upregulated in pancreatic cancer tissues compared to normal tissues (P < 0.05). Patients with low DDX60 had better survival (P < 0.05). DDX60 levels correlated significantly with multiple immune cell types, including DCs, eosinophils, macrophages, neutrophils, T cell subsets, and NK cells (P < 0.05). Baicalein inhibited Panc02 cell proliferation and induced apoptosis in a dose- and time-dependent manner (P < 0.05), accompanied by downregulation of DDX60 (P < 0.05). In vivo, baicalein significantly suppressed tumor growth and increased CD8+ T cells and macrophages in tumor tissues (P < 0.05). DDX60 expression decreased with increasing baicalein dosage (P < 0.05). Conclusion: Baicalein suppresses pancreatic cancer growth and promotes apoptosis, apparently through downregulation of DDX60 and modulation of immune responses in the tumor microenvironment.
Keywords: Baicalein, DDX60, pancreatic cancer, immune cell infiltration, cell proliferation, apoptosis
Introduction
Pancreatic cancer is one of the most lethal malignancies of the digestive system, with a steadily increasing incidence. According to the American Cancer Society, the 5-year survival rate for pancreatic cancer was only 11% in 2022, ranking it fourth in cancer-related mortality [1,2]. Its pathogenesis is complex and often insidious, so early-stage disease typically presents without obvious clinical symptoms. As a result, most patients are diagnosed at advanced stages, missing the window for curative surgical intervention. It has been reported that only 15-20% of patients are eligible for radical resection [3]. Moreover, abnormal immune cell infiltration within the tumor microenvironment (TME) plays a critical role in resistance to immunotherapy, with KRAS mutation-driven immunosuppressive networks being particularly prominent. Therefore, identifying novel therapeutic targets that modulate the immune microenvironment - especially through natural compounds - has become a major research focus.
Baicalein, a flavonoid extracted from the dried roots of Scutellaria baicalensis (family Lamiaceae), has demonstrated anti-invasive and anti-metastatic effects in various cancers, including gastric, lung, and liver malignancies. However, its precise antitumor mechanisms remain unclear [4,5]. To enhance therapeutic strategies for pancreatic cancer, this study investigated the inhibitory effects of baicalein on pancreatic cancer cells and preliminarily explored its underlying mechanisms. Using bioinformatic analysis, DDX60 was identified as a potential regulator of both cancer cell proliferation and immune infiltration. The study further assessed whether the antitumor activity of baicalein involved modulation of DDX60 expression.
Materials and methods
Database information
RNA-seq data in TPM format were obtained from UCSC XENA (https://xenabrowser.net/datapages/), uniformly processed using the Toil pipeline. The dataset included 167 GTEx normal tissue samples, 4 TCGA adjacent normal tissue samples, and 179 TCGA pancreatic tumor tissue samples.
Bioinformatic methods
Differential gene expression analysis was conducted using R packages: ggplot2 (v3.4.4), stats (v4.2.1), and car (v3.1-0). Statistical methods were selected based on data characteristics, and visualizations were generated using ggplot2.
Prognostic analysis was performed using the survival (v3.3.1), survminer (v0.4.9), and ggplot2 (v3.4.4) packages. The proportional hazards assumption was tested and Cox regression models were fitted. Results were visualized using survminer and ggplot2.
Immune infiltration analysis was conducted by correlating gene expression with immune cell infiltration matrix data. Results were visualized as lollipop plots and heatmaps using ggplot2.
Cell lines and animals
Panc02 mouse pancreatic cancer cells were obtained from the Committee for the Preservation of Typical Culture Collection, Chinese Academy of Sciences. SPF-grade male Kunming mice (18-22 g) were purchased from the Laboratory Animal Center of Chongqing Medical University.
Cell culture
Panc02 cells were cultured in DMEM high-glucose medium supplemented with 10% fetal bovine serum at 37°C in a humidified 5% CO2 incubator. Cells were passaged when confluence reached 70-80%.
MTT assay for cell growth inhibition
Panc02 cells in the logarithmic growth phase were digested with trypsin and resuspended into a single-cell suspension. Cells were seeded in 96-well plates at a density of 5 × 103 cells/200 μL per well. After attachment, cells were washed twice with PBS, and treated with 200 μL DMEM complete medium containing baicalein (CAS: 21967-41-9, Sigma, USA) at concentrations of 0, 5, 10, 20, 40, 60, 80, and 160 μmol/L. Each concentration was tested in five replicates. Cells were incubated for 24, 48, and 72 hours, and cell viability was assessed using an MTT Cell Proliferation and Cytotoxicity Assay Kit (Beyotime, Shanghai, China). After adding 20 μL of 5 g/L MTT solution to each well, plates were incubated for 4 hours. The supernatant was then removed, 150 μL of DMSO was added, and absorbance at 490 nm was measured using an automatic microplate reader. The growth inhibition rate was calculated as: Inhibition rate (%) = (1-AMedicated group/ABlank group) × 100%.
Flow cytometry for detection of apoptosis
Panc02 cells in the logarithmic growth phase were digested with trypsin and resuspended to form a single-cell suspension. Cells were seeded into 6-well plates at a density of 3 × 105 cells/well. After adherence, 2 mL of DMEM containing 0, 20, 40, or 80 μmol/L baicalein was added. After 48 hours of incubation, cells were harvested by trypsinization and kept at 4°C. Cells were centrifuged at 1500 rpm for 5 min, the supernatant was discarded, and the cells were washed twice with pre-chilled PBS. After another centrifugation, the pellet was resuspended in 200 μL of 1 × Binding Buffer. Annexin V-FITC (5 μL) was added, mixed, and incubated for 10 min at room temperature in the dark. PI (10 μL) was then added and incubated for an additional 5 min in the dark. Apoptosis was analyzed by flow cytometry. Each group was tested in duplicate.
Flow cytometry for cell proliferation analysis
Panc02 cells in the logarithmic phase were trypsinized to generate a single-cell suspension and seeded into 6-well plates at 3 × 105 cells/well. After adherence, cells were treated with 0, 20, 40, or 80 μmol/L baicalein in DMEM for 48 h. Cells were harvested, centrifuged at 1500 rpm for 5 min, and fixed in pre-chilled 75% ethanol overnight at 4°C. After washing with PBS and repeating centrifugation, 500 μL PI/RNase A staining solution (Kaiji Biotechnology, Jiangsu, China) was added. Cells were incubated for 30 min at room temperature in the dark. Cell cycle distribution was analyzed by flow cytometry using a 488 nm laser for red fluorescence detection. Each group included two replicates.
RT-qPCR for DDX60 mRNA expression
Panc02 cells were cultured as described above and then treated with 0, 20, 40, or 80 μmol/L baicalein for 48 h. Total RNA was extracted using TRIzol reagent according to the manufacturer’s instructions. RNA concentration and purity were assessed by UV spectrophotometry. cDNA was synthesized using a reverse transcription kit, and qPCR was performed using the following conditions: 95°C for 19 min; 40 cycles of 95°C for 15 s, 60°C for 30 s, and 65°C for 30 s. The following primers were used: DDX60: Forward: 5’-CGCAAGCCAGACAGTCCTACA-3’; Reverse: 5’-AAACATCGCCCTGTCTCACGGA-3’; GAPDH: Forward: 5’-CATCACTGCCACCCAGAAGACTG-3’; Reverse: 5’-ATGCCAGTGAGCTTCCCGTTCAG-3’.
Relative DDX60 expression was calculated using the 2-ΔΔCt method, with GAPDH as the reference gene. All experiments were repeated three times.
Tumor inoculation and animal grouping
Forty SPF-grade Kunming mice were housed under controlled conditions (25°C, 55% humidity, 12 h light/dark cycle) and acclimated for 3 days. Panc02 cells were prepared at 1 × 107 cells/mL, and 0.2 mL of the suspension was injected subcutaneously under the right forelimb armpit of each mouse. Mice were monitored daily for tumor development and local reactions. Tumor dimensions (length, width, and height) were measured with calipers, and volume was calculated as: Tumor volume (V) = length × width × height; Tumor formation was defined as nodules exceeding 6 mm × 5 mm × 5 mm.
After 7 days, 34 mice developed tumors and were randomized into four groups: control (n = 8), low-dose (10 mg/kg, n = 8), medium-dose (20 mg/kg, n = 9), and high-dose (40 mg/kg, n = 9). Mice were intraperitoneally injected with 0.2 mL of either normal saline or baicalein solution once daily. Tumor volume was measured on days 7, 14, and 21. On day 21, mice were anesthetized with 4-5% isoflurane and euthanized by cervical dislocation. Tumors were excised, weighed, and the tumor inhibition rate was calculated: Inhibition rate (%) = (V control - V treatment group)/V control group × 100%.
Flow cytometry analysis of immune cells in mouse tumor tissues
Tumor tissues (~1 × 1 cm3) from each mouse group were placed in 15 mL centrifuge tubes containing 3-5 mL digestion solution (5% DMEM, collagenase at 1 mg/mL, and DNase I at 200 μg/mL) and incubated at 37°C for 40 minutes. Digestion was stopped by adding 5 mL DMEM high-glucose medium with 10% FBS. The cell suspension was filtered through a 70 μm strainer, and any remaining tissue fragments were further dissociated using a 2 mL syringe. Cells were centrifuged at 400 g for 5 minutes at 4°C and resuspended in PBS to adjust the concentration to 1 × 107 cells/mL.
Aliquots of 100 μL cell suspension were stained with viability dye (1:1000 dilution) for 10 minutes at room temperature in the dark. After washing with 1 mL PBS and centrifugation, cells were resuspended in 100 μL PBS and incubated with 5 μL surface antibodies (CD3-BUV395, CD4-PerCP-Cy5.5, CD8-Alexa Fluor 700, CD11b-FITC, F4/80-BV421) for 30 minutes at room temperature in the dark, following manufacturer’s instructions. Cells were washed again and finally resuspended in 300 μL PBS for flow cytometry analysis.
Reagents used included Fixable Viability Dye eFluor™ 780 (eBioscience, USA), CD45-V500, CD3-BUV395, CD4-PerCP-Cy5.5 (BD Pharmingen, USA), CD8-Alexa Fluor 700 (eBioscience, USA), CD11b-FITC, and F4/80-BV421 (BioLegend, USA).
RT-qPCR for detection of DDX60 mRNA in tumor tissues
Tumor tissues from each group were collected, and total RNA was extracted using TRIzol reagent (Invitrogen, USA). RT-qPCR was performed to assess the relative expression of DDX60 mRNA. Experimental procedures followed the protocol described in section 1.8.
Statistical analysis
All data were analyzed using SPSS version 27.0. For measured data (mean ± SD) with a normal distribution, one-way ANOVA was performed followed by LSD-t post hoc testing. A P-value < 0.05 was considered significant.
Results
Comparison of DDX60 expression in pancreatic cancer and normal tissue
DDX60 expression was significantly higher in pancreatic cancer tissues compared to normal pancreatic tissues (P < 0.05), as shown in Figure 1.
Figure 1.
DDX60 expression in pancreatic cancer tissues and normal tissues (***P < 0.001).
Association between DDX60 expression and prognosis in pancreatic cancer
Survival analysis indicated that patients with low DDX60 expression had significantly better overall survival than those with high expression (P < 0.05), as shown in Figure 2.
Figure 2.
Analysis of DDX60 expression and patient survival prognosis.
Correlation between DDX60 expression and immune infiltration
Immune infiltration analysis revealed that DDX60 expression was significantly correlated with the infiltration of aDCs, DCs, eosinophils, macrophages, neutrophils, CD56^dim NK cells, pDCs, total T cells, T helper cells, Tcm, Th1, Th2, and Treg cells (all P < 0.05), as shown in Figure 3.
Figure 3.
Relationship between DDX60 and immune infiltration in pancreatic cancer. A: Lollipop plot of immune infiltration, *P < 0.05, **P < 0.01, ***P < 0.001. B: Heat map of immune infiltration correlation, *P < 0.05.
Effect of baicalein on Panc02 cell growth
Baicalein significantly inhibited the growth of Panc02 cells in a concentration- and time-dependent manner (P < 0.05), as presented in Table 1.
Table 1.
Effects of baicalein on the growth inhibition rate of Panc02 cells (n = 5)
| Concentration | 24 h | 48 h | 96 h |
|---|---|---|---|
| 0 μmol/L | 0 | 0 | 0 |
| 5 μmol/L | 3.72 ± 1.08* | 6.72 ± 2.10*,# | 8.46 ± 1.79*,#,∆ |
| 10 μmol/L | 5.82 ± 1.64* | 11.23 ± 2.71*,# | 13.75 ± 3.18*,#,∆ |
| 20 μmol/L | 15.23 ± 4.28* | 19.83 ± 4.79*,# | 30.21 ± 6.20*,#,∆ |
| 40 μmol/L | 37.41 ± 8.30* | 45.62 ± 6.92*,# | 57.49 ± 7.39*,#,∆ |
| 80 μmol/L | 49.54 ± 8.32* | 61.95 ± 7.90*,# | 65.62 ± 9.30*,# |
| 160 μmol/L | 67.32 ± 13.41* | 69.49 ± 8.33*,# | 71.32 ± 10.93*,# |
Note: Compared to 0 μmol/L concentration at the same time;
P < 0.05.
Compared to the same concentration for 24 h;
P < 0.05.
Compared to the same concentration for 48 h;
P < 0.05.
Effect of baicalein on apoptosis of Panc02 cells
The apoptosis rate of Panc02 cells increased significantly with rising baicalein concentrations (P < 0.05). Notably, the 80 μmol/L baicalein group showed a significantly higher apoptosis rate than all other groups, as shown in Figure 4.
Figure 4.
Effect of baicalein on the apoptosis rate of Panc02 cells. Notes: (A) 0 μmol/L baicalein; (B) 20 μmol/L baicalein; (C) 40 μmol/L baicalein; (D) 80 μmol/L baicalein; (E) Statistical plot of apoptosis rate of each concentration baicalein group (compared with 0 μmol/L group, *P < 0.05; Compared with 20 μmol/L group, #P < 0.05; Compared with 40 μmol/L, ∆P < 0.05).
Effect of baicalein on Panc02 cell proliferation
Baicalein treatment significantly reduced the proliferation of Panc02 cells in a dose-dependent manner (P < 0.05). As shown in Figure 5, the proportion of cells in the G0/G1 phase was markedly elevated in the 80 μmol/L group, while the proliferation rate was significantly lower than in other groups.
Figure 5.
Effect of baicalein on the proliferation of Panc02 cells. Note: (A) 0 μmol/L baicalein; (B) 20 μmol/L baicalein; (C) 40 μmol/L baicalein; (D) 80 μmol/L baicalein; (E) Statistical graphs of apoptosis rate in baicalein groups of each concentration (Compared to 0 μmol/L group, *P < 0.05; compared to 20 μmol/L group, #P < 0.05; compared to 40 μmol/L, ∆P < 0.05).
Effect of baicalein on DDX60 expression in Panc02 cells
DDX60 mRNA expression in Panc02 cells decreased significantly with increasing baicalein concentration (P < 0.05), as shown in Figure 6.
Figure 6.
Effects of baicalein on the expression of DDX60 gene in Pan02 cells (Compared to 0 μmol/L group, *P < 0.05; compared to 20 μmol/L group, #P < 0.05; compared to 40 μmol/L, ∆P < 0.05).
Effect of baicalein on tumor volume and inhibition in mice
In both the 14-day and 21-day experiments, tumor volumes in all baicalein-treated groups were significantly smaller than those of the control group (P < 0.05), as shown in Tables 2, 3.
Table 2.
Changes in tumor volume of mice in each group (mm3)
| Group | 7 d | 14 d | 21 d |
|---|---|---|---|
| Control group (n = 8) | 185.23 ± 17.30 | 773.45 ± 60.39 | 1608.35 ± 249.58 |
| Low dose group (n = 8) | 191.78 ± 21.39 | 709.97 ± 49.32* | 1329.48 ± 154.60* |
| Medium dose group (n = 9) | 192.53 ± 18.66 | 598.63 ± 61.59*,# | 1179.56 ± 169.80*,# |
| High-dose group (n = 9) | 187.06 ± 20.93 | 476.98 ± 45.20*,#,∆ | 1084.52 ± 210.93*,#,∆ |
Note: Compared to the control group;
P < 0.05.
Compared to the low-dose group;
P < 0.05.
Compared to the medium dose group;
P < 0.05.
Table 3.
Comparison of tumor inhibition rate of mice in each group (%)
| Group | Tumor inhibition rate |
|---|---|
| Control group (n = 8) | 0 |
| Low-dose group (n = 8) | 17.84 ± 3.40* |
| Medium dose group (n = 9) | 26.67 ± 6.94*,# |
| High-dose group (n = 9) | 32.59 ± 7.03*,#,∆ |
Note: Compared to the control group;
P < 0.05.
Compared to the low-dose group;
P < 0.05.
Compared to the medium dose group;
P < 0.05.
Effect of baicalein on tumor-infiltrating immune cells in mice
The proportions of CD8+ T cells and macrophages in tumor tissues increased significantly with higher baicalein concentrations (P < 0.05), as shown in Figures 7 and 8.
Figure 7.
Effect of baicalein on CD8+ cells in tumor tissue of mice in each group, where (A) control group, (B) low dose group, (C) medium dose group, (D) high dose group, (E) statistical results. Note: Compared to the control group, *P < 0.05; Compared to the low-dose group, #P < 0.05; Compared to the medium dose group, ∆P < 0.05.
Figure 8.
Effect of baicalein on macrophages in tumor tissue of mice in each group. In the above figure, (A) The image represents the control group; (B) The low dose group (10 mg/kg); (C) The medium dose group (20 mg/kg); (D) The high dose group (40 mg/kg); and (E) The image shows the statistical results. Note: Compared to the control group, *P < 0.05; Compared to the low-dose group, #P < 0.05; Compared to the medium dose group, ∆P < 0.05.
Effect of baicalein on DDX60 expression in tumor tissues
DDX60 mRNA expression in mouse tumor tissues decreased significantly in a dose-dependent manner with baicalein treatment (P < 0.05), as shown in Figure 9.
Figure 9.
Effect of baicalein on macrophages in tumor tissues of different mouse groups. Note: Compared to the control group, *P < 0.05; compared to the low-dose group, #P < 0.05; compared to the medium-dose group, ∆P < 0.05. In the figure, (A) The influence of DDX60 mRNA expression in each group of tumor tissues. (B) Statistical analysis of DDX60 protein expression and its gray value in each group of tumor tissues.
Discussion
Pancreatic cancer is a highly aggressive malignancy of the gastrointestinal tract, characterized by an insidious onset, late clinical presentation, early metastasis, and poor prognosis. It ranks among the top ten malignancies in terms of both incidence and mortality rates [6]. Despite extensive research, the pathogenesis of pancreatic cancer remains incompletely understood. Major risk factors include long-term smoking, excessive alcohol consumption, a family history of pancreatic cancer, obesity, chronic pancreatitis, and new-onset diabetes mellitus [7-9]. The etiology is multifactorial, involving complex interactions between genetic alterations, dysregulated signaling pathways, lifestyle behaviors, and environmental exposures, yet no unified conclusion has been reached. This lack of consensus is one of the primary barriers to advancing clinical research and treatment strategies for pancreatic cancer [10-12].
The TME of pancreatic cancer exhibits distinct features, including abundant extracellular matrix components, dense immune cell infiltration, extensive fibrosis, and profound immunosuppression, all of which contribute to its aggressiveness [13-15]. Immunosuppression is thought to result from the accumulation of bone marrow-derived cells - such as granulocytes, macrophages, and monocytes - within the tumor, which in turn impairs T-cell-mediated antitumor responses [16,17]. Consequently, dysregulation of the immune microenvironment is considered a key contributor to tumor progression, and immune-based therapeutic strategies have been increasingly investigated across various malignancies [18-20].
Baicalein, a flavonoid compound extracted from the dried root of Scutellaria baicalensis, has been widely used in traditional Chinese medicine. It exhibits diverse pharmacologic activities, including antioxidant, antibacterial, anti-inflammatory, antitumor, cardioprotective, nephroprotective, and neuroprotective effects [21-23]. Baicalin is the glycosyloxyflavone that is the 7-O-glucuronide of bicalein. In the body, baicalin is hydrolyzed into baicaleinby intestinal flora, and baicalein is then subsequently reconverted into baicalinin the liver through a second metabolic transformation [24-26]. Previous studies have shown that baicaleinexerts significant antiproliferative effects in various malignancies at both the cellular and molecular levels [27-29]. Preliminary experiments in this study suggest that baicaleinexhibits notable antitumor effects against pancreatic cancer cells; however, the specific mechanisms underlying these effects remain largely unexplored.
In this study, we propose that baicalein inhibits tumor growth by modulating immune cell infiltration within the TME. Previous research has suggested that DDX60, an RNA-binding protein (RBP), maintains the stability of double-stranded RNA (dsRNA) and participates in tumor immune regulation. Modulation of DDX60 expression has been shown to affect T cell and CD8+ T cell infiltration in tumor tissues of murine models [30,31].
Based on this, we conducted a bioinformatic analysis using pancreatic cancer data from the UCSC XENA database. The results showed that DDX60 expression was significantly upregulated in pancreatic cancer tissues compared to normal tissues, and patients with low DDX60 expression exhibited significantly better survival outcomes than those with high expression. Furthermore, DDX60 expression was strongly correlated with the infiltration levels of multiple immune cell types, including aDCs, DCs, eosinophils, macrophages, neutrophils, CD56^dim NK cells, pDCs, total T cells, T helper cells, Tcm, Th1, Th2, and Treg cells. These findings suggest that DDX60 may act as an oncogene in pancreatic cancer and is closely associated with immune dysregulation.
We further investigated the antitumor effects of baicalein in cellular and animal models, and assessed its effect on immune infiltration. Preliminary findings revealed that baicalein significantly inhibited pancreatic cancer cell proliferation and subcutaneous tumor growth, which was accompanied by downregulation of DDX60 expression. Additionally, we observed a dose-dependent increase in CD8+ T cells and macrophages within the tumor tissues of treated mice. These results align with previous studies [32,33], which reported that baicalin activated the proliferation of CD8+ T cells. These are key cytotoxic lymphocytes that eliminate malignant cells by immune activation [34,35]. Baicalein may thus stimulate CD8+ T cell proliferation and recruitment by enhancing the host immune response. Similarly, macrophages - crucial innate immune cells - contribute to immune surveillance and inflammatory regulation, and their activation plays a vital role in reshaping the TME during antitumor therapy.
Based on these findings, we hypothesize that the antitumor effect of baicalein is mediated through the regulation of DDX60, enhancement of immune activation, and modulation of the tumor immune microenvironment.
However, several limitations must be acknowledged. First, this study only provided preliminary evidence that baicalein downregulates DDX60 to influence immune cell infiltration; the detailed molecular mechanism remains unclear. Second, the experimental system was limited to mouse models and the Panc02 cell line, lacking validation with clinical specimens and pharmacokinetic data. In future work, integrating single-cell RNA sequencing could help elucidate the immunoregulatory network involving DDX60. Moreover, developing a baicalein-based nanodelivery system may enhance its tumor-targeting capabilities, offering a promising avenue for precision immunotherapy in pancreatic cancer.
In conclusion, baicalein effectively suppresses pancreatic cancer cell proliferation, induces apoptosis, and inhibits tumor growth in vivo. These effects may be mediated by downregulation of DDX60 and enhancement of immune activation within the TME, warranting further in-depth investigation.
Disclosure of conflict of interest
None.
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