Abstract
Backgrounds/Aims
Diabetes is a recognized risk factor for pancreatic cancer; however, precise molecular mechanisms remain unclear. This study aimed to assess the influence of inflammation on the progression of pancreatic cancer in a diabetic murine model utilizing circulating tumor cells (CTC).
Methods
Fifty mice were randomly allocated into five groups. The P group were injected Panc02 cells only. In the streptozotocin (STZ), STZ/P, and P/STZ groups, mice were administered intraperitoneal STZ solution (50 mg/kg) alone, prior to Panc02 cell injection, and following Panc02 cell injection, respectively. Tumor development was assessed by gross inspection. Immunohistochemistry was performed to evaluate inflammatory cytokine expression, and CTCs were detected using quantum dot-conjugated aptamers.
Results
All mice exposed to STZ developed marked hyperglycemia. Tumor volume to body weight ratio was significantly higher in both P/STZ and STZ/P groups (p < 0.001). Liver metastasis rate was highest in the P/STZ group (p = 0.05). Malondialdehyde (p < 0.001), interleukin-1β (p < 0.05), tumor necrosis factor-α (p < 0.001), and interleukin-6 (p < 0.05) levels were significantly elevated in the STZ/P group. Expression of Signal Transducer and Activator of Transcription 3 and Snail1 was increased in both STZ/P and P/STZ groups. In addition, seven mice in the STZ/P group (70%) and nine mice in the P/STZ group (90%) exhibited larger CTC-like cells (p < 0.001).
Conclusions
In STZ-induced murine models, both hyperglycemia and elevated inflammatory markers were observed. Within this diabetes-associated inflammatory microenvironment, pancreatic cancer cells demonstrated increased proliferation and metastasis, as verified by aptasensor-based CTC detection.
Keywords: Pancreatic neoplasms; Diabetes mellitus; Streptozocin; Neoplastic cells, circulating
INTRODUCTION
Pancreatic cancer (PC) is frequently diagnosed at an advanced stage and is associated with poor prognosis, in part due to the absence of early biomarkers [1]. Although general screening for PC is not recommended, early diagnosis may benefit individuals at high risk, such as those with a family history or precancerous cystic lesions [2]. Recent investigations into PC risk factors have identified associations with pancreatitis and newly developed or exacerbated diabetes [3].
Chronic inflammation is a well-established risk factor for various malignancies of the gastrointestinal tract. In a prior investigation, our laboratory explored the connection between PC and streptozotocin (STZ) administration in murine models [4]. STZ, an antineoplastic compound, is commonly utilized to induce type 1 diabetes in animal models by promoting β-cell apoptosis via deoxyribonucleic acid (DNA) alkylation and nitrogen oxide generation [5-8]. Administration of STZ in murine models has been shown to simulate features of both type 1 and type 2 diabetes observed in humans. Notably, multiple inflammatory cytokines, including tumor necrosis factor (TNF)-α, interferon-gamma (IFN-γ), and interleukins (ILs), are secreted during the early diabetic phase [9]. This inflammatory response, together with the formation of reactive oxygen species (ROS), contributes to the onset of pancreatitis—a recognized risk factor for PC [10,11]. Specifically, these pro-inflammatory cytokines can be elevated through infiltration of lymphocytes into β cells [12]. Consequently, studying PC progression and metastasis in STZ-induced diabetic mice may offer insights into the interplay between PC and a pro-inflammatory tumor microenvironment associated with pancreatitis.
Circulating tumor cells (CTCs) are gaining prominence for their utility in early cancer diagnosis and disease monitoring. Additionally, identification of stem cell-like properties such as epithelial to mesenchymal transition (EMT) in CTCs may indicate the presence of distant metastases [13]. Typically, CTC detection strategies depend on several molecular markers, notably the epithelial cell adhesion molecule (EpCAM), which is broadly found in epithelial cells and enables discrimination between CTCs and normal blood cells, and Mucin-1 (MUC1), which is commonly overexpressed in tumor cells, involved in EMT, and linked to enhanced stem cell traits [14]. The present study sought to assess how STZ, acting as a pro-inflammatory agent, influences glucose regulation and tumor progression in murine PC models through CTC analysis. CTCs were identified in blood specimens and subsequently characterized using aptasensor conjugates specific for EpCAM and MUC1.
MATERIALS AND METHODS
Materials
Cell culture reagents were obtained from Life Technologies Inc. Qdot 525 ITKTM carboxyl quantum dots (ex:390 nm, em: 525 nm; QD525) and Qdot 565 ITKTM carboxyl quantum dots (ex: 530 nm, em: 565 nm; QD565) were purchased from Invitrogen Life Technologies Corp. All monoclonal antibodies were acquired from Santa Cruz Biotechnology, Inc. Enzyme-linked immunosorbent assay (ELISA) kits for EpCAM antigen (ABIN6955627) and MUC1 antigen (ABIN6730894) detection were supplied by Antibodies Inc. (PA, USA). All additional chemicals, including STZ, horseradish peroxidase (HRP), 3, 3’, 5, 5’-tetramethylbenzidine, and 1-ethyl-3-(3-dimethylaminopropyl) N’ethylcarbodiimide hydrochloride, were procured from Sigma-Aldrich.
Animal models
Two-month-old female C57BL mice (n = 50) were obtained from Samtako Co. C57BL/6 mice serve as a standard model in preclinical research examining immunological responses and antitumor activity across different malignancies. Mice with an average weight of 25 g were housed in the Experimental Animal Center of Seoul National University Bundang Hospital at a controlled room temperature of 22°C ± 1°C and maintained under 50% to 60% relative humidity, with unrestricted access to water and chow, following a 12-hour light-dark cycle and an acclimation period of seven days. All experimental procedures adhered to the animal welfare ethical standards established by the Institutional Animal Care and Use Committee (IACUC) of Seoul National University Bundang Hospital (IACUC number: MSRI-52-17-055).
Although various studies utilize different STZ dosages and injection protocols for diabetes induction, a single or multiple dose of 35 to 70 mg/kg STZ administered intravenously or intraperitoneally (IP) is commonly used [15-17]. In this study, diabetic mice received two IP injections of STZ (50 mg/kg), following our previous methods [4]. The blood glucose levels of injected mice were measured at multiple time points to assess the onset of diabetes, using CareSens/blood glucose test strips (Seoul, Korea). Sodium citrate buffer was administered to the control group as a substitute for STZ. Previous publications have also classified mice with blood glucose levels below 250 mg/dL as diabetic [8]. Here, we considered blood glucose levels exceeding 200 mg/dL within 24 hours following STZ injection indicative of STZ-induced diabetes. Hyperglycemia was observed in 95% of the mice after STZ administration. The body weights of the animals were recorded throughout the duration of the study.
Cell culture
The Panc02 murine pancreatic ductal adenocarcinoma cell line was purchased from ATCC. The Panc02 cell line is a well-characterized murine model for pancreatic ductal adenocarcinoma originating from a chemically induced tumor in the pancreas of a C57BL/6 mouse. Cells were cultured in high-glucose Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum, 100 U/mL penicillin, and 100 μg/mL streptomycin. The cultures were maintained at 37°C in a humidified 5% CO2 environment. All reagents for cell culture were sourced from Life Technologies Inc.
Study design
The murine models were allocated into five groups, each comprising ten animals (Fig. 1). In the control group (n = 10, P group), the mice were euthanized four weeks following Panc02 cell injection (2 × 108 in 100 μL phosphate buffered saline [PBS]). For the injection procedure, general anesthesia was induced with 2% isoflurane (Hana Pharm Co.) in oxygen and subsequently maintained at 1.5%. A vertical micro-laparotomy was performed, and Panc02 cells were directly injected into the pancreatic tail using a pre-cooled, calibrated specialized syringe (Hamilton Syringe Co.). In addition, a polyethylene catheter was inserted into the right carotid artery for blood sampling, including baseline blood [18]. The abdominal cavity was then sutured. In the second group (n = 10, P/STZ group), 2 weeks after Panc02 cell injection, STZ solution (50 mg/kg) was administered by IP injection. The mice were sacrificed at four weeks post cell injection. In the third group (n = 10, STZ/P group), IP injections of STZ were administered at two and three weeks. Two weeks following STZ injection, Panc02 cells were injected using the same technique, and the mice were euthanized four weeks after cell injection. In the fourth group (n = 10, STZ group), the mice received repeated STZ injections at two and three weeks without additional Panc02 cell administration. Finally, the normal group (n = 10, N group) did not receive injections of either Panc02 cells or STZ.
Fig. 1.
Study design. STZ, streptozotocin; STZ/P, STZ injection before Panc02 cell injection; P/STZ, STZ injection after Panc02 cell injection.
All animals were euthanized by cervical dislocation under deep CO2 anesthesia. Approximately 1 ml of blood was collected via cardiac puncture. Tumor tissue, normal pancreatic tissue, and normal liver tissue were then harvested and evaluated using hematoxylin and eosin staining and immunohistochemistry. A single operator performed all procedures to ensure consistency, and every effort was made to minimize animal suffering.
Histopathologic analysis
A pathologist examined the pathological characteristics of the tumor, including cell differentiation, metastatic properties, and the extent of inflammation. Tumor volume was calculated using the following formula: largest diameter × (smallest diameter)2 × 0.5 [19]. Inflammation was assessed by identifying inflammatory cell infiltration in the adjacent pancreatic tissue. The weight of individual liver and pancreatic tissues was recorded to estimate interstitial edema. Pancreatic and liver tissues were fixed overnight in 4% PFA (paraformaldehyde) solution, dehydrated through a graded ethanol series, and embedded in paraffin. The paraffin blocks were sectioned with a microtome at 5-μm thickness and subsequently stained with hematoxylin and eosin.
Immunocytochemistry studies were performed using confocal microscopy (LSM710, Carl Zeiss, Inc.) [20]. Optical images were first captured at 100× magnification and subsequently enlarged to 200×. The imaging conditions for H33342 were as follows: 405/488 nm, anti-signal transducer and activator of transcription 3 (STAT3) antibody-QD565 (ab68153) (Abcam); 565/635 nm, anti-ECadherin-antibody QD525 (ab40772) (Abcam); 488/525 nm, anti-Snail1 antibody-QD565 (3879) (Cell signaling); 565/635 nm, anti-MUC1 antibody-QD525 (ab109185) (Abcam); 488/525 nm, anti-EpCAM antibody-QD565 (sc-66020) (1:500) (Santa Cruz); 565/635 nm, anti-NLRP3 antibody-QD525 (ab263899) (Abcam). Sections of tissue from euthanized mice were placed on sterile 35-mm confocal dishes. After a 30-minute incubation, the tissues were treated with MUC1-QD525 and/or EpCam-QD565. To ensure the removal of any unbound conjugates, cells were subjected to three washes, each for 10 minutes at 30 rpm using Tris-HCl buffer. Blood samples underwent fixation with 200 μL of 4% PFA solution, followed by three 10-minute washes at 20 rpm in PBS. Cell nuclei were stained using H33342 solution (Molecular Probes) to allow precise assessment of QD565/QD525 conjugates targeting EpCAM and MUC1 aptamer in cellular and nuclear regions, as previously described [21]. Cell viability was examined utilizing the 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) assay, which measures the conversion to formazan. Cells (1 × 104 cells/well) seeded in 96 well plates were incubated at 37°C under 5% CO2 for 24 hours. The MTT assay procedure followed was consistent with established protocols [22].
Construction of EpCAM/MUC1 aptamers conjugated with QD525/QD565 probes
A single-stranded oligonucleotide was specifically designed to fabricate the EpCAM-QD565/MUC1-QD525 aptasensor for in vitro experiments, with amine modifications at the cohesive end attached to a stem sequence (Supplementary Fig. 1). The EpCAM sequence was adjusted slightly compared to the version described in a previous report [23]. The NH2-EpCAM aptamer sequence was covalently linked to the COOH-QD565 probe (serving as the fluorophore dye) at a molar ratio of 2:1 in 0.1M TE buffer (pH 7.0) containing 78 mg/mL 1-ethyl-3-(3-dimethylaminopropyl) N’ethylcarbodiimide hydrochloride for 2 hours at room temperature following the manufacturer’s protocol. The MUC1 sequence was also slightly modified from the one previously reported [21]. A quantity of 5 pmol EpCAM-QD565 or 5 pmol MUC1-QD525 aptasensors underwent thermodynamic annealing at 94°C and 72°C by polymerase chain reaction to generate a CTC cell-bound EpCAM/MUC1 sequence exhibiting enhanced affinity for the target binding site. To assess the conjugation efficiency between the QD carboxyl groups and the amine groups of EpCAM/MUC1 aptamers, unconjugated probes remaining in the supernatant after centrifugation of the QD conjugate were collected and quantified using a NanoDrop ND-1000 Spectrometer (NanoDrop products).
Sensitivity and selectivity of aptamer/molecular beacon for CTC detection
The sensitivity and selectivity of the EpCAM/MUC1 aptasensor or antibody were assessed using a NanoDrop spectrometer and ELISA reader, as described in our previous report [24]. Preparation of aptamer-conjugated HRP was carried out as follows. The NH2-EpCAM aptamer sequence was coupled with COOH-HRP at a molar ratio of 2:1 in 0.1 M TE buffer (pH 7.0) using 78 mg/mL EDC for 2 hours at room temperature. Subsequently, 20 μL of 1 mg/mL HRP (final unit: 400 nunit) was mixed with 10 μL aptamer solution (1 mg/mL). Following a 2-hour incubation at room temperature, the resultant mixture was diluted to reach the final concentration (400 nunit). HRP aptamers were additionally incubated for 1 hour, then blocked using 1% bovine serum albumin (BSA) for 1 hour, and stored at 4°C until required.
For ELISA analysis, plates were coated with varying concentrations of EpCAM/MUC1 solution at 37°C for 2 hours, followed by blocking with 1% BSA. After washing with phosphate buffered saline containing Tween 20 (PBST), different concentrations of EpCAM/MUC1 (0.005–3 ng/mL) were combined with 5 pmol aptasensor and applied concurrently to capture the target. Upon removal of unbound target by washing three times with PBST, STA-HRP was added to bind the antibody to EpCAM/MUC1. Color development was initiated by adding 50 μL of TMB, then terminated by adding 50 μL of 2 M H2SO4. Absorbance at 450 nm was measured using a Microplate Reader, and the solution’s UV–Vis spectrum between 350 nm and 600 nm was also recorded with a NanoDrop spectrophotometer.
To determine the fluorescence intensity of the aptasensor (QD565-EpCAM-BHQ2/QD525-MUC1-BHQ1), it was combined with varying concentrations of EpCAM/MUC1 in 50 mM Tris-HCl (50 μL) for cross-reaction analysis, dissolved in 0.5 % DMSO (50 μL), with all components placed in a black 96-well plate (SPL). The mixture was incubated for 5 minutes at 25°C. Fluorescence was then assessed at emission wavelengths of 525/565 nm using a Synergy HTX microplate reader (Biotek). The quantification of EpCAM/MUC1 was based on the enhancement of fluorescence intensity. F1 and F0 represent the fluorescence intensities measured at 525/565 nm in the presence and absence of EpCAM/MUC1 or blood, respectively. Under conditions optimized for reaction, sensor sensitivity for EpCAM detection was examined using either the human TROP1/EpCam ELISA Kit (Invitrogen) or the DL-MUC1-human ELISA Kit (Wuxi Donglin Science & Tech Development Co.). Interfering agents including BSA, prostate specific antigen (PSA), vascular endothelial growth factor (VEGF), and PBS were evaluated at multiple concentrations for their effect on fluorescence intensity.
Statistical analysis
Continuous variables are presented as mean ± standard deviation, while categorical variables are presented as number (percentage). Kruskal-Wallis analysis was employed to compare continuous variables among groups. Pearson chi-square analysis was used for comparisons of categorical variables. Statistical significance was defined as p-values < 0.05, with further annotation for p < 0.001.
RESULTS
STZ administration increases the incidence of diabetes in C57BL/6 mice
Diabetes induction in C57BL/6 mice following STZ injection was assessed through serial monitoring of fasting plasma glucose levels throughout the experimental period (Fig. 2). During the study, all mice treated with STZ (STZ, P/STZ, and STZ/P groups) developed marked hyperglycemia compared to the N group (p < 0.001). Before STZ injection, fasting plasma glucose levels in the P/STZ group did not differ from the N group, but became significantly elevated after the 4th week (p < 0.05).
Fig. 2.
Changes in blood glucose levels following streptozotocin (STZ) induction in mice before and after Panc02 cell implantation (P). The time course illustrates the effects of STZ on fasting plasma glucose before and after Panc02 cell implantation (P). On day 46, plasma glucose was measured in all five groups. Error bars indicate standard deviation from independent experiments (n = 3). Data are expressed as mean ± standard deviation from three replicates.
Plasma levels of inflammatory markers in STZ-induced diabetic models
To evaluate the inflammatory impact of STZ injection, alterations in oxidative stress and inflammatory parameters were assessed in the blood samples of diabetic mice. Four weeks post-diabetes induction, significantly increased levels of the lipid peroxidation product malondialdehyde (MDA) (p < 0.001), IL-1β (p < 0.05), TNF-α (p < 0.001), and IL-6 (p < 0.05) were detected in the STZ, STZ/P, and P/STZ groups compared to the N group (Supplementary Fig. 2). The STZ/P group exhibited the highest concentrations of blood MDA (p < 0.001), IL-1β (p < 0.05), TNF-α (p < 0.001), and IL-6 (p < 0.05). Furthermore, IL-1β, TNF-α, and IL-6 levels were significantly different between the P and N groups (p < 0.05). Oxidative stress, as indicated by elevated ROS levels, was also increased following STZ administration compared to the N group.
Histopathological analysis
Gross morphological examination of abdominal organs and histopathological analysis of liver and pancreas tissues were conducted to further investigate the inflammatory response to STZ injection (Fig. 3). Among the 50 animals, deaths occurred in one mouse from the P group, one from the STZ/P group, and two from the P/STZ group during the experiment; thus, autopsies and histopathological analyses were performed on 46 mice. Histopathological evaluation revealed that the degree of inflammatory cell infiltration was highest in the P/STZ group relative to the STZ and STZ/P groups (p = 0.05). There was no significant difference in body weight among all groups. Tumor volume normalized to body weight was markedly greater in the P/STZ and STZ/P groups compared with the P group (p < 0.001). The occurrence of liver metastasis was also higher in the P/STZ group than in the P and STZ/P groups (p = 0.05).
Fig. 3.
Hematoxylin and Eosin stained microscopic images in five groups (×200). 1st row: gross evaluation of the abdominal cavity; 2nd row: histopathological assessment of liver tissue; and 3rd row: histopathological assessment of pancreatic tissue. In the control group (P), injection of Panc02 cells led to tumor formation at the pancreatic tail. Microscopically, the tumor cells showed significant pleomorphism and atypical nuclei, while the liver tissue appeared normal. In the STZ/P group, tumor formation at the pancreatic tail was observed following STZ injection. Tumor cell infiltration and scattered inflammatory cells were present in the pancreatic tissue. The liver tissue contained a small number of inflammatory cells. In the P/STZ group, an irregular tumor at the pancreatic tail (white arrows) and a metastatic nodule on the liver surface (black arrow) were observed. Both pancreatic and liver tissues exhibited tumor cells accompanied by inflammatory infiltrates. STZ, streptozotocin; STZ/P, STZ injection before Panc02 cell injection; P/STZ, STZ injection after Panc02 cell injection.
Expression of NLRP3 and EMT-like phenotype markers
Expression levels of EpCAM, MUC1, and NOD-like receptor family pyrin domain containing 3 (NLRP3) were analyzed in liver and pancreatic tissues of the various groups by confocal microscopy (Supplementary Fig. 3). NLRP3 inflammasome formation was assessed using immunofluorescence analysis. To ascertain whether these findings reflect the cancer tissue microenvironment, markers associated with EMT, including STAT3, Snail1, and E-cadherin, were also examined. Confocal microscopy of liver tissue demonstrated that the localization of NLRP3 progressively declined in the P/STZ group compared with the STZ, P, and STZ/P groups, indicating increased NLRP3 inflammasome formation (Fig. 4A, Supplementary Fig. 3). In contrast, STAT3 expression was elevated in the P/STZ group relative to the other groups. Similar trends were observed in pancreatic tissue, with higher STAT3 expression in the P and P/STZ groups (Fig. 4B).
Fig. 4.
Confocal microscopic analysis of NLRP3, STAT3, E-cadherin, and SNAIL1 expression in liver and pancreatic tissues. (A) Liver tissue was immunofluorescently stained to identify NLRP3 (green) and STAT3 (red), with H33342 (blue) marking nuclei. NLRP3 expression gradually decreased in the STZ, STZ/P, and P/STZ groups, whereas STAT3 expression increased in the STZ/P and P/STZ groups. (B) Pancreatic tissue was immunofluorescently stained to detect NLRP3 (green) and STAT3 (red), with H33342 (blue) as a nuclear marker. NLRP3 and STAT3 expression was upregulated in the P and P/STZ groups but decreased in the STZ/P group. (C) Liver tissue was immunofluorescently stained to assess E-cadherin (green) and SNAIL1 (red), with H33342 (blue) labeling nuclei. E-cadherin expression increased in the N, P, and STZ groups, while SNAIL1 expression was elevated in the STZ/P and P/STZ groups. (D) Fluorescence intensity was quantified using Zen and Image J software. Error bars represent standard deviation from independent experiments (n = 3). Results are reported as mean ± standard deviation. STZ, streptozotocin; STZ/P, STZ injection before Panc02 cell injection; P/STZ, STZ injection after Panc02 cell injection. *p < 0.05, **p < 0.001.
E-cadherin was distinctly expressed in liver tissue in the N, STZ, and P groups, while its expression was less frequently observed in the STZ/P and P/STZ groups (Fig. 4C). In contrast, Snail1 expression was elevated in the STZ/P and P/STZ groups. Neither EpCAM nor MUC1 were expressed in the N, STZ, and P groups; however, larger CTC-like cells were observed in seven mice (70%) of the STZ/P group and nine mice (90%) of the P/STZ group (Supplementary Fig. 3, p < 0.001).
Sensitivity and selectivity of EpCAM/MUC1 aptasensor
The aptamers' sensitivity in identifying EpCAM/MUC1 was assessed across varying concentrations of ligand and interfering agents and benchmarked against antibody-based ELISA. As demonstrated in Fig. 5, absorbance optical density (OD) values showed a statistically significant difference between aptamers and ELISA. The limit of detection (LOD) for aptamers was 0.0576 pg/mL, compared to 0.935 pg/mL for ELISA; the dynamic range was 3.5–2,500 pg/mL and 0.1–2,000 pg/mL, respectively. The absorbance OD value for EpCAM exceeded that of MUC1 at equivalent concentrations. Aptamers exhibited higher target binding affinity than ELISA, and specifically recognized EpCAM and MUC1-expressing CTCs. When the standard concentration of EpCAM/MUC1 was increased from 0 to 3 ng/mL, aptamers showed a pronounced enhancement in absorbance compared to ELISA. The aptamers demonstrated 96% sensitivity for EpCAM and MUC1 in murine CTCs at an LOD of 0.125 pg/mL and 98% sensitivity at an LOD of 0.576 pg/mL, respectively (Supplementary Fig. 4–7). The equation for the calibration curve for EpCAM is y (absorbance) = 2.1 × (logarithm of EpCAM concentration) + 0.245 (R2 = 0.992). For MUC1, it is y (absorbance) = 2.651 × (logarithm of MUC1 concentration) + 0.272 (R2 = 0.998).
Fig. 5.
Representative standard curve demonstrating binding sensitivity across varying concentrations. (A) Comparative analysis of the binding sensitivity between epithelial cell adhesion molecule (EpCAM) aptamer and enzyme-linked immunosorbent assay (ELISA). (B) Comparative study of Mucin-1 (MUC1) aptamer and ELISA in terms of binding sensitivity. (C) Relative fluorescence intensity (ru) of fluorescence spectra illustrating binding selectivity in response to EpCAM in the presence of interfering agents (BSA, PSA, VEGF, blank). Fluorescence intensity at an emission wavelength of 565 nm for the aptasensor (QD565-EpCAM) was determined under exposure to EpCAM (1.5 ng/mL), MUC1 (2 ng/mL), BSA (5 ng/mL), PSA (5 ng/mL), VEGF (5 ng/mL), and blank, respectively. (D) Relative fluorescence intensity (ru) profiles indicating binding selectivity corresponding to MUC1 with interfering agents. Fluorescence intensity at an emission wavelength of 525 nm for the aptasensor (QD525-MUC1) was assessed in the presence of EpCAM (1.5 ng/mL), MUC1 (2 ng/mL), BSA (5 ng/mL), PSA (5 ng/mL), VEGF (5 ng/mL), and blank, respectively. Error bars indicate standard deviation from independent experiments (n = 3). Data are shown as mean ± standard deviation. BSA, bovine serum albumin; PSA, prostate specific antigen; VEGF, vascular endothelial growth factor.
DISCUSSION
The present study demonstrates that new-onset diabetes induces acute inflammatory signals, subsequently promoting PC initiation and progression through EMT mechanisms. A murine model emulating acute inflammation-associated PC was established using STZ and Panc02 cell administration. Mice exposed to STZ developed larger tumors and displayed an increased incidence of liver metastasis. Aptasensors conjugated with QD were fabricated for CTC detection. Under these experimental parameters, aptasensors detected EpCAM and MUC1 in 10 μL of blood within less than 10 seconds using fluorescence intensity via confocal microscopy. Relative to antibody-based ELISA kits, aptasensors offered enhanced sensitivity and improved selectivity. Large CTCs were identified in murine models treated with STZ and Panc02 cell injections, indicating that inflammation contributes not only to tumorigenesis but also to metastatic processes.
Several studies have explored the contribution of inflammation to both the development and progression of cancer [25-28]. Multiple malignancies are associated with chronic inflammatory conditions affecting diverse abdominal organs, such as the gastrointestinal tract, liver, and biliary system [28-31]. Inflammatory cells and cytokines facilitate tumor progression by activating oncogenes and suppressing the function of tumor suppressor genes [21]. Tumor-infiltrating lymphocytes further enhance immunosuppressive activity against cancer cells, thereby aiding tumor proliferation [32,33]. Pro-inflammatory cytokines and chemokines are implicated in the processes of tumorigenesis and metastasis [34-36]. Recent advances in the study of the inflammatory tumor microenvironment offer new understanding for the prevention and treatment of certain malignancies through molecularly targeted therapies [37-39].
A notably high prevalence of diabetes is documented among PC patients, particularly in those with newly detected or acutely deteriorated glucose dysregulation [3,40]. The association between PC and disturbances in glucose metabolism is multifaceted, encompassing various mechanisms involved in diabetes pathogenesis [41]. Hyperinsulinemia and insulin resistance promote both adipocyte and inflammatory cell accumulation within pancreatic tissue, leading to increased oxidative stress and upregulation of oncogenic transcription factors [42,43]. These inflammatory processes alter the tumor microenvironment, trigger the activation of STAT3 and the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathways, and suppress E-cadherin expression, collectively driving EMT [44,45]. EMT features a reduction in tight junction integrity among epithelial cells; this phenotypic transition in tumor cells enables enhanced dissemination and migration to distant anatomical sites [46]. Given the pivotal role of this process in metastasis, it is posited that diabetes-induced pancreatic inflammation acts both as a risk factor for PC and as a driver of more aggressive tumor behavior. In this investigation, we established a murine model simulating diabetes-induced inflammation using STZ induction. Following STZ administration, an upregulation of inflammatory markers including MDA, IL-1β, TNF-α, and IL-6 was observed, establishing the presence of diabetes-associated inflammation. Subsequent injection of PC cells resulted in larger tumor burden and an increased incidence of liver metastasis in mice receiving additional STZ. Significant differences in E-cadherin and STAT3 expression among groups implied a greater predisposition toward EMT in the P/STZ cohort. These findings reinforce the interconnectedness of diabetes, inflammation, and PC, while also emphasizing the temporal association between inflammation and cancer progression. Despite the need for further validation, increased EpCAM/MUC1 levels and greater metastatic frequency in the P/STZ group versus the STZ/P group suggest that initiating inflammatory responses after carcinogenesis may be associated with poorer clinical outcomes.
Growing evidence indicates that the detection of CTCs in peripheral blood serves as an indicator of tumor recurrence and distant metastasis across multiple cancer types [13]. Identifying CTCs facilitates early diagnosis, assessment of treatment efficacy, and noninvasive monitoring for recurrence. Present CTC detection methods primarily depend on immunocytochemistry, immunofluorescence, and fluorescence microscopy, utilizing the morphological characteristics of CTCs to distinguish them from normal immune cells [20,47,48]. Nonetheless, the low abundance and heterogeneity of CTCs frequently result in detection failures, presenting a notable challenge for their clinical application [49]. Aptasensors have emerged as an alternative approach for CTC detection by offering a more rapid response and greater specificity related to conformational shifts in the antigen’s three-dimensional structure [50,51]. In this study, application of EpCAM/MUC1 QD-based aptasensors allowed for efficient identification of diabetes-induced inflammation-related PC in murine models. This approach also enabled reliable detection of larger CTCs in STZ-treated mice. Further investigation is required to determine the diagnostic value of QD-based aptasensors in the early identification of PC in humans.
This preclinical study demonstrates that induction of diabetes results in increased pancreatic inflammation, thereby promoting cancer initiation, progression, and distant metastasis. The study has certain limitations. First, the observed elevations in inflammatory cytokine expression, increase in tumor size, higher rates of liver metastasis, and greater expression of EMT markers and CTCs in STZ-induced mice do not clarify the precise underlying mechanisms connecting diabetes, inflammation, and PC. Second, the absence of human subject validation reduces the clinical applicability of these findings. Finally, despite the frequent use of C57BL/6 mice and Panc02 cells as a PC model, this system has inherent limitations, such as substrain variability in C57BL/5 mice and questions about how closely Panc02 cells mirror human pancreatic ductal adenocarcinoma, given differences in mutational profiles. Additional studies, particularly those involving clinical cohorts, are essential to confirm the present findings and to identify robust inflammation-associated biomarkers and therapeutic targets for PC.
SUPPLEMENTARY DATA
Supplementary data related to this article can be found at https://doi.org/10.14701/ahbps.25-120.
Funding Statement
FUNDING This work was supported by Seoul National University Bundang Hospital research grant (grant no.: 02-2016-0016).
Footnotes
CONFLICT OF INTEREST
No potential conflict of interest relevant to this article was reported.
AUTHOR CONTRIBUTIONS
Conceptualization: STK, YSY. Data curation: STK, YMK. Methodology: STK, YSY. Visualization: YP, STK, YMK. Supervision: HSH, YSY. Writing – original draft: YP, STK. Writing – review & editing: All authors.
REFERENCES
- 1.Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74:229–263. doi: 10.3322/caac.21834. [DOI] [PubMed] [Google Scholar]
- 2.Park EH, Jung KW, Park NJ, Kang MJ, Yun EH, Kim HJ, et al. Community of Population-Based Regional Cancer Registries, author. Cancer Statistics in Korea: incidence, mortality, survival, and prevalence in 2022. Cancer Res Treat. 2025;57:312–330. doi: 10.4143/crt.2025.264. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Toriola AT, Stolzenberg-Solomon R, Dalidowitz L, Linehan D, Colditz G. Diabetes and pancreatic cancer survival: a prospective cohort-based study. Br J Cancer. 2014;111:181–185. doi: 10.1038/bjc.2014.224. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Ahn KS, Hwang JY, Han HS, Kim ST, Hwang I, Chun YO. The impact of acute inflammation on progression and metastasis in pancreatic cancer animal model. Surg Oncol. 2018;27:61–69. doi: 10.1016/j.suronc.2017.11.008. [DOI] [PubMed] [Google Scholar]
- 5.Kwon NS, Lee SH, Choi CS, Kho T, Lee HS. Nitric oxide generation from streptozotocin. FASEB J. 1994;8:529–533. doi: 10.1096/fasebj.8.8.8181671. [DOI] [PubMed] [Google Scholar]
- 6.Kwon KB, Kim EK, Jeong ES, Lee YH, Lee YR, Park JW, et al. Cortex cinnamomi extract prevents streptozotocin- and cytokine-induced beta-cell damage by inhibiting NF-kappaB. World J Gastroenterol. 2006;12:4331–4337. doi: 10.3748/wjg.v12.i27.4331. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Oleson BJ, Corbett JA. Dual role of nitric oxide in regulating the response of β cells to DNA damage. Antioxid Redox Signal. 2018;29:1432–1445. doi: 10.1089/ars.2017.7351. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Like AA, Rossini AA. Streptozotocin-induced pancreatic insulitis: new model of diabetes mellitus. Science. 1976;193:415–417. doi: 10.1126/science.180605. [DOI] [PubMed] [Google Scholar]
- 9.Gorasia DG, Dudek NL, Veith PD, Shankar R, Safavi-Hemami H, Williamson NA, et al. Pancreatic beta cells are highly susceptible to oxidative and ER stresses during the development of diabetes. J Proteome Res. 2015;14:688–699. doi: 10.1021/pr500643h. [DOI] [PubMed] [Google Scholar]
- 10.Wittel UA, Rau B, Gansauge F, Gansauge S, Nussler AK, Beger HG, et al. Influence of PMN leukocyte-mediated pancreatic damage on the systemic immune response in severe acute pancreatitis in rats. Dig Dis Sci. 2004;49:1348–1357. doi: 10.1023/B:DDAS.0000037833.16433.77. [DOI] [PubMed] [Google Scholar]
- 11.Imamura M, Mikami Y, Takahashi H, Yamauchi H. Effect of a specific synthetic inhibitor of neutrophil elastase (ONO-5046) on the course of acute hemorrhagic pancreatitis in dogs. J Hepatobiliary Pancreat Surg. 1998;5:422–428. doi: 10.1007/s005340050067. [DOI] [PubMed] [Google Scholar]
- 12.James EA, Joglekar AV, Linnemann AK, Russ HA, Kent SC. The beta cell-immune cell interface in type 1 diabetes (T1D) Mol Metab. 2023;78:101809. doi: 10.1016/j.molmet.2023.101809. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Scheel C, Weinberg RA. Cancer stem cells and epithelial-mesenchymal transition: concepts and molecular links. Semin Cancer Biol. 2012;22:396–403. doi: 10.1016/j.semcancer.2012.04.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Wu J, Gu M. Microfluidic sensing: state of the art fabrication and detection techniques. J Biomed Opt. 2011;16:080901. doi: 10.1117/1.3607430. [DOI] [PubMed] [Google Scholar]
- 15.Mythili MD, Vyas R, Akila G, Gunasekaran S. Effect of streptozotocin on the ultrastructure of rat pancreatic islets. Microsc Res Tech. 2004;63:274–281. doi: 10.1002/jemt.20039. [DOI] [PubMed] [Google Scholar]
- 16.Ar'Rajab A, Ahrén B. Long-term diabetogenic effect of streptozotocin in rats. Pancreas. 1993;8:50–57. doi: 10.1097/00006676-199301000-00011. [DOI] [PubMed] [Google Scholar]
- 17.Gajdosík A, Gajdosíková A, Stefek M, Navarová J, Hozová R. Streptozotocin-induced experimental diabetes in male Wistar rats. Gen Physiol Biophys 1999;18 Spec No:54-62. [PubMed]
- 18.Roggli E, Gattesco S, Caille D, Briet C, Boitard C, Meda P, et al. Changes in microRNA expression contribute to pancreatic β-cell dysfunction in prediabetic NOD mice. Diabetes. 2012;61:1742–1751. doi: 10.2337/db11-1086. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Schmittgen TD, Zakrajsek BA, Mills AG, Gorn V, Singer MJ, Reed MW. Quantitative reverse transcription-polymerase chain reaction to study mRNA decay: comparison of endpoint and real-time methods. Anal Biochem. 2000;285:194–204. doi: 10.1006/abio.2000.4753. [DOI] [PubMed] [Google Scholar]
- 20.Motterle A, Gattesco S, Caille D, Meda P, Regazzi R. Involvement of long non-coding RNAs in beta cell failure at the onset of type 1 diabetes in NOD mice. Diabetologia. 2015;58:1827–1835. doi: 10.1007/s00125-015-3641-5. [DOI] [PubMed] [Google Scholar]
- 21.Hwang JY, Kim ST, Han HS, Kim K, Han JS. Optical aptamer probes of fluorescent imaging to rapid monitoring of circulating tumor cell. Sensors (Basel) 2016;16:1909. doi: 10.3390/s16111909. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Wu X, Pan C, Chen R, Zhang S, Zhai Y, Guo H. BML-111 attenuates high glucose-induced inflammation, oxidative stress and reduces extracellular matrix accumulation via targeting Nrf2 in rat glomerular mesangial cells. Int Immunopharmacol. 2020;79:106108. doi: 10.1016/j.intimp.2019.106108. [DOI] [PubMed] [Google Scholar]
- 23.Jiang Y, Quan J, Chen Y, Liao X, Dai Q, Lu R, et al. Fluorofenidone protects against acute kidney injury. FASEB J. 2019;33:14325–14336. doi: 10.1096/fj.201901468RR. [DOI] [PubMed] [Google Scholar]
- 24.Hwang JY, Kim ST, Kwon J, Lee J, Chun YO, Han JS, et al. Ultrasensitive fluorescence monitoring and in vivo live imaging of circulating tumor cell-derived miRNAs using molecular beacon system. ACS Sens. 2018;3:2651–2659. doi: 10.1021/acssensors.8b01095. [DOI] [PubMed] [Google Scholar]
- 25.Balkwill F, Mantovani A. Inflammation and cancer: back to Virchow? Lancet. 2001;357:539–545. doi: 10.1016/S0140-6736(00)04046-0. [DOI] [PubMed] [Google Scholar]
- 26.Zhao H, Wu L, Yan G, Chen Y, Zhou M, Wu Y, et al. Inflammation and tumor progression: signaling pathways and targeted intervention. Signal Transduct Target Ther. 2021;6:263. doi: 10.1038/s41392-021-00658-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Mantovani A, Allavena P, Sica A, Balkwill F. Cancer-related inflammation. Nature. 2008;454:436–444. doi: 10.1038/nature07205. [DOI] [PubMed] [Google Scholar]
- 28.Axelrad JE, Lichtiger S, Yajnik V. Inflammatory bowel disease and cancer: the role of inflammation, immunosuppression, and cancer treatment. World J Gastroenterol. 2016;22:4794–4801. doi: 10.3748/wjg.v22.i20.4794. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ernst PB, Gold BD. The disease spectrum of Helicobacter pylori: the immunopathogenesis of gastroduodenal ulcer and gastric cancer. Annu Rev Microbiol. 2000;54:615–640. doi: 10.1146/annurev.micro.54.1.615. [DOI] [PubMed] [Google Scholar]
- 30.Kamiza AB, Su FH, Wang WC, Sung FC, Chang SN, Yeh CC. Chronic hepatitis infection is associated with extrahepatic cancer development: a nationwide population-based study in Taiwan. BMC Cancer. 2016;16:861. doi: 10.1186/s12885-016-2918-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Kim EM, Hong ST. Clonorchis sinensis and cholangiocarcinoma. J Korean Med Sci. 2025;40:e145. doi: 10.3346/jkms.2025.40.e145. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Lopez de Rodas M, Villalba-Esparza M, Sanmamed MF, Chen L, Rimm DL, Schalper KA. Biological and clinical significance of tumour-infiltrating lymphocytes in the era of immunotherapy: a multidimensional approach. Nat Rev Clin Oncol. 2025;22:163–181. doi: 10.1038/s41571-024-00984-x. [DOI] [PubMed] [Google Scholar]
- 33.Liu Y, Liu Z, Yang Y, Cui J, Sun J, Liu Y. The prognostic and biology of tumour-infiltrating lymphocytes in the immunotherapy of cancer. Br J Cancer. 2023;129:1041–1049. doi: 10.1038/s41416-023-02321-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Kureshi CT, Dougan SK. Cytokines in cancer. Cancer Cell. 2025;43:15–35. doi: 10.1016/j.ccell.2024.11.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Lee SO, Yang X, Duan S, Tsai Y, Strojny LR, Keng P, et al. IL-6 promotes growth and epithelial-mesenchymal transition of CD133+ cells of non-small cell lung cancer. Oncotarget. 2016;7:6626–6638. doi: 10.18632/oncotarget.6570. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Ma Y, Ren Y, Dai ZJ, Wu CJ, Ji YH, Xu J. IL-6, IL-8 and TNF-α levels correlate with disease stage in breast cancer patients. Adv Clin Exp Med. 2017;26:421–426. doi: 10.17219/acem/62120. [DOI] [PubMed] [Google Scholar]
- 37.Dickerson LK, Carter JA, Kohli K, Pillarisetty VG. Emerging interleukin targets in the tumour microenvironment: implications for the treatment of gastrointestinal tumours. Gut. 2023;72:1592–1606. doi: 10.1136/gutjnl-2023-329650. [DOI] [PubMed] [Google Scholar]
- 38.Croft M, Salek-Ardakani S, Ware CF. Targeting the TNF and TNFR superfamilies in autoimmune disease and cancer. Nat Rev Drug Discov. 2024;23:939–961. doi: 10.1038/s41573-024-01053-9. [DOI] [PubMed] [Google Scholar]
- 39.Sun L, Li C, Gao T, Liu Z, Hou Y, Han W. Combining immune checkpoints with TNFSF agonists: a new horizon for cancer and autoimmune therapies. Front Immunol. 2025;16:1557176. doi: 10.3389/fimmu.2025.1557176. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Khan S, Safarudin RF, Kupec JT. Validation of the ENDPAC model: Identifying new-onset diabetics at risk of pancreatic cancer. Pancreatology. 2021;21:550–555. doi: 10.1016/j.pan.2021.02.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Duan X, Wang W, Pan Q, Guo L. Type 2 diabetes mellitus intersects with pancreatic cancer diagnosis and development. Front Oncol. 2021;11:730038. doi: 10.3389/fonc.2021.730038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Jin Q, Hart PA, Shi N, Joseph JJ, Donneyong M, Conwell DL, et al. Dietary patterns of insulinemia, inflammation and glycemia, and pancreatic cancer risk: findings from the women's health initiative. Cancer Epidemiol Biomarkers Prev. 2021;30:1229–1240. doi: 10.1158/1055-9965.EPI-20-1478. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Desai V, Patel K, Sheth R, Barlass U, Chan YM, Sclamberg J, et al. Pancreatic fat infiltration is associated with a higher risk of pancreatic ductal adenocarcinoma. Visc Med. 2020;36:220–226. doi: 10.1159/000507457. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Takahashi M, Mutoh M, Ishigamori R, Fujii G, Imai T. Involvement of inflammatory factors in pancreatic carcinogenesis and preventive effects of anti-inflammatory agents. Semin Immunopathol. 2013;35:203–227. doi: 10.1007/s00281-012-0340-x. [DOI] [PubMed] [Google Scholar]
- 45.Sato K, Hikita H, Myojin Y, Fukumoto K, Murai K, Sakane S, et al. Hyperglycemia enhances pancreatic cancer progression accompanied by elevations in phosphorylated STAT3 and MYC levels. PLoS One. 2020;15:e0235573. doi: 10.1371/journal.pone.0235573. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Hara Y, Mizukami H, Yamazaki K, Yamada T, Igawa A, Takeuchi Y, et al. Dual epigenetic changes in diabetes mellitus-associated pancreatic ductal adenocarcinoma correlate with downregulation of E-cadherin and worsened prognosis. J Pathol Clin Res. 2023;9:354–366. doi: 10.1002/cjp2.326. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Koscianska E, Starega-Roslan J, Sznajder LJ, Olejniczak M, Galka-Marciniak P, Krzyzosiak WJ. Northern blotting analysis of microRNAs, their precursors and RNA interference triggers. BMC Mol Biol. 2011;12:14. doi: 10.1186/1471-2199-12-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Chen X, Guo X, Zhang H, Xiang Y, Chen J, Yin Y, et al. Role of miR-143 targeting KRAS in colorectal tumorigenesis. Oncogene. 2009;28:1385–1392. doi: 10.1038/onc.2008.474. [DOI] [PubMed] [Google Scholar]
- 49.Mamdouhi T, Twomey JD, McSweeney KM, Zhang B. Fugitives on the run: circulating tumor cells (CTCs) in metastatic diseases. Cancer Metastasis Rev. 2019;38:297–305. doi: 10.1007/s10555-019-09795-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Wang Y, Huo T, Du Y, Qian M, Lin C, Nie H, et al. Sensitive CTC analysis and dual-mode MRI/FL diagnosis based on a magnetic core-shell aptasensor. Biosens Bioelectron. 2022;215:114530. doi: 10.1016/j.bios.2022.114530. [DOI] [PubMed] [Google Scholar]
- 51.Lv Z, Wang Q, Yang M. Multivalent duplexed-aptamer networks regulated a CRISPR-Cas12a system for circulating tumor cell detection. Anal Chem. 2021;93:12921–12929. doi: 10.1021/acs.analchem.1c02228. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.





