High-grade Pancreatic Ductal Adenocarcinoma Research Articles

Dual-energy computed tomography for predicting histological grading and survival in patients with pancreatic ductal adenocarcinoma.

We evaluated the value of dual-energy computed tomography (DECT) parameters derived from pancreatic ductal adenocarcinoma (PDAC) to discriminate between high- and low-grade tumors and predict overall survival (OS) in patients. Data were retrospectively collected from 169 consecutive patients with pathologically confirmed PDAC who underwent third-generation dual-source DECT enhanced dual-phase scanning before surgery between January 2017 and March 2023. Patients with prior treatments, other malignancies, small tumors, or poor-quality scans were excluded. Two radiologists evaluated three clinical and seven radiological features and measured sixteen DECT-derived parameters. Univariate and multivariate analyses were applied to select independent predictors. A prediction model and a corresponding nomogram were developed, and the area under the curve (AUC), calibration, and clinical applicability were assessed. The correlations between factors and OS were evaluated using Kaplan-Meier survival and Cox regression analyses. One hundred sixty-nine patients were randomly divided into training (n = 118) and validation (n = 51) cohorts, among which 43 (36.4%) and 19 (37.3%) had high-grade PDAC confirmed by pathology, respectively. The vascular invasion, normalized iodine concentration in the venous phase, and effective atomic number in the venous phase were independent predictors for histological grading. A nomogram was constructed to predict the risk of high-grade tumors in PDAC, with AUCs of 0.887 and 0.844 in the training and validation cohorts, respectively. The nomogram exhibited good calibration and was more beneficial than a single parameter in both cohorts. Pathological- and nomoscore-predicted high-grade PDACs were associated with poor OS (all p < 0.05). The nomogram, which combines DECT parameters and radiological features, can predict the histological grade and OS in patients with PDAC before surgery. Question Preoperative determination of histological grade in PDAC is crucial for guiding treatment, yet current methods are invasive and limited. Findings A DECT-based nomogram combining vascular invasion, normalized iodine concentration, and effective atomic number accurately predicts histological grade and OS in PDAC patients. Clinical relevance The DECT-based nomogram is a reliable, non-invasive tool for predicting histological grade and OS in PDAC. It provides essential information to guide personalized treatment strategies, potentially improving patient management and outcomes.

Two-tier architecture-based grading for pancreatic cancer outperforms traditional grading.

A novel architecture-based grading system for pancreatic ductal adenocarcinoma (PDAC) is tested against traditional grading. A total of 103 PDAC resections were graded by College of American Pathologists/American Joint Committee on Cancer (CAP/AJCC) guidelines and by a system using an architectural pattern (dispersed larger duct = low grade vs dense smaller duct = high grade). Survival analyses and interobserver variability were assessed. In total, 114 cases from a public data set were used for validation. Median overall survivals were 15 and 36 months for architectural high-grade and low-grade cases, respectively (P<.001). Conversely, CAP/AJCC grading showed no survival difference between well-differentiated and moderately differentiated tumors (P=.545). Architecture-based grading remained prognostically significant for recurrence-free survival (P=.004), but CAP/AJCC grading was not (P=.226). Adjusted for stage and margin status, architectural high-grade PDACs showed a hazard ratio of 2.69 relative to low grade (P<.001) for survival. The validation cohort confirmed prognostic differences in overall (P<.001) and recurrence-free survival (P=.027) for the architecture-based system, outperforming CAP/AJCC grading. Architecture-based grading exhibited a Cohen's ĸ value of 0.710 (substantial agreement), superior to traditional grading (0.488, moderate agreement). Grading PDAC based on architectural pattern results in superior prognostication and reproducibility vs CAP/AJCC grading.

Dual-layer spectral detector CT: A noninvasive preoperative tool for predicting histopathological differentiation in pancreatic ductal adenocarcinoma

PurposeTo predict histopathological differentiation grades in patients with pancreatic ductal adenocarcinoma (PDAC) before surgery with quantitative and qualitative variables obtained from dual-layer spectral detector CT (DLCT). MethodsTotally 128 patients with histopathologically confirmed PDAC and preoperative DLCT were retrospectively enrolled and categorized into the low-grade (LG) (well and moderately differentiated, n = 82) and high-grade (HG) (poorly differentiated, n = 46) subgroups. Both conventional and spectral variables for PDAC were measured. The ratio of iodine concentration (IC) values in arterial phase(AP) and venous phase (VP) was defined as iodine enhancement fraction_AP/VP (IEF_AP/VP). Necrosis was visually assessed on both conventional CT images (necrosis_con) and virtual mono-energetic images (VMIs) at 40 keV (necrosis_40keV). Forward stepwise logistic regression method was conducted to perform univariable and multivariable analysis. Receiver operating characteristic (ROC) curves and the DeLong method were used to evaluate and compare the efficiencies of variables in predicting tumor grade. ResultsNecrosis_con (odds ratio [OR] = 2.84, 95% confidence interval [CI]: 1.13–7.13; p < 0.001) was an independent predictor among conventional variables, and necrosis_40keV (OR = 5.82, 95% CI: 1.98–17.11; p = 0.001) and IEF_AP/VP (OR = 1.12, 95% CI:1.07–1.17; p < 0.001) were independent predictors among spectral variables for distinguishing LG PDAC from HG PDAC. IEF_AP/VP (AUC = 0.754, p = 0.016) and combination model (AUC = 0.812, p < 0.001) had better predictive performances than necrosis_con (AUC = 0.580). The combination model yielded the highest sensitivity (72%) and accuracy (79%), while IEF_AP/VP exhibited the highest specificity (89%). ConclusionVariables derived from DLCT have the potential to preoperatively evaluate PDAC tumor grade. Furthermore, spectral variables and their combination exhibited superior predictive performances than conventional CT variables.

Molecular heterogeneity and commonalities in pancreatic cancer precursors with gastric and intestinal phenotype

ObjectiveDue to the limited number of modifiable risk factors, secondary prevention strategies based on early diagnosis represent the preferred route to improve the prognosis of pancreatic ductal adenocarcinoma (PDAC). Here,...

Comparison of Multiple Radiomics Models for Identifying Histological Grade of Pancreatic Ductal Adenocarcinoma Preoperatively Based on Multiphasic Contrast-Enhanced Computed Tomography: A Two-Center Study in Southwest China.

Background: We designed and validated the value of multiple radiomics models for diagnosing histological grade of pancreatic ductal adenocarcinoma (PDAC), holding a promise of assisting in precision medicine and providing clinical therapeutic strategies. Methods: 198 PDAC patients receiving surgical resection and pathological confirmation were enrolled and classified as 117 low-grade PDAC and 81 high-grade PDAC group. An external validation group was used to assess models’ performance. Available radiomics features were selected using GBDT algorithm on the basis of the arterial and venous phases, respectively. Five different machine learning models were built including k-nearest neighbour, logistic regression, naive bayes model, support vector machine, and random forest using ten times tenfold cross-validation. Multivariable logistic regression analysis was applied to establish clinical model and combined model. The models’ performance was assessed according to its predictive performance, calibration curves, and decision curves. A nomogram was established for visualization. Survival analysis was conducted for stratifying the overall survival prior to treatment. Results: In the training group, the RF model demonstrated the optimal predictive ability and robustness with an AUC of 0.943; the SVM model achieved the secondary performance, followed by Bayes model. In the external validation group, these three models (Bayes, RF, SVM) also achieved the top three predictive ability. A clinical model was built by selected clinical features with an AUC of 0.728, and combined model was established by an RF model and a clinical model with an AUC of 0.961. The log-rank test revealed that the low-grade group survived longer than the high-grade group. Conclusions: The multiphasic CECT radiomics models offered an accurate and noninvasive perspective to differentiate histological grade in PDAC and advantages of machine learning models including RF, SVM and Bayes were more remarkable.

Multidrug transporter MRP4/ABCC4 as a key determinant of pancreatic cancer aggressiveness

Recent findings show that MRP4 is critical for pancreatic ductal adenocarcinoma (PDAC) cell proliferation. Nevertheless, the significance of MRP4 protein levels and function in PDAC progression is still unclear. The aim of this study was to determine the role of MRP4 in PDAC tumor aggressiveness. Bioinformatic studies revealed that PDAC samples show higher MRP4 transcript levels compared to normal adjacent pancreatic tissue and circulating tumor cells express higher levels of MRP4 than primary tumors. Also, high levels of MRP4 are typical of high-grade PDAC cell lines and associate with an epithelial-mesenchymal phenotype. Moreover, PDAC patients with high levels of MRP4 depict dysregulation of pathways associated with migration, chemotaxis and cell adhesion. Silencing MRP4 in PANC1 cells reduced tumorigenicity and tumor growth and impaired cell migration. Transcriptomic analysis revealed that MRP4 silencing alters PANC1 gene expression, mainly dysregulating pathways related to cell-to-cell interactions and focal adhesion. Contrarily, MRP4 overexpression significantly increased BxPC-3 growth rate, produced a switch in the expression of EMT markers, and enhanced experimental metastatic incidence. Altogether, our results indicate that MRP4 is associated with a more aggressive phenotype in PDAC, boosting pancreatic tumorigenesis and metastatic capacity, which could finally determine a fast tumor progression in PDAC patients.

Development and multicenter validation of a CT-based radiomics signature for discriminating histological grades of pancreatic ductal adenocarcinoma.

The histological grade of pancreatic cancer is an important independent predictor of outcome. However, we lack a method for safely and accurately obtaining the pathological grade before surgery. Radiomics has been used to discriminate between histological grades in tumors. We aimed to develop and validate a radiomics signature for the preoperative prediction of histological grades of pancreatic ductal adenocarcinoma (PDAC) that was based on contrast-enhanced computed tomography (CE-CT). This study comprised 301 patients with pathologically confirmed PDAC who were randomly divided into a training (n=151) and test group (n=150). Radiomics features were selected by a support vector machine (SVM) model, and a radiomics signature was generated by the least absolute shrinkage and selection operator (LASSO) model. An additional 100 patients from 2 other medical centers were used for external validation. Receiver operating characteristic (ROC) curve analysis was used to assess the model and to identify the optimal cutoff value. The radiomics signatures between high-grade and low-grade PDACs in the training and test groups were significantly different (P<0.05). The areas under the curve (AUCs) of the training and test datasets were 0.961 and 0.910, respectively. The optimal cutoff value of the radiomics score was 0.426. In the external validation dataset, the difference between the radiomics signatures of high-grade versus low-grade PDACs was also significant (P<0.05). The radiomics signature for the external validation data had an AUC of 0.770. The CE-CT-based radiomics signature showed moderate predictive accuracy for differentiating low-grade from high-grade PDAC and should become a new noninvasive method for the preoperative prediction of histological grades of PDAC.

Diagnostic accuracy of perfusion-CT using Peak Enhancement Intensity (PEI) in detecting high grade pancreatic ductal adenocarcinoma keeping histopathology as gold standard.

Pancreatic ductal carcinoma is the most common primary malignancy of the pancreas and is associated with a very poor prognosis, being worldwide one of the leading cause of cancer related death. The pre-operative correct identification of this group of patients is very important to minimize unnecessary resections but remains difficult owing to the post-operative assessment of some factors such as tumor resection margins and grading. Perfusion CT (P-CT) is a new imaging technique able to provide qualitative and quantitative information on perfusion parameters of tissues, which have been demonstrated to be correlated with histological markers of angiogenesis. Objectives: To estimate the diagnostic accuracy of CT perfusion using PEI in detecting high grade pancreatic ductal adenocarcinoma keeping histopathology as gold standard. Study Design: Cross sectional study. Setting: Radiology department of Allied Hospital Faisalabad. Period: 6 months after approval from June, 2016 to Nov, 2016. Material and Methods: Permission for research was sought from hospital ethical committee. Patients were collected from OPD &amp; indoor of Radiology and surgical department of Allied Hospital Faisalabad. Confounding variables were controlled by restriction (by excluding the subjects with history of metastatic disease or chemotherapy). CT-Perfusion examination was performed with the patient in supine position on a 128 slice Optima Multi detector CT scanner. Image guided (CT guided) biopsy was done on all patients and specimen was sent to the hospital pathology lab and histopathology was done by senior pathologist, who kept blinded to perfusion-CT analysis. Results: In this study, out of 100 cases, the diagnostic accuracy of CT perfusion using PEI in detecting high grade pancreatic ductal adenocarcinoma keeping histopathology as gold standard was recorded as 90.59%, 91.49%, 92.31%, 89.58% and 91% for sensitivity, specificity, positive predictive value, negative predictive value and accuracy rate. Conclusion: We concluded that diagnostic accuracy of CT perfusion using PEI is higher in detection of high grade pancreatic ductal adenocarcinoma keeping histopathology as gold standard.

An integrated epigenome and transcriptome analysis identifies PAX2 as a master regulator of drug resistance in high grade pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is notoriously difficult to treat due to its aggressive, ever resilient nature. A major drawback lies in its tumor grade; a phenomenon observed across various carcinomas, where highly differentiated and undifferentiated tumor grades, termed as low and high grade respectively, are found in the same tumor. One eminent problem due to such heterogeneity is drug resistance in PDAC. This has been implicated to ABC transporter family of proteins that are upregulated in PDAC patients. However, the regulation of these transporters with respect to tumor grade in PDAC is not well understood. To combat these issues, a study was designed to identify novel genes that might regulate drug resistance phenotype and be used as targets. By integrating epigenome with transcriptome data, several genes were identified based around high grade PDAC. Further analysis indicated oncogenic PAX2 transcription factor as a novel regulator of drug resistance in high grade PDAC cell lines. It was observed that silencing of PAX2 resulted in increased susceptibility of high grade PDAC cells to various chemotherapeutic drugs. Mechanistically, the study showed that PAX2 protein can bind and alter transcriptionally; expression of many ABC transporter genes in high grade PDAC cell lines. Overall, the study indicated that PAX2 significantly upregulated ABC family of genes resulting in drug resistance and poor survival in PDAC.

Pancreatic Ductal Adenocarcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis For Prediction Of Histopathological Grade.

PurposeTo assess the performance of combining computed tomography (CT) texture analysis with machine learning for discriminating different histopathological grades of pancreatic ductal adenocarcinoma (PDAC).MethodsFrom July 2012 to August 2017, this retrospective study comprised 56 patients with confirmed histopathological PDAC (32 men, 24 women, mean age 64.04±7.82 years) who had undergone preoperative contrast-enhanced CT imaging within 1 month before surgery. Two radiologists blinded to the histopathological outcome independently segmented lesions for quantitative texture analysis. Histogram features, co-occurrence, and run-length texture were calculated. A support-vector machine was constructed to predict the pathological grade of PDAC based on preoperative texture features.ResultsPathological analysis confirmed 37 low-grade PDAC (five well-differentiated/grade I and 32 moderately differentiated/grade II) and 19 high-grade PDAC (19 poorly differentiated/grade III) tumors. There were no significant differences in clinical or biological characteristics between patients with high-grade and low-grade tumors (P>0.05). There were significant differences between low-grade PDAC and high-grade PDAC on nine histogram features, seven run-length features, and two co-occurrence features. Cluster shade was the most important predictor (sensitivity 0.315). Using these texture features, the support-vector machine achieved 86% accuracy, 78% sensitivity, 95% and specificity.ConclusionMachine learning–based CT texture analysis accurately predicted histopathological differentiation grade of PDAC based on preoperative texture features, leading to maximization patient survival and achievement of personalized precision treatment.

Histologic Tumor Grade and Preoperative Bilary Drainage are the Unique Independent Prognostic Factors of Survival in Pancreatic Ductal Adenocarcinoma Patients After Pancreaticoduodenectomy.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal types of cancer; most patients die during the first 6 months after diagnosis. With a 5% 5-year survival rate, is the fourth leading cause of cancer death in developed countries. In this regard, several clinical, histopathologic and biological characteristics of the disease favoring long-term survival after pancreaticoduodenectomy have been reported to be significant prognostic factors. Despite the availability of this information, there is no consensus about the different prognostic factors reported in the literature, probably due to variations in patient selection, methods, and sample size studied. The aim of this study was to identify the clinical and pathologic features associated to prognosis of the disease after pancreaticoduodenectomy. The clinical and pathologic data from 78 patients who underwent a potentially curative resection for PDAC at our institution between 2003 and 2014 were analyzed retrospectively. Overall, high-grade PDAC cases showed larger tumor size (P=0.009) and a higher frequency of deaths in association with a nonsignificantly shortened patient overall survival (median of 12.5 vs. 21.7 mo; P=0.065) as compared with low-grade PDAC patients. High histologic grade (P=0.013), preoperative drainage on the main bile duct (P=0.014) and absence of adjuvant therapy (P=0.035) were associated with a significantly poorer outcome. Overall survival multivariate analysis showed histologic grade (P=0.019) and bile duct preoperative drainage (P=0.016) as the sole independent variables predicting an adverse outcome. Our results indicate that histologic tumor grade and preoperative biliary drainage are the only significant independent prognostic factors in PDAC patients after pancreatectomy.

Serotonin Elevation in a Patient With Metastatic Pancreatic Adenocarcinoma

We report a rare case of pancreatic ductal adenocarcinoma (PDAC) presenting as chronic diarrhea with serotonin elevation. PDAC is often diagnosed at an advanced stage and commonly presents with weight loss, abdominal pain, and jaundice. While PDAC can disrupt exocrine function and cause diarrhea and steatorrhea, diarrhea associated with hormone production is more typical of pancreatic neuroendocrine tumors. A 79-year-old woman with breast and endometrial cancer status post right mastectomy and total hysterectomy presented with persistent diarrhea. Prior to admission, the patient was in New Zealand and Australia when she noticed more fatigue and coughing. She took clindamycin and afterwards had up to 10 watery, non-bloody bowel movements per day. The patient was treated with loperamide and then metronidazole, for presumed Clostridium difficile infection. After no improvement, the patient presented to our institution without fever, abdominal pain, nausea, or vomiting. Gastrointestinal pathogen PCR, C. difficile, ova and parasites were sent and returned negative. Abdominal computed tomography (CT) revealed a pancreatic body/tail lesion with pancreatic ductal dilatation and hepatic lesions. Additional labs were sent for secretory tumor, pancreatic insufficiency, and pancreatic cancer. These revealed elevated CA-19-9 (44 U/mL), chromogranin A (49380 ng/mL), serum serotonin (1560 ng/mL), 24-hour urine 5-hydroxyindoleacetic acid (122 mg/day), carcinoembryonic antigen (10.3 ng/mL), alpha-fetoprotein (13.6 ng/mL), calcitonin (1492 pg/mL); normal vasoactive intestinal peptide (< 13 pg/mL); and decreased fecal pancreatic elastase (21 ug/g). The patient underwent EUS with fine needle biopsy of the pancreas and liver lesions with pathology showing high-grade PDAC. Patient was started on octreotide for diarrhea, but transitioned to pancrelipase for pancreatic insufficiency with mild improvement. Patient deferred systemic chemotherapy treatment. While impaired exocrine activity is well documented with PDAC, direct endocrine activity is very rare and poorly understood. PDAC can be associated with disseminated neuroendocrine cells, which may be missed on biopsy but identified by immunohistochemistry. The persistent diarrhea in our patient may have been due to loss of ability to secrete fat-digesting enzymes, but the highly elevated serotonin and chromogranin A suggest neuroendocrine involvement. Future studies are needed to identify the role of neuroendocrine cells in PDAC.Figure. 3: 6 x 3.0 cm lesion in the pancreatic body/tail with numerous hepatic lesions.Figure: Typical morphology of pancreatic adenocarcinoma with focal gland formation and desmoplastic stroma.Figure: Area of solid tumor growth with necrosis.

Abstract A40: Emergence of CD47- high expression cells confers enhanced tumorigenicity upon KDM6B suppression in pancreatic cancer

Abstract The role of genetic mutations in the pathogenesis of pancreatic ductal adenocarcinoma (PDAC) is well established. However, it is still unclear if epigenetic aberrations contribute to PDAC progression. We previously reported a novel role for the H3K27 demethylase KDM6B/JMJD3 in regulating PDAC progression (Carcinogenesis 2014;35(11):2404-14). KDM6B was downregulated in high grade PDACs and knockdown (KD) of KDM6B in PDAC cells increased the tumorigenicity and enhanced the aggressive phenotypes of these cells in vivo. Furthermore, CCAAT enhancer binding protein alpha gene (CEBPA) was identified as a direct target of KDM6B, and reduced KDM6B- C/EBPα axis was resulted in increased aggressiveness in PDAC cells. To dissect further the pathological effects caused by loss of KDM6B- C/EBPα function in PDAC cells, we tried to identify a surrogate molecular marker of the cells lacking of KDM6B- function. For the purpose, we used a cDNA microarray to compare the expression profiles of KDM6B- KD and control BxPC3 PDAC cells. 906 genes were upregulated and 639 downregulated in KDM6B- KD BxPC3 cells compared to the control cells. We focused on 58 genes encoding cell-surface molecules that were upregulated in KDM6B- KD BxPC3 cells and validated the expression of 9 surface marker candidates, including 3 that have already been reported to be expressed on PDAC tumor-initiating cells, namely, CD24, CD44, and CD133. Only CD47 was significantly upregulated in the KDM6B- KD BxPC3 cells as confirmed by both quantitative RT-PCR and flow cytometric analysis. CD47 was also upregulated in other PDAC cell lines following KDM6B knockdown. It has recently been reported that CD47 is upregulated in various malignancies and that an increase in CD47 expression is correlated with a poor prognosis. In line with the previous reports, CD47high cells formed about 4-fold more spheres than non-CD47high cells. The close relationship between CD47 expression and the sphere-forming ability was supported by the finding that CD47low cells formed even fewer spheres. To confirm these results in vivo, the sorted CD47high and non-CD47high cells were subcutaneously xenotransplanted into nude mice. All CD47high cells formed tumors more efficiently than the unfractionated KDM6B- KD cells, while the tumor-forming rate of non-CD47high cells was comparable to that of the Ctrl cells. In addition, when the cells were injected into the spleens of nude mice, CD47high cells demonstrated higher liver metastatic potential than the non-CD47high population. These data suggested that the increased tumor-initiating potential of KDM6B- KD cells was attributable to this induced CD47high population. Consistently, the expression of KDM6B and C/EBPα inversely correlated with CD47 expression and tumor grade in human PDAC tumors. Collectively, our data provides a link between epigenetic change and PDAC progression, thus offering a novel strategy to target PDAC aggressiveness by intervening in the dynamics of epigenetic process. Citation Format: Keisuke Yamamoto, Keisuke Tateishi, Yotaro Kudo, Koji Miyabayashi, Ryota Takahashi, Takuma Nakatsuka, Hiroaki Fujiwara, Yousuke Nakai, Yasuo Tanaka, Hideaki Ijichi, Hiroyuki Isayama, Kazuhiko Koike. Emergence of CD47- high expression cells confers enhanced tumorigenicity upon KDM6B suppression in pancreatic cancer. [abstract]. In: Proceedings of the AACR Special Conference on Chromatin and Epigenetics in Cancer; Sep 24-27, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2016;76(2 Suppl):Abstract nr A40.

Inhibition of progression of PanIN through antagonizing EGFR.

Pancreatic ductal adenocarcinoma (PDAC) is an extremely malignant tumor with high lethality in humans. Pancreatic intraepithelial neoplasia (PanIN) is the predominant precancerous lesion for PDAC. Although PanIN is frequently detected in the normal and inflamed pancreas, only a few of PanIN eventually progress into PDAC. Thus, inhibition of PanIN-to-PDAC conversion is critical for preventing the occurrence of PDAC. Here, we evaluated the effect of inhibition of epidermal growth factor receptor (EGFR) signaling on the progression of low-grade PanIN into high-grade PDAC in an established mouse PDAC model (Ptf1a-Cre; K-rasG12D). We found that intraductal infusion of EGFR inhibitors at 12 weeks of age, which induced sustained inhibition of EGFR signaling in the pancreas, significantly decreased the incidence of high-grade PanIN in these mice at 24 weeks of age. Thus, our study suggests that inhibition of EGFR signaling may prevent development of PDAC.

MicroRNA-196a and -196b as Potential Biomarkers for the Early Detection of Familial Pancreatic Cancer

Screening programs are recommended for individuals at risk (IAR) from families with familial pancreatic cancer (FPC). However, reliable imaging methods or biomarkers for early diagnosis of pancreatic ductal adenocarcinoma (PC) or its precursor lesions are still lacking. The ability of circulating microRNAs (miRNAs) to discriminate multifocal high-grade precursor lesions or PC from normal was examined. The presence of miRNA-21, -155, -196a, -196b and -210 was analyzed in the serum of transgenic KPC mice to test their ability to distinguish mice with different grades of pancreatic intraepithelial neoplasia (mPanIN1–3) or PC from control mice. Serum levels of miR-196a and -196b were significantly higher in mice with PanIN2/3 lesions (n = 10) or PC (n = 8) as compared to control mice (n = 10) or mice with PanIN1 lesions (n = 10; P = .01). In humans, miR-196a and -196b were also diagnostic. Patients with PC, sporadic (n = 9) or hereditary (n = 10), and IAR with multifocal PanIN2/3 lesions (n = 5) had significantly higher serum levels than patients with neuroendocrine pancreatic tumors (n = 10) or chronic pancreatitis (n = 10), IAR with PanIN1 or no PanIN lesions (n = 5), and healthy controls (n = 10). The combination of both miR-196a and -196b reached a sensitivity of 1 and specificity of 0.9 (area under the curve = 0.99) to diagnose PC or high-grade PanIN lesions. In addition, preoperative elevated serum levels of miR-196a and -196b in patients with PC or multifocal PanIN2/3 lesions dropped to normal after potential curative resection. The combination of miR-196a and -196b may be a promising biomarker test for the screening of IAR for FPC.

Alternatively spliced tissue factor contributes to tumor spread and activation of coagulation in pancreatic ductal adenocarcinoma

Alternatively spliced tissue factor (asTF) promotes neovascularization and monocyte recruitment via integrin ligation. While asTF mRNA has been detected in some pancreatic ductal adenocarcinoma (PDAC) cell lines and increased asTF expression can promote PDAC growth in a subcutaneous model, the expression of asTF protein in bona fide PDAC lesions and/or its role in metastatic spread are yet to be ascertained. We here report that asTF protein is abundant in lesional and stromal compartments of the five studied types of carcinoma including PDAC. Analysis of 29 specimens of PDAC revealed detectable asTF in >90% of the lesions with a range of staining intensities. asTF levels in PDAC lesions positively correlated with the degree of monocyte infiltration. In an orthotopic model, asTF-overexpressing high-grade PDAC cell line Pt45P1/asTF+ produced metastases to distal lymph nodes, which stained positive for asTF. PDAC cells stimulated with and/or overexpressing asTF exhibited upregulation of genes implicated in PDAC progression and metastatic spread. Pt45P1/asTF+ cells displayed higher coagulant activity compared to Pt45P1 cells; the same effect was observed for cell-derived microparticles (MPs). Our findings demonstrate that asTF is expressed in PDAC and lymph node metastases and potentiates PDAC spread in vivo. asTF elicits global changes in gene expression likely involved in tumor progression and metastatic dissemination, and it also enhances the procoagulant potential of PDAC cells and cell-derived MPs. Thus, asTF may comprise a novel therapeutic target to treat PDAC and, possibly, its thrombotic complications.

Abstract 1523: Trafficking of intracytoplasmic lipid droplets in pancreatic cancer cells by pigment epithelium-derived factor alters triacylglycerol metabolism and cellular invasion

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is a rapidly progressing disease with high metastatic potential, thus, it requires a robust and renewable source of energy to meet its metabolic demands. High grade PDAC tumors have been shown to lose expression of a potent negative regulator of lipid metabolism, pigment epithelium-derived factor (PEDF). Emerging data support that lipid droplets (LDs) are dynamic organelles in non-adipocytes and they are capable of participating in signaling pathways and as well as providing a source of energy. LDs are composed of a triacylglycerol (TAG) core covered by coat proteins, some of which assist in restricting lipase activity by enzymes such as adipose triglyceride lipase (ATGL). Based on a study of adipose differentiation related protein (ADRP) over expression resulting in lower metalloproteinase (MMP) levels in non-tumor cells, we proposed that ADRP-positive LDs actively participate in cellular invasion. We further postulated that expression of PEDF in PDAC tumors inhibits cellular invasion and reduces lipid energy stores due to an increase in ATGL-mediated TAG catabolism and redistribution of intracytoplasmic LDs. Methods: PANC-1 cells were transfected with the PEDF gene via the pCEP4 vector. PEDF-expressing PANC-1 cells, wild type controls and human pancreatic tumor tissue sections were immunostained for PEDF, ATGL, neutral lipid (Oil-red-O) and the two LD coat proteins, ADRP and tail interacting protein-47 (TIP-47). LD distribution (perinuclear vs. peripheral) was analyzed and matrigel cell invasion assays were performed. To determine the role of LDs in proliferation, TAG synthesis in PANC-1 cells was blocked using a diacylglycerol acyltransferase-1 (DGAT-1) inhibitor. Results: PEDF-expressing PANC-1 cells revealed a 10-fold decrease in cellular invasion and an increase in ATGL expression. Immunostains for LD coat proteins, ADRP and TIP-47, showed a predominantly perinuclear position for LDs in the wild type control cells, whereas, PEDF-expressing cells exhibited more ADRP positive LDs in the peripheral region of the cytoplasm. The LDs located closest to the nucleus had the largest mean diameter. Human PDAC tissue had minimal to no expression of PEDF and exhibited predominantly larger perinuclear LDs with more intense TIP-47 staining as compared to ARDP. Blockade of TAG synthesis with DGAT-1 inhibitor reduced LD size and significantly decreased cellular proliferation. Conclusions: These data suggest that activation of TAG catabolism in PDAC by upregulation of the lipolytic enzyme, ATGL, or blockade of TAG synthesis by a DGAT-1 inhibitor diminishes LD size. Moreover, redistribution of LDs and changes in LD coat protein expression may be one mechanism underlying the anti-invasive function of PEDF in PANC-1 cells. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1523. doi:1538-7445.AM2012-1523