Profile Of Pancreatic Cancer Research Articles

333P Feasibility and clinical utility of endoscopic ultrasound-guided tissue acquisition for comprehensive genomic profiling in pancreatic cancer: A systematic review and meta-analysis

333P Feasibility and clinical utility of endoscopic ultrasound-guided tissue acquisition for comprehensive genomic profiling in pancreatic cancer: A systematic review and meta-analysis

Fundamental insights and molecular interactions in pancreatic cancer: Pathways to therapeutic approaches

The gastrointestinal tract can be affected by a number of diseases that pancreatic cancer (PC) is a malignant manifestation of them. The prognosis of PC patients is unfavorable and because of their diagnosis at advanced stage, the treatment of this tumor is problematic. Owing to low survival rate, there is much interest towards understanding the molecular profile of PC in an attempt in developing more effective therapeutics. The conventional therapeutics for PC include surgery, chemotherapy and radiotherapy as well as emerging immunotherapy. However, PC is still incurable and more effort should be performed. The molecular landscape of PC is an underlying factor involved in increase in progression of tumor cells. In the presence review, the newest advances in understanding the molecular and biological events in PC are discussed. The dysregulation of molecular pathways including AMPK, MAPK, STAT3, Wnt/β-catenin and non-coding RNA transcripts has been suggested as a factor in development of tumorigenesis in PC. Moreover, cell death mechanisms such as apoptosis, autophagy, ferroptosis and necroptosis demonstrate abnormal levels. The EMT and glycolysis in PC cells enhance to ensure their metastasis and proliferation. Furthermore, such abnormal changes have been used to develop corresponding pharmacological and nanotechnological therapeutics for PC.

Description of technique for endoscopic ultrasound-guided tissue acquisition in pancreatic cancer for comprehensive molecular profiling: Results of a randomized trial.

e16306 Background: As theoretically actionable genomic lesions are found in almost 50% of pancreatic cancers which can impact clinical management in up to 30% of patients, there is increased focus on molecular profiling. Although EUS-FNB is an established method for achieving pathological diagnosis in pancreatic cancers, the technique of tissue acquisition for comprehensive molecular profiling (CMP) has not been described. Methods: Patients proven to have pancreatic adenocarcinoma using rapid onsite evaluation (ROSE) at EUS were randomized to undergo two or three dedicated FNB passes for CMP. Tissue was procured using 22G Franseen needle adopting the fanning technique and stylet-retraction maneuver. Genomic DNA and total RNA were extracted from formalin-fixed paraffin-embedded (FFPE) cell blocks (Qiagen AllPrep). Next-generation sequencing (NGS) was performed (Archer Panels) for analyzing 69 gene DNA mutations (single nucleotide variants, insertions, and deletions) and 53 RNA somatic oncogenic gene fusions. Main outcome measure was the proportion of specimens in which adequate DNA and RNA were extracted for CMP. Results: 33 patients (mean age 77.0 years [SD 7.7], female = 20) with pancreatic cancer (location = head/uncinate 22; other 11) were randomized to two (n = 17) or three (n = 16) FNB passes. While sufficient DNA was extracted from all 33 FFPE cell blocks, adequate RNA was extracted from 15 of 16 in the three pass (93.8%) vs. 16 of 17 in the two pass cohort (94.1%) (p = 0.99). There was no significant difference in the mean concentration of DNA (two passes 10.7 ng/ul [SD 7.1] vs. three passes 7.9 ng/ul [SD 4.4]; p = 0.19) or RNA (two passes 37.1 ng/ul [SD 26.5] vs. three passes 28.9 ng/ul [SD 13.2]; p = 0.29) between the groups. While somatic oncogene RNA fusion (LDAH-ETV1) predictive of metastatic disease was identified in one specimen, DNA mutations were identified in all 33 specimens that included one BRCA1 mutation that warranted Oxaliplatin-based chemotherapy. Conclusions: Specimens of adequate quantity and of high quality for comprehensive molecular profiling in pancreatic cancer can be procured in nearly 95% of patients by performing two dedicated passes using the 22G Franseen needle, adopting the fanning maneuver and stylet-retraction technique. Clinical trial information: NCT05043532 .

Abstract 4042: Genomic and pharmaco-genomic profiling of pancreatic cancer using patient-derived organoids

Abstract Introduction: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal common malignancies, with little improvement in patient outcomes over the past decades. We have developed a novel methodology to culture organoids from both human healthy pancreatic ductal epithelial tissues and PDAC. A collection of patient-derived organoids (PDO), grown using this protocol, numbers over 100 models to date. The 100% neoplastic purity of the organoid cultures facilitates molecular characterization that has been traditionally challenging in the pauci-cellular state of primary pancreatic tumors. These PDO open new opportunities for deep genomic and transcriptomic studies of the disease, and for individualized drug screens. Here we demonstrate that accurate predictive models of response to pharmacological treatments of PDAC can be developed using data from such screens alongside molecular profiles of the PDO. Methods: Molecular analysis of the PDO library yielded genomic and transcriptional profiles of the cultures, including those of copy number variation (CNV), mutations in the exome and mRNA expression. From these, we drew features for prediction of drug responses. Using molecular features drawn from these profiles, we developed a panel of predictive models for response to standard-of-care cytotoxic agents and a number of targeted treatments. We employed Random Forest (RF) regression as a machine-learning tool for this purpose. Results: PDO are faithful models of PDAC, whose molecular features closely resemble those of PDAC tumor specimens. Using a subset of these features, we were able to accurately learn PDO responses to cytotoxic agents: for each of the five agents considered, the predicted drug response correlated strongly (p < 10-7) with the observed value. A similar accuracy of prediction was achieved for a number of targeted agents. Conclusion: PDOs are a valuable resource for molecular and pharmacological characterization of PDAC, with a potential to guide clinical decisions with regard to treatment. Citation Format: Astrid Deschênes, Pascal Belleau, Dennis Plenker, Amber Habowski, Hardik Patel, Youngkyu Park, Hervé Tiriac, Lindsey A. Baker, Alexander Krasnitz, David A. Tuveson. Genomic and pharmaco-genomic profiling of pancreatic cancer using patient-derived organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4042.

Genomic profiling in pancreatic cancer reveals spatial genetic heterogeneity but spatial transcriptomic homogeneity

Genomic profiling in pancreatic cancer reveals spatial genetic heterogeneity but spatial transcriptomic homogeneity

Identification of genomic alterations and associated transcriptomic profiling reveal the prognostic significance of MMP14 and PKM2 in patients with pancreatic cancer.

Pancreatic cancer is characterized by multiple genomic alterations, including KRAS mutations, TP53 mutations and CDKN2A deletion. However, the prognostic relevance of those genomic alterations and associated transcriptomic profiling in pancreatic cancer are unclear. Integrated analysis of The Cancer Genome Atlas (TCGA) datasets revealed that KRAS mutation, TP53 mutation and CDKN2A deletion were all bad prognostic factors in pancreatic cancer. And KRAS mutation, TP53 mutation and CDKN2A deletion were coordinated and co-occurred in pancreatic cancer. Transcriptomic analysis showed that MMP14 and PKM2 were both up-regulated by KRAS mutation, TP53 mutation or CDKN2A deletion. Also, MMP14 and PKM2 were both associated with unfavorable outcomes in pancreatic cancer. Compared with normal tissues, MMP14 and PKM2 were up-regulated in pancreatic cancer tissues. Moreover, MMP14 and PKM2 were highly expressed in high grade of pancreatic cancer. Furthermore, MMP14 and PKM2 were correlated with each other, and the combination of MMP14 and PKM2 could be used as better prognostic markers than MMP14 or PKM2 alone. At last, the high expression and bad prognostic effects of MMP14 and PKM2 in pancreatic cancer were validated using tissue microarray. Overall, the genomic alterations and associated transcriptomic profiling analysis suggested new prognostic makers of MMP14 and PKM2 in pancreatic cancer.

Enrichment of alterations in targetable molecular pathways in KRAS wild-type (WT) pancreatic cancer (PC).

4629 Background: Genomic profiling has identified KRAS mutations in 88-90% of PC. KRAS WT tumors represent a molecularly heterogeneous group that may harbor targetable alterations (TA). We studied KRAS WT PC using NextGen sequencing (NGS) and whole transcriptome sequencing (WTS) to characterize the molecular landscape of this unique group and to assess the prevalence of TA. Methods: A total of 1164 PC tumors were tested at Caris Life Sciences by NGS (592 genes), WTS (NovaSeq), IHC and fragment analysis. Comparison of KRAS WT vs. mutant (MT) was done by Fisher-Exact or Chi2 and was corrected for multiple tests. Results: The KRAS WT cohort included 144 tumors (12.4%). No differences were seen in gender (female: 46% in both WT & MT) and age (median: 66 & 67) compared to KRAS MT. In KRAS WT tumors, targetable fusions tested by WTS and pathogenic mutations by NGS were seen in 22% (32 of 144) and 52% (75 of 144) respectively; potentially targetable amplifications (amp) were seen in 5 additional tumors. No TA were seen in 22% of WT tumors. Key alterations are in Table. Alterations inducing MAPK activation, including BRAF, RAF1, NF1 and GNAS changes were seen in 38 (26%) tumors. Frequent alterations were seen in FGFR genes (11 tumors), MET (4, including 1 exon 14 skip), and ERBB receptor and ligands (10). Fusions in ALK, ROS1, RET and NOTCH1 were seen (8), largely exclusive of other drivers. Wnt, PI3K, chromatin remodeling (CR) and DDR changes were common and sometimes seen concurrent with other alterations. Compared to KRAS MT, no difference of PD-L1 or TMB-H was seen. BRAF, APC, PBRM1, CTNNB1 mutations, MDM2 amp, gene fusions and MSI-H/dMMR were all more frequent in KRAS WT tumors (corrected p < 0.05). Conclusions: KRAS WT PC is enriched with TA (e.g., BRAF, ALK, ROS1, NRG1, MSI-H). The use of WTS in combination with NGS identifies activated molecular pathways in the majority of KRAS WT tumors. Based on our findings, comprehensive profiling of PC at the DNA and RNA level is recommended to provide patients with therapeutic opportunities beyond standard treatments. [Table: see text]

Prognostic alternative splicing signature reveals the landscape of immune infiltration in Pancreatic Cancer.

Background: Pancreatic cancer (PC) is an aggressive cancer with worse survival in the world. Emerging evidence suggested that the imbalance of alternative splicing (AS) is a hallmark of cancer and indicated poor prognosis of patients. Genes-derived splicing events can produce neoepitopes for immunotherapy. However, the profound study of splicing profiling in PC is still elusive. We aimed to identification of novel prognostic signature across a comprehensive splicing landscape and reveal their relationship with tumor-infiltrating immune cells in pancreatic cancer microenvironment.Methods: Based on integrated analysis of splicing profiling and clinical data, differentially splicing events were filtered out. Then, stepwise Cox regression analysis was applied to identify survival-related splicing events and construct prognostic signature. Functional enrichment analysis was performed to explore biology function. Kaplan-Meier curves and receiver operating characteristic (ROC) curves were performed to validate the predictive effect of predictive signature. We also verified the clinical value of prognostic signature under the influence of different clinical parameters. For deeper analysis, we evaluated the correlation between prognostic signature and infiltrating immune cells by CIBERSORT.Results: According to systematic analyzing, a final six splicing events were identified and validated the good prognostic capability in entire TCGA dataset, validation set 1 and validation set 2 by Kaplan-Meier curves (P < 0.0001). The area under the curve (AUC) of ROC curves were also confirmed the high predictive efficiency of the prognostic signature in these three cohorts (AUC = 0.857, 0.895 and 0.788). In order to validate whether prognostic signature highlights a correlation between AS and immune contexture, CIBERSORT was performed to analyze the proportion of tumor-infiltrating immune cells in PC. Based on prognostic signature, we identified survival-related immune cells including CD8 T cells (P = 0.0111), activated CD4 memory T cells (P = 0.0329) and resting mast cells (P = 0.0352).Conclusion: In conclusion, our study contribute to provide a promising prognostic signature based on six splicing events and revealed prognosis-related immune cells which indeed represented novel tumor drivers and provide potential targets for personalized therapeutic.

Liquid Biopsy as Surrogate for Tissue for Molecular Profiling in Pancreatic Cancer: A Meta-Analysis Towards Precision Medicine.

Liquid biopsy (LB) is a non-invasive approach representing a promising tool for new precision medicine strategies for cancer treatment. However, a comprehensive analysis of its reliability for pancreatic cancer (PC) is lacking. To this aim, we performed the first meta-analysis on this topic. We calculated the pooled sensitivity, specificity, positive (LR+) and negative (LR−) likelihood ratio, and diagnostic odds ratio (DOR). A summary receiver operating characteristic curve (SROC) and area under curve (AUC) were used to evaluate the overall accuracy. We finally assessed the concordance rate of all mutations detected by multi-genes panels. Fourteen eligible studies involving 369 patients were included. The overall pooled sensitivity and specificity were 0.70 and 0.86, respectively. The LR+ was 3.85, the LR- was 0.34 and DOR was 15.84. The SROC curve with an AUC of 0.88 indicated a relatively high accuracy of LB for molecular characterization of PC. The concordance rate of all mutations detected by multi-genes panels was 31.9%. LB can serve as surrogate for tissue in the molecular profiling of PC, because of its relatively high sensitivity, specificity and accuracy. It represents a unique opportunity to be further explored towards its introduction in clinical practice and for developing new precision medicine approaches against PC.

Analysis of nuclear magnetic resonance-based metabonomics of pancreatic cancer

Objective To investigate the clinical value of serum metabonomic profile of pancreatic cancer using nuclear magnetic resonance (NMR)-based metabonomics. Methods The retrospective case-control study was adopted. The clinical data of 23 patients with pancreatic cancer (PC group) and 16 healthy volunteers (control group) who were admitted to the Fujian Medical University Union Hospital between December 2013 and December 2014 were collected. The serum of the 2 groups was measured by 1H NMR spectroscopy. Multivariate statistical analyses were performed to identify the characteristic metabolites in the 2 groups, including principal component analysis (PCA), partial least squares discriminant analysis(PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Observation indicators included: (1) multivariate statistical analysis of serum metabonomic profile, results of PCA, PLS-DA and OPLS-DA, (2) screening of metabolites. Measurement data with normal distribution were presented as ±s. The comparison between groups was evaluated with the t test. The count data were analyzed using the chi-square test. Results (1) The multivariate statistical analysis of serum metabonomic profile: results of PCA showed that expression rates of principal component 1 (PC1) and principal component 2 (PC2) to original data were 54.9% and 23.5%, with both cumulative contribution rate of 78.4%. Results of PLS-DA showed that the separative trend between PC group and control group was appeared, and variance of X and Y matrixes and predictive value were 0.254, 0.816 and 0.385. Results of OPLS-DA showed that the differences of samples between the 2 groups were further increased, and differential metabolites were screened according to the distinction of scores between the 2 groups, value of R2X, R2Y and Q2 was 0.254, 0.816 and 0.433. (2) Screening of metabolites: 35 serum metabolites were detected in the 2 groups. Compared with the control group, levels of 3-hydroxybuyarate, citrate, formate, glutamate, isoleucine, methionine and phenylalanine in the PC group were elevated (r=0.524, 0.511, 0.656, 0.566, 0.503, 0.498, 0.648, P<0.05), and levels of 3-methylhistidine, alanine, glutamine, LDL and VLDL in the PC group were decreased (r=-0.607, -0.508, -0.560, -0.568, -0.559, P<0.05). Conclusions Compared with healthy controls, several amino acids, citrate and lipoproteins demonstrate the metabolic differences in the serum of patients with pancreatic cancer. NMR based metabonomic profile technology can distinguish the difference of serum metabolites between patients with pancreatic cancer and healthy controls. NMR based metabonomic technology may be a promising method for the diagnosis of pancreatic cancer. Key words: Pancreatic neoplasms; Nuclear magnetic resonance; Metabonomics; Diagnosis; Serum biomarker

A Novel Multivariate Index for Pancreatic Cancer Detection Based On the Plasma Free Amino Acid Profile.

BackgroundThe incidence of pancreatic cancer (PC) continues to increase in the world, while most patients are diagnosed with advanced stages and survive <12 months. This poor prognosis is attributable to difficulty of early detection. Here we developed and evaluated a multivariate index composed of plasma free amino acids (PFAAs) for early detection of PC.MethodsWe conducted a cross-sectional study in multi-institutions in Japan. Fasting plasma samples from PC patients (n = 360), chronic pancreatitis (CP) patients (n = 28), and healthy control (HC) subjects (n = 8372) without apparent cancers who were undergoing comprehensive medical examinations were collected. Concentrations of 19 PFAAs were measured by liquid chromatography–mass spectrometry. We generated an index consisting of the following six PFAAs: serine, asparagine, isoleucine, alanine, histidine, and tryptophan as variables for discrimination in a training set (120 PC and matching 600 HC) and evaluation in a validation set (240 PC, 28 CP, and 7772 HC).ResultsSeveral amino acid concentrations in plasma were significantly altered in PC. Plasma tryptophan and histidine concentrations in PC were particularly low, while serine was particularly higher than that of HC. The area under curve (AUC) based on receiver operating characteristic (ROC) curve analysis of the resulting index to discriminate PC from HC were 0.89 [95% confidence interval (CI), 0.86–0.93] in the training set. In the validation set, AUCs based on ROC curve analysis of the PFAA index were 0.86 (95% CI, 0.84–0.89) for all PC patients versus HC subjects, 0.81 (95% CI, 0.75–0.86) for PC patients from stage IIA to IIB versus HC subjects, and 0.87 (95% CI, 0.80–0.93) for all PC patients versus CP patients.ConclusionsThese findings suggest that the PFAA profile of PC was significantly different from that of HC. The PFAA index is a promising biomarker for screening and diagnosis of PC.

PWE-200 Metabolomic profiling in pancreatic cancer; in search of new biomarkers

Introduction Pancreatic cancer is a devastating disease with a poor outcome. Current biomarkers fall short in accessibility, sensitivity, specificity and their ability to distinguish malignant from benign conditions. Metabolomics aims to decipher molecular signatures that will distinguish disease from controls, ultimately leading to novel targets for diagnosis and treatment. The aim of this novel study was to characterise potentially new pancreatic cancer biomarkers. Method Urine and serum samples from 32 patients with pancreatic cancer (PC), were compared with healthy controls and patients with chronic pancreatitis and benign jaundice. Two analytical platforms, UHPLC-MS and GC-TOF-MS, were used in this study in order to minimise false negatives and identify a quantitative compliment of all metabolites across a wide molecular weight range. GC-TOF-MS can identify very low molecular weight polar metabolites Results After univariate analysis, a total of 747 serum metabolites and 638 urinary metabolites were identified as significantly different in comparison to healthy controls. When chronic pancreatitis and benign jaundice controls were used for comparison to pancreatic cancer then 185 and 176 serum and 333 and 51 urinary metabolites were identified as statistically significant at differentiating these groups respectively. Multivariate analysis showed good discrimination between resectable and non-resectable cases, based on metabolite profile. Urine profiles, in particular, showed consistent separation between resectable and non-resectable disease. When participants without definitive pathology were removed from analysis, the separation improved further. It was so clear that only an unsupervised PCA analysis was sufficient to visualise group separation. Importantly there did not seem to be any effect from diabetes or jaundice on the differentiation of metabolite profiles. Conclusion In this novel study, metabolite profiling can distinguish patients with pancreatic cancer from controls. Furthermore, multivariate analysis of metabolite profiles is able to distinguish resectable from irresectable disease with 95% confidence intervals. Multiple putative biomarkers have been identified and will be presented. Disclosure of interest None Declared.

NMR-based Metabolite Profiling of Pancreatic Cancer

Metabolite profiles of serum from pancreatic cancer (PC) patients (n=51) and non-disease controls (n=47) were measured using 1H nuclear magnetic resonance (NMR) spectroscopy with a focus on the metabolic changes associated with PC pathology and the development and external validation of the statistical models developed using the metabolite data. Univariate statistical analysis indicated 42 metabolite features showing significant differences between PC and controls (p<0.05). Based on multivariate regression analysis of the data from 38 PC patients and 32 controls, twelve distinguishing metabolites (alanine, choline, citrate, creatinine, glucose, glutamine, glutamic acid, 3- hydroxybutyrate, lactate, lipids, methionine and valine) were determined based on their ranked importance in a partial least square discriminant analysis (PLS-DA) model. A cross-validated regression PLS-DA model built using these metabolites differentiated the cancer and control groups with high accuracy and an area under the receiver operating characteristic curve (AUROC) of 0.95. Notably, external validation of this model using the NMR data from a second, distinct set of samples (13 PC patients and 15 controls) collected approximately 1 year later showed an AUROC of 0.86, which represents very good performance compared to the current approaches for identifying pancreatic cancer patients. Metabolic changes in pancreatic cancer patients compared to healthy controls as shown in this study demonstrate the potential for the development of regression models based on blood metabolites to identify patients with pancreatic cancer. Keywords: 1H NMR, early detection, MCCV analysis, metabolite profiling, metabolomics, pancreatic cancer.

NCOA3-mediated upregulation of mucin expression via transcriptional and post-translational changes during the development of pancreatic cancer.

Pancreatic cancer (PC) is characterized by aberrant overexpression of mucins that contribute to its pathogenesis. Although the inflammatory cytokines contribute to mucin overexpression, the mucin profile of PC is markedly distinct from that of normal or inflamed pancreas. We postulated that de novo expression of various mucins in PC involves chromatin modifications. Analysis of chromatin modifying enzymes by PCR array identified differential expression of NCOA3 in MUC4-expressing PC cell lines. Immunohistochemistry analysis in tumor tissues from patients and spontaneous mouse models, and microarray analysis following the knockdown of NCOA3 were performed to elucidate its role in mucin regulation and overall impact on PC. Silencing of NCOA3 in PC cell lines resulted in significant downregulation of two most differentially expressed mucins in PC, MUC4 and MUC1 (P<0.01). Immunohistochemistry analysis in PC tissues and metastatic lesions established an association between NCOA3 and mucin (MUC1 and MUC4) expression. Spontaneous mouse model of PC (K-ras(G12D); Pdx-1cre) showed early expression of Ncoa3 during pre-neoplastic lesions. Mechanistically, NCOA3 knockdown abrogated retinoic acid-mediated MUC4 upregulation by restricting MUC4 promoter accessibility as demonstrated by micrococcus nuclease digestion (P<0.05) and chromatin immuno-precipitation analysis. NCOA3 also created pro-inflammatory conditions by upregulating chemokines like CXCL1, 2, 5 and CCL20 (P<0.001). AKT, ubiquitin C, ERK1/2 and NF-κB occupied dominant nodes in the networks significantly modulated after NCOA3 silencing. In addition, NCOA3 stabilized mucins post translationally through fucosylation by FUT8, as the knockdown of FUT8 resulted in the downregulation of MUC4 and MUC1 at protein levels.

Evidence for the importance of personalized molecular profiling in pancreatic cancer.

There is a growing body of evidence that targeted gene therapy holds great promise for the future treatment of cancer. A crucial step in this therapy is the accurate identification of appropriate candidate genes/pathways for targeted treatment. One approach is to identify variant genes/pathways that are significantly enriched in groups of afflicted individuals relative to control subjects. However, if there are multiple molecular pathways to the same cancer, the molecular determinants of the disease may be heterogeneous among individuals and possibly go undetected by group analyses. In an effort to explore this question in pancreatic cancer, we compared the most significantly differentially expressed genes/pathways between cancer and control patient samples as determined by group versus personalized analyses. We found little to no overlap between genes/pathways identified by gene expression profiling using group analyses relative to those identified by personalized analyses. Our results indicate that personalized and not group molecular profiling is the most appropriate approach for the identification of putative candidates for targeted gene therapy of pancreatic and perhaps other cancers with heterogeneous molecular etiology.

Transcriptional regulatory network and protein–protein interaction to reveal the mechanism of pancreatic cancer

The development of pancreatic cancer (PC) may involve the over-expression of oncogenes, inactivation tumor suppressor genes or the deregulation of various signaling proteins. Thus identification and analysis of transcriptional regulatory relationship as well as protein-protein interaction (PPI) in PC to provide deep insights into the pathogenetic mechanism of pancreatic cancer. In this study, we downloaded the gene expression profile of PC from Gene Expression Omnibus and identified differentially expressed genes (DEGs) in PC patients compared with controls. To further understand how these DEGs act together to account for the initiation of pancreatic cancer, a transcriptional regulatory network was constructed to find the notes for GO function and KEGG pathways annotation, aiming to explore the clusters and pathways in PC. A total of 1,821 transcriptional regulatory relationships were identified. Then, a PPI network was constructed and noted by GO and KEGG, and some special modules, clusters and pathways were identified to involved in PC. Finally, we constructed the transcriptional regulatory network and PPI network of pancreatic cancer. Comparing the pathways involved in Transcriptional regulatory network and PPI network, pathway in cancer, PC, p53 signaling pathway, Hematopoietic cell lineage and graft-versus-host disease co-existed in these two network, so we predict these pathways may play key factors in development of cancer.

P-0044 - The Exploration of Micrornas Expression Profiling in Pancreatic Cancer

P-0044 - The Exploration of Micrornas Expression Profiling in Pancreatic Cancer

MiRNA profiling in pancreatic cancer and restoration of chemosensitivity

Pancreatic cancers relapse due to small but distinct population of cancer stem cells (CSCs) which are in turn regulated by miRNAs. The present study identifies a series of miRNAs which were either upregulated (e.g. miR-146) or downregulated (e.g. miRNA-205, miRNA-7) in gemcitabine resistant MIA PaCa-2 cancer cells and clinical metastatic pancreatic cancer tissues. Gemcitabine resistant MIA PaCa-2 cells possessed distinct ALDH-positive CSC fraction expressing stem cell markers OCT3/4 and CD44 and chemoresistance marker class IIIβ-tubulin (TUBB3) which decreases on transfection with miR-205 resulting in the restoration of chemosensitivity to gemcitabine.

Abstract 1294: Suppression of uPA in chemo-sensitization and p53 regulation in pancreatic cancer cells

Abstract Despite new knowledge of the molecular profile of pancreatic cancer and its precursor lesions, survival rates have changed very little over the last 40 years. The ability to predict which patients would benefit most from surgical intervention and/or chemotherapy would be a great clinical asset. Researchers have demonstrated that uPA is frequently present in a higher concentration in the serum of pancreaticobiliary cancer patients. It is known that uPA is involved in ECM degradation and has been correlated with malignant transformation of cancer cells. Emerging data have suggested that the capability of a tumor to grow and propagate is dependent on a small subset of cells within a tumor called cancer stem cells (CSCs) or cancer initiating cells. Under in vitro cell culture conditions, these cells possess sphere-forming ability, which is known to be one of the properties of CSCs. Interestingly, the significance of this sphere formation ability still remains unclear. Recent studies have demonstrated that these sphere-forming cells acquired chemoresistance to cisplatin. In the present study, as observed by FACS analysis, we show that a sub-population of MIA PaCa-2 and PANC-1 pancreatic cancer cells possess cancer stem cell properties. RNAi-mediated suppression of uPA in these cells retarded their tumor forming ability in a nude mouse model. We also observed that uPA-suppressed MIA PaCa-2 and PANC-1 cells, after supplementation with uPA protein regained their cancer stem cell phenotype and showed increased expression of Lhx-2. To determine whether these sub-population cells possess any chemoresistance, we treated these cells with varying concentrations of gemcitabine (0-1000 nM) and observed that these cells were resistant to gemcitabine even at the 1000 nM concentration. Further suppression of uPA using siRNA in these cells sensitized these cells to gemcitabine. In addition, to determine whether uPA has any transcriptional role, we examined whether uPA interacted with any known transcription factors we used a TF-protein array. We observed that uPA interacted with Hoxa-5 very strongly. To further determine whether the interaction of uPA with Hoxa-5 invokes any regulatory response, we used a p53 promoter known to possess Hoxa-5 binding regions to drive a Luciferace gene, both with and without the presence of uPA. We observed that uPA retarded p53 promoter activity. Finally, nude mice implanted with MIA PaCa-2 cancer stem cells were susceptible to gemcitabine treatment after uPA downregulation. Taken together, these results indicate that targeting uPA can sensitize chemoresistant pancreatic cells to gemcitabine. 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 1294. doi:1538-7445.AM2012-1294

Invasive markers identified by gene expression profiling in pancreatic cancer

BackgroundMolecular profiling has proven utility as a diagnostic and predictive tool in clinical oncology. However, a clinically relevant gene expression profile in pancreatic cancer remains elusive. MethodsPrimary and metastatic pancreatic cancer cell lines (BxPC-3 and AsPC-1), were stimulated with phorbol-12-myristate 13-acetate (PMA), a known inducer of cell invasion. Affymetrix gene expression microarray analysis was performed, comparing gene expression to unstimulated controls. Differential expression was identified using ArrayAssist, and confirmed using quantitative real-time PCR. Bioinformatic analysis was performed using Pathway Studio and GOstat. The derived gene expression was further validated in fresh frozen pancreatic tumour samples. The ability of the derived 3 gene expression markersto differentiate between pancreatic adenocarcinoma (PDAC) and other neoplasms, and its association with clinicopathological variables was examined. ResultsPMA-induced significant changes in cell line gene expression, from which distinctive 3 potential invasive markers were derived. Expression of these genes, uPA, MMP-1 and IL1-R1 was confirmed in human pancreatic tumours, and was found to differentiate PDAC from other pancreatic neoplasms. The expression of IL1-R1 in PDAC is a novel finding. We found that the expression of MMP-1 was associated with high-grade PDAC (p = 0.035, Wilcoxon rank sum). ConclusionWe have identified three potential invasive markers, uPA, MMP-1 and IL1-R1, whose gene expression may differentiate PDAC from other pancreatic neoplasms, and potentially reflect a more invasive phenotype.