Novel Biomarker For Pancreatic Cancer Research Articles

T034 Identification of serum microrna-25 as a novel biomarker for pancreatic cancer

T034 Identification of serum microrna-25 as a novel biomarker for pancreatic cancer

Large scale proteomics of circulating extracellular vesicles to reveal novel biomarkers for pancreatic cancer.

523 Background: Robust biomarkers are urgently needed to assist in diagnosing pancreatic cancer. Earlier cancer diagnosis could increase survival rates by an estimated 5-fold and more reliable and real-time assessment of treatment effects in patients with cancer could improve quality of life and reduce healthcare costs. Isolation of circulating extracellular vesicles (cEVs) as ‘liquid biopsies’ offers an advantageous approach to diagnose and monitor disease status. Methods: We conducted a comprehensive proteomics study of cEVs from plasma samples to identify EV proteins that may be used as biomarkers for the diagnosis and prognosis of pancreatic cancer. Patients with pancreatic ductal adenocarcinoma (PDAC) of various tumor stages, chronic pancreatitis, intraductal papillary mucinous neoplasm (IPMN), and age-matched controls were enrolled. EVs were isolated directly from plasma samples using the affinity-based EVTrap method then subject to quantitation by liquid chromatography-tandem mass spectrometry. Results: A total of 124 patients (93 with PDAC, 12 with chronic pancreatitis, 8 with IPMN and 11 controls) were included in the discovery cohort. The isolation of EVs with EVtrap allowed the identification on average of 912 EV proteins per 100µL of sample. Principal component analysis of the cEV proteome showed clear separation between PDAC and benign pancreatic diseases. Individuals with IPMN were more closely related to controls, whereas chronic pancreatitis cases were more related to PDAC. At the functional level, we noted that cytokeratin, protein folding chaperons, and actin dynamics regulators were among protein clusters more highly altered in the cEV of patients with PDAC. We further identified new cEV markers associated with metastatic disease, such as PSMB4, RUVBL2, and ANKAR, as well as other EV proteins with strong correlation to prognosis, such as CRP, RALB, and CD55. Finally, we validated a 7-protein PDACEV signature in a validation cohort of 36 separate patients (24 with PDAC, 6 with chronic pancreatitis and 6 with IPMN) which yielded an 89% prediction accuracy for the diagnosis of PDAC. Conclusions: This study provides a valuable resource to the scientific community with a comprehensive catalog of novel proteins on circulating EVs that may assist in the development of novel biomarkers and improve the outcomes of patients with pancreatic cancer.

Serum exosomal miR-451a acts as a candidate marker for pancreatic cancer.

The aim of this study was to explore the diagnostic efficiency of serum exosomal miR-451a as a novel biomarker for pancreatic cancer. Serum samples were collected prior to treatment. First, we analyzed microRNA (miRNA) profiles in serum exosomes from eight pancreatic cancer patients and eight healthy volunteers. We then validated the usefulness of the selected exosomal miRNAs as biomarkers in another 191 pancreatic cancer patients, 95 pancreatic benign disease (PB) patients, and 90 healthy controls. The expression of miR-451a in serum-derived exosomes from pancreatic cancer patients was significantly upregulated compared with those from PB patients and healthy individuals. Serum exosomal miR-451a showed excellent diagnostic power in identifying pancreatic cancer patients. In addition, exosomal miR-451a showed a significant association with clinical stage and distant metastasis in pancreatic cancer, and the expression level of serum exosomal miR-451a was sensitive to therapy and relapse. Serum exosomal miR-451a might serve as a novel diagnostic marker for pancreatic cancer.

LncRNAs: Novel Biomarkers for Pancreatic Cancer.

Pancreatic cancer is one of the most deadly neoplasms and the seventh major cause of cancer-related deaths among both males and females. This cancer has a poor prognosis due to the lack of appropriate methods for early detection of cancer. Long non-coding RNAs (lncRNAs) have been recently found to influence the progression and initiation of pancreatic cancer. MACC1-AS1, LINC00976, LINC00462, LINC01559, HOXA-AS2, LINC00152, TP73-AS1, XIST, SNHG12, LUCAT1, and UCA1 are among the oncogenic lncRNAs in pancreatic cancer. On the other hand, LINC01111, LINC01963, DGCR5, MEG3, GAS5, and LINC00261 are among tumor suppressor lncRNAs in this tissue. In the current review, we summarize the roles of these two classes of lncRNAs in pancreatic cancer and discuss their potential as attractive diagnostic and prognostic biomarkers for pancreatic cancer. We also identified that the low expression of MEG3, LINC01963, and LINC00261 and the high expression of MACC1-AS1, LINC00462, LINC01559, and UCA1 were significantly correlated with worse survival in pancreatic cancer patients. Further research on these lncRNAs will provide new clues that could potentially improve the early diagnosis, prognostic prediction, and personalized treatments of patients with pancreatic cancer.

Increased levels of circulating circular RNA (hsa_circ_0013587) may serve as a novel biomarker for pancreatic cancer.

Aim: Circular RNAcan serve as a biomarker for early diagnosis of pancreatic cancer. Materials& methods: Analyzed the expression of various differentially expressed circular RNAs in the pancreatic cancer tissues by gene chipand identified the expression of hsa_circ_0013587 in pancreatic cancer cells, tissues and plasma by quantitative reverse transcription PCR(qRT-PCR). Results: Hsa_circ_0013587 was highly expressed in the pancreatic cancer tissues, cell lines and plasma samples from patients with pancreatic cancer. Notably, hsa_circ_0013587 was upregulated in pancreatic cancer patients with later clinical stages III-IV as compared with those detected in early clinical stages I-II. Conclusion: A high expression of hsa_circ_0013587 may serve as a novel diagnostic and therapeutic biomarker for pancreatic cancer.

Identification of Serum microRNA-25 as a novel biomarker for pancreatic cancer.

To identify serum microRNA-25 (miR-25) as a diagnostic biomarker for pancreatic cancer (PCa) and to evaluate its supplementary role with serum carbohydrate antigen 19-9 (CA19-9) in early identification of cancers.Eighty patients with pancreatic cancer and 91 non-cancer controls were enrolled in this study. Quantitative reverse transcription-polymerase chain reaction (RT-PCR) was used to detect the expression level of miR-25. Levels of CA19-9, carcinoembryonic antigen (CEA) and carbohydrate antigen 125 (CA125) were measured by chemiluminescent immunoassay. The logistic model was established to evaluate the correlation of miR-25 with clinical characteristics. A risk model for PCa was conducted by R statistical software. Diagnostic utility for PCa and correlation with clinical characteristics were analyzed.The expression level of miR-25, in the PCa group was significantly higher (P < .05). Risk Model illustrated the relation between miR-25 and pancreatic cancer. With the combination of CA19-9, the performance of miR-25 in early stages (I+II) in the diagnosis of PCa was profoundly better than CA19-9 and miR-25 alone. This combination was more effective for discriminating PCa from non-cancer controls (AUC-ROC, 0.985; sensitivity, 97.50%; specificity, 90.11%) compared with CA19-9 alone or the combination of CA19-9 and CA125.The expression level of miR-25 among pancreatic cancer patients was significantly higher than that in the control group. miR-25 existed as one of the most relevant factors of PCa. miR-25 can serve as a novel noninvasive approach for PCa diagnosis, and with the supplementary of CA19-9, the combination was more effective, especially in early tumor screening.

Centromere protein F is identified as a novel therapeutic target by genomics profile and contributing to the progression of pancreatic cancer

Pancreatic cancer (PC) is the most severe and serious deadliest cancer type worldwide. Centromeric proteins (CENPs) family are involved in centromere formation and kinetochore organization during mitosis and play an important role in cancers. Here, we analyzed all CENPs in a panel of PC tissues and non-tumor tissues by genomics profile. We identified that CENPF is significantly upregulated in PC and correlated with poor prognosis of patients. Furthermore, silencing CENPF significantly inhibited PC cell proliferation, migration and epithelial-mesenchymal transition (EMT), and caused cell cycle arrest at the G2/M phase, meanwhile, in vivo growth of pancreatic cells. Moreover, the TNF pathway and longevity regulating pathways are two potential pathways, which were regulated by CENPF. These findings investigated the clinical and functional contribution of CENPF as a novel biomarker for PC.

A Prognostic Prediction Model Developed Based on Four CpG Sites and Weighted Correlation Network Analysis Identified DNAJB1 as a Novel Biomarker for Pancreatic Cancer.

BackgroundThe prognosis of pancreatic cancer, which is among the solid tumors associated with high mortality, is poor. There is a need to improve the overall survival rate of patients with pancreatic cancer.Materials and MethodsThe Cancer Genome Atlas (TCGA) dataset with 153 samples and the International Cancer Genome Consortium (ICGC) dataset with 235 samples were used as the discovery and validation cohorts, respectively. The least absolute shrinkage and selection operator regression was used to construct the prognostic prediction model based on the DNA methylation markers. The predictive efficiency of the model was evaluated based on the calibration curve, concordance index, receiver operating characteristic curve, area under the curve, and decision curve. The xenograft model and cellular functional experiments were used to investigate the potential role of DNAJB1 in pancreatic cancer.ResultsA prognostic prediction model based on four CpG sites (cg00609645, cg13512069, cg23811464, and cg03502002) was developed using TCGA dataset. The model effectively predicted the overall survival rate of patients with pancreatic cancer, which was verified in the ICGC dataset. Next, a nomogram model based on the independent prognostic factors was constructed to predict the overall survival rate of patients with pancreatic cancer. The nomogram model had a higher predictive value than TCGA or ICGC datasets. The low-risk group with improved prognosis exhibited less mutational frequency and high immune infiltration. The brown module with 247 genes derived from the WGCNA analysis was significantly correlated with the prognostic prediction model, tumor grade, clinical stage, and T stage. The bioinformatic analysis indicated that DNAJB1 can serve as a novel biomarker for pancreatic cancer. DNAJB1 knockdown significantly inhibited the proliferation, migration, and invasion of pancreatic cancer cells in vivo and in vitro.ConclusionThe prognostic prediction model based on four CpG sites is a new method for predicting the prognosis of patients with pancreatic cancer. The molecular characteristic analyses, including Gene Ontology, Gene Set Enrichment Analysis, mutation spectrum, and immune infiltration of the subgroups, stratified by the model provided novel insights into the initiation and development of pancreatic cancer. DNAJB1 may serve as diagnostic and prognostic biomarkers for pancreatic cancer.

Multi-omics analysis based on integrated genomics, epigenomics and transcriptomics in pancreatic cancer.

Aim: Integrated analysis of genomics, epigenomics, transcriptomics and clinical information contributes to identify specific molecular subgroups and find novel biomarkers for pancreatic cancer. Materials & methods: The DNA copy number variation, the simple nucleotide variation, methylation and mRNA data of pancreatic cancer patients were obtained from The Cancer Genome Atlas. Four molecular subgroups (iC1, iC2, iC3 and iC4) of pancreatic cancer were identified by integrating analysis. Results: The iC1 subgroup harbors better prognosis, higher immune score, lesser DNA copy number variation mutations and better genomic stability compared with iC2, iC3 and iC4 subgroups. Three new genes (GRAP2, ICAM3 and A2ML1) correlated with prognosis were identified. Conclusion: Integrated multi-omics analysis provides fresh insight into molecular classification of pancreatic cancer, which may help discover new prognostic biomarkers and reveal the underlying mechanism of pancreatic cancer.

MiR-3940-5p/miR-8069 ratio in urine exosomes is a novel diagnostic biomarker for pancreatic ductal adenocarcinoma.

Despite the development of several therapeutic options, the prognosis of pancreatic cancer remains poor. One reason for this is the difficulty of diagnosing the disease at an early stage. For example, carbohydrate antigen (CA) 19-9, which is the most widely used biomarker for pancreatic cancer, cannot be used to detect the disease at early stages. Some studies have attempted to find novel biomarkers for pancreatic cancer. The aim of the present study was to find a novel diagnostic biomarker for pancreatic ductal adenocarcinoma (PDAC) in urine exosomes. Exosomes were isolated from urine and serum samples of patients with PDAC and control subjects, or culture media of cancer cell lines. MicroRNAs (miRNAs) were purified from exosomes. Novel biomarker candidates for PDCA were identisfied from urine exosome miRNA using expression profiling, and validated in a larger number of samples using 3D digital PCR. The results of a preliminary analysis of nine PDAC and seven control subjects revealed that the miR-3940-5p/miR-8069 ratio in urine exosomes was elevated in the patients with PDAC. Experiments using cultured cancer cell lines revealed that the elevation of the miR-3940-5p/miR-8069 ratio was specific for PDAC. Furthermore, the elevation of the miR-3940-5p/miR-8069 ratio in exosomes tended to be higher in the urine than in the serum of patients with PDAC. Validation experiments on 43 PDAC, 12 chronic pancreatitis and 25 control subjects demonstrated that the miR-3940-5p/miR-8069 ratio in urine exosomes was elevated in PDAC at a relatively early stage of the disease. When this ratio was used in combination with CA19-9 for the diagnosis of PDAC, the sensitivity and positive predictive value improved to 93.0 and 78.4%, respectively, when either of them was positive. Additionally, the positive predictive value reached 100% when both were positive. The negative predictive value also improved to 89.7% when both were negative. The miR-3940-5p/miR-8069 ratio in urine exosomes may be useful as a tool for the diagnosis of PDAC, particularly when used in combination with CA19-9.

Alpha-1-acid glycoprotein 1 (AGP1) as a novel biomarker for pancreatic cancer.

e15708 Background: Pancreatic cancer is a heterogeneous disease with an aggressive clinical course. Most patients are detected late due to the insidious onset of symptoms and lack of effective molecular markers. The purpose of this study was to develop protein markers for improved prognostication and non-invasive diagnosis. Methods: A mass spectrometry (MS)-based discovery approach was applied to pancreatic cancer tissues and healthy pancreas. In the verification phase, extracellular proteins with differential expression were further quantified in targeted mode using parallel reaction monitoring (PRM). Next, a tissue microarray (TMA) cohort including 140 pancreatic cancer resection specimens was constructed, in order to validate protein expression status and investigate potential prognostic implications. The levels of protein candidates were finally assessed in a panel of 80 serum samples with ELISA. Results: Protein sequencing with nano-liquid chromatography tandem MS (nano-LC-MS/MS) and targeted PRM identified alpha-1-acid glycoprotein 1 (AGP1) as a potential pancreatic cancer biomarker. Using TMA and immunohistochemistry, AGP1 expression was significantly associated with shorter overall survival (HR = 2.217; 95% CI 1.296-3.794, p = 0.004). Multivariable analysis confirmed the results (HR = 1.867; 95% CI 1.078-3.235, p = 0.026). Circulating levels of AGP1 yielded an area under the curve (AUC) of 0.85 for the discrimination of resectable pancreatic cancer and IPMN from healthy controls. Combining AGP1 with CA 19-9 displayed an AUC of 0.98 with an overall sensitivity of 96% at 90% specificity. Conclusions: This study suggests that AGP1 is a valid biomarker for pancreatic cancer.

A Comprehensive Proteome Analysis of Peripheral Blood Mononuclear Cells (PBMCs) to Identify Candidate Biomarkers of Pancreatic Cancer

Pancreatic cancer (PC) is currently the fourth leading cause of cancer-related mortality worldwide. Peripheral blood mononuclear cells (PBMCs) is a subpopulation of accessible and functional immune cells. Comparative analysis of the proteome of PBMCs can help us elucidate the mechanism of disease and find potential biomarkers for diagnosis. PBMCs were collected from healthy individuals, patients with benign diseases, and pancreatic cancer. iTRAQ-2DLC-MS/MS and SWATH methodologies were applied to make a comparative proteomics analysis of PBMCs. A total of 3,357 proteins with a false discovery rate (FDR) <1% were identified, of which 114 proteins were found dysregulated in the PC group. An extensive SWATH library was constructed which showed a potential application for large scale clinical sample analysis. A PBMCs proteome with extensive protein representation was achieved, which will potentially allow the identification of novel biomarkers for PC.

Abstract 3688: A novel biomarker for pancreatic cancer, sTRA, and CA19-9 define separate subpopulations of PDAC cells with distinctions in behavior and molecular characteristics

Abstract Cancer cells in pancreatic ductal adenocarcinomas (PDACs) exhibit tremendous diversity in behavior and phenotype, but no biomarkers are available to identify subtypes with clinically significant differences in behavior. We recently identified a new marker of pancreatic cancer, called sTRA, that is expressed on cancer cells with different morphologies and molecular characteristics than cancer cells expressing the biomarker CA19-9. Here we tested the hypothesis that the two types of cells have differences between them in behavior, gene expression, and associations with outcome. In cell line models, sTRA-expressing cancer cells were more resistant to drugs, more invasive, and slower-growing than the CA19-9-expressing cells. Patient-derived xenograft tumors produced either CA19-9 or sTRA, and RNA-seq analysis revealed significant, nonrandom differences between the sTRA-expressing and CA19-9-expressing tumors. Each subpopulation was found in lymph nodes or livers with levels that significantly correlated with their matched primary tumors. In an analysis of two tissue microarrays covering 45 and 41 patients, the tumors containing high levels of sTRA-expressing cancer cells had the shortest survival times. These data support the existence of two distinct subtypes of PDAC cells, respectively marked by CA19-9 and sTRA. Together the markers could have value for predicting the behavior of tumors and for isolating, characterizing, and targeting specific subtypes of cancer cells. Citation Format: Daniel Barnett, Ying Liu, ChongFeng Gao, Luke Wisniewski, Katie Partyka, Anna Barry, Galen Hostetter, Aatur Singhi, Randall E. Brand, Richard R. Drake, Brian B. Haab. A novel biomarker for pancreatic cancer, sTRA, and CA19-9 define separate subpopulations of PDAC cells with distinctions in behavior and molecular characteristics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3688.

LncRNA co-expression network analysis reveals novel biomarkers for pancreatic cancer.

High mortality and low survival rates for pancreatic ductal adenocarcinoma (PDAC) mainly result from the delay in diagnosis and treatment. Therefore, there is an urgent need to identify early PDAC biomarkers and new therapeutic targets. In this study, we applied a commonly used systems biology approach, the weighted gene co-expression network analysis (WGCNA), on lncRNA expression data. Eleven lncRNAs, namely A2M-AS1, DLEU2, LINC01133, LINC00675, MIR155HG, SLC25A25-AS1, LINC01857, LOC642852 (LINC00205), ITGB2-AS1, TSPOAP1-AS1 and PSMB8-AS1 have been identified and validated on an independent PDAC expression dataset. Furthermore, we characterized them by functional and pathway enrichment analysis and identified which lncRNAs showed differential expression, differential promoter methylation levels and copy number alterations between normal and PDAC samples. Finally, we also performed a survival analysis and identified A2M-AS1, LINC01133, LINC00205 and TSPOAP1-AS1 as prognostic biomarkers for PDAC. Interestingly, although only a few cancer-associated lncRNAs have been functionally characterized, LINC00675 and LINC01133 lncRNAs have already been demonstrated to be involved in PDAC development and progression. Therefore, our results provide new potential diagnostic/prognostic biomarkers and therapeutic targets for PDAC that deserve to be further investigated. Moreover, these lncRNAs may improve the understanding about molecular pathogenesis of PDAC.

Retraction: "Identification of Novel Biomarkers for Pancreatic Cancer Using Integrated Transcriptomics With Functional Pathways Analysis" by Zhang, X., Tong, P., Chen, J., Pei, Z., Zhang, X., Chen, W., Xu, J. and Wang, J.

The above article from the Journal of Cellular Physiology, published online on 10 March 2016 in Wiley Online Library as Early View (http://onlinelibrary.wiley.com/enhanced/doi/10.1002/jcp.25353/), has been retracted by agreement between Gary Stein, the journal's Editor-in-Chief, and Wiley Periodicals, Inc. The retraction has been agreed following an investigation at the University of Texas, MD Anderson Cancer Center, which confirmed that the article was submitted and approved for publication by Dr. Jin Wang without acknowledgement of NIH funding received or the consent and authorship of Dr. Ann Killary and Dr. Subrata Sen, with whom the manuscript was originally drafted.

Identification of cystatin SN as a novel biomarker for pancreatic cancer.

Cystatin SN (cystatin 1, CST1) is a member of the cystatin superfamily that inhibits the proteolytic activity of cysteine proteases. CST1 is a tumor biomarker that provides useful information for the diagnosis of esophageal, gastric, and colorectal carcinomas. However, the significance of CST1 in pancreatic cancer is unknown. The aim of this study was to assess whether CST1 is a potential biomarker for early diagnosis of malignant pancreatic neoplasms. Microarray analysis of mRNA extracted from pancreatic cancer and pancreatic normal tissues was performed. Bioinformatics revealed that CST1 was one of the highest expressed genes on the array in pancreatic cancer, compared with normal tissue. In addition, the upregulation of CST1 in pancreatic cancer and several pancreatic cancer cell lines was confirmed using real-time PCR (RT-PCR), immunohistochemistry, and Western blotting. Next, CST1 knockdown using siRNA reduced the expression of the proliferation-related proteins p-AKT and PCNA significantly, as well as colony formation and xenograft development in vitro. Consistent with this, CST1 mRNA overexpression was correlated closely with malignancy-associated proteins such as PCNA, cyclin D1, cyclin A2, and cyclin E in pancreatic cancer cell lines. In conclusion, our data suggest that CST1 might contribute to the proliferation of pancreatic cancer cells and could be a potential biomarker for the early detection of pancreatic cancer.

Serum fucosylated haptoglobin as a novel prognostic biomarker predicting high-Gleason prostate cancer.

Fucosylation is an oligosaccharide modification associated with cancer and inflammation, which is catalyzed by fucosyltransferases. Fucosylated haptoglobin (Fuc-Hpt) has been identified as a novel biomarker for pancreatic cancer. In this study, we evaluated serum Fuc-Hpt as a biomarker for prostate cancer, and investigated the expression of fucosyltransferases and haptoglobin in prostate cancer cell lines. We measured the preoperative serum Fuc-Hpt levels in 98 patients who underwent radical prostatectomy (RP) using an established lectin-antibody ELISA. Fucosyltransferase and haptoglobin mRNA and protein expressions in prostate cancer cell lines were determined using quantitative PCR and Western blotting. Serum Fuc-Hpt levels were significantly associated with Gleason score (GS), but not prostate-specific antigen (PSA) levels. The area under the receiver-operator characteristics curve (AUC) for the prediction of GS ≥7 in prostatectomy specimens by Fuc-Hpt was 0.753, in contrast to the PSA AUC of 0.561 and the PSAD AUC of 0.558. The Fuc-Hpt AUC for the prediction of GS upgrade from GS 6 at biopsy to GS ≥7 after RP was 0.689, in contrast to the PSA AUC of 0.588 and PSAD AUC of 0.557. Multivariable analysis revealed that Fuc-Hpt levels were significantly associated with biochemical recurrence after prostatectomy. A high expression of alpha-(1-6) fucosyltransferase (FUT8) and haptoglobin was observed in prostate cancer cell line, suggesting that certain kinds of prostate cancer cells produce Fuc-Hpt. Elevated serum Fuc-Hpt level could be a novel cancer biomarker for predicting the prognosis of patients with prostate cancer, particularly those with high GSs.

Feasibility of Fecal MicroRNAs as Novel Biomarkers for Pancreatic Cancer

IntroductionPancreatic cancer (PCA) is an aggressive tumor that associates with high mortality rates. Majority of PCA patients are diagnosed usually at late tumor stages when the therapeutic options are limited. MicroRNAs (miRNA) are involved in tumor development and are commonly dysregulated in PCA. As a proof-of-principle study, we aimed to evaluate the potential of fecal miRNAs as biomarkers for pancreatic cancer.Materials and MethodsTotal RNA was extracted from feces using Qiagen's miRNA Mini Kit. For miRNA expression analyses we selected a subset of 7 miRNAs that are frequently dysregulated in PCA (miR-21, -143, -155, -196a, -210, -216a, -375). Subsequently, expression levels of these miRNAs were determined in fecal samples from controls (n = 15), chronic pancreatitis (n = 15) and PCA patients (n = 15) using quantitative TaqMan-PCR assays.ResultsAll selected miRNAs were detectable in fecal samples with high reproducibility. Four of seven miRNAs (miR-216a, -196a, -143 und -155) were detected at lower concentrations in feces of PCA patients when compared to controls (p<0.05). Analysis of fecal miRNA expression in controls and patients with chronic pancreatitis and PCA revealed that the expression of miR-216a, -196a, -143 und -155 were highest in controls and lowest in PCA. The expression of the remaining three miRNAs (miR-21, -210 and -375) remained unchanged among controls and the patients with either chronic pancreatitis or PCA.ConclusionOur data provide novel evidence for the differential expression of miRNAs in feces of patients with PCA. If successfully validated in large-scale prospective studies, the fecal miRNA biomarkers may offer novel tools for PCA screening research.

Identification and Validation of Src and Phospho-Src Family Proteins in Circulating Mononuclear Cells as Novel Biomarkers for Pancreatic Cancer

There is an urgent need to develop novel markers of pancreatic cancer to facilitate early diagnosis. Pancreatic carcinoma is characterized by marked stroma formation with a high number of infiltrating tumor-associated macrophages (TAMs) that originate from circulating mononuclear cells (MNCs). We hypothesized that differential analysis of protein expression and phosphorylation in circulating MNCs from healthy nude mice and nude mice bearing orthotopic human pancreatic cancer would identify a surrogate marker of pancreatic cancer. These differences were analyzed by two-dimensional gel electrophoresis followed by Western blot analysis using antibody against phosphorylated tyrosine proteins (pY). Protein and phosphorylated protein spots of interest were identified by mass spectrometry and validated by Western blot analysis as candidate markers for pancreatic cancer. We found that the expression and phosphorylation of Src family proteins were significantly higher in circulating MNCs from mice bearing pancreatic cancer than in circulating MNCs from healthy mice. TAMs in mice with pancreatic tumors also had higher Src family protein expression and phosphorylation than resident macrophages in the pancreas of healthy mice. The expression and phosphorylation of Src family proteins were correlated with tumor weight; however, increased Src expression and phosphorylation also occurred in MNCs from mice with chronic pancreatitis. This is the first report to explore novel pancreatic tumor markers in circulating MNCs. Although the specificity of the marker for pancreatic cancer was low, it could be used to monitor the disease or to select high-risk patients with chronic pancreatitis.

Plectin-1 as a Novel Biomarker for Pancreatic Cancer

We are in great need of specific biomarkers to detect pancreatic ductal adenocarcinoma (PDAC) at an early stage, ideally before invasion. Plectin-1 (Plec1) was recently identified as one such biomarker. However, its suitability as a specific biomarker for human pancreatic cancer, and its usability as an imaging target, remain to be assessed. Specimens of human PDAC, chronic pancreatitis, and normal pancreata were evaluated by immunohistochemistry and Western blot analysis. To validate Plec1 as an imaging target, Plec1-targeting peptides (tPTP) were used as a contrast agent for single photon emission computed tomography in an orthotopic and liver metastasis murine model of PDAC. Plec1 expression was noted to be positive in all PDACs but negative in benign tissues. Plec1 expression increases during pancreatic carcinogenesis. It was found to be misexpressed in only 0% to 3.85% of early PDAC precursor lesions (PanIN I/II) but in 60% of PanIN III lesions. Plec1 expression was further noted to be retained in all metastatic foci assayed and clearly highlighted these metastatic deposits in lymph nodes, liver, and peritoneum. In vivo imaging using tPTP specifically highlighted the primary and metastatic tumors. Biodistribution studies performed after imaging show that the primary pancreatic tumors and liver metastases retained 1.9- to 2.9-fold of tPTP over normal pancreas and 1.7-fold over normal liver. Plec1 is the first biomarker to identify primary and metastatic PDAC by imaging and may also detect preinvasive PanIN III lesions. Strategies designed to image Plec1 could therefore improve detection and staging.