Dataset Information

Laminin, gamma 2 (LAMC2): a promising new putative pancreatic cancer biomarker identified by proteomic analysis of pancreatic adenocarcinoma tissues.

ABSTRACT: In pancreatic cancer, the incidence and mortality curves coincide. One major reason for this high mortality rate in pancreatic ductal adenocarcinoma (PDAC) patients is the dearth of effective diagnostic, prognostic, and disease-monitoring biomarkers. Unfortunately, existing tumor markers, as well as current imaging modalities, are not sufficiently sensitive and/or specific for early-stage diagnosis. There is, therefore, an urgent need for improved serum markers of the disease. Herein, we performed Orbitrap® mass spectrometry proteomic analysis of four PDAC tissues and their adjacent benign tissues and identified a total of 2190 nonredundant proteins. Sixteen promising candidates were selected for further scrutiny using a systematic scoring algorithm. Our preliminary serum verification of the top four candidates (DSP, LAMC2, GP73, and DSG2) in 20 patients diagnosed with pancreatic cancer and 20 with benign pancreatic cysts, showed a significant (p < 0.05) elevation of LAMC2 in pancreatic cancer serum. Extensive validation of LAMC2 in healthy, benign, and PDAC sera from geographically diverse cohorts (n = 425) (Japan, Europe, and USA) demonstrated a significant increase in levels in early-stage PDAC compared with benign diseases. The sensitivity of LAMC2 was comparable to CA19.9 in all data sets, with an AUC value greater than 0.85 in discriminating healthy patients from early-stage PDAC patients. LAMC2 exhibited diagnostic complementarity with CA19.9 by showing significant (p < 0.001 in two out of three cohorts) elevation in PDAC patients with clinically low CA19.9 levels.

SUBMITTER: Kosanam H

PROVIDER: S-EPMC3790293 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Laminin, gamma 2 (LAMC2): a promising new putative pancreatic cancer biomarker identified by proteomic analysis of pancreatic adenocarcinoma tissues.

Kosanam Hari H Prassas Ioannis I Chrystoja Caitlin C CC Soleas Ireena I Chan Alison A Dimitromanolakis Apostolos A Blasutig Ivan M IM Rückert Felix F Gruetzmann Robert R Pilarsky Christian C Maekawa Masato M Brand Randall R Diamandis Eleftherios P EP

Molecular & cellular proteomics : MCP 20130624 10

In pancreatic cancer, the incidence and mortality curves coincide. One major reason for this high mortality rate in pancreatic ductal adenocarcinoma (PDAC) patients is the dearth of effective diagnostic, prognostic, and disease-monitoring biomarkers. Unfortunately, existing tumor markers, as well as current imaging modalities, are not sufficiently sensitive and/or specific for early-stage diagnosis. There is, therefore, an urgent need for improved serum markers of the disease. Herein, we perform ...[more]

PMID: 23798558

Similar Datasets

Project description:Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer with an abysmal prognosis rate over the last few decades. Early diagnosis and prevention could effectively combat this malignancy. Therefore, it is crucial to discover potential biomarkers to identify asymptomatic premalignant or early malignant tumors of PDAC. Gene expression analysis is a powerful technique to identify candidate biomarkers involved in disease progression. In the present study, five independent gene expression datasets, including 321 PDAC tissues and 208 adjacent non-cancerous tissue samples, were subjected to statistical and bioinformatics analysis. A total of 20 differentially expressed genes (DEGs) were identified in PDAC tissues compared to non-cancerous tissue samples. Gene ontology and pathway enrichment analysis showed that DEGs were mainly enriched in extracellular matrix (ECM), cell adhesion, ECM-receptor interaction, and focal adhesion signaling. The protein-protein interaction network was constructed, and the hub genes were evaluated. Collagen type XII alpha 1 chain (COL12A1), fibronectin 1 (FN1), integrin subunit alpha 2 (ITGA2), laminin subunit beta 3 (LAMB3), laminin subunit gamma 2 (LAMC2), thrombospondin 2 (THBS2), and versican (VCAN) were identified as hub genes. The correlation analysis revealed that identified hub genes were significantly interconnected. Wherein COL12A1, FN1, ITGA2, LAMB3, LAMC2, and THBS2 were significantly associated with PDAC pathological stages. The Kaplan-Meier survival plots revealed that ITGA2, LAMB3, and LAMC2 expression were inversely correlated with a prolonged patient survival period. Furthermore, the Human Protein Atlas database was used to validate the expression and cellular origins of hub genes encoded proteins. The protein expression of hub genes was higher in pancreatic cancer tissue than in normal pancreatic tissue samples, wherein ITGA2, LAMB3, and LAMC2 were exclusively expressed in pancreatic cancer cells. Pancreatic cancer cell-specific expression of these three proteins may play pleiotropic roles in cancer progression. Our results collectively suggest that ITGA2, LAMB3, and LAMC2 could provide deep insights into pancreatic carcinogenesis molecular mechanisms and provide attractive therapeutic targets.

Project description:BackgroundThe identification of differentially expressed tumor-associated proteins and genomic alterations driving neoplasia is critical in the development of clinical assays to detect cancers and forms the foundation for understanding cancer biology. One of the challenges in the analysis of pancreatic ductal adenocarcinoma (PDAC) is the low neoplastic cellularity and heterogeneous composition of bulk tumors. To enrich neoplastic cells from bulk tumor tissue, coring, and laser microdissection (LMD) sampling techniques have been employed. In this study, we assessed the protein and KRAS mutation changes associated with samples obtained by these enrichment techniques and evaluated the fraction of neoplastic cells in PDAC for proteomic and genomic analyses.MethodsThree fresh frozen PDAC tumors and their tumor-matched normal adjacent tissues (NATs) were obtained from three sampling techniques using bulk, coring, and LMD; and analyzed by TMT-based quantitative proteomics. The protein profiles and characterizations of differentially expressed proteins in three sampling groups were determined. These three PDACs and samples of five additional PDACs obtained by the same three sampling techniques were also subjected to genomic analysis to characterize KRAS mutations.ResultsThe neoplastic cellularity of eight PDACs ranged from less than 10% to over 80% based on morphological review. Distinctive proteomic patterns and abundances of certain tumor-associated proteins were revealed when comparing the tumors and NATs by different sampling techniques. Coring and bulk tissues had comparable proteome profiles, while LMD samples had the most distinct proteome composition compared to bulk tissues. Further genomic analysis of bulk, cored, or LMD samples demonstrated that KRAS mutations were significantly enriched in LMD samples while coring was less effective in enriching for KRAS mutations when bulk tissues contained a relatively low neoplastic cellularity.ConclusionsIn addition to bulk tissues, samples from LMD and coring techniques can be used for proteogenomic studies. The greatest enrichment of neoplastic cellularity is obtained with the LMD technique.

Project description:PurposeHypodensity of pancreatic ductal adenocarcinoma (PDAC) during contrast-enhanced computed tomography (CECT) examination is common, but a minority of PDAC patients exhibit hyperdense images. The present study examined the clinical characteristics and protein landscape of PDAC with hyperdensity.Materials and methodsA total of 844 pathologically confirmed PDAC patients who underwent CECT before surgery were included. During the parenchymal phase of CECT, patients were assigned to the hyperdense or hypodense group based on CT values. Clinical and CT characteristics for predicting relapse-free survival (RFS) and overall survival (OS) were analyzed using the Kaplan-Meier method and Cox proportional hazards model. The expression of the tumor angiogenesis marker CD31 and stroma-related protein CTHRC1 were analyzed using immunohistochemistry (IHC) assay to evaluate differences between the two groups. Proteomics was performed to compare the possible mechanisms underlying the differential enhancement on CT scans.ResultsBased on CECT, 43 and 801 PDAC patients had hyperdense and hypodense lesions, respectively. All 43 patients presented a hyperdense lesion in the parenchymal phase. The mean CECT values of the hyperdense group were higher than the hypodense group (102.5 ± 17.4 and 53.7 ± 18.7, respectively, P < 0.001). The hyperdense group had a better prognosis than the hypodense group (median RFS, 19.97 vs. 12.34 months, P = 0.0176; median OS, 33.6 vs. 20.3 months, P = 0.047). Multivariate analysis showed that age, higher CA19-9 levels (> 300 U/ml), tumor stage, tumor differentiation, tumor CT density, and adjuvant chemotherapy were significant independent prognostic factors for OS. CD31 immunohistochemical staining showed that the hyperdense PDACs had a higher microvessel density than the hypodense group (P < 0.001). CTHRC1 expression was higher in the hypodense group (P = 0.019). Sixty-eight differentially expressed proteins were found using the tandem mass tag labeling-based quantification of the proteomes of PDAC tissue samples, and 7 proteins (POFUT1, PKP2, P0DOX4, ITPR1, HBG2, IGLC3, SAA2) were related to angiogenesis.ConclusionPatients who presented with a hyperdense mass on CECT had a higher microvessel density and better prognosis. Anti-angiogenic therapy may be suitable for these patients.

Dataset Information

Laminin, gamma 2 (LAMC2): a promising new putative pancreatic cancer biomarker identified by proteomic analysis of pancreatic adenocarcinoma tissues.

Publications

Laminin, gamma 2 (LAMC2): a promising new putative pancreatic cancer biomarker identified by proteomic analysis of pancreatic adenocarcinoma tissues.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets