72 research outputs found

    Generation of Small 32P-Labeled Peptides as a Potential Approach to Colorectal Cancer Therapy

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    Cancers have been revealed to be extremely heterogenous in terms of the frequency and types of mutations present in cells from different malignant tumors. Thus, it is likely that uniform clinical treatment is not optimal for all patients, and that the development of individualized therapeutic regimens may be beneficial. We describe the generation of multiple, unique small peptides nine to thirty-four amino acids in length which, when labeled with the radioisotope 32P, bind with vastly differing efficiencies to cell lines derived from different colon adenocarcinomas. In addition, the most effective of these peptides permanently transfers the 32P radioisotope to colorectal cancer cellular proteins within two hours at a rate that is more than 150 times higher than in cell lines derived from other cancers or from the normal tissues tested. Currently, the only two FDA-approved radioimmunotherapeutic agents in use both employ antibodies directed against the B cell marker CD20 for the treatment of non-Hodgkin's lymphoma. By using the method described herein, large numbers of different 32P-labeled peptides can be readily produced and assayed against a broad spectrum of cancer types. This report proposes the development and use of 32P-labeled peptides as potential individualized peptide-binding therapies for the treatment of colon adenocarcinoma patients

    Silencing of Claudin-11 Is Associated with Increased Invasiveness of Gastric Cancer Cells

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    Claudins are membrane proteins that play critical roles in tight junction (TJ) formation and function. Members of the claudin gene family have been demonstrated to be aberrantly regulated, and to participate in the pathogenesis of various human cancers. In the present study, we report that claudin-11 (CLDN11) is silenced in gastric cancer via hypermethylation of its promoter region.Levels of CLDN11 methylation and mRNA expression were measured in primary gastric cancer tissues, noncancerous gastric mucosae, and cell lines of gastric origin using quantitative methylation-specific PCR (qMSP) and quantitative reverse transcriptase-PCR (qRT-PCR), respectively. Analyses of paired gastric cancers and adjacent normal gastric tissues revealed hypermethylation of the CLDN11 promoter region in gastric cancers, and this hypermethylation was significantly correlated with downregulation of CLDN11 expression vs. normal tissues. The CLDN11 promoter region was also hypermethylated in all gastric cancer cell lines tested relative to immortalized normal gastric epithelial cells. Moreover, CLDN11 mRNA expression was inversely correlated with its methylation level. Treatment of CLDN11-nonexpressing gastric cancer cells with 5-aza-2'-deoxycytidine restored CLDN11 expression. Moreover, siRNA-mediated knockdown of CLDN11 expression in normal gastric epithelial cells increased their motility and invasiveness.These data suggest that hypermethylation of CLDN11, leading to downregulated expression, contributes to gastric carcinogenesis by increasing cellular motility and invasiveness. A further understanding of the mechanisms underlying the role of claudin proteins in gastric carcinogenesis will likely help in the identification of novel approaches for diagnosis and therapy of gastric cancer

    Criteria for preclinical models of cholangiocarcinoma:scientific and medical relevance

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    Cholangiocarcinoma (CCA) is a rare malignancy that develops at any point along the biliary tree. CCA has a poor prognosis, its clinical management remains challenging, and effective treatments are lacking. Therefore, preclinical research is of pivotal importance and necessary to acquire a deeper understanding of CCA and improve therapeutic outcomes. Preclinical research involves developing and managing complementary experimental models, from in vitro assays using primary cells or cell lines cultured in 2D or 3D to in vivo models with engrafted material, chemically induced CCA or genetically engineered models. All are valuable tools with well-defined advantages and limitations. The choice of a preclinical model is guided by the question(s) to be addressed; ideally, results should be recapitulated in independent approaches. In this Consensus Statement, a task force of 45 experts in CCA molecular and cellular biology and clinicians, including pathologists, from ten countries provides recommendations on the minimal criteria for preclinical models to provide a uniform approach. These recommendations are based on two rounds of questionnaires completed by 35 (first round) and 45 (second round) experts to reach a consensus with 13 statements. An agreement was defined when at least 90% of the participants voting anonymously agreed with a statement. The ultimate goal was to transfer basic laboratory research to the clinics through increased disease understanding and to develop clinical biomarkers and innovative therapies for patients with CCA

    A Multicenter, Double-Blinded Validation Study of Methylation Biomarkers for Progression Prediction in Barrett's Esophagus

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    Esophageal adenocarcinoma risk in Barrett’s esophagus (BE) is increased 30- to 125-fold versus the general population. Among all BE patients, however, neoplastic progression occurs only once per 200 patient-years. Molecular biomarkers are therefore needed to risk-stratify patients for more efficient surveillance endoscopy and to improve the early detection of progression. We therefore performed a retrospective, multicenter, double-blinded validation study of 8 BE progression prediction methylation biomarkers. Progression or nonprogression were determined at 2 years (tier 1) and 4 years (tier 2). Methylation was assayed in 145 nonprogressors (NPs) and 50 progressors (Ps) using real-time quantitative methylation-specific PCR. Ps were significantly older than NPs (70.6 vs. 62.5 years, p < 0.001). We evaluated a linear combination of the 8 markers, using coefficients from a multivariate logistic regression analysis. Areas under the ROC curve (AUCs) were high in the 2-, 4-year and combined data models (0.843, 0.829 and 0.840; p<0.001, p<0.001 and p<0.001, respectively). In addition, even after rigorous overfitting correction, the incremental AUCs contributed by panels based on the 8 markers plus age vs. age alone were substantial (Δ-AUC = 0.152, 0.114 and 0.118, respectively) in all three models. A methylation biomarker-based panel to predict neoplastic progression in BE has potential clinical value in improving both the efficiency of surveillance endoscopy and the early detection of neoplasia

    The genome-wide gene expression profiling to predict competitive endogenous RNA network in hepatocellular cancer

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    To assess the potential competitive endogenous RNA (ceRNA) network in hepatocellular cancer (HCC), the lncRNA, mRNA, and microRNA microarrays were conducted on 3 pairs of HCC and paired normal liver tissue. After that, the arrays were normalized and analyzed with gene oncology (GO) and pathway analysis. Next, we screened out the pseudogenes and their cognate protein coding genes which are both down-regulated in HCC. Finally, the up-regulated microRNA binding sites were predicted on the most down-regulated pseudogene and its cognate protein-coding gene. All the array data were uploaded to Gene Expression Omnibus (accession number GSE64633)
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