Pancreatic Cancer Biomarkers and Their Implication in Cancer Diagnosis and Epidemiology

Methods and Technologies Branch, Epidemiology and Genetics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institues of Health (NIH), 6130 Executive Blvd., Suite 5100. Bethesda, MD 20892-7324, USA. .
Cancers 12/2010; 2(4):1830-1837. DOI: 10.3390/cancers2041830
Source: PubMed


Pancreatic cancer is the fourth most common cause of cancer-related mortality in the United States. Biomarkers are needed to detect this cancer early during the disease development and for screening populations to identify those who are at risk. In cancer, "biomarker" refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker might be either a molecule secreted by a tumor or it can be a specific response of the body to the presence of cancer. Genetic, epigenetic, proteomic, glycomic, and imaging biomarkers can be used for cancer diagnosis, prognosis, and epidemiology. A number of potential biomarkers have been identified for pancreatic cancer. These markers can be assayed in non-invasively collected biofluids. These biomarkers need analytical and clinical validation so that they can be used for the purpose of screening and diagnosing pancreatic cancer and determining disease prognosis. In this article, the latest developments in pancreatic cancer biomarkers are discussed.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction.
    Full-text · Article · May 2011 · Journal of Biomedical Informatics
  • [Show abstract] [Hide abstract]
    ABSTRACT: Biochemical, epigenetic, genetic, and imaging biomarkers are used to identify people at high risk for developing cancer. In cancer epidemiology, epigenetic biomarkers offer advantages over other types of biomarkers because they are expressed against a person's genetic background and environmental exposure, and because epigenetic events occur early in cancer development. This chapter describes epigenetic biomarkers that are being used to study the epidemiology of different types of cancer. Because epigenetic alterations can be reversed by chemicals and activate gene expression, epigenetic biomarkers potentially have numerous clinical applications in cancer intervention and treatment and significant implications in public health. This review discusses cancer biomarkers, the characteristics of an ideal biomarker for cancer, and technologies for biomarker detection.
    No preview · Article · Jan 2012 · Methods in molecular biology (Clifton, N.J.)
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Pancreatic cancer (PC) is a leading cause of cancer related deaths in United States. The lack of early symptoms results in latestage detection and a high mortality rate. Currently, the only potentially curative approach for PC is surgical resection, which is often unsuccessful because the invasive and metastatic nature of the tumor masses makes their complete removal difficult. Consequently, patients suffer relapses from remaining cancer stem cells or drug resistance that eventually lead to death. To improve the survival rate, the early detection of PC is critical. Current biomarker research in PC indicates that a serum carbohydrate antigen, CA 19-9, is the only available biomarker with approximately 90% specificity to PC. However, the efficacy of CA 19-9 for assessing prognosis and monitoring patients with PC remains contentious. Thus, advances in technology and the detection of new biomarkers with high specificity to PC are needed to reduce the mortality rate of pancreatic cancer.
    Full-text · Article · Feb 2012 · Current pharmaceutical design