Theranostic and prognostic biomarkers: Genomic applications in urological malignancies
Department of Pathology, Johns Hopkins Medical Institutions, Baltimore, MD 21231, USA. Pathology
(Impact Factor: 2.19).
06/2010; 42(4):384-94. DOI: 10.3109/00313021003779145
Compared to other solid tumours such as breast, colon, and lung, the current clinical management of urological malignancies is lagging behind in terms of utilisation of clinically robust molecular tests that can identify patients that are more likely to respond to a given targeted agent, or even those in need of a more aggressive treatment approach based on well-validated molecular prognosticators. Several promising biomarkers for detection, prognosis, and targeted therapeutics are now under evaluation. The following review discusses some of the candidate biomarkers that may soon make their transition into clinically applicable assays in urological oncology patients.
Available from: ncbi.nlm.nih.gov
- "However half of muscle invasive UC patients develop subsequent metastatic disease after the first aggressive treatment , . Previous studies have identified several potential molecular biomarkers for bladder cancer , . Inactivation of tumor suppressor genes TP53 and Rb and Ras oncogene activation have been regarded as important key players in bladder cancer carcinogenesis . "
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ABSTRACT: Onco-miR-182-5p has been reported to be over-expressed in bladder cancer (BC) tissues however a detailed functional analysis of miR-182-5p has not been carried out in BC. Therefore the purpose of this study was to: 1. conduct a functional analysis of miR-182-5p in bladder cancer, 2. assess its usefulness as a tumor marker, 3. identify miR-182-5p target genes in BC. Initially we found that miR-182-5p expression was significantly higher in bladder cancer compared to normal tissues and high miR-182-5p expression was associated with shorter overall survival in BC patients. To study the functional significance of miR-182-5p, we over-expressed miR-182-5p with miR-182-5p precursor and observed that cell proliferation, migration and invasion abilities were increased in BC cells. However cell apoptosis was inhibited by miR-182-5p. We also identified Smad4 and RECK as potential target genes of miR-182-5p using several algorithms. 3'UTR luciferase activity of these target genes was significantly decreased and protein expression of these target genes was significantly up-regulated in miR-182-5p inhibitor transfected bladder cancer cells. MiR-182-5p also increased nuclear beta-catenin expression and while Smad4 repressed nuclear beta-catenin expression. In conclusion, our data suggests that miR-182-5p plays an important role as an oncogene by knocking down RECK and Smad4, resulting in activation of the Wnt-beta-catenin signaling pathway in bladder cancer.
PLoS ONE 11/2012; 7(11):e51056. DOI:10.1371/journal.pone.0051056 · 3.23 Impact Factor
- "Detection of gene fusions has led to a paradigm shift in the diagnosis, classification, and treatment options for hematologic cancers.[123–125] These gene fusions provide CaP specific markers which have promise in improving diagnosis, as well as molecular classification of prostate tumors. "
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ABSTRACT: Prevalent gene fusions involving regulatory sequences of the androgen receptor (AR) regulated genes (primarily TMPRSS2) and protein coding sequences of nuclear transcription factors of the ETS gene family (predominantly ERG) result in unscheduled androgen dependent ERG expression in prostate cancer (CaP).Cumulative data from a large number of studies in the past six years accentuate ERG alterations in more than half of all CaP patients in Western countries. Studies underscore that ERG functions are involved in the biology of CaP. ERG expression in normal context is selective to endothelial cells, specific hematopoetic cells and pre-cartilage cells. Normal functions of ERG are highlighted in hematopoetic stem cells. Emerging data continues to unravel molecular and cellular mechanisms by which ERG may contribute to CaP. Herein, we focus on biological and clinical aspects of ERG oncogenic alterations, potential of ERG-based stratification of CaP and the possibilities of targeting the ERG network in developing new therapeutic strategies for the disease.
Journal of Carcinogenesis 12/2011; 10(1):37. DOI:10.4103/1477-3163.91122
Available from: PubMed Central
- "Theranostics, an emerging field in personalized medicine, utilizes molecular biomarkers to select patients for treatments that are expected to benefit them and are unlikely to produce side effects, and provides an early indication of treatment efficacy in individual patients. Therefore, theranostic tests, which lead to rapid and more accurate diagnosis and allow for a more efficient use of drugs, and thus improved patient management, are increasingly used in cancer, cardiovascular and infectious diseases, or prediction of drug toxicity [79,80]. "
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ABSTRACT: ABSTRACT: The search and validation of novel disease biomarkers requires the complementary power of professional study planning and execution, modern profiling technologies and related bioinformatics tools for data analysis and interpretation. Biomarkers have considerable impact on the care of patients and are urgently needed for advancing diagnostics, prognostics and treatment of disease. This survey article highlights emerging bioinformatics methods for biomarker discovery in clinical metabolomics, focusing on the problem of data preprocessing and consolidation, the data-driven search, verification, prioritization and biological interpretation of putative metabolic candidate biomarkers in disease. In particular, data mining tools suitable for the application to omic data gathered from most frequently-used type of experimental designs, such as case-control or longitudinal biomarker cohort studies, are reviewed and case examples of selected discovery steps are delineated in more detail. This review demonstrates that clinical bioinformatics has evolved into an essential element of biomarker discovery, translating new innovations and successes in profiling technologies and bioinformatics to clinical application.
Journal of Clinical Bioinformatics 01/2011; 1(1):2. DOI:10.1186/2043-9113-1-2
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