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      Identification of a 4-microRNA Signature for Clear Cell Renal Cell Carcinoma Metastasis and Prognosis

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          Abstract

          Renal cell carcinoma (RCC) metastasis portends a poor prognosis and cannot be reliably predicted. Early determination of the metastatic potential of RCC may help guide proper treatment. We analyzed microRNA (miRNA) expression in clear cell RCC (ccRCC) for the purpose of developing a miRNA expression signature to determine the risk of metastasis and prognosis. We used the microarray technology to profile miRNA expression of 78 benign kidney and ccRCC samples. Using 28 localized and metastatic ccRCC specimens as the training cohort and the univariate logistic regression and risk score methods, we developed a miRNA signature model in which the expression levels of miR-10b, miR-139-5p, miR-130b and miR-199b-5p were used to determine the status of ccRCC metastasis. We validated the signature in an independent 40-sample testing cohort of different stages of primary ccRCCs using the microarray data. Within the testing cohort patients who had at least 5 years follow-up if no metastasis developed, the signature showed a high sensitivity and specificity. The risk status was proven to be associated with the cancer-specific survival. Using the most stably expressed miRNA among benign and tumorous kidney tissue as the internal reference for normalization, we successfully converted his signature to be a quantitative PCR (qPCR)-based assay, which showed the same high sensitivity and specificity. The 4-miRNA is associated with ccRCC metastasis and prognosis. The signature is ready for and will benefit from further large clinical cohort validation and has the potential for clinical application.

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          Most cited references 27

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          Reduced accumulation of specific microRNAs in colorectal neoplasia.

          Short non-coding RNAs are known to regulate cellular processes including development, heterochromatin formation, and genomic stability in eukaryotes. Given the impact of these processes on cellular identity, a study was undertaken to investigate possible changes in microRNA (miRNA) levels during tumorigenesis. A total of 28 different miRNA sequences was identified in a colonic adenocarcinoma and normal mucosa, including 3 novel sequences and a further 7 that had previously been cloned only from mice. Human homologues of murine miRNA sequences, miR-143 and miR-145, consistently display reduced steady-state levels of the mature miRNA at the adenomatous and cancer stages of colorectal neoplasia.
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            Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues.

            Proper normalization is a critical but often an underappreciated aspect of quantitative gene expression analysis. This study describes the identification and characterization of appropriate reference RNA targets for the normalization of microRNA (miRNA) quantitative RT-PCR data. miRNA microarray data from dozens of normal and disease human tissues revealed ubiquitous and stably expressed normalization candidates for evaluation by qRT-PCR. miR-191 and miR-103, among others, were found to be highly consistent in their expression across 13 normal tissues and five pair of distinct tumor/normal adjacent tissues. These miRNAs were statistically superior to the most commonly used reference RNAs used in miRNA qRT-PCR experiments, such as 5S rRNA, U6 snRNA, or total RNA. The most stable normalizers were also highly conserved across flash-frozen and formalin-fixed paraffin-embedded lung cancer tumor/NAT sample sets, resulting in the confirmation of one well-documented oncomir (let-7a), as well as the identification of novel oncomirs. These findings constitute the first report describing the rigorous normalization of miRNA qRT-PCR data and have important implications for proper experimental design and accurate data interpretation.
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              Epidemiologic and socioeconomic burden of metastatic renal cell carcinoma (mRCC): a literature review.

              Renal cell carcinoma (RCC), the most common form of kidney cancer, initially has an asymptomatic clinical course; 25-30% of patients present with metastatic disease at time of diagnosis. Worldwide incidence and mortality rates are rising at a rate of approximately 2-3% per decade. Metastatic RCC (mRCC) is one of the most treatment-resistant malignancies; outcomes are generally poor and median survival after diagnosis is less than one year. Surgery and chemotherapy have limited or no effect, leaving mRCC patients underserved in the realm of cancer treatment. As the world's population ages and the prevalence of risk factors (obesity, hypertension) increases, the burden of mRCC is predicted to increase significantly. With a shift in treatment of mRCC to novel therapies, such as molecularly targeted therapies (MTTs) (e.g., sorafenib and sunitinib), clinicians, payers, and other healthcare decision-makers must re-evaluate the optimal role for new treatments. Timely understanding of the burden of mRCC on individuals and society clearly is needed at this juncture. Using a comprehensive literature review, we assessed the epidemiologic, economic, and health-related quality of life (HRQOL) burdens of mRCC. The annual incidence of mRCC in major European countries, the US, and Japan ranges from 1500 to 8600 cases. However, prevalence data were lacking. The estimated economic burden of mRCC is large; $107-$556 million (2006 USD) in the US and $446 million-$1.6 billion (2006 USD) collectively in select countries worldwide. MTTs have potential to reduce the burden of mRCC and provide substantial value beyond their clinical effectiveness.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                18 May 2012
                : 7
                : 5
                Affiliations
                [1 ]Department of Molecular Medicine, City of Hope National Medical Center and Beckman Research Institute, Duarte, California, United States of America
                [2 ]Department of Pathology, City of Hope National Medical Center and Beckman Research Institute, Duarte, California, United States of America
                [3 ]Department of Information Sciences, City of Hope National Medical Center and Beckman Research Institute, Duarte, California, United States of America
                [4 ]Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center and Beckman Research Institute, Duarte, California, United States of America
                [5 ]Department of Cancer Biology, City of Hope National Medical Center and Beckman Research Institute, Duarte, California, United States of America
                National Cancer Institute, National Institutes of Health, United States of America
                Author notes

                Conceived and designed the experiments: XW HW. Performed the experiments: LW CG JMJ YL JJW MC. Analyzed the data: XW XL SKP BM SHO HG. Contributed reagents/materials/analysis tools: XW RAN NHR SPW RAF LW. Wrote the paper: XW SKP SPW LMW HW.

                Article
                PONE-D-11-19678
                10.1371/journal.pone.0035661
                3356334
                22623952
                Wu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 10
                Categories
                Research Article
                Biology
                Genetics
                Human Genetics
                Genome-Wide Association Studies
                Genomics
                Genome Expression Analysis
                Medicine
                Diagnostic Medicine
                Pathology
                General Pathology
                Biomarkers
                Molecular Pathology
                Oncology
                Basic Cancer Research
                Metastasis
                Cancer Detection and Diagnosis
                Early Detection
                Urology
                Renal Cancer

                Uncategorized

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