Article
Free circulating mRNA in plasma from breast cancer patients and clinical outcome.
Department of Medical Oncology, Hospital Universitario Puerta de Hierro, C/ San Martín de Porres, 4, E-28035 Madrid, Spain.
Cancer Letters (impact factor:
4.24).
06/2008;
263(2):312-20.
DOI:10.1016/j.canlet.2008.01.008
Source: PubMed
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Citations (0)
- Cited In (3)
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Article: Circulating microRNAs in breast cancer and healthy subjects.
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ABSTRACT: It has been demonstrated that extracellular mRNA can be detected in the circulation. Our hypothesis was that circulating miRNAs are also present and differentially expressed in the serum of breast cancer patients compared to controls. We measured miRNA in the serum of samples with and without the addition of miRNA prior to analysis. To test our RNA extraction efficiency, we spiked-in serial dilutions of single-strand C elegens miR-39 (cel-miR-39) and human miR-145 (has-miR-145) into goat serum and a 10 year old human serum specimen. We next analyzed miR-16, -145, and -155 in archived serum specimens from 21 participants, 13 of whom did and 8 of whom did not have breast cancer. We were able to detect the miRNAs from all the serum samples to which the miRNAs had been added. We were also able to detect endogenous miR-16, -145, and -155 in all serum samples. While the expression of all three miRNAs was similar in samples from healthy women compared to those with breast cancer, women with progesterone receptor (PR, p = 0.016) positive tumors had higher miR-155 expression than tumors that were negative for these receptors. 1) RNA species can be detected in archived serum; 2) miR-155 may be differentially expressed in the serum of women with hormone sensitive compared to women with hormone insensitive breast cancer. Screening serum for miRNAs that predict the presence of breast cancer is feasible, and may be useful for breast cancer detection.BMC Research Notes 06/2009; 2:89. -
Article: MDM2, E-cadherin, Survivin and Her2 mRNA Status in Peripheral Blood of Patients with Breast Cancer
Middle East Journal of Cancer. 01/2013; 4(1):7-14. -
Article: Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases.
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ABSTRACT: Identification of molecular classifiers from genome-wide gene expression analysis is an important practice for the investigation of biological systems in the post-genomic era--and one with great potential for near-term clinical impact. The 'Top-Scoring Pair' (TSP) classification method identifies pairs of genes whose relative expression correlates strongly with phenotype. In this study, we sought to assess the effectiveness of the TSP approach in the identification of diagnostic classifiers for a number of human diseases including bacterial and viral infection, cardiomyopathy, diabetes, Crohn's disease, and transformed ulcerative colitis. We examined transcriptional profiles from both solid tissues and blood-borne leukocytes. The algorithm identified multiple predictive gene pairs for each phenotype, with cross-validation accuracy ranging from 70 to nearly 100 percent, and high sensitivity and specificity observed in most classification tasks. Performance compared favourably with that of pre-existing transcription-based classifiers, and in some cases was comparable to the accuracy of current clinical diagnostic procedures. Several diseases of solid tissues could be reliably diagnosed through classifiers based on the blood-borne leukocyte transcriptome. The TSP classifier thus represents a simple yet robust method to differentiate between diverse phenotypic states based on gene expression profiles. Two-transcript classifiers have the potential to reliably classify diverse human diseases, through analysis of both local diseased tissue and the immunological response assayed through blood-borne leukocytes. The experimental simplicity of this method results in measurements that can be easily translated to clinical practice.BMC Genomics 12/2009; 10:583. · 4.07 Impact Factor
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Keywords
breast cancer
clinical outcome
cyclin D1 mRNA
good-prognosis groups
negative vascular invasion
patients
patients non-responsive
poor outcome
possible markers
real-time PCR cyclin D1
relapse
significant relation
thymidylate synthase