Free circulating mRNA in plasma from breast cancer patients and clinical outcome
ABSTRACT We studied by real-time PCR cyclin D1 and thymidylate synthase (TS) mRNA in plasma as possible markers of clinical outcome in breast cancer. We observed poor outcome in patients with presence of cyclin D1 mRNA in good-prognosis groups, such as negative vascular invasion. Presence of both markers was associated with non-response to treatment after relapse. In patients treated with tamoxifen, a trend to significant relation between poor outcome and cyclin D1 mRNA was found. Cyclin D1 mRNA in plasma could identify patients with poor overall survival in good-prognosis groups and patients non-responsive to tamoxifen.
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- "In this respect, it was reported that plasma mammaglobin mRNA alone or in combination with CA15-3 may be used as a valuable non-invasive approach for the diagnosis and detection of metastasized breast cancer . Furthermore, levels of CCND1 mRNA, which encodes the cell-cycle protein cyclin D1, identified patients with breast cancer with poor overall survival in good-prognosis groups and patients who were non-responsive to tamoxifen . "
ABSTRACT: During tumor development, tumor cells release their nucleic acids into the blood circulation. This process occurs by apoptotic and necrotic cell deaths along with active cell secretion, resulting in high levels of circulating DNA, mRNA, and microRNA in the blood of patients with breast cancer. As circulating cell-free tumor nucleic acids may reflect the characteristics of the primary tumor and even of micrometastatic cells, they may be excellent blood biomarkers for screening breast cancer. Assays that allow the repetitive monitoring of patients by using blood samples as liquid biopsy may be efficient in assessing cancer progression in patients whose tumor tissue is not available. This review evaluates the recent data on the potential use of circulating cell-free nucleic acids as biomarkers for breast cancer.Breast cancer research: BCR 09/2013; 15(5):211. DOI:10.1186/bcr3446 · 5.49 Impact Factor
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- "Cell-free nucleic acids derived from tumors are detectable in plasma of cancer patients and may show diagnostic and prognostic values , . The use of these markers in plasma as a source of tumor information would be important, since they are obtained by a non-invasive method that would be useful during patients' follow-up and treatment monitoring. "
ABSTRACT: We studied anomalous extracellular mRNAs in plasma from patients with diffuse large B-cell lymphoma (DLBCL) and their survival implications. mRNAs studied have been reported in the literature as markers of poor (BCL2, CCND2, MYC) and favorable outcome (LMO2, BCL6, FN1) in tumors. These markers were also analyzed in lymphoma tissues to test possible associations with their presence in plasma. mRNA from 42 plasma samples and 12 tumors from patients with DLBCL was analyzed by real-time PCR. Samples post-treatment were studied. The immunohistochemistry of BCL2 and BCL6 was defined. Presence of circulating tumor cells was determined by analyzing the clonality of the immunoglobulin heavy-chain genes by PCR. In DLBCL, MYC mRNA was associated with short overall survival. mRNA targets with unfavorable outcome in tumors were associated with characteristics indicative of poor prognosis, with partial treatment response and with short progression-free survival in patients with complete response. In patients with low IPI score, unfavorable mRNA targets were related to shorter overall survival, partial response, high LDH levels and death. mRNA disappeared in post-treatment samples of patients with complete response, and persisted in those with partial response or death. No associations were found between circulating tumor cells and plasma mRNA. Absence of BCL6 protein in tumors was associated with presence of unfavorable plasma mRNA. Through a non-invasive procedure, tumor-derived mRNAs can be obtained in plasma. mRNA detected in plasma did not proceed from circulating tumor cells. In our study, unfavorable targets in plasma were associated with poor prognosis in B-cell lymphomas, mainly MYC mRNA. Moreover, the unfavorable targets in plasma could help us to classify patients with poor outcome within the good prognosis group according to IPI.PLoS ONE 12/2009; 4(12):e8173. DOI:10.1371/journal.pone.0008173 · 3.23 Impact Factor
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- "Of particular interest are the simplicity, robustness and accuracy of two-transcript classifiers using a data source that provides an easily accessed transcriptomic 'readout' from pathologies of disparate tissues. Recent studies have examined the utility of serum-borne mRNA in the prediction of diseases, with varying fidelity [40,41]. These methods are constrained by the finite stability of RNA transcripts in the circulation. "
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(1):583. DOI:10.1186/1471-2164-10-583 · 3.99 Impact Factor