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      Use of Formalin-Fixed Paraffin-Embedded Samples for Gene Expression Studies in Breast Cancer Patients

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          Abstract

          To obtain gene expression profiles from samples collected in clinical trials, we conducted a pilot study to assess feasibility and estimate sample attrition rates when profiling formalin-fixed, paraffin-embedded specimens. Ten matched fresh-frozen and fixed breast cancer samples were profiled using the Illumina HT-12 and Ref-8 chips, respectively. The profiles obtained with Ref 8, were neither technically nor biologically reliable since they failed to yield the expected separation between estrogen receptor positive and negative samples. With the use of Affymetrix HG-U133 2.0 Plus chips on fixed samples and a quantitative polymerase chain reaction -based sample pre-assessment step, results were satisfactory in terms of biological reliability, despite the low number of present calls (M = 21%±5). Compared with the Illumina DASL WG platform, Affymetrix data showed a wider interquartile range (1.32 vs 0.57, P<2.2 E-16,) and larger fold changes. The Affymetrix chips were used to run a pilot study on 60 fixed breast cancers. By including in the workflow the sample pre-assessment steps, 96% of the samples predicted to give good results (44/46), were in fact rated as satisfactory from the point of view of technical and biological meaningfulness. Our gene expression profiles showed strong agreement with immunohistochemistry data, were able to reproduce breast cancer molecular subtypes, and allowed the validation of an estrogen receptor status classifier derived in frozen samples. The approach is therefore suitable to profile formalin-fixed paraffin-embedded samples collected in clinical trials, provided that quality controls are run both before (sample pre-assessment) and after hybridization on the array.

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          Most cited references35

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          Gene expression in fixed tissues and outcome in hepatocellular carcinoma.

          It is a challenge to identify patients who, after undergoing potentially curative treatment for hepatocellular carcinoma, are at greatest risk for recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissue. We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed, paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of tissue samples from 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (P=0.04). We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlated with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. Copyright 2008 Massachusetts Medical Society.
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            Gene expression profiling in breast cancer: classification, prognostication, and prediction.

            Microarray-based gene expression profiling has had a major effect on our understanding of breast cancer. Breast cancer is now perceived as a heterogeneous group of different diseases characterised by distinct molecular aberrations, rather than one disease with varying histological features and clinical behaviour. Gene expression profiling studies have shown that oestrogen-receptor (ER)-positive and ER-negative breast cancers are distinct diseases at the transcriptomic level, that additional molecular subtypes might exist within these groups, and that the prognosis of patients with ER-positive disease is largely determined by the expression of proliferation-related genes. On the basis of these principles, a molecular classification system and prognostic multigene classifiers based on microarrays or derivative technologies have been developed and are being tested in randomised clinical trials and incorporated into clinical practice. In this review, we focus on the conceptual effect and potential clinical use of the molecular classification of breast cancer, and discuss prognostic and predictive multigene predictors. Copyright © 2011 Elsevier Ltd. All rights reserved.
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              Determinants of RNA Quality from FFPE Samples

              The large archives of formalin-fixed paraffin-embedded (FFPE) tissue specimens that exist are a highly valuable source of sample material for molecular biological analysis, including gene expression profiling. However, current data on adverse effects of standard pathological practice on the usefulness of biomolecular analytes obtained from such archived specimens is largely anecdotal. Here, we present a systematic examination of the most relevant parameters for integrity and useability of RNA obtained from FFPE samples, including storage time and conditions, fixation time, and specimen size. The results are particularly relevant for any application relying on cDNA synthesis as an initial step of the procedure, such as RT-PCR, and microarray analysis.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 April 2015
                2015
                : 10
                : 4
                : e0123194
                Affiliations
                [1 ]Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
                [2 ]Department of Pathology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
                [3 ]Department of Medical Oncology, Ospedale San Raffaele, Milan, Italy
                University of Torino, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: VM VC GB. Performed the experiments: VM EDB MS PM BP. Analyzed the data: MC GB MD. Wrote the paper: VM MC GB LG MGD VC.

                Article
                PONE-D-14-49610
                10.1371/journal.pone.0123194
                4386823
                25844937
                864e56c7-ca17-4a67-95c4-82a2e3b43da2
                Copyright @ 2015

                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

                History
                : 4 November 2014
                : 18 February 2015
                Page count
                Figures: 5, Tables: 1, Pages: 20
                Funding
                This work was supported by: the Italian Association for Cancer Research (AIRC) [IG 4915 to LG] and [IG 10611 to MGD] and the Ministero della Salute (Progetto Oncologico di Medicina Molecolare: I Tumori Femminili). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                All microarray files are available from the GEO database (accession number GSE3855).

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                Uncategorized

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