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      Inferring tumour purity and stromal and immune cell admixture from expression data

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          Abstract

          Infiltrating stromal and immune cells form the major fraction of normal cells in tumour tissue and not only perturb the tumour signal in molecular studies but also have an important role in cancer biology. Here we describe ‘Estimation of STromal and Immune cells in MAlignant Tumours using Expression data’ (ESTIMATE)—a method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples. ESTIMATE scores correlate with DNA copy number-based tumour purity across samples from 11 different tumour types, profiled on Agilent, Affymetrix platforms or based on RNA sequencing and available through The Cancer Genome Atlas. The prediction accuracy is further corroborated using 3,809 transcriptional profiles available elsewhere in the public domain. The ESTIMATE method allows consideration of tumour-associated normal cells in genomic and transcriptomic studies. An R-library is available on https://sourceforge.net/projects/estimateproject/.

          Abstract

          Tumour biopsies contain contaminating normal cells and these can influence the analysis of tumour samples. In this study, Yoshihara et al. develop an algorithm based on gene expression profiles from The Cancer Genome Atlas to estimate the number of contaminating normal cells in tumour samples.

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          Most cited references 18

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          Effector memory T cells, early metastasis, and survival in colorectal cancer.

          The role of tumor-infiltrating immune cells in the early metastatic invasion of colorectal cancer is unknown. We studied pathological signs of early metastatic invasion (venous emboli and lymphatic and perineural invasion) in 959 specimens of resected colorectal cancer. The local immune response within the tumor was studied by flow cytometry (39 tumors), low-density-array real-time polymerase-chain-reaction assay (75 tumors), and tissue microarrays (415 tumors). Univariate analysis showed significant differences in disease-free and overall survival according to the presence or absence of histologic signs of early metastatic invasion (P<0.001). Multivariate Cox analysis showed that an early conventional pathological tumor-node-metastasis stage (P<0.001) and the absence of early metastatic invasion (P=0.04) were independently associated with increased survival. As compared with tumors with signs of early metastatic invasion, tumors without such signs had increased infiltrates of immune cells and increased levels of messenger RNA (mRNA) for products of type 1 helper effector T cells (CD8, T-BET [T-box transcription factor 21], interferon regulatory factor 1, interferon-gamma, granulysin, and granzyme B) but not increased levels of inflammatory mediators or immunosuppressive molecules. The two types of tumors had significant differences in the levels of expression of 65 combinations of T-cell markers, and hierarchical clustering showed that markers of T-cell migration, activation, and differentiation were increased in tumors without signs of early metastatic invasion. The latter type of tumors also had increased numbers of CD8+ T cells, ranging from early memory (CD45RO+CCR7-CD28+CD27+) to effector memory (CD45RO+CCR7-CD28-CD27-) T cells. The presence of high levels of infiltrating memory CD45RO+ cells, evaluated immunohistochemically, correlated with the absence of signs of early metastatic invasion, a less advanced pathological stage, and increased survival. Signs of an immune response within colorectal cancers are associated with the absence of pathological evidence of early metastatic invasion and with prolonged survival. Copyright 2005 Massachusetts Medical Society.
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            Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study.

            Although prognostic gene expression signatures for survival in early-stage lung cancer have been proposed, for clinical application, it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.
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              The emerging role of EpCAM in cancer and stem cell signaling.

              Initially discovered as a dominant antigen on colon carcinomas, the epithelial cell adhesion molecule (EpCAM) was considered a mere cell adhesion molecule and reliable surface-binding site for therapeutic antibodies. Recent findings can better explain the relevance of EpCAM's high-level expression on human cancers and cancer propagating cells, and its negative prognostic potential for survival of patients with certain cancers. EpCAM has oncogenic potential and is activated by release of its intracellular domain, which can signal into the cell nucleus by engagement of elements of the wnt pathway.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                11 October 2013
                : 4
                Affiliations
                [1 ]Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Centre , Houston, Texas 77030, USA
                [2 ]Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences , Niigata 951-8510, Japan
                [3 ]Department of Systems Biology, The University of Texas MD Anderson Cancer Centre , Houston, Texas 77030, USA
                [4 ]Catedra de Bioinformatica, Tecnologico de Monterrey, Campus Monterrey , Monterrey, Nuevo Leon 64849, Mexico
                [5 ]USC Epigenome Centre, University of Southern California , Los Angeles , California 90033, USA
                [6 ]Gynecology Service, Department of Surgery, Memorial Sloan-Kettering Cancer Centre , New York, New York 10065, USA
                [7 ]The Broad Institute of Harvard and MIT , Cambridge, Massachusetts 02142, USA
                Author notes
                Article
                ncomms3612
                10.1038/ncomms3612
                3826632
                24113773
                Copyright © 2013, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/

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