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      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma

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          Abstract

          Pancreatic ductal adenocarcinoma (PDAC) remains a lethal disease with a 5-year survival of 4%. A key hallmark of PDAC is extensive stromal involvement, which makes capturing precise tumor-specific molecular information difficult. Here, we have overcome this problem by applying blind source separation to a diverse collection of PDAC gene expression microarray data, which includes primary, metastatic, and normal samples. By digitally separating tumor, stroma, and normal gene expression, we have identified and validated two tumor-specific subtypes including a “basal-like” subtype which has worse outcome, and is molecularly similar to basal tumors in bladder and breast cancer. Furthermore, we define “normal” and “activated” stromal subtypes which are independently prognostic. Our results provide new insight into the molecular composition of PDAC which may be used to tailor therapies or provide decision support in a clinical setting where the choice and timing of therapies is critical.

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          Most cited references 28

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          Oncogenic pathway signatures in human cancers as a guide to targeted therapies.

          The development of an oncogenic state is a complex process involving the accumulation of multiple independent mutations that lead to deregulation of cell signalling pathways central to the control of cell growth and cell fate. The ability to define cancer subtypes, recurrence of disease and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Various studies have also demonstrated the potential for using gene expression profiles for the analysis of oncogenic pathways. Here we show that gene expression signatures can be identified that reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumours and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumour subtypes. Clustering tumours based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Predictions of pathway deregulation in cancer cell lines are also shown to predict the sensitivity to therapeutic agents that target components of the pathway. Linking pathway deregulation with sensitivity to therapeutics that target components of the pathway provides an opportunity to make use of these oncogenic pathway signatures to guide the use of targeted therapeutics.
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            Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.

            Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies. Copyright © 2014 Elsevier Inc. All rights reserved.
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              Cancer-associated stromal fibroblasts promote pancreatic tumor progression.

              Pancreatic adenocarcinoma is characterized by a dense background of tumor associated stroma originating from abundant pancreatic stellate cells. The aim of this study was to determine the effect of human pancreatic stellate cells (HPSC) on pancreatic tumor progression. HPSCs were isolated from resected pancreatic adenocarcinoma samples and immortalized with telomerase and SV40 large T antigen. Effects of HPSC conditioned medium (HPSC-CM) on in vitro proliferation, migration, invasion, soft-agar colony formation, and survival in the presence of gemcitabine or radiation therapy were measured in two pancreatic cancer cell lines. The effects of HPSCs on tumors were examined in an orthotopic murine model of pancreatic cancer by co-injecting them with cancer cells and analyzing growth and metastasis. HPSC-CM dose-dependently increased BxPC3 and Panc1 tumor cell proliferation, migration, invasion, and colony formation. Furthermore, gemcitabine and radiation therapy were less effective in tumor cells treated with HPSC-CM. HPSC-CM activated the mitogen-activated protein kinase and Akt pathways in tumor cells. Co-injection of tumor cells with HPSCs in an orthotopic model resulted in increased primary tumor incidence, size, and metastasis, which corresponded with the proportion of HPSCs. HPSCs produce soluble factors that stimulate signaling pathways related to proliferation and survival of pancreatic cancer cells, and the presence of HPSCs in tumors increases the growth and metastasis of these cells. These data indicate that stellate cells have an important role in supporting and promoting pancreatic cancer. Identification of HPSC-derived factors may lead to novel stroma-targeted therapies for pancreatic cancer.
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature genetics
                1061-4036
                1546-1718
                23 May 2016
                07 September 2015
                October 2015
                17 June 2016
                : 47
                : 10
                : 1168-1178
                Affiliations
                [1 ]Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC
                [2 ]University of North Carolina-Rex Healthcare, Chapel Hill, NC
                [3 ]Department of Genetics, University of North Carolina, Chapel Hill, NC
                [4 ]Department of Epidemiology, University of North Carolina, Chapel Hill, NC
                [5 ]Department of Pharmacology, University of North Carolina, Chapel Hill, NC
                [6 ]Eppley Cancer Institute, University of Nebraska, Lincoln, NE
                [7 ]Department of Surgery, University of North Carolina, Chapel Hill, NC
                [8 ]Department of Surgery and Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine Northwestern University, Chicago, IL
                [9 ]Department of Surgery, NorthShore University HealthSystem, Evanston, IL
                [10 ]Department of Pathology, David Rubenstein Center for Pancreatic Cancer Research, Human Oncology and Pathogenesis Program, Memorial Sloan-Kettering Cancer Center, New York, NY
                Author notes
                Correspondence to Jen Jen Yeh, jen_jen_yeh@ 123456med.unc.edu
                Article
                NIHMS716599
                10.1038/ng.3398
                4912058
                26343385

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