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 rate 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, including data from primary tumor, metastatic and normal samples. By digitally separating tumor, stromal and normal gene expression, we have identified and validated two tumor subtypes, including a 'basal-like' subtype that has worse outcome and is molecularly similar to basal tumors in bladder and breast cancers. Furthermore, we define 'normal' and 'activated' stromal subtypes, which are independently prognostic. Our results provide new insights 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 are critical.

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

Andrea Bild, Guang Yao, Jeffrey Chang … (2006)

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.

Katherine A. Hoadley, Christina Yau, Denise M Wolf … (2014)

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.

Rosa F. Hwang, Todd W. Moore, Thiruvengadam Arumugam … (2008)

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.