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Lung Metastasis Genes Couple Breast Tumor Size And Metastatic Spread

A. Minn, G. Gupta, D. Padua, P. Bos, D. Nguyen, D. Nuyten, B. Kreike, Y. Zhang, Y. Wang, H. Ishwaran, J. Foekens, M. van de Vijver, J. Massagué
Published 2007 · Biology, Medicine

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The association between large tumor size and metastatic risk in a majority of clinical cancers has led to questions as to whether these observations are causally related or whether one is simply a marker for the other. This is partly due to an uncertainty about how metastasis-promoting gene expression changes can arise in primary tumors. We investigated this question through the analysis of a previously defined “lung metastasis gene-expression signature” (LMS) that mediates experimental breast cancer metastasis selectively to the lung and is expressed by primary human breast cancer with a high risk for developing lung metastasis. Experimentally, we demonstrate that the LMS promotes primary tumor growth that enriches for LMS+ cells, and it allows for intravasation after reaching a critical tumor size. Clinically, this corresponds to LMS+ tumors being larger at diagnosis compared with LMS− tumors and to a marked rise in the incidence of metastasis after LMS+ tumors reach 2 cm. Patients with LMS-expressing primary tumors selectively fail in the lung compared with the bone or other visceral sites and have a worse overall survival. The mechanistic linkage between metastasis gene expression, accelerated tumor growth, and likelihood of metastatic recurrence provided by the LMS may help to explain observations of prognostic gene signatures in primary cancer and how tumor growth can both lead to metastasis and be a marker for cells destined to metastasize.
This paper references
10.1038/nature04296
Oncogenic pathway signatures in human cancers as a guide to targeted therapies
A. Bild (2006)
Kogalur UB (2007) R News, in press
H Ishwaran (2007)
10.1016/S0140-6736(05)17947-1
Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer
Y. Wang (2005)
10.1056/NEJMOA052933
Concordance among gene-expression-based predictors for breast cancer.
C. Fan (2006)
10.1016/S0076-6879(06)11009-5
9) TM4 Microarray Software Suite
A. Saeed (2006)
10.1073/PNAS.0401736101
Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes.
Jennifer Pittman (2004)
10.1016/S1535-6108(03)00132-6
A multigenic program mediating breast cancer metastasis to bone.
Y. Kang (2003)
BMC Genomics 7:96
Z Hu (2006)
10.1002/cncr.11859
Is breast cancer survival improving?
S. Giordano (2004)
10.1038/418823a
Metastasis genes: A progression puzzle
R. Bernards (2002)
10.1056/NEJMOA041588
A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer.
S. Paik (2004)
BioTechniques 34:374–378
AI Saeed (2003)
10.1038/nature03799
Genes that mediate breast cancer metastasis to lung
A. Minn (2005)
10.1038/ng1060
A molecular signature of metastasis in primary solid tumors
S. Ramaswamy (2003)
10.1056/NEJME068292
Sorting out breast-cancer gene signatures.
J. Massagué (2007)
10.1056/NEJMOA021967
A gene-expression signature as a predictor of survival in breast cancer.
M. J. van de Vijver (2002)
10.1038/ng1752
Genetic regulators of large-scale transcriptional signatures in cancer
A. S. Adler (2006)
10.1073/pnas.0932692100
Repeated observation of breast tumor subtypes in independent gene expression data sets
T. Sørlie (2003)
10.1038/415530a
Gene expression profiling predicts clinical outcome of breast cancer
L. J. Veer (2002)
10.1073/PNAS.0409462102
Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival.
H. Chang (2005)
10.1186/1471-2164-7-96
The molecular portraits of breast tumors are conserved across microarray platforms
Z. Hu (2006)
10.1200/JCO.2005.03.8802
Genes associated with breast cancer metastatic to bone.
M. Smid (2006)
10.1038/bjc.1984.112
Breast cancer: relationship between the size of the primary tumour and the probability of metastatic dissemination.
S. Koscielny (1984)
10.1038/nature05760
Mediators of vascular remodelling co-opted for sequential steps in lung metastasis
G. Gupta (2007)
10.1073/pnas.091062498
Significance analysis of microarrays applied to the ionizing radiation response
V. G. Tusher (2001)
10.1038/nrc865
Metastasis: Dissemination and growth of cancer cells in metastatic sites
A. Chambers (2002)
10.1200/JCO.2000.18.3.591
Clinical progression of breast cancer malignant behavior: what to expect and when to expect it.
R. Heimann (2000)
10.1038/nrc1098
The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited
I. Fidler (2003)
10.2144/03342MT01
TM4: a free, open-source system for microarray data management and analysis.
A. Saeed (2003)



This paper is referenced by
10.7150/thno.43198
Non-canonical signaling pathway of SNAI2 induces EMT in ovarian cancer cells by suppressing miR-222-3p transcription and upregulating PDCD10
Lili Fan (2020)
10.1007/s10549-011-1345-1
Young age, increased tumor proliferation and FOXM1 expression predict early metastatic relapse only for endocrine-dependent breast cancers
C. Yau (2011)
10.1080/00949655.2015.1017823
Tuning-parameter selection in regularized estimations of large covariance matrices
Y. Fang (2013)
10.1007/s10585-009-9249-8
Gene expression profiles and breast cancer metastasis: a genetic perspective
K. Hunter (2009)
10.18632/oncotarget.16244
Systematic functional perturbations uncover a prognostic genetic network driving human breast cancer
T. Gallenne (2017)
10.1093/annonc/mdp579
Discordant expression of molecular markers between primary and nodal metastases: a histopathological manifestation of the 'self (stem cell)-seeding' nature of breast cancer disease?
E. López-Bonet (2010)
10.1016/bs.acr.2015.04.011
The Tumor Macroenvironment: Cancer-Promoting Networks Beyond Tumor Beds.
Melanie R. Rutkowski (2015)
10.1038/onc.2009.139
Anchorage-independent cell growth signature identifies tumors with metastatic potential
S. Mori (2009)
A Systems Genetics Analysis of Metastatic Mammary Cancer Development in Mice Fed Varying Levels of Dietary Fat
R. R. Gordon (2009)
Elucidating the role of E2F2 loss in mediating human breast cancer metastasis
I. Yuwanita (2015)
10.1172/JCI33295
Breast cancer: origins and evolution.
K. Polyak (2007)
10.1007/978-1-4939-3363-1_1
Significance of Studying Circulating Tumor Cells
Ram H. Datar (2016)
10.1038/s41523-019-0102-1
pAKT pathway activation is associated with PIK3CA mutations and good prognosis in luminal breast cancer in contrast to p-mTOR pathway activation
A. Sonnenblick (2019)
10.1186/s12885-015-1108-1
ADAM12-L is a direct target of the miR-29 and miR-200 families in breast cancer
Sara Duhachek-Muggy (2015)
10.3233/BD-2008-29104
Cancer stem cells, self-seeding, and decremented exponential growth: theoretical and clinical implications.
L. Norton (2008)
10.18632/ONCOTARGET.403
T cell- but not tumor cell-produced TGF-β1 promotes the development of spontaneous mammary cancer
A. Sarkar (2011)
10.2147/OTT.S97192
Enrichment of CD44 in basal-type breast cancer correlates with EMT, cancer stem cell gene profile, and prognosis
Hanxiao Xu (2016)
10.1007/s00432-008-0536-6
Gene expression of ceramide kinase, galactosyl ceramide synthase and ganglioside GD3 synthase is associated with prognosis in breast cancer
E. Ruckhäberle (2008)
Signatures génétiques pour diagnostiquer le cancer
Joan Massagué (2009)
10.1186/gb-2010-11-2-r18
A fuzzy gene expression-based computational approach improves breast cancer prognostication
Benjamin Haibe-Kains (2009)
10.18632/oncotarget.15856
Breast cancer subtypes predict the preferential site of distant metastases: a SEER based study
Q. Wu (2017)
Self-Seeding in Cancer
Christos (2016)
10.1074/mcp.M113.037176
Ferritin Heavy Chain in Triple Negative Breast Cancer: A Favorable Prognostic Marker that Relates to a Cluster of Differentiation 8 Positive (CD8+) Effector T-cell Response*
N. Q. Liu (2014)
10.3389/fphar.2012.00140
New and Paradoxical Roles of Matrix Metalloproteinases in the Tumor Microenvironment
A. Noël (2012)
10.1016/j.ygyno.2014.06.026
Endometrial Carcinoma Recurrence Score (ECARS) validates to identify aggressive disease and associates with markers of epithelial-mesenchymal transition and PI3K alterations.
E. Wik (2014)
10.1007/s10585-013-9594-5
Risk factors and survival outcomes in patients with brain metastases from breast cancer
A. Minisini (2013)
10.1038/s41419-018-0486-0
Tumor-associated macrophages promote progression and the Warburg effect via CCL18/NF-kB/VCAM-1 pathway in pancreatic ductal adenocarcinoma
H. Ye (2018)
10.1038/onc.2013.219
Annexin A2 depletion delays EGFR endocytic trafficking via cofilin activation and enhances EGFR signaling and metastasis formation
M. D. Graauw (2014)
10.1186/1755-8794-1-42
The removal of multiplicative, systematic bias allows integration of breast cancer gene expression datasets – improving meta-analysis and prediction of prognosis
A. Sims (2008)
Gene expression profiling of luminal B breast cancers reveals NHERF1 as a new marker of endocrine resistance
Thomas KarnEugen (2011)
10.18632/ONCOTARGET.2783
Epidermal growth factor-induced cyclooxygenase-2 enhances head and neck squamous cell carcinoma metastasis through fibronectin up-regulation
Jinn-Yuan Hsu (2015)
10.1158/0008-5472.CAN-07-5644
Subtypes of breast cancer show preferential site of relapse.
M. Smid (2008)
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