A systems biology approach to defining metastatic biomarkers and signaling pathways
Focus Article
Natalie E. Goldberger, Kent W. Hunter
Published Online: May 04 2009
DOI: 10.1002/wsbm.6
Full article on Wiley Online Library:
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Abstract Metastasis is the final stage of cancer and the primary cause of mortality for most solid malignancies. This terminal phase
of cancer progression has been investigated using a variety of high‐throughput technologies (i.e., gene expression arrays,
array comparative genomic hybridization (aCGH), and proteomics) to identify prognostic expression profiles and better characterize
the metastatic process. For decades, the predominant model for the metastatic process has been the ‘progression model’, yet
recent microarray results tend to support an inherent metastatic capability within primary tumors. Moreover, studies using
a highly metastatic transgenic mammary tumor model suggest that germline polymorphisms are significant determinants of metastatic
efficiency. Likewise, a strong concordance of survival has been observed between family members with cancer, further supporting
the link between genetic inheritance and survival. In addition, chromosomal aberrations and signaling pathways related to
metastatic capacity have been identified by array comparative genomic hybridization (aCGH) and proteomic studies, respectively.
Lastly, carcinoma enzyme activity profiles using activity‐based proteomics (ABPP), may be more clinically useful than expression‐based
proteomics for certain cancers. Most importantly, the application of these high‐throughput techniques should expedite the
search for additional biomarkers, germline polymorphisms, and expression signatures with greater prognostic value. Copyright
© 2009 John Wiley & Sons, Inc.
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References 1 Steeg PS. Tumor metastasis: mechanistic insights and clinical challenges Nat Med 2006 12:895-904 et al. Gene expression profiling predicts clinical outcome of breast cancer Nature 2002 415:530-536 et al. A molecular signature of metastasis in primary solid tumors Nat Genet 2003 33:49-54 et al. A gene-expression signature as a predictor of survival in breast cancer N Engl J Med 2002 347:1999-2009 et al. Gene expression profiles of primary breast tumors maintained in distant metastases Proc Natl Acad Sci U S A 2003 100:15901-15905 et al. Identification of inbred mouse strains harboring genetic modifiers of mammary tumor age of onset and metastatic progression Int J Cancer 1998 77:640-644 et al. Predisposition to efficient mammary tumor metastatic progression is linked to the breast cancer metastasis suppressor gene Brms1 Cancer Res 2001 61:8866-8872 et al. Sipa1 is a candidate for underlying the metastasis efficiency modifier locus Mtes1 Nat Genet 2005 37:1055-1062 et al. Germline polymorphisms in SIPA1 are associated with metastasis and other indicators of poor prognosis in breast cancer Breast Cancer Res 2006 8:R16et al. Survival in breast cancer is familial Breast Cancer Res Treat 2008 110:177-182 et al. Concordance of survival in family members with prostate cancer J Clin Oncol 2008 26:1705-1709 et al. Familial concordance in cancer survival: a Swedish population-based study Lancet Oncol 2007 8:1001-1006 et al. Survival in bladder and renal cell cancers is familial J Am Soc Nephrol 2008 19:985-991 et al. Genes that mediate breast cancer metastasis to lung Nature 2005 436:518-524 et al. A multigenic program mediating breast cancer metastasis to bone Cancer Cell 2003 3:537-549 et al. Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival Proc Natl Acad Sci USA 2005 102:3738-3743 et al. Gene expression programs in response to hypoxia: cell type specificity and prognostic significance in human cancers PLoS Med 2006 3:e47et al. Determination of stromal signatures in breast carcinoma PLoS Biol 2005 3:e187et al. Characterization of heterotypic interaction effects in vitro to deconvolute global gene expression profiles in cancer Genome Biol 2007 8:R191et al. MicroRNA expression profiles classify human cancers Nature 2005 435:834-838 et al. MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias Proc Natl Acad Sci U S A 2004 101:11755-11760 et al. MicroRNA gene expression deregulation in human breast cancer Cancer Res 2005 65:7065-7070 et al. MicroRNA signature predicts survival and relapse in lung cancer Cancer Cell 2008 13:48-57 et al. Unique microRNA molecular profiles in lung cancer diagnosis and prognosis Cancer Cell 2006 9:189-198 et al. Reduced accumulation of specific microRNAs in colorectal neoplasia Mol Cancer Res 2003 1:882-891 et al. An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues Proc Natl Acad Sci USA 2004 101:9740-9744 et al. The miR-200 family inhibits epithelialmesenchymal transition and cancer cell migration by direct targeting of E-cadherin transcriptional repressors ZEB1 and ZEB2 J Biol Chem 2008 283:14910-14914 et al. Endogenous human microRNAs that suppress breast cancer metastasis Nature 2008 451:147-152 et al. MicroRNA-21 targets tumor suppressor genes in invasion and metastasis Cell Res 2008 18:350-359 et al. The microRNAs miR-373 and miR-520c promote tumour invasion and metastasis Nat Cell Biol 2008 10:202-210 et al. microRNAs exhibit high frequency genomic alterations in human cancer Proc Natl Acad Sci USA 2006 103:9136-9141 et al. Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia Proc Natl Acad Sci USA 2002 99:15524-15529 et al. Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors Proc Natl Acad Sci USA 2002 99:12963-12968 et al. Comparative oncogenomics identifies NEDD9 as a melanoma metastasis gene Cell 2006 125:1269-1281 et al. Array-based Comparative Genomic Hybridization (aCGH) analysis is a useful tool for distinguishing primary pulmonary from metastatic neuroendocrine carcinoma to the lung Appl Immunohistochem Mol Morphol 2008 16:291-295 et al. Using array-comparative genomic hybridization to define molecular portraits of primary breast cancers Oncogene 2007 26:1959-1970 et al. Genomic and transcriptional aberrations linked to breast cancer pathophysiologies Cancer Cell 2006 10:529-541 et al. High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer Genome Biol 2007 8:R215et al. Whole genome scanning identifies genotypes associated with recurrence and metastasis in prostate tumors Hum Mol Genet 2004 13:1303-1313 et al. Clonal and parallel evolution of primary lung cancers and their metastases revealed by molecular dissection of cancer cells Clin Cancer Res 2007 13:111-120 et al. Heterogeneity of mammary lesions represent molecular differences BMC Cancer 2006 6:275et al. High-resolution array comparative genomic hybridization of single micrometastatic tumor cells Nucleic Acids Res 2008 36:e39et al. Identification of alterations in DNA copy number in host stromal cells during tumor progression Proc Natl Acad Sci USA 2006 103:19848-19853 et al. No evidence of clonal somatic genetic alterations in cancer-associated fibroblasts from human breast and ovarian carcinomas Nat Genet 2008 40:650-655 et al. Molecular characterization of the tumor microenvironment in breast cancer Cancer Cell 2004 6:17-32 et al. Genetic alterations in the peritumoral stromal cells of malignant and borderline epithelial ovarian tumors as indicated by allelic imbalance on chromosome 3p Int J Cancer 2004 109:247-252 et al. Total-genome analysis of BRCA1/2-related invasive carcinomas of the breast identifies tumor stroma as potential landscaper for neoplastic initiation Am J Hum Genet 2006 78:961-972 et al. Correlation between protein and mRNA abundance in yeast Mol Cell Biol 1999 19:1720-1730 et al. Proteomic phenotyping: metastatic and invasive breast cancer Cancer Lett 2004 210:245-253 et al. Alterations in Gemin5 expression contribute to alternative mRNA splicing patterns and tumor cell motility Cancer Res 2008 68:639-644 et al. Quantitative proteomic and genomic profiling reveals metastasis-related protein expression patterns in gastric cancer cells J Proteome Res 2006 5:2727-2742 et al. Parallel analysis of transcript and translation profiles: identification of metastasis-related signal pathways differentially regulated by drug and genetic modifications J Proteome Res 2006 5:1555-1567 et al. Tissue microarrays for high-throughput molecular profiling of tumor specimens Nat Med 1998 4:844-847 et al. Tissue microarray technology for high-throughput molecular profiling of cancer Hum Mol Genet 2001 10:657-662 et al. Automated quantitative analysis of HDM2 expression in malignant melanoma shows association with early-stage disease and improved outcome Cancer Res 2004 64:8767-8772 et al. Quantitative determination of expression of the prostate cancer protein alpha-methylacyl-CoA racemase using automated quantitative analysis (AQUA): a novel paradigm for automated and continuous biomarker measurements Am J Pathol 2004 164:831-840 et al. Using a xenograft model of human breast cancer metastasis to find genes associated with clinically aggressive disease Cancer Res 2005 65:5578-5587 et al. Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression Cancer Cell 2005 8:393-406 et al. Direct cancer tissue proteomics: a method to identify candidate cancer biomarkers from formalin-fixed paraffin-embedded archival tissues Oncogene 2007 26:65-76 et al. Proteases and protease inhibitors in tumor progression Adv Exp Med Biol 1997 425:89-97 et al. Carcinoma and stromal enzyme activity profiles associated with breast tumor growth in vivo Proc Natl Acad Sci USA 2004 101:13756-13761
Resources
Further Readings
Hunter, K., D.R. Welch, and E.T. Liu, Genetic background is an important . Nat Genet, 2003. 34(1): p. 23-4.
Hunter, K.W., Host genetics and tumour metastasis . Br J Cancer, 2004. 90(4): p.752-5.
Hunter, K.W., Allelic diversity in the host genetic background may be an important determinant in tumor metastatic dissemination . Cancer Lett, 2003. 200(2): p. 97-105.
Crawford, N.P. and K.W. Hunter, New perspectives on hereditary influences in metastatic progression . Trends Genet, 2006. 22(10): p. 555-61.
Irish, J.M., N. Kotecha, and G.P. Nolan, Mapping normal and cancer cell signalling networks: towards single-cell proteomics . Nat Rev Cancer, 2006. 6(2): p. 146-55.
Kang, Y., Functional genomic analysis of cancer metastasis: biologic insights and clinical implications . Expert Rev Mol Diagn, 2005. 5(3): p. 385-95.
Frank, S.A., Genetic predisposition to cancer - insights from population genetics. Nat Rev Genet, 2004. 5(10): p. 764-72.
Rifai, N., M.A. Gillette, and S.A. Carr, Protein biomarker discovery and validation: the long and uncertain path to clinical utility . Nat Biotechnol, 2006. 24(8): p. 971-83.
Fidler, I.J., The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited . Nat Rev Cancer, 2003. 3(6): p. 453-8.
