Transcriptional networks inferred from molecular signatures of breast cancer.

Global genomic approaches in cancer research have provided new and innovative strategies for the identification of signatures that differentiate various types of human cancers. Computational analysis of the promoter composition of the genes within these signatures may provide a powerful method for deducing the regulatory transcriptional networks that mediate their collective function. In this study we have systematically analyzed the promoter composition of gene classes derived from previously established genetic signatures that recently have been shown to reliably and reproducibly distinguish five molecular subtypes of breast cancer associated with distinct clinical outcomes. Inferences made from the trends of transcription factor binding site enrichment in the promoters of these gene groups led to the identification of regulatory pathways that implicate discrete transcriptional networks associated with specific molecular subtypes of breast cancer. One of these inferred pathways predicted a role for nuclear factor-kappaB in a novel feed-forward, self-amplifying, autoregulatory module regulated by the ERBB family of growth factor receptors. The existence of this pathway was verified in vivo by chromatin immunoprecipitation and shown to be deregulated in breast cancer cells overexpressing ERBB2. This analysis indicates that approaches of this type can provide unique insights into the differential regulatory molecular programs associated with breast cancer and will aid in identifying specific transcriptional networks and pathways as potential targets for tumor subtype-specific therapeutic intervention.

[1]  Sin Lam Tan,et al.  Mice and Men: Their Promoter Properties , 2006, PLoS genetics.

[2]  R. Tibshirani,et al.  Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[3]  H. Nakshatri,et al.  Identification of signal transduction pathways involved in constitutive NF-κB activation in breast cancer cells , 2002, Oncogene.

[4]  Z. Zhai,et al.  NIK is a component of the EGF/heregulin receptor signaling complexes , 2003, Oncogene.

[5]  A. Pardee,et al.  The nuclear factor kappa B (NF-κB): A potential therapeutic target for estrogen receptor negative breast cancers , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[6]  R. Tibshirani,et al.  Repeated observation of breast tumor subtypes in independent gene expression data sets , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[7]  R. Coffey,et al.  Her-2/neu overexpression induces NF-κB via a PI3-kinase/Akt pathway involving calpain-mediated degradation of IκB-α that can be inhibited by the tumor suppressor PTEN , 2001, Oncogene.

[8]  G. Church,et al.  Identifying regulatory networks by combinatorial analysis of promoter elements , 2001, Nature Genetics.

[9]  L. Magnelli,et al.  Brn-3a, a neuronal transcription factor of the POU gene family: Indications for its involvement in cancer and angiogenesis , 2002, Molecular biotechnology.

[10]  Debajit K. Biswas,et al.  NF-κB activation in human breast cancer specimens and its role in cell proliferation and apoptosis , 2004 .

[11]  K. Gardner,et al.  Targeting Combinatorial Transcriptional Complex Assembly at Specific Modules within the Interleukin-2 Promoter by the Immunosuppressant SB203580* , 2003, Journal of Biological Chemistry.

[12]  D. Mercola,et al.  Inhibition of Egr-1 expression reverses transformation of prostate cancer cells in vitro and in vivo , 2003, Oncogene.

[13]  R. Nahta,et al.  Herceptin: mechanisms of action and resistance. , 2006, Cancer letters.

[14]  C. Perou,et al.  Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma , 2006, Modern Pathology.

[15]  K. Gardner,et al.  Pharmacologic profiling of transcriptional targets deciphers promoter logic , 2005, The Pharmacogenomics Journal.

[16]  H. Sakurai,et al.  TGF-beta-activated kinase 1 stimulates NF-kappa B activation by an NF-kappa B-inducing kinase-independent mechanism. , 1998, Biochemical and biophysical research communications.

[17]  D. Koller,et al.  From signatures to models: understanding cancer using microarrays , 2005, Nature Genetics.

[18]  W. McGuire,et al.  Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene. , 1987, Science.

[19]  T. Werner,et al.  MatInd and MatInspector: new fast and versatile tools for detection of consensus matches in nucleotide sequence data. , 1995, Nucleic acids research.

[20]  J. Thiery,et al.  Complex networks orchestrate epithelial–mesenchymal transitions , 2006, Nature Reviews Molecular Cell Biology.

[21]  J. Schellens,et al.  Current knowledge and future directions of the selective epidermal growth factor receptor inhibitors erlotinib (Tarceva) and gefitinib (Iressa). , 2005, The oncologist.

[22]  J. Massagué,et al.  Smad transcription factors. , 2005, Genes & development.

[23]  Michael Karin,et al.  NF-κB in cancer: a marked target , 2003 .

[24]  C. Arteaga.  Inhibition of TGFβ signaling in cancer therapy , 2006 .

[25]  V. Gorgoulis,et al.  Involvement of E2F transcription factor family in cancer. , 2005, European journal of cancer.

[26]  A. Ullrich,et al.  Heregulin‐dependent regulation of HER2/neu oncogenic signaling by heterodimerization with HER3. , 1995, The EMBO journal.

[27]  D. Botstein,et al.  Singular value decomposition for genome-wide expression data processing and modeling. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[28]  J. Nesland,et al.  EGFR family expression in breast carcinomas. c‐erbB‐2 and c‐erbB‐4 receptors have different effects on survival , 2002, The Journal of pathology.

[29]  S. Chanock,et al.  Functional profiling of uncommon VCAM1 promoter polymorphisms prevalent in African American populations , 2007, Human mutation.

[30]  J. Downing,et al.  Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. , 2002, Cancer cell.

[31]  K. Nakai,et al.  Genome-wide analysis reveals strong correlation between CpG islands with nearby transcription start sites of genes and their tissue specificity. , 2005, Gene.

[32]  S. Shen-Orr,et al.  Superfamilies of Evolved and Designed Networks , 2004, Science.

[33]  D. Brutlag,et al.  A genome-wide analysis of CpG dinucleotides in the human genome distinguishes two distinct classes of promoters , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[34]  Lakshmanan K. Iyer,et al.  A combined approach to data mining of textual and structured data to identify cancer-related targets , 2006, BMC Bioinformatics.

[35]  J. Adams,et al.  Development of the Proteasome Inhibitor Velcade™ (Bortezomib) , 2004, Cancer investigation.

[36]  Wenwu Cui,et al.  Human promoter genomic composition demonstrates non-random groupings that reflect general cellular function , 2005, BMC Bioinformatics.

[37]  D. Seldin,et al.  Roles of IKK kinases and protein kinase CK2 in activation of nuclear factor-kappaB in breast cancer. , 2001, Cancer research.

[38]  J. Xu,et al.  Curcumin inhibits human colon cancer cell growth by suppressing gene expression of epidermal growth factor receptor through reducing the activity of the transcription factor Egr-1 , 2006, Oncogene.

[39]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[40]  M. Eccles,et al.  A PANorama of PAX genes in cancer and development , 2006, Nature Reviews Cancer.

[41]  M. Daidone,et al.  Breast cancer stem cells: an overview. , 2006, European journal of cancer.

[42]  Kevin Gardner,et al.  Kinetic profiles of p300 occupancy in vivo predict common features of promoter structure and coactivator recruitment. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[43]  M. Frommer,et al.  CpG islands in vertebrate genomes. , 1987, Journal of molecular biology.

[44]  T. Barrette,et al.  Mining for regulatory programs in the cancer transcriptome , 2005, Nature Genetics.

[45]  P. Brown,et al.  Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[46]  T. Sørlie,et al.  Evaluation of MetriGenix custom 4D™ arrays applied for detection of breast cancer subtypes , 2006, BMC Cancer.

[47]  William Stafford Noble,et al.  Assessing computational tools for the discovery of transcription factor binding sites , 2005, Nature Biotechnology.

[48]  A. Michelson.  Deciphering genetic regulatory codes: A challenge for functional genomics , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[49]  S. Safe,et al.  Mechanisms of Inhibitory Aryl Hydrocarbon Receptor-Estrogen Receptor Crosstalk in Human Breast Cancer Cells , 2000, Journal of Mammary Gland Biology and Neoplasia.

[50]  Y. Yarden,et al.  Untangling the ErbB signalling network , 2001, Nature Reviews Molecular Cell Biology.

[51]  Debajit K. Biswas,et al.  Epidermal growth factor-induced nuclear factor κB activation: A major pathway of cell-cycle progression in estrogen-receptor negative breast cancer cells , 2000 .

[52]  A. Thor,et al.  Relationship of epidermal growth factor receptor expression to ErbB-2 signaling activity and prognosis in breast cancer patients. , 2005, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[53]  A. Chinnaiyan,et al.  Integrative analysis of the cancer transcriptome , 2005, Nature Genetics.

[54]  E. Bottinger,et al.  A mechanism of suppression of TGF–β/SMAD signaling by NF-κB/RelA , 2000, Genes & Development.

[55]  Michael Karin,et al.  IKK/NF-κB signaling: balancing life and death – a new approach to cancer therapy , 2005 .

[56]  A. Butte,et al.  Coordinated reduction of genes of oxidative metabolism in humans with insulin resistance and diabetes: Potential role of PGC1 and NRF1 , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[57]  Persons Dl,et al.  Quantitation of HER-2/neu and c-myc gene amplification in breast carcinoma using fluorescence in situ hybridization , 1997 .

[58]  J. Guan,et al.  The Grb7 family proteins: structure, interactions with other signaling molecules and potential cellular functions , 2001, Oncogene.

[59]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[60]  H. Hsu,et al.  Nur77 family of nuclear hormone receptors. , 2004, Current drug targets. Inflammation and allergy.

[61]  C. Sotiriou,et al.  Bortezomib (PS-341, Velcade) increases the efficacy of trastuzumab (Herceptin) in HER-2–positive breast cancer cells in a synergistic manner , 2006, Molecular Cancer Therapeutics.

[62]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.

[63]  J. Saint-Jeannet,et al.  Sox proteins and neural crest development. , 2005, Seminars in cell & developmental biology.