94
Views
39
CrossRef citations to date
0
Altmetric
Review

Application of DNA microarray technology in determining breast cancer prognosis and therapeutic response

, , , , , & show all
Pages 1069-1083 | Published online: 24 Nov 2005

Bibliography

  • LEVI F, LUCCHINI F, NEGRI E, LA VECCHIA C: Trends in mortality from major cancers in the European Union, including acceding countries, in 2004. Cancer (2004) 101:2843–2850.
  • BARKER S: Anti-estrogens in the treatment of breast cancer: current status and future directions. Curr. Opin. Investig Drugs (2003) 4:652–657.
  • HENDERSON IC, BERRY DA, DEMETRI GD et al.: Improved outcomes from adding sequential Paclitaxel but not from escalating Doxorubicin dose in an adjuvant chemotherapy regimen for patients with node-positive primary breast cancer. J. Clin. Oncol. (2003) 21:976–983.
  • HUDIS CA: Current status and future directions in breast cancer therapy. Clin. Breast Cancer (2003) 4\(Suppl. 2):570–575.
  • CLARKE R, LIU MC, BOUKER KB et al.: Antiestrogen resistance in breast cancer and the role of estrogen receptor signaling. Oncogene (2003) 22:7316–7339.
  • KAKLAIVIANI V O'REGAN RM: New targeted therapies in breast cancer. Semin. Oncol. (2004) 31:20–25.
  • PICCART MJ, SOTIRIOU C, CARDOSO F: New data on chemotherapy in the adjuvant setting. Breast (2003) 12:373–378.
  • SLAMON DJ, LEYLAND-JONES B, SHAK S et al.: Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl. J. Med. (2001) 344:783–792.
  • ••Seminal paper describing the clinicalefficacy of trastuzamab.
  • GEE JM, HARPER ME, HUTCHESON IR et al.: The antiepidermal growth factor receptor agent gefitinib (ZD1839/Iressa) improves antihormone response and prevents development of resistance in breast cancer in vitro. Endocrinology (2003) 144:5105–5117.
  • HISCOX S, MORGAN L, BARROW D et al.: Tamoxifen resistance in breast cancer cells is accompanied by an enhanced motile and invasive phenotype: inhibition by gefitinib ('Iressa', ZD1839). Clin. Exp. Metastasis (2004) 21:201–212.
  • RUGO HS: Bevacizumab in the treatment of breast cancer: rationale and current data. Oncologist (2004) 9\(Suppl. 0:43–49.
  • NO AUTHORS LISTED: Polychemotherapy for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists' Collaborative Group. Lancet (1998) 352:930–942.
  • ••Meta-analysis of all the majorchemotherapy trials.
  • RAMASWAMY S, GOLUB TR: DNA microarrays in clinical oncology. J. Clin. Oncol. (2002) 20:1932–1941.
  • GOLUB TR, SLONIM DK, TAMAYO P et al.: Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science (1999) 286:531–537.
  • HARDIMAN G: Microarray platforms-comparisons and contrasts. Pharmacogenomics (2004) 5:487–502.
  • •Excellent review.
  • HARDIMAN G: Microarray technologies 2003 - an overview. Pharmacogenomics (2003) 4:251–256.
  • CHURCHILL GA: Fundamentals of experimental design for cDNA microarrays. Nat. Genet. (2002) 32(Suppl.):490–495.
  • SCHULZE A, DOWNWARD J: Navigating gene expression using microarrays-a technology review. Nat. Cell Biol. (2001) 3:E190–E195.
  • BRAZMA A, CULHANE AC: Algorithmsfor gene expression analysis. In: Encyclopedia Of Genetics, Genomics, Proteomics And Bioinformatics. Dunn MJ, Jorde LB, Little PFR, Subramaniam S (Eds), John Wiley and Sons (2005).
  • DOPAZO J, ZANDERS E, DRAGONI I, AMPHLETT G, FALCIANI F: Methods and approaches in the analysis of gene expression data./ Immunol. Methods (2001) 250:93–112.
  • EISEN MB, SPELLMAN PT, BROWN PO, BOTSTEIN D: Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA (1998) 95:14863–14868.
  • ••Key paper describing analysis of DNAmicroarray data.
  • DODUIT S, SPEED TP: Comparison of discrimination methods for the classification of tumours using gene expression data. J. Am. Statist. Assoc. (2000) 97:78–87.
  • KHAN J, WET JS, RINGNER M et al: Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med. (2001) 7:673–679.
  • FUREY TS, CRISTIANINI N, DUFFY Net al: Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics (2000) 16:906–914.
  • CULHANE AC, PERRIERE G, CONSIDINE EC, COTTER TG, HIGGINS DG: Between-group analysis of microarray data. Bioinformatics (2002) 18:1600–1608.
  • TUSHER VG, TIBSHIRANI R, CHUG: Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl Acad. Sci. USA (2001) 98:5116–5121.
  • WETTENHALL JM, SMYTH GK: limmaGUI: a graphical user interface for linear modeling of microarray data. Bioinformatics (2004) 20:3705–3706.
  • CLEATOR S, ASHWORTH A: Molecular profiling of breast cancer: clinical implications. Br. J. Cancer (2004) 90:1120–1124.
  • CULHANE A. PERRIERE G, HIGGINS D: Cross-platform comparison and visualisation of gene expression data using co-inertia analysis. BMC Bioinformatics (2003) 4:59.
  • SHEN R, GHOSH D, CHINNAIYAN AM: Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data. BMC Genomics (2004) 5:94.
  • VAN 'T VEER LJ, DAI H, VAN DE VIJVER MJ et al: Gene expression profiling predicts clinical outcome of breast cancer. Nature (2002) 415:530–536.
  • ••Seminal paper describing the 70-geneprognostic signature.
  • HUANG E, CHENG SH, DRESSMAN H et al.: Gene expression predictors of breast cancer outcomes. Lancet (2003) 361:1590–1596.
  • SORLIE T, PEROU CM, TIBSHIRANI R et al.: Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. USA (2001) 98:10869–10874.
  • •Important paper describing breast cancer subtypes.
  • SOTIRIOU C, NEO SY, MCSHANE LM et al.: Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc. Natl Acad. Sci. USA (2003) 100:10393–10398.
  • AHR A, HOLTRICH U, SOLBACH C et al.: Molecular classification of breast cancer patients by gene expression profiling. J. Pathol (2001) 195:312–320.
  • BERTUCCI F, FINETTI P, ROUGEMONT Jet al: Gene expression profiling identifies molecular subtypes of inflammatory breast cancer. Cancer Res. (2005) 65:2170–2178.
  • BERTUCCI F, FINETTI P, ROUGEMONT Jet al: Gene expression profiling for molecular characterization of inflammatory breast cancer and prediction of response to chemotherapy. Cancer Res. (2004) 64:8558–8565.
  • BERTUCCI F, NASSER V, HOULGATTE R, BIRNBAUM D: [Gene expression profiling using cDNA arrays and prognosis of breast cancer]. Bull. Cancer (2002) 89:571–574.
  • BOURAS T, SOUTHEY MC, CHANG AC et al.: Stanniocalcin 2 is an estrogen-responsive gene coexpressed with the estrogen receptor in human breast cancer. Cancer Res. (2002) 62:1289–1295.
  • BUCHHOLZ TA, STIVERS DN, STEC J et al.: Global gene expression changes during neoadjuvant chemotherapy for human breast cancer. Cancer J. (2002) 8:461–468.
  • DRESSMAN MA, BARAS A. MALINOWSKI R et al.: Gene expression profiling detects gene amplification and differentiates tumor types in breast cancer. Cancer Res. (2003) 63:2194–2199.
  • DRESSMAN MA, WALZ TM, LAVEDAN C et al.: Genes that co-cluster with estrogen receptor alpha in microarray analysis of breast biopsies. Pharmacogenomics J. (2001) 1:135–141.
  • GRUVBERGER S, RINGNER M, CHEN Y et al.: Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns. Cancer Res. (2001) 61:5979–5984.
  • GRUVBERGER SK, RINGNER M, EDEN P et al.: Expression profiling to predict outcome in breast cancer: the influence of sample selection. Breast Cancer Res. (2003) 5:23–26.
  • HEDENFALK I, RINGNER M, BEN-DORA et al.: Molecular classification of familial non-BRCA1 /BRCA2 breast cancer. Proc. Natl. Acad. Sci. USA (2003) 100:2532–2537.
  • MARTIN KJ, KRITZMAN BM, PRICE LM et al.: Linking gene expression patterns to therapeutic groups in breast cancer. Cancer Res. (2000) 60:2232–2238.
  • NAGAI MA, DA ROS N, NETO MM et al.: Gene expression profiles in breast tumors regarding the presence or absence of estrogen and progesterone receptors. Int. J. Cancer (2004) 111:892–899.
  • PEROU CM, JEFFREY SS, VAN DE RIJN M et al.: Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc. Natl Acad. Sci. USA (1999) 96:9212–9217.
  • ••Important paper regarding breastcancer classification.
  • PEROU CM, SORLIE T, EISEN MB et al: Molecular portraits of human breast tumours. Nature (2000) 406:747–752.
  • PITTMAN J, HUANG E, DRESSMAN H et al.: Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes. Proc. Natl Acad. Sci. USA (2004) 101:8431–8436.
  • POLLACK JR, SORLIE T, PEROU CMet 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.
  • SORLIE T, TIBSHIRANI R, PARKER J et al.: Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Nail. Acad. Sci. USA (2003) 100:8418–8423.
  • SOTIRIOU C, POWLES TJ, DOWSETT M et al.: Gene expression profiles derived from fine needle aspiration correlate with response to systemic chemotherapy in breast cancer. Breast Cancer Res. (2002) 4:R3.
  • TROESTER MA, HOADLEY KA, SORLIE T et al.: Cell-type-specific responses to chemotherapeutics in breast cancer. Cancer Res. (2004) 64:4218–4226.
  • UNGER MA, RISHI M, CLEMMER VB et al.: Characterization of adjacent breast tumors using oligonucleotide microarrays. Breast Cancer Res. (2001) 3:336–341.
  • VAN DE VIJVER MJ, HE YD, VAN'T VEER LJ et al.: A gene-expression signature as a predictor of survival in breast cancer. N EngL J. Med. (2002) 347:1999–2009.
  • ••Validation of the 70-geneprognostic signature.
  • WEIGELT B, GLAS AM, WESSELS LF, WITTEVEEN AT, PETERSE JL, VAN'T VEER LJ: Gene expression profiles of primary breast tumors maintained in distant metastases. Proc. Natl. Acad. Sci. USA (2003) 100:15901–15905.
  • ZHAO H, LANGEROD A. JI Yet al.: Different gene expression patterns in invasive lobular and ductal carcinomas of the breast. MoL Biol. Cell (2004) 15:2523–2536.
  • WEST M, BLANCHETTE C, DRESSMAN H et al.: Predicting the clinical status of human breast cancer by using gene expression profiles. Proc. Natl. Acad. Sci. USA (2001) 98:11462–11467.
  • HEDENFALK I, DUGGAN D, CHEN Y et al.: Gene-expression profiles in hereditary breast cancer. N EngL J. Med. (2001) 344:539–548.
  • NAGAHATA T, ONDA M, EMI M et aL: Expression profiling to predict postoperative prognosis for estrogen receptor-negative breast cancers by analysis of 25,344 genes on a cDNA microarray. Cancer Sci. (2004) 95:218–225.
  • WANG Y, KLIJN JG, ZHANG Y et al.: Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet (2005) 365:671–679.
  • •Recent paper describing the 76-gene prognostic signature.
  • BERTUCCI F, HOULGATTE R, GRANJEAUD S et al.: Prognosis of breast cancer and gene expression profiling using DNA arrays. Ann. IVY Acad. Sci. (2002) 975:217–231.
  • AYERS M, SYMMANS WF, STEC J et aL: Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer. 1 Clin. OncoL (2004) 22:2284–2293.
  • •Describes the use of gene expression signatures to predict therapeutic response.
  • BERTUCCI F, BORIE N, GINESTIER C et al.: Identification and validation of an ERBB2 gene expression signature in breast cancers. Oncogene (2004) 23:2564–2575.
  • CHANG JC, WOOTEN EC, TSIMELZON A et al.: Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet (2003) 362:362–369.
  • JANSEN MP, FOEKENS JA, VAN STAVEREN IL et al.: Molecular classification of tamoxifen-resistant breast carcinomas by gene expression profiling. 1 Clin. OncoL (2005) 23:732–740.
  • PUSZTAI L, AYERS M, STEC J et al.: Gene expression profiles obtained from fine-needle aspirations of breast cancer reliably identify routine prognostic markers and reveal large-scale molecular differences between estrogen-negative and estrogen-positive tumors. Clin. Cancer Res. (2003) 9:2406–2415.
  • RAIVIASWAMY S, ROSS KN, LANDER ES, GOLUB TR: A molecular signature of metastasis in primary solid tumors. Nat. Genet. (2003) 33:49–54.
  • •Seminal paper regarding metastasis expression signature.
  • SCHANER ME, ROSS DT, CIARAVINO G et al.: Gene expression patterns in ovarian carcinomas. MoL Biol. Cell (2003) 14:4376–4386.
  • SELARU FM, YIN J, OLARU A et ell.: An unsupervised approach to identify molecular phenotypic components influencing breast cancer features. Cancer Res. (2004) 64:1584–1588.
  • SIGNORETTI S, DI MARCOTULLIO L, RICHARDSON A et al.: Oncogenic role of the ubiquitin ligase subunit Skp2 in human breast cancer. J. Clin. Invest. (2002) 110:633–641.
  • SHEK LL, GODOLPHIN W: Model for breast cancer survival: relative prognostic roles of axillary nodal status, TNM stage, estrogen receptor concentration, and tumor necrosis. Cancer Res. (1988) 48:5565–5569.
  • FIDLER IJ: The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited. Nat. Rev. Cancer (2003) 3:453–458.
  • KERBEL RS, CORNIL I, THEODORESCU D: Importance of orthotopic transplantation procedures in assessing the effects of transfected genes on human tumor growth and metastasis. Cancer Metastasis Rev. (1991) 10:201–215.
  • FIDLER IJ: Rationale and methods for the use of nude mice to study the biology and therapy of human cancer metastasis. Cancer Metastasis Rev. (1986) 5:29–49.
  • BERNARDS R, WEINBERG RA: A progression puzzle. Nature (2002) 418:823.
  • LIOTTA LA, KOHN EC: Cancer's deadly signature. Nat. Genet. (2003) 33:10–11.
  • EIFEL P, AXELSON JA, COSTA J et al.: National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer, November 1–3, 2000.1 Nail Cancer Inst. (2001) 93:979–989.
  • GOLDHIRSCH k WOOD WC, GELBER RD et al.: Meeting highlights: updated international expert consensus on the primary therapy of early breast cancer. Clin. Oncol. (2003) 21:3357–3365.
  • CALDAS C, APARICIO SA: The molecular outlook. Nature (2002) 415:484–485.
  • DAI H, VAN'T VEER L, LAMB J et ell.: A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients. Cancer Res. (2005) 65:4059–4066.
  • SENN HJ, THURLIMANN B, GOLDHIRSCH A et al.: Comments on the St. Gallen Consensus 2003 on the Primary Therapy of Early Breast Cancer. Breast (2003) 12:569–582.
  • EIN-DOR L, KELA I, GETZ G, GIVOL D, DOMANY E: Outcome signature genes in breast cancer: is there a unique set? Bioinfirmatics (2005) 21:171–178.
  • JENSSEN TK, HOVIG E: Gene-expression profiling in breast cancer. Lancet (2005) 365:634–635.
  • MICHIELS S, KOSCIELNY S, HILL C: Prediction of cancer outcome with microarrays: a multiple random validation strategy. Lancet (2005) 365:488–492.
  • •Paper describing the dangers associated with patient selection.
  • SPRUESSEL A, STEIMANN G, JUNG M et al.: Tissue ischemia time affects gene and protein expression patterns within minutes following surgical tumor excision. Biotechniques (2004) 36:1030–1037.
  • HAYES DF: Determination of clinical utility of tumor markers: a tumor marker utility grading system. Recent Res. Cancer Res. (1998) 152:71–85.
  • HAYES DF, TROCK B, HARRIS AL: Assessing the clinical impact of prognostic factors: when is 'statistically significant' clinically useful? Breast Cancer Res. Treat. (1998) 52:305–319.
  • TUMA RS: Trial and error: prognostic gene signature study design altered. J. Nail Cancer Inst. (2005) 97:331–333.
  • WANG H, HEX, BAND M, WILSON C, LIU L: A study of inter-lab and inter-platform agreement of DNA microarray data. BMC Genomics (2005) 6:71.
  • VAN 'T VEER LJ: Microarrays for patient management in breast cancer. In: Breast International Group (BIG) Newsletter. (2004):3–6.
  • THOR AD, BERRY DA, BUDMAN DR et al: erbB-2, p53, and efficacy of adjuvant therapy in lymph node-positive breast cancer. J. Nail Cancer Inst. (1998) 90:1346–1360.
  • JARVINEN TA, TANNER M, RANTANEN Vet al.: Amplification and deletion of topoisomerase IIalpha associate with ErbB-2 amplification and affect sensitivity to topoisomerase II inhibitor doxorubicin in breast cancer. Am. J. Pathol (2000) 156:839–847.
  • SMITH IE, LIPTON L: Preoperative/ neoadjuvant medical therapy for early breast cancer. Lancet Oncol (2001) 2:561–570.
  • SYMMANS WF, AYERS M, CLARK EA et al.: Total RNA yield and microarray gene expression profiles from fine-needle aspiration biopsy and core-needle biopsy samples of breast carcinoma. Cancer (2003) 97:2960–2971.
  • KUERER HM, NEWMAN LA, SMITH TL et al.: Clinical course of breast cancer patients with complete pathologic primary tumor and axillary lymph node response to doxorubicin-based neoadjuvant chemotherapy. J. Clin. Oncol (1999) 17:460–469.
  • CHOLLET P, AMAT S, CURE H et al.:Prognostic significance of a complete pathological response after induction chemotherapy in operable breast cancer. Br. J. Cancer (2002) 86:1041–1046.
  • COLLEONI M, WALE G, ZAHRIEH D et al.: Chemotherapy is more effective in patients with breast cancer not expressing steroid hormone receptors: a study of preoperative treatment. Clin. Cancer Res. (2004) 10:6622–6628.
  • PETIT T, WILT M, VELTEN M et al.: Comparative value of tumour grade, hormonal receptors, Ki-67, HER-2 and topoisomerase II alpha status as predictive markers in breast cancer patients treated with neoadjuvant anthracycline-based chemotherapy. Eur. J. Cancer (2004) 40:205–211.
  • COLLEONI M, MINCHELLA I, MAZZAROL Get al: Response to primary chemotherapy in breast cancer patients with tumors not expressing estrogen and progesterone receptors. Ann. Oncol (2000) 11:1057–1059.
  • COCQUYT VF, BLONDEEL PN, DEPYPERE HT et al: Different responses to preoperative chemotherapy for invasive lobular and invasive ductal breast carcinoma. Eur. j Surg. Oncol (2003) 29:361–367.
  • MATHIEU MC, ROUZIER R, LLOMBART-CUSSAC A et al: The poor responsiveness of infiltrating lobular breast carcinomas to neoadjuvant chemotherapy can be explained by their biological profile. Eur. J. Cancer (2004) 40:342–351.
  • SIMON R, RADMACHER MD, DOBBIN K: Design of studies using DNA microarrays. Genet. Epidemiol (2002) 23:21–36.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.