Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review
  • Published:

Array-based pharmacogenomics of molecular-targeted therapies in oncology

The Pharmacogenomics Journal volume 12, pages 185–196 (2012)Cite this article

Subjects

Abstract

The advent of microarrays over the past decade has transformed the way genome-wide studies are designed and conducted, leading to an unprecedented speed of acquisition and amount of new knowledge. Microarray data have led to the identification of molecular subclasses of solid tumors characterized by distinct oncogenic pathways, as well as the development of multigene prognostic or predictive models equivalent or superior to those of established clinical parameters. In the field of molecular-targeted therapy for cancer, in particular, the application of array-based methodologies has enabled the identification of molecular targets with ‘key’ roles in neoplastic transformation or tumor progression and the subsequent development of targeted agents, which are most likely to be active in the specific molecular setting. Herein, we present a summary of the main applications of whole-genome expression microarrays in the field of molecular-targeted therapies for solid tumors and we discuss their potential in the clinical setting. An emphasis is given on deciphering the molecular mechanisms of drug action, identifying novel therapeutic targets and suitable agents to target them with, and discovering molecular markers/signatures that predict response to therapy or optimal drug dose for each patient.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2

Similar content being viewed by others

References

  1. Mountzios G, Sanoudou D, Syrigos KN . Clinical pharmacogenetics in oncology: the paradigm of molecular targeted therapies. Curr Pharm Des 2010; 16: 2184–2193.

    Article  PubMed  Google Scholar 

  2. Dhanasekaran SM, Barrette TR, Ghosh D, Shah R, Varambally S, Kurachi K et al. Delineation of prognostic biomarkers in prostate cancer. Nature 2001; 412: 822–826.

    Article  CAS  PubMed  Google Scholar 

  3. Luo J, Zha S, Gage WR, Dunn TA, Hicks JL, Bennett CJ et al. Alpha-methylacyl-CoA racemase: a new molecular marker for prostate cancer. Cancer Res 2002; 62: 2220–2226.

    CAS  PubMed  Google Scholar 

  4. Rubin MA, Zhou M, Dhanasekaran SM, Varambally S, Barrette TR, Sanda MG et al. alpha-Methylacyl coenzyme A racemase as a tissue biomarker for prostate cancer. JAMA 2002; 287: 1662–1670.

    Article  CAS  PubMed  Google Scholar 

  5. Lapointe J, Li C, Higgins JP, van de Rijn M, Bair E, Montgomery K et al. Gene expression profiling identifies clinically relevant subtypes of prostate cancer. Proc Natl Acad Sci USA 2004; 101: 811–816.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Bertucci F, Finetti P, Rougemont J, Charafe-Jauffret E, Cervera N, Tarpin C et al. Gene expression profiling identifies molecular subtypes of inflammatory breast cancer. Cancer Res 2005; 65: 2170–2178.

    Article  CAS  PubMed  Google Scholar 

  7. Curtin JA, Fridlyand J, Kageshita T, Patel HN, Busam KJ, Kutzner H et al. Distinct sets of genetic alterations in melanoma. N Engl J Med 2005; 353: 2135–2147.

    Article  CAS  PubMed  Google Scholar 

  8. Bhattacharjee A, Richards WG, Staunton J, Li C, Monti S, Vasa P et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl Acad Sci USA 2001; 98: 13790–13795.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. van de Vijver MJ, He YD, van’t Veer LJ, Dai H, Hart AA, Voskuil DW et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002; 347: 1999–2009.

    Article  CAS  PubMed  Google Scholar 

  10. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004; 351: 2817–2826.

    Article  CAS  PubMed  Google Scholar 

  11. van ‘t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002; 415: 530–536.

    Article  PubMed  Google Scholar 

  12. Sotiriou C, Pusztai L . Gene-expression signatures in breast cancer. N Engl J Med 2009; 360: 790–800.

    Article  CAS  PubMed  Google Scholar 

  13. Lacayo NJ, Meshinchi S, Kinnunen P, Yu R, Wang Y, Stuber CM et al. Gene expression profiles at diagnosis in de novo childhood AML patients identify FLT3 mutations with good clinical outcomes. Blood 2004; 104: 2646–2654.

    Article  CAS  PubMed  Google Scholar 

  14. Rosenwald A, Wright G, Chan WC, Connors JM, Campo E, Fisher RI et al. The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N Engl J Med 2002; 346: 1937–1947.

    Article  PubMed  Google Scholar 

  15. Shipp MA, Ross KN, Tamayo P, Weng AP, Kutok JL, Aguiar RC et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat Med 2002; 8: 68–74.

    Article  CAS  PubMed  Google Scholar 

  16. Chang JC, Wooten EC, Tsimelzon A, Hilsenbeck SG, Gutierrez MC, Elledge R et al. Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet 2003; 362: 362–369.

    Article  CAS  PubMed  Google Scholar 

  17. Capdevila J, Elez E, Macarulla T, Ramos FJ, Ruiz-Echarri M, Tabernero J . Anti-epidermal growth factor receptor monoclonal antibodies in cancer treatment. Cancer Treat Rev 2009; 35: 354–363.

    Article  CAS  PubMed  Google Scholar 

  18. Lynch TJ, Bell DW, Sordella R, Gurubhagavatula S, Okimoto RA, Brannigan BW et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 2004; 350: 2129–2139.

    Article  CAS  PubMed  Google Scholar 

  19. Paez JG, Janne PA, Lee JC, Tracy S, Greulich H, Gabriel S et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 2004; 304: 1497–1500.

    Article  CAS  PubMed  Google Scholar 

  20. Pao W, Miller V, Zakowski M, Doherty J, Politi K, Sarkaria I et al. EGF receptor gene mutations are common in lung cancers from ‘never smokers’ and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc Natl Acad Sci USA 2004; 101: 13306–13311.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Solmi R, Lauriola M, Francesconi M, Martini D, Voltattorni M, Ceccarelli C et al. Displayed correlation between gene expression profiles and submicroscopic alterations in response to cetuximab, gefitinib and EGF in human colon cancer cell lines. BMC Cancer 2008; 8: 227.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Hopfner M, Sutter AP, Gerst B, Zeitz M, Scherubl H . A novel approach in the treatment of neuroendocrine gastrointestinal tumours. Targeting the epidermal growth factor receptor by gefitinib (ZD1839). Br J Cancer 2003; 89: 1766–1775.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Inoue R, Matsuyama H, Yano S, Yamamoto Y, Iizuka N, Naito K . Gefitinib-related gene signature in bladder cancer cells identified by a cDNA microarray. Anticancer Res 2006; 26 (6B): 4195–4202.

    CAS  PubMed  Google Scholar 

  24. Ferry DR, Anderson M, Beddard K, Tomlinson S, Atherfold P, Obszynska J et al. A phase II study of gefitinib monotherapy in advanced esophageal adenocarcinoma: evidence of gene expression, cellular, and clinical response. Clin Cancer Res 2007; 13: 5869–5875.

    Article  CAS  PubMed  Google Scholar 

  25. Frederick BA, Helfrich BA, Coldren CD, Zheng D, Chan D, Bunn Jr PA et al. Epithelial to mesenchymal transition predicts gefitinib resistance in cell lines of head and neck squamous cell carcinoma and non-small cell lung carcinoma. Mol Cancer Ther 2007; 6: 1683–1691.

    Article  CAS  PubMed  Google Scholar 

  26. Fuchs BC, Fujii T, Dorfman JD, Goodwin JM, Zhu AX, Lanuti M et al. Epithelial-to-mesenchymal transition and integrin-linked kinase mediate sensitivity to epidermal growth factor receptor inhibition in human hepatoma cells. Cancer Res 2008; 68: 2391–2399.

    Article  CAS  PubMed  Google Scholar 

  27. Coldren CD, Helfrich BA, Witta SE, Sugita M, Lapadat R, Zeng C et al. Baseline gene expression predicts sensitivity to gefitinib in non-small cell lung cancer cell lines. Mol Cancer Res 2006; 4: 521–528.

    Article  CAS  PubMed  Google Scholar 

  28. Jimeno A, Rubio-Viqueira B, Amador ML, Grunwald V, Maitra A, Iacobuzio-Donahue C et al. Dual mitogen-activated protein kinase and epidermal growth factor receptor inhibition in biliary and pancreatic cancer. Mol Cancer Ther 2007; 6: 1079–1088.

    Article  CAS  PubMed  Google Scholar 

  29. Jain A, Tindell CA, Laux I, Hunter JB, Curran J, Galkin A et al. Epithelial membrane protein-1 is a biomarker of gefitinib resistance. Proc Natl Acad Sci USA 2005; 102: 11858–11863.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Kakiuchi S, Daigo Y, Ishikawa N, Furukawa C, Tsunoda T, Yano S et al. Prediction of sensitivity of advanced non-small cell lung cancers to gefitinib (Iressa, ZD1839). Hum Mol Genet 2004; 13: 3029–3043.

    Article  CAS  PubMed  Google Scholar 

  31. Hoadley KA, Weigman VJ, Fan C, Sawyer LR, He X, Troester MA et al. EGFR associated expression profiles vary with breast tumor subtype. BMC Genomics 2007; 8: 258.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Shepherd FA, Rodrigues Pereira J, Ciuleanu T, Tan EH, Hirsh V, Thongprasert S et al. Erlotinib in previously treated non-small-cell lung cancer. N Engl J Med 2005; 353: 123–132.

    Article  CAS  PubMed  Google Scholar 

  33. Moore MJ, Goldstein D, Hamm J, Figer A, Hecht JR, Gallinger S et al. Erlotinib plus gemcitabine compared with gemcitabine alone in patients with advanced pancreatic cancer: a phase III trial of the National Cancer Institute of Canada Clinical Trials Group. J Clin Oncol 2007; 25: 1960–1966.

    Article  CAS  PubMed  Google Scholar 

  34. Yang SX, Simon RM, Tan AR, Nguyen D, Swain SM . Gene expression patterns and profile changes pre- and post-erlotinib treatment in patients with metastatic breast cancer. Clin Cancer Res 2005; 11: 6226–6232.

    Article  CAS  PubMed  Google Scholar 

  35. Buchanan FG, Holla V, Katkuri S, Matta P, DuBois RN . Targeting cyclooxygenase-2 and the epidermal growth factor receptor for the prevention and treatment of intestinal cancer. Cancer Res 2007; 67: 9380–9388.

    Article  CAS  PubMed  Google Scholar 

  36. Chinnaiyan P, Huang S, Vallabhaneni G, Armstrong E, Varambally S, Tomlins SA et al. Mechanisms of enhanced radiation response following epidermal growth factor receptor signaling inhibition by erlotinib (Tarceva). Cancer Res 2005; 65: 3328–3335.

    Article  CAS  PubMed  Google Scholar 

  37. Balko JM, Potti A, Saunders C, Stromberg A, Haura EB, Black EP . Gene expression patterns that predict sensitivity to epidermal growth factor receptor tyrosine kinase inhibitors in lung cancer cell lines and human lung tumors. BMC Genomics 2006; 7: 289.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Cunningham D, Humblet Y, Siena S, Khayat D, Bleiberg H, Santoro A et al. Cetuximab monotherapy and cetuximab plus irinotecan in irinotecan-refractory metastatic colorectal cancer. N Engl J Med 2004; 351: 337–345.

    Article  CAS  PubMed  Google Scholar 

  39. Bonner JA, Harari PM, Giralt J, Azarnia N, Shin DM, Cohen RB et al. Radiotherapy plus cetuximab for squamous-cell carcinoma of the head and neck. N Engl J Med 2006; 354: 567–578.

    Article  CAS  PubMed  Google Scholar 

  40. Pirker R, Pereira JR, Szczesna A, von Pawel J, Krzakowski M, Ramlau R et al. Cetuximab plus chemotherapy in patients with advanced non-small-cell lung cancer (FLEX): an open-label randomised phase III trial. Lancet 2009; 373: 1525–1531.

    Article  CAS  PubMed  Google Scholar 

  41. Debucquoy A, Haustermans K, Daemen A, Aydin S, Libbrecht L, Gevaert O et al. Molecular response to cetuximab and efficacy of preoperative cetuximab-based chemoradiation in rectal cancer. J Clin Oncol 2009; 27: 2751–2757.

    Article  CAS  PubMed  Google Scholar 

  42. Daemen A, Gevaert O, De Bie T, Debucquoy A, Machiels JP, De Moor B et al. Integrating microarray and proteomics data to predict the response on cetuximab in patients with rectal cancer. Pac Symp Biocomput 2008: 166–177.

  43. Van Cutsem E, Kohne CH, Hitre E, Zaluski J, Chang Chien CR, Makhson A et al. Cetuximab and chemotherapy as initial treatment for metastatic colorectal cancer. N Engl J Med 2009; 360: 1408–1417.

    Article  CAS  PubMed  Google Scholar 

  44. Balko JM, Black EP . A gene expression predictor of response to EGFR-targeted therapy stratifies progression-free survival to cetuximab in KRAS wild-type metastatic colorectal cancer. BMC Cancer 2009; 9: 145.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Holmes WE, Sliwkowski MX, Akita RW, Henzel WJ, Lee J, Park JW et al. Identification of heregulin, a specific activator of p185erbB2. Science 1992; 256: 1205–1210.

    Article  CAS  PubMed  Google Scholar 

  46. Cho HS, Mason K, Ramyar KX, Stanley AM, Gabelli SB, Denney Jr DW et al. Structure of the extracellular region of HER2 alone and in complex with the Herceptin Fab. Nature 2003; 421: 756–760.

    Article  CAS  PubMed  Google Scholar 

  47. Kumar-Sinha C, Ignatoski KW, Lippman ME, Ethier SP, Chinnaiyan AM . Transcriptome analysis of HER2 reveals a molecular connection to fatty acid synthesis. Cancer Res 2003; 63: 132–139.

    CAS  PubMed  Google Scholar 

  48. Le XF, Lammayot A, Gold D, Lu Y, Mao W, Chang T et al. Genes affecting the cell cycle, growth, maintenance, and drug sensitivity are preferentially regulated by anti-HER2 antibody through phosphatidylinositol 3-kinase-AKT signaling. J Biol Chem 2005; 280: 2092–2104.

    Article  CAS  PubMed  Google Scholar 

  49. Leyland-Jones B . Trastuzumab: hopes and realities. Lancet Oncol 2002; 3: 137–144.

    Article  CAS  PubMed  Google Scholar 

  50. Hayes DF, Thor AD . c-erbB-2 in breast cancer: development of a clinically useful marker. Semin Oncol 2002; 29: 231–245.

    Article  CAS  PubMed  Google Scholar 

  51. Dressman MA, Baras A, Malinowski R, Alvis LB, Kwon I, Walz TM et al. Gene expression profiling detects gene amplification and differentiates tumor types in breast cancer. Cancer Res 2003; 63: 2194–2199.

    CAS  PubMed  Google Scholar 

  52. Willis S, Hutchins AM, Hammet F, Ciciulla J, Soo WK, White D et al. Detailed gene copy number and RNA expression analysis of the 17q12-23 region in primary breast cancers. Genes Chromosomes Cancer 2003; 36: 382–392.

    Article  CAS  PubMed  Google Scholar 

  53. Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 2003; 100: 8418–8423.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA et al. Molecular portraits of human breast tumours. Nature 2000; 406: 747–752.

    Article  CAS  PubMed  Google Scholar 

  55. Vegran F, Boidot R, Coudert B, Fumoleau P, Arnould L, Garnier J et al. Gene expression profile and response to trastuzumab-docetaxel-based treatment in breast carcinoma. Br J Cancer 2009; 101: 1357–1364.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Gu L, Lau SK, Loera S, Somlo G, Kane SE . Protein kinase A activation confers resistance to trastuzumab in human breast cancer cell lines. Clin Cancer Res 2009; 15: 7196–7206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Rusnak DW, Lackey K, Affleck K, Wood ER, Alligood KJ, Rhodes N et al. The effects of the novel, reversible epidermal growth factor receptor/ErbB-2 tyrosine kinase inhibitor, GW2016, on the growth of human normal and tumor-derived cell lines in vitro and in vivo. Mol Cancer Ther 2001; 1: 85–94.

    CAS  PubMed  Google Scholar 

  58. Kim HP, Han SW, Kim SH, Im SA, Oh DY, Bang YJ et al. Combined lapatinib and cetuximab enhance cytotoxicity against gefitinib-resistant lung cancer cells. Mol Cancer Ther 2008; 7: 607–615.

    Article  CAS  PubMed  Google Scholar 

  59. Ritter CA, Perez-Torres M, Rinehart C, Guix M, Dugger T, Engelman JA et al. Human breast cancer cells selected for resistance to trastuzumab in vivo overexpress epidermal growth factor receptor and ErbB ligands and remain dependent on the ErbB receptor network. Clin Cancer Res 2007; 13: 4909–4919.

    Article  CAS  PubMed  Google Scholar 

  60. Konecny GE, Pegram MD, Venkatesan N, Finn R, Yang G, Rahmeh M et al. Activity of the dual kinase inhibitor lapatinib (GW572016) against HER-2-overexpressing and trastuzumab-treated breast cancer cells. Cancer Res 2006; 66: 1630–1639.

    Article  CAS  PubMed  Google Scholar 

  61. Xia W, Husain I, Liu L, Bacus S, Saini S, Spohn J et al. Lapatinib antitumor activity is not dependent upon phosphatase and tensin homologue deleted on chromosome 10 in ErbB2-overexpressing breast cancers. Cancer Res 2007; 67: 1170–1175.

    Article  CAS  PubMed  Google Scholar 

  62. Cameron D, Casey M, Oliva C, Newstat B, Imwalle B, Geyer CE . Lapatinib plus capecitabine in women with HER-2-positive advanced breast cancer: final survival analysis of a phase III randomized trial. Oncologist 2010; 15: 924–934.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Hegde PS, Rusnak D, Bertiaux M, Alligood K, Strum J, Gagnon R et al. Delineation of molecular mechanisms of sensitivity to lapatinib in breast cancer cell lines using global gene expression profiles. Mol Cancer Ther 2007; 6: 1629–1640.

    Article  CAS  PubMed  Google Scholar 

  64. Kim JW, Kim HP, Im SA, Kang S, Hur HS, Yoon YK et al. The growth inhibitory effect of lapatinib, a dual inhibitor of EGFR and HER2 tyrosine kinase, in gastric cancer cell lines. Cancer Lett 2008; 272: 296–306.

    Article  CAS  PubMed  Google Scholar 

  65. Kim HP, Yoon YK, Kim JW, Han SW, Hur HS, Park J et al. Lapatinib, a dual EGFR and HER2 tyrosine kinase inhibitor, downregulates thymidylate synthase by inhibiting the nuclear translocation of EGFR and HER2. PLoS One 2009; 4: e5933.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Medina PJ, Goodin S . Lapatinib: a dual inhibitor of human epidermal growth factor receptor tyrosine kinases. Clin Ther 2008; 30: 1426–1447.

    Article  CAS  PubMed  Google Scholar 

  67. Di Cosimo S, Baselga J . Targeted therapies in breast cancer: where are we now? Eur J Cancer 2008; 44: 2781–2790.

    Article  CAS  PubMed  Google Scholar 

  68. Havaleshko DM, Smith SC, Cho H, Cheon S, Owens CR, Lee JK et al. Comparison of global versus epidermal growth factor receptor pathway profiling for prediction of lapatinib sensitivity in bladder cancer. Neoplasia 2009; 11: 1185–1193.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Du Y, Wang K, Fang H, Li J, Xiao D, Zheng P et al. Coordination of intrinsic, extrinsic, and endoplasmic reticulum-mediated apoptosis by imatinib mesylate combined with arsenic trioxide in chronic myeloid leukemia. Blood 2006; 107: 1582–1590.

    Article  CAS  PubMed  Google Scholar 

  70. McLean LA, Gathmann I, Capdeville R, Polymeropoulos MH, Dressman M . Pharmacogenomic analysis of cytogenetic response in chronic myeloid leukemia patients treated with imatinib. Clin Cancer Res 2004; 10 (1 Part 1): 155–165.

    Article  CAS  PubMed  Google Scholar 

  71. Kaneta Y, Kagami Y, Katagiri T, Tsunoda T, Jin-nai I, Taguchi H et al. Prediction of sensitivity to STI571 among chronic myeloid leukemia patients by genome-wide cDNA microarray analysis. Jpn J Cancer Res 2002; 93: 849–856.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Radich JP, Dai H, Mao M, Oehler V, Schelter J, Druker B et al. Gene expression changes associated with progression and response in chronic myeloid leukemia. Proc Natl Acad Sci USA 2006; 103: 2794–2799.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Grosso S, Puissant A, Dufies M, Colosetti P, Jacquel A, Lebrigand K et al. Gene expression profiling of imatinib and PD166326-resistant CML cell lines identifies Fyn as a gene associated with resistance to BCR-ABL inhibitors. Mol Cancer Ther 2009; 8: 1924–1933.

    Article  CAS  PubMed  Google Scholar 

  74. Quek R, George S . Gastrointestinal stromal tumor: a clinical overview. Hematol Oncol Clin North Am 2009; 23: 69–78, viii.

    Article  PubMed  Google Scholar 

  75. Febbo PG, Thorner A, Rubin MA, Loda M, Kantoff PW, Oh WK et al. Application of oligonucleotide microarrays to assess the biological effects of neoadjuvant imatinib mesylate treatment for localized prostate cancer. Clin Cancer Res 2006; 12: 152–158.

    Article  CAS  PubMed  Google Scholar 

  76. Vitali R, Mancini C, Cesi V, Tanno B, Mancuso M, Bossi G et al. Slug (SNAI2) down-regulation by RNA interference facilitates apoptosis and inhibits invasive growth in neuroblastoma preclinical models. Clin Cancer Res 2008; 14: 4622–4630.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Ochs MF, Rink L, Tarn C, Mburu S, Taguchi T, Eisenberg B et al. Detection of treatment-induced changes in signaling pathways in gastrointestinal stromal tumors using transcriptomic data. Cancer Res 2009; 69: 9125–9132.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Moses AV, Jarvis MA, Raggo C, Bell YC, Ruhl R, Luukkonen BG et al. A functional genomics approach to Kaposi's sarcoma. Ann N Y Acad Sci 2002; 975: 180–191.

    Article  CAS  PubMed  Google Scholar 

  79. Price ND, Trent J, El-Naggar AK, Cogdell D, Taylor E, Hunt KK et al. Highly accurate two-gene classifier for differentiating gastrointestinal stromal tumors and leiomyosarcomas. Proc Natl Acad Sci USA 2007; 104: 3414–3419.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Karaman MW, Herrgard S, Treiber DK, Gallant P, Atteridge CE, Campbell BT et al. A quantitative analysis of kinase inhibitor selectivity. Nat Biotechnol 2008; 26: 127–132.

    Article  CAS  PubMed  Google Scholar 

  81. Huang F, Reeves K, Han X, Fairchild C, Platero S, Wong TW et al. Identification of candidate molecular markers predicting sensitivity in solid tumors to dasatinib: rationale for patient selection. Cancer Res 2007; 67: 2226–2238.

    Article  CAS  PubMed  Google Scholar 

  82. Lombardo LJ, Lee FY, Chen P, Norris D, Barrish JC, Behnia K et al. Discovery of N-(2-chloro-6-methyl- phenyl)-2-(6-(4-(2-hydroxyethyl)- piperazin-1-yl)-2-methylpyrimidin-4-ylamino)thiazole-5-carboxamide (BMS-354825), a dual Src/Abl kinase inhibitor with potent antitumor activity in preclinical assays. J Med Chem 2004; 47: 6658–6661.

    Article  CAS  PubMed  Google Scholar 

  83. Shah NP, Tran C, Lee FY, Chen P, Norris D, Sawyers CL . Overriding imatinib resistance with a novel ABL kinase inhibitor. Science 2004; 305: 399–401.

    Article  CAS  PubMed  Google Scholar 

  84. Talpaz M, Shah NP, Kantarjian H, Donato N, Nicoll J, Paquette R et al. Dasatinib in imatinib-resistant Philadelphia chromosome-positive leukemias. N Engl J Med 2006; 354: 2531–2541.

    Article  CAS  PubMed  Google Scholar 

  85. Ishizawar R, Parsons SJ . c-Src and cooperating partners in human cancer. Cancer Cell 2004; 6: 209–214.

    Article  CAS  PubMed  Google Scholar 

  86. Yeatman TJ . A renaissance for SRC. Nat Rev Cancer 2004; 4: 470–480.

    Article  CAS  PubMed  Google Scholar 

  87. Nam S, Kim D, Cheng JQ, Zhang S, Lee JH, Buettner R et al. Action of the Src family kinase inhibitor, dasatinib (BMS-354825), on human prostate cancer cells. Cancer Res 2005; 65: 9185–9189.

    Article  CAS  PubMed  Google Scholar 

  88. Paripati A, Kingsley C, Weiss GJ . Pathway targets to explore in the treatment of small cell and large cell lung cancers. J Thorac Oncol 2009; 4: 1313–1321.

    Article  PubMed  Google Scholar 

  89. Weiss GJ, Kingsley C . Pathway targets to explore in the treatment of non-small cell lung cancer. J Thorac Oncol 2008; 3: 1342–1352.

    Article  PubMed  Google Scholar 

  90. Wang XD, Reeves K, Luo FR, Xu LA, Lee F, Clark E et al. Identification of candidate predictive and surrogate molecular markers for dasatinib in prostate cancer: rationale for patient selection and efficacy monitoring. Genome Biol 2007; 8: R255.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Wang C, Maass T, Krupp M, Thieringer F, Strand S, Worns MA et al. A systems biology perspective on cholangiocellular carcinoma development: focus on MAPK-signaling and the extracellular environment. J Hepatol 2009; 50: 1122–1131.

    Article  CAS  PubMed  Google Scholar 

  92. Cheepala SB, Yin W, Syed Z, Gill JN, McMillian A, Kleiner HE et al. Identification of the B-Raf/Mek/Erk MAP kinase pathway as a target for all-trans retinoic acid during skin cancer promotion. Mol Cancer 2009; 8: 27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Newell P, Toffanin S, Villanueva A, Chiang DY, Minguez B, Cabellos L et al. Ras pathway activation in hepatocellular carcinoma and anti-tumoral effect of combined sorafenib and rapamycin in vivo. J Hepatol 2009; 51: 725–733.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Sos ML, Michel K, Zander T, Weiss J, Frommolt P, Peifer M et al. Predicting drug susceptibility of non-small cell lung cancers based on genetic lesions. J Clin Invest 2009; 119: 1727–1740.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Sos ML, Fischer S, Ullrich R, Peifer M, Heuckmann JM, Koker M et al. Identifying genotype-dependent efficacy of single and combined PI3K- and MAPK-pathway inhibition in cancer. Proc Natl Acad Sci USA 2009; 106: 18351–18356.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Ji RR, de Silva H, Jin Y, Bruccoleri RE, Cao J, He A et al. Transcriptional profiling of the dose response: a more powerful approach for characterizing drug activities. PLoS Comput Biol 2009; 5: e1000512.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. von Eyben FE . Epidermal growth factor receptor inhibition and non-small cell lung cancer. Crit Rev Clin Lab Sci 2006; 43: 291–323.

    Article  CAS  PubMed  Google Scholar 

  98. Potti A, Mukherjee S, Petersen R, Dressman HK, Bild A, Koontz J et al. A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N Engl J Med 2006; 355: 570–580.

    Article  CAS  PubMed  Google Scholar 

  99. Potti A, Dressman HK, Bild A, Riedel RF, Chan G, Sayer R et al. Genomic signatures to guide the use of chemotherapeutics. Nat Med 2006; 12: 1294–1300.

    Article  CAS  PubMed  Google Scholar 

  100. Potti A, Dressman HK, Bild A, Riedel RF, Chan G, Sayer R et al. Retraction: genomic signatures to guide the use of chemotherapeutics. Nat Med 2011; 17: 135.

    Article  CAS  PubMed  Google Scholar 

  101. Potti A, Mukherjee S, Petersen R, Dressman HK, Bild A, Koontz J et al. Retraction: a genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N Engl J Med 2006; 355: 570–580. N Engl J Med 2011; 364(12): 1176.

    Article  CAS  PubMed  Google Scholar 

  102. Bonnefoi H, Potti A, Delorenzi M, Mauriac L, Campone M, Tubiana-Hulin M et al. Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial. Lancet Oncol 2007; 8: 1071–1078.

    Article  CAS  PubMed  Google Scholar 

  103. Bonnefoi H, Potti A, Delorenzi M, Mauriac L, Campone M, Tubiana-Hulin M et al. Retraction—validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial. Lancet Oncol 2011; 12: 116.

    Article  PubMed  Google Scholar 

  104. Linton K, Hey Y, Dibben S, Miller C, Freemont A, Radford J et al. Methods comparison for high-resolution transcriptional analysis of archival material on Affymetrix Plus 2.0 and Exon 1.0 microarrays. Biotechniques 2009; 47: 587–596.

    Article  CAS  PubMed  Google Scholar 

  105. Roberts L, Bowers J, Sensinger K, Lisowski A, Getts R, Anderson MG . Identification of methods for use of formalin-fixed, paraffin-embedded tissue samples in RNA expression profiling. Genomics 2009; 94: 341–348.

    Article  CAS  PubMed  Google Scholar 

  106. Schwers S, Reifenberger E, Gehrmann M, Izmailov A, Bohmann K . A high-sensitivity, medium-density, and target amplification-free planar waveguide microarray system for gene expression analysis of formalin-fixed and paraffin-embedded tissue. Clin Chem 2009; 55: 1995–2003.

    Article  CAS  PubMed  Google Scholar 

  107. Jacobson TA, Lundahl J, Mellstedt H, Moshfegh A . Gene expression analysis using long-term preserved formalin-fixed and paraffin-embedded tissue of non-small cell lung cancer. Int J Oncol 2011; 38: 1075–1081.

    PubMed  Google Scholar 

  108. Grenert JP, Smith A, Ruan W, Pillai R, Wu AH . Gene expression profiling from formalin-fixed, paraffin-embedded tissue for tumor diagnosis. Clin Chim Acta 2011; 412: 1462–1464.

    Article  CAS  PubMed  Google Scholar 

  109. Simon RM, Paik S, Hayes DF . Use of archived specimens in evaluation of prognostic and predictive biomarkers. J Natl Cancer Inst 2009; 101: 1446–1452.

    Article  PubMed  PubMed Central  Google Scholar 

  110. Shendure J . The beginning of the end for microarrays? Nat Methods 2008; 5: 585–587.

    Article  CAS  PubMed  Google Scholar 

  111. Sanoudou D . Pharmacogenomics: achievements, challenges and prospects, for patients, pharmaceutical industries and healthcare systems. Curr Pharm Des 2010; 16: 2182–2183.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

DS is supported by Grants from the European Community's Seventh Framework Programme FP7/2007–2013 under grant agreement #HEALTH-F2-2009-241526, ‘EUTrigTreat’, the European Community's Sixth Framework Programme FP6 under grant agreement #LSHG-CT-2006-037277, ‘VALAPODYN’, the Hellenic Cardiological Society and the John S Latsis Public Benefit Foundation.

Author information

Author notes

  1. D Sanoudou and G Mountzios: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Pharmacology, Medical School, University of Athens, Athens, Greece

    D Sanoudou

  2. Department of Medical Oncology and Translational Research, 251 Airforce General Hospital, Athens, Greece

    G Mountzios

  3. Molecular Biology Division, Biomedical Research Foundation of the Academy of Athens, Athens, Greece

    D A Arvanitis

  4. 2nd Department of Internal Medicine, Medical Oncology Unit, Medical School, University of Athens, ‘Hippocrateion’ Hospital, Athens, Greece

    D Pectasides

Authors
  1. D Sanoudou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. G Mountzios
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. D A Arvanitis
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D Pectasides
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to D Sanoudou.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sanoudou, D., Mountzios, G., Arvanitis, D. et al. Array-based pharmacogenomics of molecular-targeted therapies in oncology. Pharmacogenomics J 12, 185–196 (2012). https://doi.org/10.1038/tpj.2011.53

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/tpj.2011.53

Keywords

This article is cited by

Search

Advanced search

Quick links