A pathway-based classification of breast cancer integrating data on differentially expressed genes, copy number variations and MicroRNA target genes

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• 作者：Hae-Seok Eo (1)
  Jee Yeon Heo (1)
  Yongjin Choi (1)
  Youngdon Hwang (1)
  Hyung-Seok Choi (1)
  
• 关键词：breast cancer ; classification ; copy number variation ; differentially expressed gene ; microRNA ; pathway
• 刊名：Molecules and Cells
• 出版年：2012
• 出版时间：October 2012
• 年：2012
• 卷：34
• 期：4
• 页码：393-398
• 全文大小：462KB
• 参考文献：1. Barrett, T., Troup, D.B., Wilhite, S.E., Ledoux, P., Evangelista, C., Kim, I.F., Tomashevsky, M., Marshall, K.A., Phillippy, K.H., Sherman, P.M., et al. (2011). NCBI GEO: archive for functional genomics data sets-10 years on. Nucleic Acids Res. / 39, D1005鈥揇1010. CrossRef
  2. Baselga, J. (2011). Targeting the phosphoinositide-3 (PI3) kinase pathway in breast cancer. Oncologist / 16, 12鈥?9. CrossRef
  3. Beroukhim, R., Getz, G., Nghiemphu, L., Barretina, J., Hsueh, T., Linhart, D., Vivanco, I., Lee, J.C., Huang, J.H., Alexander, A., et al. (2007). Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma. Proc. Natl. Acad. Sci. USA / 104, 20007鈥?0012. CrossRef
  4. Blenkiron, C., Goldstein, L.D., Thorne, N.P., Spiteri, I., Chin, S.F., Dunning, M.J., Barbosa-Morais, N.L., Teschendorff, A.E., Green, A.R., Ellis, I.O., et al. (2007). MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype. Genome Biol. / 8, R214. CrossRef
  5. Brown, A.M. (2001). Wnt signaling in breast cancer: have we come full circle? Breast Cancer Res. / 3, 351鈥?55. CrossRef
  6. Cerami, E.G., Gross, B.E., Demir, E., Rodchenkov, I., Babur, O., Anwar, N., Schultz, N., Bader, G.D., and Sander, C. (2011). Pathway Commons, a web resource for biological pathway data. Nucleic Acids Res. / 39, D685鈥揇690. CrossRef
  7. Chen, D.T., Nasir, A., Culhane, A., Venkataramu, C., Fulp, W., Rubio, R., Wang, T., Agrawal, D., McCarthy, S.M., Gruidl, M., et al., (2010). Proliferative genes dominate malignancy-risk gene signature in histologically-normal breast tissue. Breast Cancer Res. Treat. / 119, 335鈥?46. CrossRef
  8. Cho, S., Jun, Y., Lee, S., Choi, H.S., Jung, S., Jang, Y., Park, Kim, S., Lee, S., and Kim, W. (2011). miRGator v2.0: an integrated system for functional investigation of microRNAs. Nucleic Acids Res. / 39, D158鈥?62. CrossRef
  9. Chuang, H.Y., Lee, E., Liu, Y.T., Lee, D., and Ideker, T. (2007). Network-based classification of breast cancer metastasis. Mol. Syst. Biol. / 3, 140. CrossRef
  10. Dedeurwaerder, S., Desmedt, C., Calonne, E., Singhal, S.K., Haibe-Kains, B., Defrance, M., Michiels, S., Volkmar, M., Deplus, R., Luciani, J., et al. (2011). DNA methylation profiling reveals a predominant immune component in breast cancers. EMBO Mol. Med. / 3, 726鈥?41. CrossRef
  11. Desmedt, C., Haibe-Kains, B., Wirapati, P., Buyse, M., Larsimont, D., Bontempi, G., Delorenzi, M., Piccart, M., and Sotiriou, C. (2008). Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin. Cancer Res. / 14, 5158鈥?165. CrossRef
  12. Donahue, T.R., Tran, L.M., Hill, R., Li, Y., Kovochich, A., Calvopina, J.H., Patel, S.G., Wu, N., Hindoyan, A., Farrell, J.J., et al. (2012). Integrative survival-based molecular profiling of human pancreatic cancer. Clin. Cancer Res. / 18, 1352鈥?363. CrossRef
  13. Figueiredo, J.C., Knight, J.A., Cho, S., Savas, S., Onay, U.V., Briollais, L., Goodwin, P.J., McLaughlin, J.R., Andrulis, I.L., and Ozcelik, H. (2007). Polymorphisms cMyc-N11S and p27-V109G and breast cancer risk and prognosis. BMC Cancer / 7, 99. CrossRef
  14. Gu, L., Waliany, S., and Kane, S.E. (2009). Darpp-32 and its truncated variant t-Darpp have antagonistic effects on breast cancer cell growth and herceptin resistance. PLoS One / 4, e6220. CrossRef
  15. Hawthorn, L., Luce, J., Stein, L., and Rothschild, J. (2010). Integration of transcript expression, copy number and LOH analysis of infiltrating ductal carcinoma of the breast. BMC Cancer / 10, 460. CrossRef
  16. Henderson, I.C., and Patek, A.J. (1998). The relationship between prognostic and predictive factors in the management of breast cancer. Breast Cancer Res. Treat. / 52, 261鈥?88. CrossRef
  17. Huang, W., Sherman, B.T., Stephens, R., Baseler, M.W., Lane, H.C., and Lempicki, R.A. (2008). DAVID gene ID conversion tool. Bioinformation / 2, 428鈥?30. CrossRef
  18. Kao, K.J., Chang, K.M., Hsu, H.C., and Huang, A.T. (2011). Correlation of microarray-based breast cancer molecular subtypes and clinical outcomes: implications for treatment optimization. BMC Cancer / 11, 143. CrossRef
  19. Karnoub, A.E., Dash, A.B., Vo, A.P., Sullivan, A., Brooks, M.W., Bell, G.W., Richardson, A.L., Polyak, K., Tubo, R., and Wein-berg, R.A. (2007). Mesenchymal stem cells within tumour stroma promote breast cancer metastasis. Nature / 449, 557鈥?63. CrossRef
  20. Kaufmann, L.A.R., and Rousseeu, P.J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis (New York: Wiley Inc.). CrossRef
  21. Kim, J.H., Kang, S., Kim, T.W., Yin, L., Liu, R., and Kim, S.J. (2012). Expression profiling after induction of demethylation in MCF-7 breast cancer cells identifies involvement of TNF- med 伪 iated cancer pathways. Mol. Cells / 33, 127鈥?33. CrossRef
  22. Krijgsman, O., Roepman, P., Zwart, W., Carroll, J.S., Tian, S., de Snoo, F.A., Bender, R.A., Bernards, R., and Glas, A.M. (2012). A diagnostic gene profile for molecular subtyping of breast cancer associated with treatment response. Breast Cancer Res. Treat. / 133, 37鈥?7. CrossRef
  23. Lee, E., Chuang, H.Y., Kim, J.W., Ideker, T., and Lee, D. (2008). Inferring pathway activity toward precise disease classification. PLoS Comput. Biol. / 4, e1000217. CrossRef
  24. Loi, S., Haibe-Kains, B., Majjaj, S., Lallemand, F., Durbecq, V., Larsimont, D., Gonzalez-Angulo, A.M., Pusztai, L., Symmans, W.F., Bardelli, A., et al. (2010). PIK3CA mutations associated with gene signature of low mTORC1 signaling and better outcomes in estrogen receptor-positive breast cancer. Proc. Natl. Acad. Sci. USA / 107, 10208鈥?0213. CrossRef
  25. Lu, X., Lu, X., Wang, Z.C., Iglehart, J.D., Zhang, X., and Richardson, A.L. (2008). Predicting features of breast cancer with gene expression patterns. Breast Cancer Res. Treat. / 108, 191鈥?01. CrossRef
  26. Nordgard, S.H., Johansen, F.E., Alnaes, G.I., Bucher, E., Syv盲nen, A.C., Naume, B., B酶rresen-Dale, A.L., and Kristensen, V.N. (2008). Genome-wide analysis identifies 16q deletion associated with survival, molecular subtypes, mRNA expression, and germline haplotypes in breast cancer patients. Genes Chromosomes Cancer / 47, 680鈥?96. CrossRef
  27. Oliveira, A.L., Rodrigues, F.F., Santos, R.E., Aoki, T., Rocha, M.N., Longui, C.A., and Melo, M.B. (2010). GSTT1, GSTM1, and GSTP1 polymorphisms and chemotherapy response in locally advanced breast cancer. Genet. Mol. Res. / 9, 1045鈥?053. CrossRef
  28. Parker, J.S., Mullins, M., Cheang, M.C., Leung, S., Voduc, D., Vickery, T., Davies, S., Fauron, C., He, X., Hu, Z., et al. (2009). Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. / 27, 1160鈥?167. CrossRef
  29. Pedraza, V., Gomez-Capilla, J.A., Escaramis, G., Gomez, C., Torn茅, P., Rivera, J.M., Gil, A., Araque, P., Olea, N., Estivill, X., et al. (2010). Gene expression signatures in breast cancer distinguish phenotype characteristics, histologic subtypes, and tumor invasiveness. Cancer / 116, 486鈥?96. CrossRef
  30. Perou, C.M., S酶rlie, T., Eisen, M.B., van de Rijn, M., Jeffrey, S.S., Rees, C.A., Pollack, J.R., Ross, D.T., Johnsen, H., Akslen, L.A., et al. (2000). Molecular portraits of human breast tumours. Nature / 406, 747鈥?52. CrossRef
  31. Pusztai, L., Cristofanilli, M., and Paik, S. (2007). New generation of molecular prognostic and predictive tests for breast cancer. Semin. Oncol. / 34, S10鈥揝16. CrossRef
  32. Qu, S., Cai, Q., Gao, Y.T., Lu, W., Cai, H., Su, Y., Wang, S.E., Shu, X.O., and Zheng, W. (2008). ERBB2 genetic polymorphism and breast cancer risk in Chinese women: a population-based casecontrol study. Breast Cancer Res. Treat. / 110, 169鈥?76. CrossRef
  33. Richardson, A.L., Wang, Z.C., De Nicolo, A., Lu, X., Brown, M., Miron, A., Liao, X., Iglehart, J.D., Livingston, D.M., and Ganesan, S. (2006). X chromosomal abnormalities in basal-like human breast cancer. Cancer Cell / 9, 121鈥?32. CrossRef
  34. Ross, J.S. (2009). Multigene classifiers, prognostic factors, and predictors of breast cancer clinical outcome. Adv. Anat. Pathol. / 16, 204鈥?15. CrossRef
  35. Ross, J.S., Hatzis, C., Symmans, W.F., Pusztai, L., and Hortob谩gyi, G.N. (2008). Commercialized multigene predictors of clinical outcome for breast cancer. Oncologist / 13, 477鈥?93. CrossRef
  36. Rouzier, R., Perou, C.M., Symmans, W.F., Ibrahim, N., Cristofanilli, M., Anderson, K., Hess, K.R., Stec, J., Ayers, M., Wagner, P., et al. (2005). Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin. Cancer Res. / 11, 5678鈥?685. CrossRef
  37. Sircoulomb, F., Bekhouche, I., Finetti, P., Ad茅la茂de, J., Ben Hamida, A., Bonansea, J., Raynaud, S., Innocenti, C., Charafe-Jauffret, E., Tarpin, C., et al., (2010). Genome profiling of ERBB2-amplified breast cancers. BMC Cancer / 10, 539. CrossRef
  38. Smid, M., Wang, Y., Zhang, Y., Sieuwerts, A.M., Yu, J., Klijn, J.G., Foekens, J.A., and Martens, J.W. (2008). Subtypes of breast cancer show preferential site of relapse. Cancer Res. / 68, 3108鈥?114. CrossRef
  39. Sontrop, H.M., Verhaegh, W.F., Reinders, M.J., and Moerland, P.D. (2011). An evaluation protocol for subtype-specific breast cancer event prediction. PLoS One / 6, e21681. CrossRef
  40. S酶rlie, T., Perou, C.M., Tibshirani, R., Aas, T., Geisler, S., Johnsen, H., Hastie, T., Eisen, M.B., van de Rijn, M., Jeffrey, S.S., et al. (2001). Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. USA / 98, 10869鈥?0874. CrossRef
  41. Taylor, B.S., Schultz, N., Hieronymus, H., Gopalan, A., Xiao, Y., Carver, B.S., Arora, V.K., Kaushik, P., Cerami, E., Reva, B., et al. (2010). Integrative genomic profiling of human prostate cancer. Cancer Cell / 18, 11鈥?2. CrossRef
  42. Turashvili, G., Bouchal, J., Baumforth, K., Wei, W., Dziechciarkova, M., Ehrmann, J., Klein, J., Fridman, E., Skarda, J., Srovnal, J., et al. (2007). Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis. BMC Cancer / 27, 55. CrossRef
  43. van鈥檛 Veer, L.J., Dai, H., van de Vijver, M.J., He, Y.D., Hart, A.A., Mao, M., Peterse, H.L., van der Kooy, K., Marton, M.J., Witteveen, A.T., et al. (2002). Gene expression profiling predicts clinical outcome of breast cancer. Nature / 415, 530鈥?36. CrossRef
  
• 作者单位：Hae-Seok Eo (1)
  Jee Yeon Heo (1)
  Yongjin Choi (1)
  Youngdon Hwang (1)
  Hyung-Seok Choi (1)
  
  1. Bio&Health Team, Future IT R&D Laboratory, LGE Advanced Research Institute, Seoul, 137-724, Korea
  
• ISSN：0219-1032

文摘

Breast cancer is a clinically heterogeneous disease characterized by distinct molecular aberrations. Understanding the heterogeneity and identifying subgroups of breast cancer are essential to improving diagnoses and predicting therapeutic responses. In this paper, we propose a classification scheme for breast cancer which integrates data on differentially expressed genes (DEGs), copy number variations (CNVs) and microRNAs (miRNAs)-regulated mRNAs. Pathway information based on the estimation of molecular pathway activity is also applied as a postprocessor to optimize the classifier. A total of 250 malignant breast tumors were analyzed by k-means clustering based on the patterns of the expression profiles of 215 intrinsic genes, and the classification performances were compared with existing breast cancer classifiers including the BluePrint and the 625-gene classifier. We show that a classification scheme which incorporates pathway information with various genetic variations achieves better performance than classifiers based on the expression levels of individual genes, and propose that the identified signature serves as a basic tool for identifying rational therapeutic opportunities for breast cancer patients.