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Cancers  2010 

Reinventing Diagnostics for Personalized Therapy in Oncology

DOI: 10.3390/cancers2021066

Keywords: lung, breast, genomics, classification, biomarkers, personalized therapy

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Human cancers are still diagnosed and classified using the light microscope. The criteria are based upon morphologic observations by pathologists and tend to be subject to interobserver variation. In preoperative biopsies of non-small cell lung cancers, the diagnostic concordance, even amongst experienced pulmonary pathologists, is no better than a coin-toss. Only 25% of cancer patients, on average, benefit from therapy as most therapies do not account for individual factors that influence response or outcome. Unsuccessful first line therapy costs Canada CAN$1.2 billion for the top 14 cancer types, and this extrapolates to $90 billion globally. The availability of accurate drug selection for personalized therapy could better allocate these precious resources to the right therapies. This wasteful situation is beginning to change with the completion of the human genome sequencing project and with the increasing availability of targeted therapies. Both factors are giving rise to attempts to correlate tumor characteristics and response to specific adjuvant and neoadjuvant therapies. Static cancer classification and grading systems need to be replaced by functional classification systems that not only account for intra- and inter- tumor heterogeneity, but which also allow for the selection of the correct chemotherapeutic compounds for the individual patient. In this review, the examples of lung and breast cancer are used to illustrate the issues to be addressed in the coming years, as well as the emerging technologies that have great promise in enabling personalized therapy.


[1]  Uluc, K.; Kujoth, G.C.; Baskaya, M.K. Operating microscopes: past, present, and future. Neurosurg. Focus?2009, 27, E4.
[2]  Titford, M. The long history of hematoxylin. Biotech. Histochem.?2005, 80, 73–78, doi:10.1080/10520290500138372.
[3]  Miyamoto, H.; Miller, J.S.; Fajardo, D.A.; Lee, T.K.; Netto, G.J.; Epstein, J.I. Non-invasive papillary urothelial neoplasms: the 2004 WHO/ISUP classification system. Pathol. Int.?2010, 60, 1–8, doi:10.1111/j.1440-1827.2009.02477.x.
[4]  Hodges, K.B.; Lopez-Beltran, A.; Davidson, D.D.; Montironi, R.; Cheng, L. Urothelial dysplasia and other flat lesions of the urinary bladder: clinicopathologic and molecular featuRes. Hum. Pathol.?2010, 41, 155–162, doi:10.1016/j.humpath.2009.07.002.
[5]  D'Angelo, E.; Prat, J. Uterine sarcomas: a review. Gynecol. Oncol.?2010, 116, 131–139, doi:10.1016/j.ygyno.2009.09.023.
[6]  Weis, E.; Rootman, J.; Joly, T.J.; Berean, K.W.; Al-Katan, H.M.; Pasternak, S.; Bonavolonta, G.; Strianese, D.; Saeed, P.; Feldman, K.A.; Vangveeravong, S.; Lapointe, J.S.; White, V.A. Epithelial lacrimal gland tumors: pathologic classification and current understanding. Arch. Ophthalmol.?2009, 127, 1016–1028, doi:10.1001/archophthalmol.2009.209.
[7]  Wallace, W.A. The challenge of classifying poorly differentiated tumors in the lung. Histopathology?2009, 54, 28–42, doi:10.1111/j.1365-2559.2008.03181.x.
[8]  Tefferi, A.; Thiele, J.; Vardiman, J.W. The 2008 World Health Organization classification system for myeloproliferative neoplasms: order out of chaos. Cancer?2009, 115, 3842–3847.
[9]  Scheithauer, B.W. Development of the WHO classification of tumors of the central nervous system: a historical perspective. Brain Pathol.?2009, 19, 551–564, doi:10.1111/j.1750-3639.2008.00192.x.
[10]  Grignon, D.J. The current classification of urothelial neoplasms. Mod. Pathol.?2009, 22 (Suppl. 2), S60–S69, doi:10.1038/modpathol.2008.235.
[11]  Verghese, E.T.; den Bakker, M.A.; Campbell, A.; Hussein, A.; Nicholson, A.G.; Rice, A.; Corrin, B.; Rassl, D.; Langman, G.; Monaghan, H.; Gosney, J.; Seet, J.; Kerr, K.; Suvarna, S.K.; Burke, M.; Bishop, P.; Pomplun, S.; Willemsen, S.; Addis, B. Interobserver variation in the classification of thymic tumors––a multicenter study using the WHO classification system. Histopathology?2008, 53, 218–223, doi:10.1111/j.1365-2559.2008.03088.x.
[12]  Trembath, D.; Miller, C.R.; Perry, A. Gray zones in brain tumor classification: evolving concepts. Adv. Anat. Pathol.?2008, 15, 287–297, doi:10.1097/PAP.0b013e3181836a03.
[13]  Schiffer, C.A. World Health Organization and international prognostic scoring system: the limitations of current classification systems in assessing prognosis and determining appropriate therapy in myelodysplastic syndromes. Semin. Hematol.?2008, 45, 3–7, doi:10.1053/j.seminhematol.2007.10.002.
[14]  Scheithauer, B.W.; Fuller, G.N.; VandenBerg, S.R. The 2007 WHO classification of tumors of the nervous system: controversies in surgical neuropathology. Brain Pathol.?2008, 18, 307–316.
[15]  Okumura, M.; Shiono, H.; Minami, M.; Inoue, M.; Utsumi, T.; Kadota, Y.; Sawa, Y. Clinical and pathological aspects of thymic epithelial tumors. Gen. Thorac. Cardiovasc. Surg.?2008, 56, 10–16.
[16]  Marchevsky, A.M.; McKenna, R.J., Jr.; Gupta, R. Thymic epithelial neoplasms: a review of current concepts using an evidence-based pathology approach. Hematol. Oncol. Clin. North Am.?2008, 22, 543–562.
[17]  Ito, Y.; Hirokawa, M.; Fukushima, M.; Inoue, H.; Yabuta, T.; Uruno, T.; Kihara, M.; Higashiyama, T.; Takamura, Y.; Miya, A.; Kobayashi, K.; Matsuzuka, F.; Miyauchi, A. Prevalence and prognostic significance of poor differentiation and tall cell variant in papillary carcinoma in Japan. World J. Surg.?2008, 32, 1535–1543, doi:10.1007/s00268-007-9406-7.
[18]  Fuller, G.N. The WHO Classification of Tumors of the Central Nervous System, 4th edition. Arch. Pathol. Lab. Med.?2008, 132, 906.
[19]  Egevad, L. Recent trends in Gleason grading of prostate cancer: I. Pattern interpretation. Anal. Quant. Cytol. Histol.?2008, 30, 190–198.
[20]  Burger, M.; Denzinger, S.; Wieland, W.F.; Stief, C.G.; Hartmann, A.; Zaak, D. Does the current World Health Organization classification predict the outcome better in patients with noninvasive bladder cancer of early or regular onset? BJU Int?2008, 102, 194–197, doi:10.1111/j.1464-410X.2008.07538.x.
[21]  Ferrone, C.R.; Tang, L.H.; Tomlinson, J.; Gonen, M.; Hochwald, S.N.; Brennan, M.F.; Klimstra, D.S.; Allen, P.J. Determining prognosis in patients with pancreatic endocrine neoplasms: can the WHO classification system be simplified? J. Clin. Oncol.?2007, 25, 5609–5615, doi:10.1200/JCO.2007.12.9809.
[22]  Riquet, M.; Foucault, C.; Berna, P.; Assouad, J.; Dujon, A.; Danel, C. Prognostic value of histology in resected lung cancer with emphasis on the relevance of the adenocarcinoma subtyping. Ann. Thorac. Surg.?2006, 81, 1988–1995, doi:10.1016/j.athoracsur.2006.01.021.
[23]  Pajtler, M.; Audy-Jurkovic, S.; Milicic-Juhas, V.; Staklenac, B.; Pauzar, B. Interobserver variability in cytologic subclassification of squamous intraepithelial lesions--the Bethesda System vs. World Health Organization classification. Coll. Antropol.?2006, 30, 137–142.
[24]  Epstein, J.I.; Allsbrook, W.C., Jr.; Amin, M.B.; Egevad, L.L. Update on the Gleason grading system for prostate cancer: results of an international consensus conference of urologic pathologists. Adv. Anat. Pathol.?2006, 13, 57–59, doi:10.1097/01.pap.0000202017.78917.18.
[25]  Willis, J.; Smith, C.; Ironside, J.W.; Erridge, S.; Whittle, I.R.; Everington, D. The accuracy of meningioma grading: a 10-year retrospective audit. Neuropathol. Appl. Neurobiol.?2005, 31, 141–149, doi:10.1111/j.1365-2990.2004.00621.x.
[26]  Oyama, T.; Allsbrook, W.C., Jr.; Kurokawa, K.; Matsuda, H.; Segawa, A.; Sano, T.; Suzuki, K.; Epstein, J.I. A comparison of interobserver reproducibility of Gleason grading of prostatic carcinoma in Japan and the United States. Arch. Pathol. Lab. Med.?2005, 129, 1004–1010.
[27]  Wolfson, W.L. Interobserver variability among expert uropathologists. Am. J. Surg.Pathol.?2009, 33, 801–802, doi:10.1097/PAS.0b013e31819b3718.
[28]  Izadi-Mood, N.; Yarmohammadi, M.; Ahmadi, S.A.; Irvanloo, G.; Haeri, H.; Meysamie, A.P.; Khaniki, M. Reproducibility determination of WHO classification of endometrial hyperplasia/well differentiated adenocarcinoma and comparison with computerized morphometric data in curettage specimens in Iran. Diagn. Pathol.?2009, 4, 10, doi:10.1186/1746-1596-4-10.
[29]  Eefting, D.; Schrage, Y.M.; Geirnaerdt, M.J.; Le Cessie, S.; Taminiau, A.H.; Bovee, J.V.; Hogendoorn, P.C. Assessment of interobserver variability and histologic parameters to improve reliability in classification and grading of central cartilaginous tumors. Am. J. Surg. Pathol.?2009, 33, 50–57, doi:10.1097/PAS.0b013e31817eec2b.
[30]  Darvishian, F.; Singh, B.; Simsir, A.; Ye, W.; Cangiarella, J.F. Atypia on breast core needle biopsies: reproducibility and significance. Ann. Clin. Lab. Sci.?2009, 39, 270–276.
[31]  Adams, A.L.; Chhieng, D.C.; Bell, W.C.; Winokur, T.; Hameed, O. Histologic grading of invasive lobular carcinoma: does use of a 2-tiered nuclear grading system improve interobserver variability? Ann. Diagn. Pathol.?2009, 13, 223–225, doi:10.1016/j.anndiagpath.2009.03.004.
[32]  Mhawech-Fauceglia, P.; Herrmann, F.; Bshara, W.; Zhang, S.; Penetrante, R.; Lele, S.; Odunsi, K.; Rodabaugh, K. Intraobserver and interobserver variability in distinguishing between endocervical and endometrial adenocarcinoma on problematic cases of cervical curettings. Int. J. Gynecol. Pathol.?2008, 27, 431–436, doi:10.1097/PGP.0b013e3181601792.
[33]  Kummerlin, I.; ten Kate, F.; Smedts, F.; Horn, T.; Algaba, F.; Trias, I.; de la Rosette, J.; Laguna, M.P. Core biopsies of renal tumors: a study on diagnostic accuracy, interobserver, and intraobserver variability. Eur. Urol.?2008, 53, 1219–1225, doi:10.1016/j.eururo.2007.11.054.
[34]  Gilles, F.H.; Tavare, C.J.; Becker, L.E.; Burger, P.C.; Yates, A.J.; Pollack, I.F.; Finlay, J.L. Pathologist interobserver variability of histologic featuRes. in childhood brain tumors: Results from the CCG-945 study. Pediatr. Dev. Pathol.?2008, 11, 108–117, doi:10.2350/07-06-0303.1.
[35]  Evans, A.J.; Henry, P.C.; Van der Kwast, T.H.; Tkachuk, D.C.; Watson, K.; Lockwood, G.A.; Fleshner, N.E.; Cheung, C.; Belanger, E.C.; Amin, M.B.; Boccon-Gibod, L.; Bostwick, D.G.; Egevad, L.; Epstein, J.I.; Grignon, D.J.; Jones, E.C.; Montironi, R.; Moussa, M.; Sweet, J.M.; Trpkov, K.; Wheeler, T.M.; Srigley, J.R. Interobserver variability between expert urologic pathologists for extraprostatic extension and surgical margin status in radical prostatectomy specimens. Am. J. Surg. Pathol.?2008, 32, 1503–1512, doi:10.1097/PAS.0b013e31817fb3a0.
[36]  Elsheikh, T.M.; Asa, S.L.; Chan, J.K.; DeLellis, R.A.; Heffess, C.S.; LiVolsi, V.A.; Wenig, B.M. Interobserver and intraobserver variation among experts in the diagnosis of thyroid follicular lesions with borderline nuclear featuRes. of papillary carcinoma. Am. J. Clin. Pathol.?2008, 130, 736–744, doi:10.1309/AJCPKP2QUVN4RCCP.
[37]  Veloso, S.G.; Lima, M.F.; Salles, P.G.; Berenstein, C.K.; Scalon, J.D.; Bambirra, E.A. Interobserver agreement of Gleason score and modified Gleason score in needle biopsy and in surgical specimen of prostate cancer. Int. Braz. J. Urol.?2007, 33, 639–646; discussion 647–651, doi:10.1590/S1677-55382007000500005.
[38]  Gonul, I.I.; Poyraz, A.; Unsal, C.; Acar, C.; Alkibay, T. Comparison of 1998 WHO/ISUP and 1973 WHO classifications for interobserver variability in grading of papillary urothelial neoplasms of the bladder. Pathological evaluation of 258 cases. Urol. Int.?2007, 78, 338–344, doi:10.1159/000100839.
[39]  Engers, R. Reproducibility and reliability of tumor grading in urological neoplasms. World J. Urol.?2007, 25, 595–605, doi:10.1007/s00345-007-0209-0.
[40]  Vainer, B. Interobserver variability in gastrointestinal pathology. Scand. J. Gastroenterol.?2006, 41, 765–766, doi:10.1080/00365520600670349.
[41]  Raab, S.S.; Meier, F.A.; Zarbo, R.J.; Jensen, D.C.; Geisinger, K.R.; Booth, C.N.; Krishnamurti, U.; Stone, C.H.; Janosky, J.E.; Grzybicki, D.M. The "Big Dog" effect: variability assessing the causes of error in diagnoses of patients with lung cancer. J. Clin. Oncol.?2006, 24, 2808–2814, doi:10.1200/JCO.2005.04.3661.
[42]  Glaessgen, A.; Hamberg, H.; Pihl, C.G.; Sundelin, B.; Nilsson, B.; Egevad, L. Interobserver reproducibility of percent Gleason grade 4/5 in prostate biopsies. J. Urol.?2004, 171, 664–667, doi:10.1097/01.ju.0000108198.98598.00.
[43]  Costantini, M.; Sciallero, S.; Giannini, A.; Gatteschi, B.; Rinaldi, P.; Lanzanova, G.; Bonelli, L.; Casetti, T.; Bertinelli, E.; Giuliani, O.; Castiglione, G.; Mantellini, P.; Naldoni, C.; Bruzzi, P. Interobserver agreement in the histologic diagnosis of colorectal polyps. the experience of the multicenter adenoma colorectal study (SMAC). J. Clin. Epidemiol.?2003, 56, 209–214, doi:10.1016/S0895-4356(02)00587-5.
[44]  Nicholson, A.G.; Perry, L.J.; Cury, P.M.; Jackson, P.; McCormick, C.M.; Corrin, B.; Wells, A.U. Reproducibility of the WHO/IASLC grading system for pre-invasive squamous lesions of the bronchus: a study of inter-observer and intra-observer variation. Histopathology?2001, 38, 202–208, doi:10.1046/j.1365-2559.2001.01078.x.
[45]  Granados, R.; Aramburu, J.A.; Murillo, N.; Camarmo, E.; de la Cal, M.A.; Fernandez-Segoviano, P. Fine-needle aspiration biopsy of liver masses: diagnostic value and reproducibility of cytological criteria. Diagn. Cytopathol.?2001, 25, 365–375, doi:10.1002/dc.10025.
[46]  Jaffe, E.S.; Harris, N.L.; Stein, H.; Isaacson, P.G. Classification of lymphoid neoplasms: the microscope as a tool for disease discovery. Blood?2008, 112, 4384–4399, doi:10.1182/blood-2008-07-077982.
[47]  He, Y.D.; Friend, S.H. Microarrays--the 21st century divining rod? Nat. Med.?2001, 7, 658–659, doi:10.1038/89022.
[48]  Fujita, H.; So, Y.; Asada, Y.; Tatibana, K.; Hayakawa, M.; Matuo, T.; Minami, T.; Imamura, S.; Fujisawa, S.; Ito, K. Studies on lymphoma, reticulosis and its related diseases, especially about classification, histology and cytology with electron microscopy. Hifuka Kiyo?1962, 57, 3–61.
[49]  Kohler, G.; Milstein, C. Continuous cultuRes. of fused cells secreting antibody of predefined specificity. Nature?1975, 256, 495–497, doi:10.1038/256495a0.
[50]  Mullis, K.; Faloona, F.; Scharf, S.; Saiki, R.; Horn, G.; Erlich, H. Specific enzymatic amplification of DNA in vitro: the polymerase chain reaction. Cold Spring Harb. Symp. Quant. Biol.?1986, 51, 263–273, doi:10.1101/SQB.1986.051.01.032.
[51]  Herzenberg, L.A.; Parks, D.; Sahaf, B.; Perez, O.; Roederer, M. The history and future of the fluorescence activated cell sorter and flow cytometry: a view from Stanford. Clin. Chem.?2002, 48, 1819–1827.
[52]  Pennisi, E. Human genome: Finally, the book of life and instructions for navigating it. Science?2000, 288, 2304–2307, doi:10.1126/science.288.5475.2304.
[53]  Canadian Institute for Health Information. Drug Expenditure in Canada, 1985 to 2008; Canadian Institute for Health Information: Ottawa, Ontario, Canada, 2009.
[54]  Spear, B.B.; Heath-Chiozzi, M.; Huff, J. Clinical application of pharmacogenetics. Trends Mol. Med.?2001, 7, 201–204, doi:10.1016/S1471-4914(01)01986-4.
[55]  Parkin, D.M.; Bray, F.; Ferlay, J.; Pisani, P. Global Cancer Statistics, 2002. CA Cancer J. Clin.?2005, 55, 74–108, doi:10.3322/canjclin.55.2.74.
[56]  World Health Organization. Cancer. Fact sheet No. 297; WHO: Geneva, Swizerland, 2009.
[57]  US National Cancer Insitute. Surveillance, Epidemiology and End Results (SEER) Program; NCI: Rockville, MD, USA, 2009. Available online: http://seer.cancer.gov/ (accessed online on 24 May 2010).
[58]  Rossi, G.; Pelosi, G.; Graziano, P.; Barbareschi, M.; Papotti, M. A reevaluation of the clinical significance of histological subtyping of non--small-cell lung carcinoma: diagnostic algorithms in the era of personalized treatments. Int. J. Surg. Pathol.?2009, 17, 206–218, doi:10.1177/1066896909336178.
[59]  Travis, W.D.; Brambilla, E.; Muller-Hermelink, H.K.; Harris, C.C. Pathology and Genetics of Tumors of the Lung, Pleura, Thymus and Heart, 4th ed. ed.; IARC Press: Lyon, France, 2004.
[60]  Thomas, J.S.; Lamb, D.; Ashcroft, T.; Corrin, B.; Edwards, C.W.; Gibbs, A.R.; Kenyon, W.E.; Stephens, R.J.; Whimster, W.F. How reliable is the diagnosis of lung cancer using small biopsy specimens? Report of a UKCCCR Lung Cancer Working Party. Thorax?1993, 48, 1135–1139, doi:10.1136/thx.48.11.1135.
[61]  Edwards, S.L.; Roberts, C.; McKean, M.E.; Cockburn, J.S.; Jeffrey, R.R.; Kerr, K.M. Preoperative histological classification of primary lung cancer: accuracy of diagnosis and use of the non-small cell category. J. Clin. Pathol.?2000, 53, 537–540, doi:10.1136/jcp.53.7.537.
[62]  Trani, L.; Myerson, J.; Ashley, S.; Young, K.; Sheri, A.; Hubner, R.; Puglisi, M.; Popat, S.; O'Brien, M.E. Histology classification is not a predictor of clinical outcomes in advanced non-small cell lung cancer (NSCLC) treated with vinorelbine or gemcitabine combinations. Lung Cancer?2010, doi:10.1016/j.lungcan.2010.02.003.
[63]  Hirsch, F.R.; Spreafico, A.; Novello, S.; Wood, M.D.; Simms, L.; Papotti, M. The prognostic and predictive role of histology in advanced non-small cell lung cancer: a literature review. J. Thorac. Oncol.?2008, 3, 1468–1481, doi:10.1097/JTO.0b013e318189f551.
[64]  Pelosi, G.; Fraggetta, F.; Pasini, F.; Maisonneuve, P.; Sonzogni, A.; Iannucci, A.; Terzi, A.; Bresaola, E.; Valduga, F.; Lupo, C.; Viale, G. Immunoreactivity for thyroid transcription factor-1 in stage I non-small cell carcinomas of the lung. Am. J. Surg. Pathol.?2001, 25, 363–372, doi:10.1097/00000478-200103000-00011.
[65]  Tan, D.; Li, Q.; Deeb, G.; Ramnath, N.; Slocum, H.K.; Brooks, J.; Cheney, R.; Wiseman, S.; Anderson, T.; Loewen, G. Thyroid transcription factor-1 expression prevalence and its clinical implications in non-small cell lung cancer: a high-throughput tissue microarray and immunohistochemistry study. Hum. Pathol.?2003, 34, 597–604, doi:10.1016/S0046-8177(03)00180-1.
[66]  Au, N.H.C.M.; Gown, A.M.M.; Cheang, M.M.; Huntsman, D.M.; Yorida, E.B.; Elliott, W.M.P.; Flint, J.M.; English, J.M.; Gilks, C.B.M.; Grimes, H.L.P. p63 Expression in Lung Carcinoma: A Tissue Microarray Study of 408 Cases. Appl. Immunohistochem. Mol. Morphol.?2004, 12, 240–247, doi:10.1097/00129039-200409000-00010.
[67]  Monica, V.; Ceppi, P.; Righi, L.; Tavaglione, V.; Volante, M.; Pelosi, G.; Scagliotti, G.V.; Papotti, M. Desmocollin-3: a new marker of squamous differentiation in undifferentiated large-cell carcinoma of the lung. Mod. Pathol.?2009, 22, 709–717, doi:10.1038/modpathol.2009.30.
[68]  Wigle, D.A.; Jurisica, I.; Radulovich, N.; Pintilie, M.; Rossant, J.; Liu, N.; Lu, C.; Woodgett, J.; Seiden, I.; Johnston, M.; Keshavjee, S.; Darling, G.; Winton, T.; Breitkreutz, B.J.; Jorgenson, P.; Tyers, M.; Shepherd, F.A.; Tsao, M.S. Molecular profiling of non-small cell lung cancer and correlation with disease-free survival. Cancer Res.?2002, 62, 3005–3008.
[69]  Blackhall, F.H.; Wigle, D.A.; Jurisica, I.; Pintilie, M.; Liu, N.; Darling, G.; Johnston, M.R.; Keshavjee, S.; Waddell, T.; Winton, T.; Shepherd, F.A.; Tsao, M.S. Validating the prognostic value of marker genes derived from a non-small cell lung cancer microarray study. Lung Cancer?2004, 46, 197–204, doi:10.1016/j.lungcan.2004.04.002.
[70]  Choi, N.; Son, D.S.; Lee, J.; Song, I.S.; Kim, K.A.; Park, S.H.; Lim, Y.S.; Seo, G.J.; Han, J.; Kim, H.; Lee, H.W.; Kang, J.J.; Seo, J.S.; Kim, J.H.; Kim, J. The signature from messenger RNA expression profiling can predict lymph node metastasis with high accuracy for non-small cell lung cancer. J. Thorac. Oncol.?2006, 1, 622–628, doi:10.1097/01243894-200609000-00005.
[71]  Potti, A.; Mukherjee, S.; Petersen, R.; Dressman, H.K.; Bild, A.; Koontz, J.; Kratzke, R.; Watson, M.A.; Kelley, M.; Ginsburg, G.S.; West, M.; Harpole, D.H., Jr.; Nevins, J.R. A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. N. Engl. J. Med.?2006, 355, 570–580, doi:10.1056/NEJMoa060467.
[72]  Corson, T.W.; Zhu, C.Q.; Lau, S.K.; Shepherd, F.A.; Tsao, M.S.; Gallie, B.L. KIF14 messenger RNA expression is independently prognostic for outcome in lung cancer. Clin. Cancer Res.?2007, 13, 3229–3234, doi:10.1158/1078-0432.CCR-07-0393.
[73]  Guo, N.L.; Wan, Y.W.; Tosun, K.; Lin, H.; Msiska, Z.; Flynn, D.C.; Remick, S.C.; Vallyathan, V.; Dowlati, A.; Shi, X.; Castranova, V.; Beer, D.G.; Qian, Y. Confirmation of gene expression-based prediction of survival in non-small cell lung cancer. Clin. Cancer Res.?2008, 14, 8213–8220, doi:10.1158/1078-0432.CCR-08-0095.
[74]  Lonergan, K.M.; Chari, R.; Coe, B.P.; Wilson, I.M.; Tsao, M.S.; Ng, R.T.; Macaulay, C.; Lam, S.; Lam, W.L. Transcriptome profiles of carcinoma-in-situ and invasive non-small cell lung cancer as revealed by SAGE. PLoS One?2010, 5, e9162, doi:10.1371/journal.pone.0009162.
[75]  Zhu, C.Q.; Blackhall, F.H.; Pintilie, M.; Iyengar, P.; Liu, N.; Ho, J.; Chomiak, T.; Lau, D.; Winton, T.; Shepherd, F.A.; Tsao, M.S. Skp2 gene copy number aberrations are common in non-small cell lung carcinoma, and its overexpression in tumors with ras mutation is a poor prognostic marker. Clin. Cancer Res.?2004, 10, 1984–1991, doi:10.1158/1078-0432.CCR-03-0470.
[76]  Zhu, C.Q.; Cutz, J.C.; Liu, N.; Lau, D.; Shepherd, F.A.; Squire, J.A.; Tsao, M.S. Amplification of telomerase (hTERT) gene is a poor prognostic marker in non-small-cell lung cancer. Br. J. Cancer?2006, 94, 1452–1459, doi:10.1038/sj.bjc.6603110.
[77]  Go, H.; Jeon, Y.K.; Park, H.J.; Sung, S.W.; Seo, J.W.; Chung, D.H. High MET gene copy number leads to shorter survival in patients with non-small cell lung cancer. J. Thorac. Oncol.?2010, 5, 305–313, doi:10.1097/JTO.0b013e3181ce3d1d.
[78]  Tsao, M.S.; Sakurada, A.; Cutz, J.C.; Zhu, C.Q.; Kamel-Reid, S.; Squire, J.; Lorimer, I.; Zhang, T.; Liu, N.; Daneshmand, M.; Marrano, P.; da Cunha Santos, G.; Lagarde, A.; Richardson, F.; Seymour, L.; Whitehead, M.; Ding, K.; Pater, J.; Shepherd, F.A. Erlotinib in lung cancer - molecular and clinical predictors of outcome. N. Engl. J. Med.?2005, 353, 133–144, doi:10.1056/NEJMoa050736.
[79]  Zhu, C.; da Cunha Santos, G.; Ding, K.; Sakurada, A.; Cutz, J.; Liu, N.; Zhang, T.; Marrano, P.; Whitehead, M.; Squire, J.; Kamel-Reid, S.; Seymour, L.; Shepherd, F.; Tsao, M. Role of KRAS and EGFR as biomarkers of response to erlotinib in National Cancer Institute of Canada Clinical Trials Group Study BR.21. J. Clin. Oncol.?2008, 26, 4268–4275, doi:10.1200/JCO.2007.14.8924.
[80]  Dahabreh, I.; Linardou, H.; Siannis, F.; Kosmidis, P.; Bafaloukos, D.; Murray, S. Somatic EGFR mutation and gene copy gain as predictive biomarkers for response to tyrosine kinase inhibitors in non-small cell lung cancer. Clin. Cancer Res.?2010, 16, 291–303, doi:10.1158/1078-0432.CCR-09-1660.
[81]  Lynch, T.; Bell, D.; Sordella, R.; Gurubhagavatula, S.; Okimoto, R.; Brannigan, B.; Harris, P.; Haserlat, S.; Supko, J.; Haluska, F.; Louis, D.; Christiani, D.; Settleman, J.; Haber, D. 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, doi:10.1056/NEJMoa040938.
[82]  Paez, J.; J?nne, P.; Lee, J.; Tracy, S.; Greulich, H.; Gabriel, S.; Herman, P.; Kaye, F.; Lindeman, N.; Boggon, T.; Naoki, K.; Sasaki, H.; Fujii, Y.; Eck, M.; Sellers, W.; Johnson, B.; Meyerson, M. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science?2004, 304, 1497–1500, doi:10.1126/science.1099314.
[83]  Price, D.; Figg, W. Mutations in the EGFR: the importance of genotyping. Cancer Biol. Ther.?2004, 3, 434–435, doi:10.4161/cbt.3.5.984.
[84]  Bell, D.; Lynch, T.; Haserlat, S.; Harris, P.; Okimoto, R.; Brannigan, B.; Sgroi, D.; Muir, B.; Riemenschneider, M.; Iacona, R.; Krebs, A.; Johnson, D.; Giaccone, G.; Herbst, R.; Manegold, C.; Fukuoka, M.; Kris, M.; Baselga, J.; Ochs, J.; Haber, D. Epidermal growth factor receptor mutations and gene amplification in non-small-cell lung cancer: molecular analysis of the IDEAL/INTACT gefitinib trials. J. Clin. Oncol.?2005, 23, 8081–8092, doi:10.1200/JCO.2005.02.7078.
[85]  Kelly, K.; Chansky, K.; Gaspar, L.; Albain, K.; Jett, J.; Ung, Y.; Lau, D.; Crowley, J.; Gandara, D. Phase III trial of maintenance gefitinib or placebo after concurrent chemoradiotherapy and docetaxel consolidation in inoperable stage III non-small-cell lung cancer: SWOG S0023. J. Clin. Oncol.?2008, 26, 2450–2456, doi:10.1200/JCO.2007.14.4824.
[86]  Valencia-Sanchez, M.A.; Liu, J.; Hannon, G.J.; Parker, R. Control of translation and mRNA degradation by miRNAs and siRNAs. Genes Dev.?2006, 20, 515–524, doi:10.1101/gad.1399806.
[87]  Bishop, J.A.; Benjamin, H.; Cholakh, H.; Chajut, A.; Clark, D.P.; Westra, W.H. Accurate classification of non-small cell lung carcinoma using a novel microRNA-based approach. Clin. Cancer Res.?2010, 16, 610–619, doi:10.1158/1078-0432.CCR-09-2638.
[88]  Hu, Z.; Chen, X.; Zhao, Y.; Tian, T.; Jin, G.; Shu, Y.; Chen, Y.; Xu, L.; Zen, K.; Zhang, C.; Shen, H. Serum MicroRNA signatures identified in a genome-wide serum microrna expression profiling predict survival of non-small-cell lung cancer. J. Clin. Oncol.?2010, 28, 1721–1726, doi:10.1200/JCO.2009.24.9342.
[89]  Yu, L.; Todd, N.W.; Xing, L.; Xie, Y.; Zhang, H.; Liu, Z.; Fang, H.; Zhang, J.; Katz, R.L.; Jiang, F. Early detection of lung adenocarcinoma in sputum by a panel of microRNA markers. Int. J. Cancer?2010, doi:10.1002/ijc.25289.
[90]  Perou, C.M.; Sorlie, 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.; Fluge, O.; Pergamenschikov, A.; Williams, C.; Zhu, S.X.; Lonning, P.E.; Borresen-Dale, A.L.; Brown, P.O.; Botstein, D. Molecular portraits of human breast tumors. Nature?2000, 406, 747–752, doi:10.1038/35021093.
[91]  Lonning, P.E.; Sorlie, T.; Perou, C.M.; Brown, P.O.; Botstein, D.; Borresen-Dale, A.L. Microarrays in primary breast cancer--lessons from chemotherapy studies. Endocr. Relat. Cancer?2001, 8, 259–263, doi:10.1677/erc.0.0080259.
[92]  Sorlie, T.; Perou, C.M.; Tibshirani, R.; Aas, T.; Geisler, S.; Johnsen, H.; Hastie, T.; Eisen, M.B.; van de Rijn, M.; Jeffrey, S.S.; Thorsen, T.; Quist, H.; Matese, J.C.; Brown, P.O.; Botstein, D.; Eystein Lonning, P.; Borresen-Dale, A.L. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. USA?2001, 98, 10869–10874, doi:10.1073/pnas.191367098.
[93]  Sorlie, T.; Tibshirani, R.; Parker, J.; Hastie, T.; Marron, J.S.; Nobel, A.; Deng, S.; Johnsen, H.; Pesich, R.; Geisler, S.; Demeter, J.; Perou, C.M.; Lonning, P.E.; Brown, P.O.; Borresen-Dale, A.L.; Botstein, D. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl. Acad. Sci. USA?2003, 100, 8418–8423, doi:10.1073/pnas.0932692100.
[94]  Rouzier, R.; Perou, C.M.; Symmans, W.F.; Ibrahim, N.; Cristofanilli, M.; Anderson, K.; Hess, K.R.; Stec, J.; Ayers, M.; Wagner, P.; Morandi, P.; Fan, C.; Rabiul, I.; Ross, J.S.; Hortobagyi, G.N.; Pusztai, L. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin. Cancer Res.?2005, 11, 5678–5685, doi:10.1158/1078-0432.CCR-04-2421.
[95]  Sotiriou, C.; Powles, T.J.; Dowsett, M.; Jazaeri, A.A.; Feldman, A.L.; Assersohn, L.; Gadisetti, C.; Libutti, S.K.; Liu, E.T. Gene expression profiles derived from fine needle aspiration correlate with response to systemic chemotherapy in breast cancer. Breast Cancer Res.?2002, 4, R3, doi:10.1186/bcr433.
[96]  van de Vijver, M.; He, Y.; van't Veer, L.; Dai, H.; Hart, A.; Voskuil, D.; Schreiber, G.; Peterse, J.; Roberts, C.; Marton, M.; Parrish, M.; Atsma, D.; Witteveen, A.; Glas, A.; Delahaye, L.; van der Velde, T.; Bartelink, H.; Rodenhuis, S.; Rutgers, E.; Friend, S.; Bernards, R. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med.?2002, 347, 1999–2009, doi:10.1056/NEJMoa021967.
[97]  Ma, X.J.; Salunga, R.; Tuggle, J.T.; Gaudet, J.; Enright, E.; McQuary, P.; Payette, T.; Pistone, M.; Stecker, K.; Zhang, B.M.; Zhou, Y.X.; Varnholt, H.; Smith, B.; Gadd, M.; Chatfield, E.; Kessler, J.; Baer, T.M.; Erlander, M.G.; Sgroi, D.C. Gene expression profiles of human breast cancer progression. Proc. Natl. Acad. Sci. USA?2003, 100, 5974–5979, doi:10.1073/pnas.0931261100.
[98]  Weigelt, B.; Glas, A.; Wessels, L.; Witteveen, A.; Peterse, J.; van't Veer, L. Gene expression profiles of primary breast tumors maintained in distant metastases. Proc. Natl. Acad. Sci. USA?2003, 100, 15901–15905.
[99]  Fischer, D.C.; Noack, K.; Runnebaum, I.B.; Watermann, D.O.; Kieback, D.G.; Stamm, S.; Stickeler, E. Expression of splicing factors in human ovarian cancer. Oncol. Rep.?2004, 11, 1085–1090.
[100]  Weigelt, B.; van't Veer, L. Hard-wired genotype in metastatic breast cancer. Cell Cycle?2004, 3, 756–757, doi:10.4161/cc.3.6.926.
[101]  Nakatsu, N.; Yoshida, Y.; Yamazaki, K.; Nakamura, T.; Dan, S.; Fukui, Y.; Yamori, T. Chemosensitivity profile of cancer cell lines and identification of genes determining chemosensitivity by an integrated bioinformatical approach using cDNA arrays. Mol. Cancer Ther.?2005, 4, 399–412.
[102]  Weigelt, B.; Hu, Z.; He, X.; Livasy, C.; Carey, L.; Ewend, M.; Glas, A.; Perou, C.; Van't Veer, L. Molecular portraits and 70-gene prognosis signature are preserved throughout the metastatic process of breast cancer. Cancer Res.?2005, 65, 9155–9158, doi:10.1158/0008-5472.CAN-05-2553.
[103]  Ioannidis, J.P.; Allison, D.B.; Ball, C.A.; Coulibaly, I.; Cui, X.; Culhane, A.C.; Falchi, M.; Furlanello, C.; Game, L.; Jurman, G.; Mangion, J.; Mehta, T.; Nitzberg, M.; Page, G.P.; Petretto, E.; van Noort, V. Repeatability of published microarray gene expression analyses. Nat. Genet.?2009, 41, 149–155, doi:10.1038/ng.295.
[104]  Chen, X.; Wang, L. Integrating biological knowledge with gene expression profiles for survival prediction of cancer. J. Comput. Biol.?2009, 16, 265–278, doi:10.1089/cmb.2008.12TT.
[105]  Smith, D.D.; Saetrom, P.; Snove, O., Jr.; Lundberg, C.; Rivas, G.E.; Glackin, C.; Larson, G.P. Meta-analysis of breast cancer microarray studies in conjunction with conserved cis-elements suggest patterns for coordinate regulation. BMC Bioinformatics?2008, 9, 63, doi:10.1186/1471-2105-9-63.
[106]  Lu, X.; Wang, Z.C.; Iglehart, J.D.; Zhang, X.; Richardson, A.L. Predicting featuRes. of breast cancer with gene expression patterns. Breast Cancer Res. Treat.?2008, 108, 191–201, doi:10.1007/s10549-007-9596-6.
[107]  Naderi, A.; Teschendorff, A.E.; Barbosa-Morais, N.L.; Pinder, S.E.; Green, A.R.; Powe, D.G.; Robertson, J.F.; Aparicio, S.; Ellis, I.O.; Brenton, J.D.; Caldas, C. A gene-expression signature to predict survival in breast cancer across independent data sets. Oncogene?2007, 26, 1507–1516, doi:10.1038/sj.onc.1209920.
[108]  Frkovic-Grazio, S.; Bracko, M. Long term prognostic value of NottinghAm. histological grade and its components in early (pT1N0M0) breast carcinoma. J. Clin. Pathol.?2002, 55, 88–92, doi:10.1136/jcp.55.2.88.
[109]  Tang, P.; Skinner, K.A.; Hicks, D.G. Molecular classification of breast carcinomas by immunohistochemical analysis: are we ready? Diagn. Mol. Pathol.?2009, 18, 125–132.
[110]  Nielsen, T.O.; Hsu, F.D.; Jensen, K.; Cheang, M.; Karaca, G.; Hu, Z.; Hernandez-Boussard, T.; Livasy, C.; Cowan, D.; Dressler, L.; Akslen, L.A.; Ragaz, J.; Gown, A.M.; Gilks, C.B.; van de Rijn, M.; Perou, C.M. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin. Cancer Res.?2004, 10, 5367–5374, doi:10.1158/1078-0432.CCR-04-0220.
[111]  Moyano, J.V.; Evans, J.R.; Chen, F.; Lu, M.; Werner, M.E.; Yehiely, F.; Diaz, L.K.; Turbin, D.; Karaca, G.; Wiley, E.; Nielsen, T.O.; Perou, C.M.; Cryns, V.L. AlphaB-crystallin is a novel oncoprotein that predicts poor clinical outcome in breast cancer. J. Clin. Invest?2006, 116, 261–270.
[112]  Cheang, M.C.; Chia, S.K.; Voduc, D.; Gao, D.; Leung, S.; Snider, J.; Watson, M.; Davies, S.; Bernard, P.S.; Parker, J.S.; Perou, C.M.; Ellis, M.J.; Nielsen, T.O. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J. Natl. Cancer Inst.?2009, 101, 736–750, doi:10.1093/jnci/djp082.
[113]  Weigelt, B.; Baehner, F.L.; Reis-Filho, J.S. The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade. J. Pathol.?2010, 220, 263–280.
[114]  Dressman, H.K.; Hans, C.; Bild, A.; Olson, J.A.; Rosen, E.; Marcom, P.K.; Liotcheva, V.B.; Jones, E.L.; Vujaskovic, Z.; Marks, J.; Dewhirst, M.W.; West, M.; Nevins, J.R.; Blackwell, K. Gene expression profiles of multiple breast cancer phenotypes and response to neoadjuvant chemotherapy. Clin. Cancer Res.?2006, 12, 819–826, doi:10.1158/1078-0432.CCR-05-1447.
[115]  Sorlie, T.; Perou, C.M.; Fan, C.; Geisler, S.; Aas, T.; Nobel, A.; Anker, G.; Akslen, L.A.; Botstein, D.; Borresen-Dale, A.L.; Lonning, P.E. Gene expression profiles do not consistently predict the clinical treatment response in locally advanced breast cancer. Mol. Cancer Ther.?2006, 5, 2914–2918, doi:10.1158/1535-7163.MCT-06-0126.
[116]  Lee, J.K.; Coutant, C.; Kim, Y.C.; Qi, Y.; Theodorescu, D.; Symmans, W.F.; Baggerly, K.; Rouzier, R.; Pusztai, L. Prospective comparison of clinical and genomic multivariate predictors of response to neoadjuvant chemotherapy in breast cancer. Clin. Cancer Res.?2010, 16, 711–718, doi:10.1158/1078-0432.CCR-09-2247.
[117]  Bauer, J.A.; Chakravarthy, A.B.; Rosenbluth, J.M.; Mi, D.; Seeley, E.H.; De Matos Granja-Ingram, N.; Olivares, M.G.; Kelley, M.C.; Mayer, I.A.; Meszoely, I.M.; Means-Powell, J.A.; Johnson, K.N.; Tsai, C.J.; Ayers, G.D.; Sanders, M.E.; Schneider, R.J.; Formenti, S.C.; Caprioli, R.M.; Pietenpol, J.A. Identification of markers of taxane sensitivity using proteomic and genomic analyses of breast tumors from patients receiving neoadjuvant paclitaxel and radiation. Clin. Cancer Res.?2010, 16, 681–690, doi:10.1158/1078-0432.CCR-09-1091.
[118]  Osako, T.; Horii, R.; Matsuura, M.; Domoto, K.; Ide, Y.; Miyagi, Y.; Takahashi, S.; Ito, Y.; Iwase, T.; Akiyama, F. High-grade breast cancers include both highly sensitive and highly resistant subsets to cytotoxic chemotherapy. J. Cancer Res. Clin. Oncol.?2010, doi:10.1007/s00432-010-0798-7.
[119]  Fu, G.; Song, X.C.; Yang, X.; Peng, T.; Wang, Y.; Zhou, G.W. Protein Subcellular Localization Profiling of Breast Cancer Cells by Dissociable Antibody MicroArray (DAMA) Staining. Proteomics?2010, 10, 1536–1544, doi:10.1002/pmic.200900585.
[120]  Isakoff, S.J. Triple-Negative Breast Cancer: Role of Specific Chemotherapy Agents. Cancer J.?2010, 16, 53–61, doi:10.1097/PPO.0b013e3181d24ff7.
[121]  Seal, M.D.; Chia, S.K. What Is the Difference Between Triple-Negative and Basal Breast Cancers? Cancer J.?2010, 16, 12–16, doi:10.1097/PPO.0b013e3181cf04be.
[122]  Venkitaraman, R. Triple-negative/basal-like breast cancer: clinical, pathologic and molecular featuRes. Expert Rev. Anticancer Ther.?2010, 10, 199–207, doi:10.1586/era.09.189.
[123]  Perez, E.A.; Moreno-Aspitia, A.; Aubrey Thompson, E.; Andorfer, C.A. Adjuvant therapy of triple negative breast cancer. Breast Cancer Res. Treat.?2010, 120, 285–291, doi:10.1007/s10549-010-0736-z.
[124]  Schulz, D.M.; Bollner, C.; Thomas, G.; Atkinson, M.; Esposito, I.; Hofler, H.; Aubele, M. Identification of differentially expressed proteins in triple-negative breast carcinomas using DIGE and mass spectrometry. J. Proteome Res.?2009, 8, 3430–3438, doi:10.1021/pr900071h.
[125]  Agarwal, R.; Gonzalez-Angulo, A.M.; Myhre, S.; Carey, M.; Lee, J.S.; Overgaard, J.; Alsner, J.; Stemke-Hale, K.; Lluch, A.; Neve, R.M.; Kuo, W.L.; Sorlie, T.; Sahin, A.; Valero, V.; Keyomarsi, K.; Gray, J.W.; Borresen-Dale, A.L.; Mills, G.B.; Hennessy, B.T. Integrative analysis of cyClin. protein levels identifies cyClin. b1 as a classifier and predictor of outcomes in breast cancer. Clin. Cancer Res.?2009, 15, 3654–3662, doi:10.1158/1078-0432.CCR-08-3293.
[126]  Rha, S.Y.; Jeung, H.C.; Seo, M.Y.; Kim, S.C.; Yang, W.I.; Moon, Y.W.; Chung, H.C. Prediction of high-risk patients by genome-wide copy number alterations from remaining cancer after neoadjuvant chemotherapy and surgery. Int. J. Oncol.?2009, 34, 837–846.
[127]  Shadeo, A.; Lam, W.L. Comprehensive copy number profiles of breast cancer cell model genomes. Breast Cancer Res.?2006, 8, R9, doi:10.1186/bcr1370.
[128]  Heselmeyer-Haddad, K.; Chaudhri, N.; Stoltzfus, P.; Cheng, J.C.; Wilber, K.; Morrison, L.; Auer, G.; Ried, T. Detection of chromosomal aneuploidies and gene copy number changes in fine needle aspirates is a specific, sensitive, and objective genetic test for the diagnosis of breast cancer. Cancer Res.?2002, 62, 2365–2369.
[129]  Raphael, B.J.; Volik, S.; Yu, P.; Wu, C.; Huang, G.; Linardopoulou, E.V.; Trask, B.J.; Waldman, F.; Costello, J.; Pienta, K.J.; Mills, G.B.; Bajsarowicz, K.; Kobayashi, Y.; Sridharan, S.; Paris, P.L.; Tao, Q.; Aerni, S.J.; Brown, R.P.; Bashir, A.; Gray, J.W.; Cheng, J.F.; de Jong, P.; Nefedov, M.; Ried, T.; Padilla-Nash, H.M.; Collins, C.C. A sequence-based survey of the complex structural organization of tumor genomes. Genome Biol.?2008, 9, R59, doi:10.1186/gb-2008-9-3-r59.
[130]  Letessier, A.; Mozziconacci, M.J.; Murati, A.; Juriens, J.; Adelaide, J.; Birnbaum, D.; Chaffanet, M. Multicolour-banding fluorescence in situ hybridization (mbanding-FISH) to identify recurrent chromosomal alterations in breast tumor cell lines. Br. J. Cancer?2005, 92, 382–388.
[131]  Sigurdsson, S.; Bodvarsdottir, S.K.; Anamthawat-Jonsson, K.; Steinarsdottir, M.; Jonasson, J.G.; Ogmundsdottir, H.M.; Eyfjord, J.E. p53 abnormality and chromosomal instability in the same breast tumor cells. Cancer Genet. Cytogenet.?2000, 121, 150–155, doi:10.1016/S0165-4608(00)00260-0.
[132]  Bozhanov, S.S.; Angelova, S.G.; Krasteva, M.E.; Markov, T.L.; Christova, S.L.; Gavrilov, I.G.; Georgieva, E.I. Alterations in p53, BRCA1, ATM, PIK3CA, and HER2 genes and their effect in modifying clinicopathological characteristics and overall survival of Bulgarian patients with breast cancer. J. Cancer Res. Clin. Oncol.?2010, doi:10.1007/s00432-010-0824-9.
[133]  Takahashi, S.; Moriya, T.; Ishida, T.; Shibata, H.; Sasano, H.; Ohuchi, N.; Ishioka, C. Prediction of breast cancer prognosis by gene expression profile of TP53 status. Cancer Sci.?2008, 99, 324–332, doi:10.1111/j.1349-7006.2007.00691.x.
[134]  Ozcelik, H.; Pinnaduwage, D.; Bull, S.B.; Andrulis, I.L. Type of TP53 mutation and ERBB2 amplification affects survival in node-negative breast cancer. Breast Cancer Res. Treat.?2007, 105, 255–265, doi:10.1007/s10549-006-9452-0.
[135]  Langerod, A.; Zhao, H.; Borgan, O.; Nesland, J.M.; Bukholm, I.R.; Ikdahl, T.; Karesen, R.; Borresen-Dale, A.L.; Jeffrey, S.S. TP53 mutation status and gene expression profiles are powerful prognostic markers of breast cancer. Breast Cancer Res.?2007, 9, R30, doi:10.1186/bcr1675.
[136]  Di Leo, A.; Tanner, M.; Desmedt, C.; Paesmans, M.; Cardoso, F.; Durbecq, V.; Chan, S.; Perren, T.; Aapro, M.; Sotiriou, C.; Piccart, M.J.; Larsimont, D.; Isola, J. p-53 gene mutations as a predictive marker in a population of advanced breast cancer patients randomly treated with doxorubicin or docetaxel in the context of a phase III clinical trial. Ann. Oncol.?2007, 18, 997–1003, doi:10.1093/annonc/mdm075.
[137]  Werner, G.; Bartel, M.; Wellinghausen, N.; Essig, A.; Klare, I.; Witte, W.; Poppert, S. Detection of mutations conferring resistance to linezolid in Enterococcus spp. by fluorescence in situ hybridization. J. Clin. Microbiol.?2007, 45, 3421–3423, doi:10.1128/JCM.00179-07.
[138]  O'Day, E.; Lal, A. MicroRNAs and their target gene networks in breast cancer. Breast Cancer Res.?2010, 12, 201, doi:10.1186/bcr2484.
[139]  Cascio, S.; D'Andrea, A.; Ferla, R.; Surmacz, E.; Gulotta, E.; Amodeo, V.; Bazan, V.; Gebbia, N.; Russo, A. miR-20b modulates VEGF expression by targeting HIF-1alpha and STAT3 in MCF-7 breast cancer cells. J. Cell Physiol.?2010, 224, 242–249.
[140]  Heneghan, H.M.; Miller, N.; Lowery, A.J.; Sweeney, K.J.; Newell, J.; Kerin, M.J. Circulating microRNAs as novel minimally invasive biomarkers for breast cancer. Ann. Surg.?2010, 251, 499–505, doi:10.1097/SLA.0b013e3181cc939f.
[141]  Sempere, L.F.; Christensen, M.; Silahtaroglu, A.; Bak, M.; Heath, C.V.; Schwartz, G.; Wells, W.; Kauppinen, S.; Cole, C.N. Altered MicroRNA expression confined to specific epithelial cell subpopulations in breast cancer. Cancer Res.?2007, 67, 11612–11620, doi:10.1158/0008-5472.CAN-07-5019.
[142]  Edwards, P.A. Fusion genes and chromosome translocations in the common epithelial cancers. J. Pathol.?2010, 220, 244–254.
[143]  Scopelliti, A.; Cammareri, P.; Catalano, V.; Saladino, V.; Todaro, M.; Stassi, G. Therapeutic implications of Cancer Initiating Cells. Expert Opin. Biol. Ther.?2009, 9, 1005–1016, doi:10.1517/14712590903066687.
[144]  Sakariassen, P.; Immervoll, H.; Chekenya, M. Cancer stem cells as mediators of treatment resistance in brain tumors: status and controversies. Neoplasia?2007, 9, 882–892, doi:10.1593/neo.07658.
[145]  Bidlingmaier, S.; Zhu, X.; Liu, B. The utility and limitations of glycosylated human CD133 epitopes in defining cancer stem cells. J. Mol. Med.?2008, 86, 1025–1032, doi:10.1007/s00109-008-0357-8.
[146]  Bertolini, G.; Roz, L.; Perego, P.; Tortoreto, M.; Fontanella, E.; Gatti, L.; Pratesi, G.; Fabbri, A.; Andriani, F.; Tinelli, S.; Roz, E.; Caserini, R.; Lo Vullo, S.; Camerini, T.; Mariani, L.; Delia, D.; Calabro, E.; Pastorino, U.; Sozzi, G. Highly tumorigenic lung cancer CD133+ cells display stem-like featuRes. and are spared by cisplatin treatment. Proc. Natl. Acad. Sci. USA?2009, 106, 16281–16286, doi:10.1073/pnas.0905653106.
[147]  Levina, V.; Marrangoni, A.M.; DeMarco, R.; Gorelik, E.; Lokshin, A.E. Drug-selected human lung cancer stem cells: cytokine network, tumorigenic and metastatic properties. PLoS One?2008, 3, e3077.
[148]  Levina, V.; Marrangoni, A.; Wang, T.; Parikh, S.; Su, Y.; Herberman, R.; Lokshin, A.; Gorelik, E. Elimination of human lung cancer stem cells through targeting of the stem cell factor-c-kit autocrine signaling loop. Cancer Res.?2010, 70, 338–346.
[149]  Salnikov, A.V.; Gladkich, J.; Moldenhauer, G.; Volm, M.; Mattern, J.; Herr, I. CD133 is indicative for a resistance phenotype but does not represent a prognostic marker for survival of non-small cell lung cancer patients. Int. J. Cancer?2010, 126, 950–958.
[150]  Al-Hajj, M.; Wicha, M.; Benito-Hernandez, A.; Morrison, S.; Clarke, M. Prospective identification of tumorigenic breast cancer cells. Proc. Natl. Acad. Sci. USA?2003, 100, 3983–3988, doi:10.1073/pnas.0530291100.
[151]  Pece, S.; Tosoni, D.; Confalonieri, S.; Mazzarol, G.; Vecchi, M.; Ronzoni, S.; Bernard, L.; Viale, G.; Pelicci, P.G.; Di Fiore, P.P. Biological and molecular heterogeneity of breast cancers correlates with their cancer stem cell content. Cell?2010, 140, 62–73, doi:10.1016/j.cell.2009.12.007.
[152]  Hennessy, B.T.; Gonzalez-Angulo, A.M.; Stemke-Hale, K.; Gilcrease, M.Z.; Krishnamurthy, S.; Lee, J.S.; Fridlyand, J.; Sahin, A.; Agarwal, R.; Joy, C.; Liu, W.; Stivers, D.; Baggerly, K.; Carey, M.; Lluch, A.; Monteagudo, C.; He, X.; Weigman, V.; Fan, C.; Palazzo, J.; Hortobagyi, G.N.; Nolden, L.K.; Wang, N.J.; Valero, V.; Gray, J.W.; Perou, C.M.; Mills, G.B. Characterization of a naturally occurring breast cancer subset enriched in epithelial-to-mesenchymal transition and stem cell characteristics. Cancer Res.?2009, 69, 4116–4124, doi:10.1158/0008-5472.CAN-08-3441.
[153]  Silva, F.P.; Swagemakers, S.M.; Erpelinck-Verschueren, C.; Wouters, B.J.; Delwel, R.; Vrieling, H.; van der Spek, P.; Valk, P.J.; Giphart-Gassler, M. Gene expression profiling of minimally differentiated acute myeloid leukemia: M0 is a distinct entity subdivided by RUNX1 mutation status. Blood?2009, 114, 3001–3007, doi:10.1182/blood-2009-03-211334.
[154]  Hicks, M.J.; Mackay, B. Comparison of ultrastructural featuRes. among neuroblastic tumors: maturation from neuroblastoma to ganglioneuroma. Ultrastruct. Pathol.?1995, 19, 311–322, doi:10.3109/01913129509064236.
[155]  Estrov, Z. Stem cells and somatic cells: reprogramming and plasticity. Clin. Lymphoma Myeloma?2009, 9 (Suppl. 3), S319–S328, doi:10.3816/CLM.2009.s.031.
[156]  Kasemeier-Kulesa, J.; Teddy, J.; Postovit, L.; Seftor, E.; Seftor, R.; Hendrix, M.; Kulesa, P. Reprogramming multipotent tumor cells with the embryonic neural crest microenvironment. Dev. Dyn.?2008, 237, 2657–2666, doi:10.1002/dvdy.21613.
[157]  Postovit, L.; Margaryan, N.; Seftor, E.; Hendrix, M. Role of nodal signaling and the microenvironment underlying melanoma plasticity. Pigment Cell Melanoma Res.?2008, 21, 348–357, doi:10.1111/j.1755-148X.2008.00463.x.
[158]  Hendrix, M.; Seftor, E.; Seftor, R.; Kasemeier-Kulesa, J.; Kulesa, P.; Postovit, L. Reprogramming metastatic tumour cells with embryonic microenvironments. Nat. Rev. Cancer?2007, 7, 246–255, doi:10.1038/nrc2108.
[159]  Postovit, L.; Costa, F.; Bischof, J.; Seftor, E.; Wen, B.; Seftor, R.; Feinberg, A.; Soares, M.; Hendrix, M. The commonality of plasticity underlying multipotent tumor cells and embryonic stem cells. J. Cell. Biochem.?2007, 101, 908–917, doi:10.1002/jcb.21227.
[160]  Wang, J.; Rao, S.; Chu, J.; Shen, X.; Levasseur, D.N.; Theunissen, T.W.; Orkin, S.H. A protein interaction network for pluripotency of embryonic stem cells. Nature?2006, 444, 364–368, doi:10.1038/nature05284.
[161]  Taranger, C.; Noer, A.; S?rensen, A.; H?kelien, A.; Boquest, A.; Collas, P. Induction of dedifferentiation, genomewide transcriptional programming, and epigenetic reprogramming by extracts of carcinoma and embryonic stem cells. Mol. Biol. Cell?2005, 16, 5719–5735, doi:10.1091/mbc.E05-06-0572.
[162]  Summerer, D.; Schracke, N.; Wu, H.; Cheng, Y.; Bau, S.; Stahler, C.F.; Stahler, P.F.; Beier, M. Targeted high throughput sequencing of a cancer-related exome subset by specific sequence capture with a fully automated microarray platform. Genomics?2010, 95, 241–246, doi:10.1016/j.ygeno.2010.01.006.
[163]  Roukos, D.H. Novel clinico-genome network modeling for revolutionizing genotype-phenotype-based personalized cancer care. Expert Rev. Mol. Diagn.?2010, 10, 33–48, doi:10.1586/erm.09.69.
[164]  Huang, Y.W.; Huang, T.H.; Wang, L.S. Profiling DNA methylomes from microarray to genome-scale sequencing. Technol. Cancer Res. Treat.?2010, 9, 139–147.
[165]  Bell, D.W. Our changing view of the genomic landscape of cancer. J. Pathol.?2010, 220, 231–243.
[166]  Aparicio, S.A.; Huntsman, D.G. Does massively parallel DNA resequencing signify the end of histopathology as we know it? J. Pathol.?2010, 220, 307–315.
[167]  Shah, S.P.; Morin, R.D.; Khattra, J.; Prentice, L.; Pugh, T.; Burleigh, A.; Delaney, A.; Gelmon, K.; Guliany, R.; Senz, J.; Steidl, C.; Holt, R.A.; Jones, S.; Sun, M.; Leung, G.; Moore, R.; Severson, T.; Taylor, G.A.; Teschendorff, A.E.; Tse, K.; Turashvili, G.; Varhol, R.; Warren, R.L.; Watson, P.; Zhao, Y.; Caldas, C.; Huntsman, D.; Hirst, M.; Marra, M.A.; Aparicio, S. Mutational evolution in a lobular breast tumor profiled at single nucleotide resolution. Nature?2009, 461, 809–813, doi:10.1038/nature08489.
[168]  Reis-Filho, J.S. Next-generation sequencing. Breast Cancer Res.?2009, 11 (Suppl. 3), S12, doi:10.1186/bcr2431.
[169]  Morrissy, A.S.; Morin, R.D.; Delaney, A.; Zeng, T.; McDonald, H.; Jones, S.; Zhao, Y.; Hirst, M.; Marra, M.A. Next-generation tag sequencing for cancer gene expression profiling. Genome Res.?2009, 19, 1825–1835, doi:10.1101/gr.094482.109.
[170]  Mardis, E.R.; Wilson, R.K. Cancer genome sequencing: a review. Hum Mol. Genet?2009, 18, R163–R168, doi:10.1093/hmg/ddp396.
[171]  Mardis, E.R. New strategies and emerging technologies for massively parallel sequencing: applications in medical research. Genome Med.?2009, 1, 40, doi:10.1186/gm40.
[172]  Levin, J.Z.; Berger, M.F.; Adiconis, X.; Rogov, P.; Melnikov, A.; Fennell, T.; Nusbaum, C.; Garraway, L.A.; Gnirke, A. Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts. Genome Biol.?2009, 10, R115, doi:10.1186/gb-2009-10-10-r115.
[173]  Kato, K. Impact of the next generation DNA sequencers. Int. J. Clin. Exp Med.?2009, 2, 193–202.
[174]  Salehi-Ashtiani, K.; Yang, X.; Derti, A.; Tian, W.; Hao, T.; Lin, C.; Makowski, K.; Shen, L.; Murray, R.R.; Szeto, D.; Tusneem, N.; Smith, D.R.; Cusick, M.E.; Hill, D.E.; Roth, F.P.; Vidal, M. Isoform discovery by targeted cloning, 'deep-well' pooling and parallel sequencing. Nat. Methods?2008, 5, 597–600, doi:10.1038/nmeth.1224.
[175]  Morozova, O.; Marra, M.A. From cytogenetics to next-generation sequencing technologies: advances in the detection of genome rearrangements in tumors. Biochem. Cell Biol.?2008, 86, 81–91, doi:10.1139/O08-003.
[176]  Morozova, O.; Marra, M.A. Applications of next-generation sequencing technologies in functional genomics. Genomics?2008, 92, 255–264, doi:10.1016/j.ygeno.2008.07.001.
[177]  Marguerat, S.; Wilhelm, B.T.; Bahler, J. Next-generation sequencing: applications beyond genomes. Biochem. Soc. Trans.?2008, 36, 1091–1096, doi:10.1042/BST0361091.
[178]  Kobel, M.; Gilks, C.B.; Huntsman, D.G. Adult-type granulosa cell tumors and FOXL2 mutation. Cancer Res.?2009, 69, 9160–9162, doi:10.1158/0008-5472.CAN-09-2669.
[179]  Schrader, K.A.; Gorbatcheva, B.; Senz, J.; Heravi-Moussavi, A.; Melnyk, N.; Salamanca, C.; Maines-Bandiera, S.; Cooke, S.L.; Leung, P.; Brenton, J.D.; Gilks, C.B.; Monahan, J.; Huntsman, D.G. The specificity of the FOXL2 c.402C>G Somatic mutation: a survey of solid tumors. PLoS One?2009, 4, e7988, doi:10.1371/journal.pone.0007988.
[180]  Shah, S.P.; Kobel, M.; Senz, J.; Morin, R.D.; Clarke, B.A.; Wiegand, K.C.; Leung, G.; Zayed, A.; Mehl, E.; Kalloger, S.E.; Sun, M.; Giuliany, R.; Yorida, E.; Jones, S.; Varhol, R.; Swenerton, K.D.; Miller, D.; Clement, P.B.; Crane, C.; Madore, J.; Provencher, D.; Leung, P.; DeFazio, A.; Khattra, J.; Turashvili, G.; Zhao, Y.; Zeng, T.; Glover, J.N.; Vanderhyden, B.; Zhao, C.; Parkinson, C.A.; Jimenez-Linan, M.; Bowtell, D.D.; Mes-Masson, A.M.; Brenton, J.D.; Aparicio, S.A.; Boyd, N.; Hirst, M.; Gilks, C.B.; Marra, M.; Huntsman, D.G. Mutation of FOXL2 in granulosa-cell tumors of the ovary. N. Engl. J. Med.?2009, 360, 2719–2729, doi:10.1056/NEJMoa0902542.


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