Has discovery-based cancer research been a bust?

Clinical and Translational Oncology

Volumn 15, Issue 11, 2013, Pages 865-870

  Epstein, R J ^a,b  

^a GARVAN INSTITUTE OF MEDICAL RESEARCH   (Australia)

^b ST VINCENT S HOSPITAL   (Australia)

Author keywords

CDNA microarray; Pathway fingerprinting; Personalized medicine; Proteomics; Target specific anticancer drug therapy

Indexed keywords

BIOLOGICAL MARKER; MAMMALIAN TARGET OF RAPAMYCIN; MITOGEN ACTIVATED PROTEIN KINASE;

ARTICLE; CANCER REGRESSION; CANCER RESEARCH; CHROMOSOME ABERRATION; DRUG SCREENING; GENE AMPLIFICATION; GENE EXPRESSION PROFILING; HIGH THROUGHPUT SCREENING; HUMAN GENOME; MOLECULARLY TARGETED THERAPY; PROTEOMICS; SIGNAL NOISE RATIO;

BIOMEDICAL RESEARCH; HUMANS; MUTATION; NEOPLASMS; PREDICTIVE VALUE OF TESTS; TUMOR MARKERS, BIOLOGICAL;

EID: 84886585870     PISSN: 1699048X     EISSN: 16993055     Source Type: Journal    
DOI: 10.1007/s12094-013-1071-8     Document Type: Article

References (56)

1. Winquist RJ, Furey BF, Boucher DM. Cancer stem cells as the relevant biomass for drug discovery. Curr Opin Pharmacol. 2010;10(4):385-90. doi:10.1016/j. coph.2010.06.008.
2. Schmid EF, Smith DA. R&D technology investments: misguided and expensive or a better way to discover medicines? Drug Discov Today. 2006;11(17-18):775-84. doi:10.1016/j.drudis.2006.07.007. (Pubitemid 44280023)
3. Yang Y, Adelstein SJ, Kassis AI. Target discovery from data mining approaches. Drug Discov Today. 2009;14(3-4):147-54. doi:10.1016/j.drudis.2008. 12. 005.
4. Sims AH. Bioinformatics and breast cancer: what can high-throughput genomic approaches actually tell us? J Clin Pathol. 2009;62(10):879-85. doi:10.1136/jcp.2008.060376.
5. Xie L, Qian X, Liu B. MicroRNAs: novel biomarkers for gastrointestinal carcinomas. Mol Cell Biochem. 2010;341(1-2):291-9. doi:10.1007/s11010-010-0463- 0.
6. Nathanson KL. Using genetics and genomics strategies to personalize therapy for cancer: focus on melanoma. Biochem Pharmacol. 2010;80(5):755-61. doi:10.1016/j.bcp.2010.04.017.
7. Nielsen TO. Microarray analysis of sarcomas. Adv Anat Pathol. 2006;13(4):166-73. doi:00125480-200607000-00003. (Pubitemid 44341652)
8. Benvenuti S, Arena S, Bardelli A. Identification of cancer genes by mutational profiling of tumor genomes. FEBS Lett. 2005;579(8):1884-90. doi:10.1016/j. febslet.2005.02.015. (Pubitemid 40342669)
9. Davies H, Bignell GR, Cox C, Stephens P, Edkins S, Clegg S, et al. Mutations of the BRAF gene in human cancer. Nature. 2002;417(6892):949-54. doi:10.1038/nature00766. (Pubitemid 34716871)
10. Samuels Y, Wang Z, Bardelli A, Silliman N, Ptak J, Szabo S, et al. High frequency of mutations of the PIK3CA gene in human cancers. Science. 2004;304(5670):554. doi:10.1126/science.1096502. (Pubitemid 38541907)
11. Epstein RJ. Growth of the Asian health-care market: global implications for the pharmaceutical industry. Nat Rev Drug Discov. 2007;6(10):785-92. doi:10.1038/nrd2360. (Pubitemid 47500505)
12. Macarron R, Banks MN, Bojanic D, Burns DJ, Cirovic DA, Garyantes T, et al. Impact of high-throughput screening in biomedical research. Nat Rev Drug Discov. 2011;10(3):188-95. doi:10.1038/nrd3368.
13. Roberts NJ, Vogelstein JT, Parmigiani G, Kinzler KW, Vogelstein B, Velculescu VE. The predictive capacity of personal genome sequencing. Sci Transl Med. 2012;. doi:10.1126/scitranslmed.3003380.
14. Fojo T, Parkinson DR. Biologically targeted cancer therapy and marginal benefits: are we making too much of too little or are we achieving too little by giving too much? Clin Cancer Res. 2010;16(24):5972-80. doi:10.1158/1078-0432. CCR-10-1277.
15. Simon R. Lost in translation: problems and pitfalls in translating laboratory observations to clinical utility. Eur J Cancer. 2008;44(18):2707-13. doi:10.1016/j.ejca.2008.09.009.
16. Epstein RJ. Unblocking blockbusters: using Boolean text-mining to optimise clinical trial design and timeline for novel anticancer drugs. Cancer Inform. 2009;7:231-8.
17. Chin L, Hahn WC, Getz G, Meyerson M. Making sense of cancer genomic data. Genes Dev. 2011;25(6):534-55. doi:10.1101/gad.2017311.
18. Stricker T, Catenacci DV, Seiwert TY. Molecular profiling of cancer-the future of personalized cancer medicine: a primer on cancer biology and the tools necessary to bring molecular testing to the clinic. Semin Oncol. 2011;38(2):173-85. doi:10.1053/j.seminoncol.2011.01.013.
19. Bakry R, Rainer M, Huck CW, Bonn GK. Protein profiling for cancer biomarker discovery using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and infrared imaging: a review. Anal Chim Acta. 2011;690(1):26-34. doi:10.1016/j.aca.2011.01.044.
20. Akerley WL 3rd. Contemporary adjuvant treatment of breast cancer. Surg Oncol Clin N Am. 1995;4(4):685-99.
21. Chen W, Chen M, Barak LS. Development of small molecules targeting the Wnt pathway for the treatment of colon cancer: a high-throughput screening approach. Am J Physiol Gastrointest Liver Physiol. 2010;299(2):G293-300. doi:10.1152/ajpgi.00005.2010.
22. Diamandis M, White NM, Yousef GM. Personalized medicine: marking a new epoch in cancer patient management. Mol Cancer Res. 2010;8(9):1175-87. doi:10.1158/1541-7786.MCR-10-0264.
23. Schrattenholz A, Groebe K, Soskic V. Systems biology approaches and tools for analysis of interactomes and multi-target drugs. Methods Mol Biol. 2010;662:29-58. doi:10.1007/978-1-60761-800-3-2.
24. Sikaroodi M, Galachiantz Y, Baranova A. Tumor markers: the potential of "omics" approach. Curr Mol Med. 2010;10(2):249-57. doi:10.2174/156652 410790963277.
25. Yu DH, Chatterton JE, Bliesath JR, Sundaram R, Ke N, Nguy V, et al. A 96-well surrogate survival assay coupled with a special short interfering RNA vector for assessing cancer gene targets with enhanced signal/noise ratio and its utility in HTS for cancer therapeutic targets. Assay Drug Dev Technol. 2005;3(4):401-11. doi:10.1089/adt.2005.3.401. (Pubitemid 41489396)
26. Ma S, Funk CC, Price ND. Systems approaches to molecular cancer diagnostics. Discov Med. 2010;10(55):531-42.
27. Glick M, Jenkins JL, Nettles JH, Hitchings H, Davies JW. Enrichment of highthroughput screening data with increasing levels of noise using support vector machines, recursive partitioning, and laplacian-modified naive Bayesian classifiers. J Chem Inf Model. 2006;46(1):193-200. doi:10.1021/ci050374h. (Pubitemid 43282114)
28. Kreeger PK, Lauffenburger DA. Cancer systems biology: a network modeling perspective. Carcinogenesis. 2010;31(1):2-8. doi:10.1093/carcin/bgp261.
29. Bansal V, Libiger O, Torkamani A, Schork NJ. Statistical analysis strategies for association studies involving rare variants. Nat Rev Genet. 2010;11(11):773-85. doi:10.1038/nrg2867.
30. Epstein RJ. Digitization and its discontents: future shock in predictive oncology. Semin Oncol. 2010;37(1):60-4. doi:10.1053/j.seminoncol.2009.12.006.
31. Epstein RJ. TNM: therapeutically not mandatory. Eur J Cancer. 2009;45(7): 1111-6. doi:10.1016/j.ejca.2009.02.020.
32. Kepp O, Galluzzi L, Lipinski M, Yuan J, Kroemer G. Cell death assays for drug discovery. Nat Rev Drug Discov. 2011;10(3):221-37. doi:10.1038/nrd3373.
33. Sharma SV, Settleman J. Exploiting the balance between life and death: targeted cancer therapy and "oncogenic shock". Biochem Pharmacol. 2010;80(5): 666-73. doi:10.1016/j.bcp.2010.03.001.
34. van Vliet E. Current standing and future prospects for the technologies proposed to transform toxicity testing in the 21st century. ALTEX. 2011;28(1):17-44.
35. Epstein RJ. Maintenance therapy to suppress micrometastasis: the new challenge for adjuvant cancer treatment. Clin Cancer Res. 2005;11(15):5337-41. doi:10.1158/1078-0432.CCR-05-0437. (Pubitemid 41060805)
36. Lo SS, Mumby PB, Norton J, Rychlik K, Smerage J, Kash J, et al. Prospective multicenter study of the impact of the 21-gene recurrence score assay on medical oncologist and patient adjuvant breast cancer treatment selection. J Clin Oncol. 2010;28(10):1671-6. doi:10.1200/JCO.2008.20.2119.
37. Brauchli P, Thurlimann B, Crowe SN, Herrmann R. What is the value of the 21-gene recurrence score? J Clin Oncol. 2010;28(32):e671-2. doi:10.1200/JCO. 2010.30.3313 author reply 3-4.
38. Tang G, Cuzick J, Costantino JP, Dowsett M, Forbes JF, Crager M, et al. Risk of recurrence and chemotherapy benefit for patients with node-negative, estrogen receptor-positive breast cancer: recurrence score alone and integrated with pathologic and clinical factors. J Clin Oncol. 2011;29(33):4365-72. doi:10.1200/JCO.2011.35.3714.
39. Cuzick J, Dowsett M, Pineda S, Wale C, Salter J, Quinn E, et al. Prognostic value of a combined estrogen receptor, progesterone receptor, ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and comparison with the genomic health recurrence score in early breast cancer. J Clin Oncol. 2011;29(32):4273-8. doi:10.1200/JCO.2010.31.2835.
40. Hakonarson H, Grant SF. Planning a genome-wide association study: points to consider. Ann Med. 2011;43(6):451-60. doi:10.3109/07853890.2011.573803.
41. Meyskens FL Jr, Szabo E. Diet and cancer: the disconnect between epidemiology and randomized clinical trials. Cancer Epidemiol Biomarkers Prev. 2005;14(6):1366-9. doi:10.1158/1055-9965.EPI-04-0666. (Pubitemid 40807332)
42. Harvey AL, Cree IA. High-throughput screening of natural products for cancer therapy. Planta Med. 2010;76(11):1080-6. doi:10.1055/s-0030-1250162.
43. Zhao Y. Posterior probability of discovery and expected rate of discovery for multiple hypothesis testing and high-throughput assays. J Am Stat Assoc. 2011;106:984-6.
44. Simon R, Radmacher MD, Dobbin K, McShane LM. Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. J Natl Cancer Inst. 2003;95(1):14-8. (Pubitemid 36124291)
45. Eddy JA, Sung J, Geman D, Price ND. Relative expression analysis for molecular cancer diagnosis and prognosis. Technol Cancer Res Treat. 2010;9(2):149-59 pii: c4306/Relative-Expression-Analysis-for-Molecular-Cancer- Diagnosis-and-Prognosis-149-160-p17776.html.
46. Chiorino G. Mello Grand M, Scatolini M, Ostano P. From single gene to integrative molecular concept MAPS: pitfalls and potentials of microarray technology. J Biol Regul Homeost Agents. 2008;22(1):7-16. pii: AID-2. (Pubitemid 351577888)
47. Nelson PT, Wang WX, Wilfred BR, Tang G. Technical variables in highthroughput miRNA expression profiling: much work remains to be done. Biochim Biophys Acta. 2008;1779(11):758-65. doi:10.1016/j.bbagrm.2008.03.012.
48. Martin-Subero JI, Esteller M. Profiling epigenetic alterations in disease. Adv Exp Med Biol. 2011;711:162-77.
49. Iwadate Y. Clinical proteomics in cancer research-promises and limitations of current two-dimensional gel electrophoresis. Curr Med Chem. 2008;15(23): 2393-400.
50. Wlodkowic D, Cooper JM. Microfabricated analytical systems for integrated cancer cytomics. Anal Bioanal Chem. 2010;398(1):193-209. doi:10.1007/s00216- 010-3722-8.
51. Brennan DJ, O'Connor DP, Rexhepaj E, Ponten F, Gallagher WM. Antibodybased proteomics: fast-tracking molecular diagnostics in oncology. Nat Rev Cancer. 2010;10(9):605-17. doi:10.1038/nrc2902.
52. Harsha HC, Pandey A. Phosphoproteomics in cancer. Mol Oncol. 2010;4(6):482-95. doi:10.1016/j.molonc.2010.09.004.
53. van der Meel R, Gallagher WM, Oliveira S, O'Connor AE, Schiffelers RM, Byrne AT. Recent advances in molecular imaging biomarkers in cancer: application of bench to bedside technologies. Drug Discov Today. 2010;15(3-4):102-14. doi:10.1016/j.drudis.2009.12.003.
54. Shagam JY. Cancer-focused molecular imaging. Radiol Technol. 2010;82(1): 59-80. pii: 82/1/59.
55. Baudot A, Real FX, Izarzugaza JM, Valencia A. From cancer genomes to cancer models: bridging the gaps. EMBO Rep. 2009;10(4):359-66. doi:10.1038/embor. 2009.46.
56. Yilmaz S, Jonveaux P, Bicep C, Pierron L, Smail-Tabbone M, Devignes MD. Gene-disease relationship discovery based on model-driven data integration and database view definition. Bioinformatics. 2009;25(2):230-6. doi:10.1093/ bioinformatics/btn612.