Skip to main content
SpringerLink
Log in

Translational Medicine: Application of Omics for Drug Target Discovery and Validation

  • Chapter
  • First Online:
An Omics Perspective on Cancer Research

Abstract

Drug research and development is a long, expensive and risky process. The novel omics technologies (genomics, transcriptomics, proteomics and metabonomics) and systems biology have brought unprecedented abilities to screen cells at the gene, transcript, protein, metabolite and their interaction network level in searching of novel drug targets, elucidating the primary mechanism-of-action of a drug, understanding side effects in unanticipated off-target interaction, validating existing drug candidates and finding new potential therapeutic applications for an established drug, hence to facilitate the translation from bench to bedside. This chapter provides an overview of recent applications of various omics technologies and systems biology to drug development.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Al-Saffar NM, Troy H, de Molina AR et al (2006) Noninvasive magnetic resonance spectroscopic pharmacodynamic markers of the choline kinase inhibitor MN58b in human carcinoma models. Cancer Res 66:427–434

    Article  CAS  PubMed  Google Scholar 

  • Austin MJF, Babiss L (2006) Commentary: where and how could biomarkers be used in 2016. AAPS J 8:E185–189

    Article  Google Scholar 

  • Basil CF, Zhao YD, Zavaglia K et al (2006) Common cancer biomarkers. Cancer Res 66:2953–2961

    Article  CAS  PubMed  Google Scholar 

  • Chen H, Pan Z, Talaty N et al (2006) Combining desorption electrospray ionization mass spectrometry and nuclear magnetic resonance for differential metabolomics without sample preparation. Rapid Commun Mass Spectrom 20:1577–1584

    Article  CAS  PubMed  Google Scholar 

  • Chin L, Meyerson M, Aldape K et al (2008) Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455:1061–1068

    Article  Google Scholar 

  • Cho WC, Yip TT, Yip C et al (2004) Identification of serum amyloid a protein as a potentially useful biomarker to monitor relapse of nasopharyngeal cancer by serum proteomic profiling. Clin Cancer Res 10:43–52

    Article  CAS  PubMed  Google Scholar 

  • Cho WC, Yip TT, Ngan RK et al (2007) ProteinChip array profiling for identification of disease- and chemotherapy-associated biomarkers of nasopharyngeal carcinoma. Clin Chem 53:241–250

    Article  CAS  PubMed  Google Scholar 

  • Clayton TA, Lindon JC, Cloarec O et al (2006) Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature 440:1073–1077

    Article  CAS  PubMed  Google Scholar 

  • Coen M, Ruepp SU, Lindon JC et al (2004) Integrated application of transcriptomics and metabonomics yields new insight into the toxicity due to paracetamol in the mouse. J Pharm Biomed Anal 35:93–105

    Article  CAS  PubMed  Google Scholar 

  • Conradas KA, Yi M, Simpson KA et al (2005) A combined proteome and microarray investigation of inorganic phosphate-induced pre-osteoblast cells. Mol Cell Proteomics 4:1284–1296

    Article  Google Scholar 

  • Corradi B, Fazio G, Palmi C et al (2008) Efficient detection of leukemia-related fusion transcripts by multiplex PCR applied on a microelectronic platform. Leukemia 22:294–302

    Article  CAS  PubMed  Google Scholar 

  • Craig A, Sidaway J, Holmes E et al (2006) Systems toxicology: Integrated genomic, proteomic and metabonomic analysis of methapyrilene induced hepatotoxicity in the rat. J Proteome Res 5:1586–1601

    Article  CAS  PubMed  Google Scholar 

  • Davidov EJ, Holland JM, Marple EW, Naylor S (2003) Advancing drug discovery through systems biology. Drug Discov Today 8:175–183

    Article  CAS  PubMed  Google Scholar 

  • Dear JW, Leelahavanichkul A, Aponte A et al (2007) Liver proteomics for therapeutic drug discovery: inhibition of the cyclophilin receptor CD147 attenuates sepsis-induced acute renal failure. Crit Care Med 35:2319–2328

    Article  CAS  PubMed  Google Scholar 

  • Dieterle F, Schlotterbeck GT, Ross A et al (2006) Application of metabonomics in a compound ranking study in early drug development revealing drug-induced excretion of choline into urine. Chem Res Toxicol 19:1175–1181

    Article  CAS  PubMed  Google Scholar 

  • Fiegl H, Millinger S, Mueller-Holzner E et al (2005) Circulating tumor-specific DNA: a marker for monitoring efficacy of adjuvant therapy in cancer patients. Cancer Res 65:1141–1145

    Article  CAS  PubMed  Google Scholar 

  • Fiehn O (2002) Metabolomics – the link between genotypes and phenotypes. Plant Mol Biol 48:155–171

    Article  CAS  PubMed  Google Scholar 

  • Goodacre R (2007) Metabolomics of a superorganism. J Nutrit 137:S259–266

    Google Scholar 

  • Hegi ME, Diserens AC, Gorlia T et al (2005) MGMT gene silencing and benefit from temozolomide in glioblastoma. N Engl J Med 352:997–1003

    Article  CAS  PubMed  Google Scholar 

  • Heijne WH, Stierum RH, Slijper M et al (2003) Toxicogenomics of bromobenzene hepatotoxicity: a combined transcriptomics and proteomics approach. Biochem Pharmacol 65:857–875

    Article  CAS  PubMed  Google Scholar 

  • Holly MK, Dear JW, Hu X et al (2006) Biomarker and drug–target discovery using proteomics in a new rat model of sepsis-induced acute renal failure. Kidney Int 70:496–506

    CAS  PubMed  Google Scholar 

  • Huang HL, Stasyk T, Morandell S et al (2006a) Biomarker discovery in breast cancer serum using 2-D differential gel electrophoresis/MALDI-TOF/TOF and data validation by routine clinical assays. Electrophoresis 27:1641–1650

    Article  CAS  PubMed  Google Scholar 

  • Huang RL, Wallqvist A, Covell DG (2006b) Targeting changes in cancer: assessing pathway stability by comparing pathway gene expression coherence levels in tumor and normal tissues. Mol Cancer Ther 5:2417–2427

    Article  CAS  PubMed  Google Scholar 

  • Irizarry RA, Ladd-Acosta C, Carvalho B et al (2008) Comprehensive high-throughput arrays for relative methylation (CHARM). Genome Res 18:780–790

    Article  CAS  PubMed  Google Scholar 

  • Issa JP, Kantarjian H (2005) Azacitidine. Nat Rev Drug Discov:S6-7

    Google Scholar 

  • Jones S, Zhang XS, Parsons DW et al (2008) Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 321:1801–1806

    Article  CAS  PubMed  Google Scholar 

  • Keay SK, Szekely Z, Conrads TP et al (2004) An antiproliferative factor from interstitial cystitis patients is a frizzled 8 protein-related sialoglycopeptide. Proc Natl Acad Sci USA 101:11803–11808

    Article  CAS  PubMed  Google Scholar 

  • Keun HC, Athersuch TJ (2007) Application of metabonomics in drug development. Pharmacogenomics 8:731–741

    Article  CAS  PubMed  Google Scholar 

  • Le Morvan V, Bellott R, Moisan F et al (2006) Relationships between genetic polymorphisms and anticancer drug cytotoxicity vis-a-vis the NCI-60 panel. Pharmacogenomics 7:843–852

    Article  PubMed  Google Scholar 

  • Lee KH, Yim EK, Kim CJ et al (2005) Proteomic analysis of anti-cancer effects by paclitaxel treatment in cervical cancer cells. Gynecol Oncol 98:45–53

    Article  CAS  PubMed  Google Scholar 

  • Lee HK, Lewis LD, Tsongalis GJ et al (2007) Validation of a CYP2D6 genotyping panel on the NanoChip molecular biology workstation. Clin Chem 53:823–828

    Article  CAS  PubMed  Google Scholar 

  • Lesche R, Eckhardt F (2007) DNA methylation markers: A versatile diagnostic tool for routine clinical use. Curr Opin Mol Ther 9:222–230

    CAS  PubMed  Google Scholar 

  • Li R, Wang H, Bekele BN et al (2006) Identification of putative oncogenes in lung adenocarcinoma by a comprehensive functional genomic approach. Oncogene 25:2628–2635

    Article  CAS  PubMed  Google Scholar 

  • Liu YJ, Liu XG, Wang L et al (2008) Genome-wide association scanc identified CTNNBL1 as a novel gene for obesity. Human Mol Genetics 17:1803–1813

    Article  CAS  Google Scholar 

  • Nelson WG, Yegnasubramanian S, Agoston AT et al (2007) Abnormal DNA methylation, epigenetics, and prostate cancer. Front Biosci 12:4254–4266

    Article  CAS  PubMed  Google Scholar 

  • Nikolsky Y, Ekins S, Nikolskaya T et al (2005) A novel method for generation of signature networks as biomarkers from complex high throughput data. Toxicol Lett 158:20–29

    Article  CAS  PubMed  Google Scholar 

  • Paik S, Tang G, Shak S et al (2006) Gene expression and benefit of chemotherapy in women with nodenegative, estrogen receptor-positive breast cancer. J Clin Oncol 24:1–10

    Article  Google Scholar 

  • Parsons DW, Jones S, Zhang XS et al (2008) An integrated genomic analysis of human glioblastoma Multiforme. Science 321:1807–1812

    Article  CAS  PubMed  Google Scholar 

  • Patil ST, Higgs RE, Brandt JE et al (2007) Identifying pharmacodynamic protein markers of centrally active drugs in humans: a pilot study in a novel clinical model. J Proteome Res 3:955–966

    Article  Google Scholar 

  • Rhodes DR, Yu JJ, Shanker K et al (2004) Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression. Proc Natl Acad Sci USA 101:9309–9314

    Article  CAS  PubMed  Google Scholar 

  • Ross JS (2008) Multigene predictors in early-stage breast cancer: moving in or moving out? Expert Rev Mol Diagn 8:129–135

    Article  CAS  PubMed  Google Scholar 

  • Ruepp SU, Tonge RP, Shaw J et al (2002) Genomics and proteomics analysis of acetaminophen toxicity in mouse liver. Toxicol Sci 65:135–150

    Article  CAS  PubMed  Google Scholar 

  • Shen L, Kondo Y, Ahmed S et al (2007) Drug sensitivity prediction by CpG island methylation profile in the NCI-60 cancer cell line panel. Cancer Res 67:11335–11343

    Article  CAS  PubMed  Google Scholar 

  • Soga T, Baran R, Suematsu M et al (2006) Differential metabolomics reveals ophthalmic acid as an oxidative stress biomarker indicating hepatic glutathione consumption. J Biol Chem 281:16768–16776

    Article  CAS  PubMed  Google Scholar 

  • Staunton JE, Slonim DK, Coller HA et al (2001) Chemosensitivity prediction by transcriptional profiling. Proc Natl Acad Sci USA 98:10787–10792

    Article  CAS  PubMed  Google Scholar 

  • Zembutsu H, Ohnishi Y, Tsunoda T et al (2002) Genome-wide cDNA microarray screening to correlate gene expression profiles with sensitivity of 85 human cancer xenografts to anticancer drugs. Cancer Res 62:518–527

    CAS  PubMed  Google Scholar 

  • Zhang XW (2007) Biomarker validation: movement towards personalized medicine. Expert Rev Mol Diagn 7:469–471

    Article  CAS  PubMed  Google Scholar 

  • Zhang Z, Bast RC, Yu YH et al (2004) Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Res 64:5882–5890

    Article  CAS  PubMed  Google Scholar 

  • Zhang XW, Li L, Wei D et al (2007a) Moving cancer diagnostics from bench to bedside. Trends Biotechnol 25:166–173

    Article  PubMed  Google Scholar 

  • Zhang XW, Wei D, Yap YL et al (2007b) Mass spectrometry-based ‘omics’ technologies in cancer diagnostics. Mass Spectrom Rev 26:403–431

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was partly supported by Guangdong Scientific Development Grant 2006B13001003 and 2007A020100001-4.

Author information

Authors and Affiliations

  1. College of Light Industry and Food Sciences, South China University of Technology, Guangzhou, China

    Xuewu Zhang, Wei Wang, Kaijun Xiao & Lei Shi

Authors
  1. Xuewu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kaijun Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lei Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xuewu Zhang .

Editor information

Editors and Affiliations

  1. Dept. Clinical Oncology, Queen Elizabeth Hospital, Gascoigne Road 30, Kowloon, Hong Kong/PR China

    William C.S. Cho

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Zhang, X., Wang, W., Xiao, K., Shi, L. (2010). Translational Medicine: Application of Omics for Drug Target Discovery and Validation. In: Cho, W. (eds) An Omics Perspective on Cancer Research. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2675-0_13

Download citation

Publish with us

Policies and ethics

Search

Navigation