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Strategies for Genomic and Proteomic Profiling of Cancers

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Abstract

Omics-based technology platforms have made new kinds of cancer profiling tests feasible. There are several valuable examples in clinical practice, and many more under development. A concerted, transparent process of discovery with lock-down of candidate assays and classifiers and clear specification of intended clinical use is essential. The Institute of Medicine has now proposed a three-stage scheme of confirming and validating analytical findings, validating performance on clinical specimens, and demonstrating explicit clinical utility for an approvable test (Micheel et al., Evolution of translational omics: lessons learned and path forward, 2012).

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References

  1. Collins FS (2010) Research agenda: opportunities for research and NIH. Science 327:36–37

    Article  Google Scholar 

  2. Farrah T, Deutsch EW, Omenn GS, Campbell DS, Sun Z, Bletz JA, Mallick P, Katz JE, Malmström J, Ossola R, Watts JD, Lin B, Zhang H, Moritz RL, Aebersold R (2011) A high-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas. Mol Cell Proteomics 10:9. doi:10.1074/mcp.M110.006353

  3. Lander ES, Linton LM, Birren B et al (2001) Initial sequencing and analysis of the human genome. Nature 409:860–921

    Article  Google Scholar 

  4. Menon R, Omenn GS (2010) Proteomic characterization of novel alternative splice variant proteins in human epidermal growth factor receptor 2/neu-induced breast cancers. Cancer Res 70:3440–3449

    Google Scholar 

  5. Menon R, Zhang Q, Zhang Y, Fermin D, Bardeesy N, DePinho RA, Lu C, Hanash SM, Omenn GS, States DJ (2009) Identification of novel alternative splice isoforms of circulating proteins in a mouse model of human pancreatic cancer. Cancer Res 69:300–309

    Article  Google Scholar 

  6. Menon R, Roy A, Mukerjee S, Belkin S, Zhang Y, Omenn GS (2011) Functional implications of structural predictions for alternative splice proteins expressed in Her2/neu-induced breast cancers. J Proteome Res 10:5503–5511

    Article  Google Scholar 

  7. Micheel C, Nass S, Omenn GS (eds) (2012) Evolution of translational omics: lessons learned and path forward. National Academy Press, Washington, DC

  8. Omenn GS (2012) Gene-environment interactions: eco-genetics and toxicogenomics. In: Ginsburg G, Willard H (eds) Genomic and personalized medicine, 2nd edn. Elsevier, New York, pp 50–59

  9. Omenn GS, Yocum AK, Menon R (2010) Alternative splice variants, a new class of protein cancer biomarker candidates: findings in pancreatic cancer and breast cancer with systems biology implications. Dis Mark 28:241–251

    Article  Google Scholar 

  10. Ostroff RM, Bigbee WL, Franklin W et al (2010) Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer. PLoS One 5:e15003. doi:10.1371/journal.pone.0015003

  11. Shedden K, Taylor JM, Enkemann SA (2008) Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nat Med 14:822–827

    Article  Google Scholar 

  12. Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, Laxman B, Mehra R, Lonigro RJ, Li Y, Nyati MK, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn GS, Ghosh D, Pennathur S, Alexander DC, Berger A, Shuster JR, Wei JT, Varambally S, Beecher C, Chinnaiyan AM (2009) Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature 457:910–914

    Article  Google Scholar 

  13. Tarcea VG, Weymouth T, Ade A et al (2009) Michigan Molecular Interactions r2: from interacting proteins to pathways. Nucl Acids Res 37:D642–646

    Google Scholar 

  14. Tomlins SA, Rhodes DR, Perner S et al (2005) Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 310:644–648

    Article  Google Scholar 

  15. Van de Vijver MJ, He YD, van’t Veer LJ (2002) A gene-expression signature as a predictor of survival in breast cancer. NEJM 347:1999–2009

    Article  Google Scholar 

  16. Venter JC, Adams MD, Myers EW et al (2001) The sequence of the human genome. Science 281:1304–1351

    Article  Google Scholar 

  17. Wang XV, Verhaak RG, Purdom E, Spellman PT, Speed TP (2011) Unifying gene expression measures from multiple platforms using factor analysis. PLoS One 6:e17691

    Google Scholar 

  18. Zhang Z, Chan DW (2010) The road from discovery to clinical diagnostics: lessons learned from the first FDA-cleared in vitro diagnostic multivariate index assay of proteomic biomarkers. Cancer Epidemiol Biomark Prev 19:2995–2999

    Article  Google Scholar 

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Correspondence to Gilbert S. Omenn.

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Omenn, G.S. Strategies for Genomic and Proteomic Profiling of Cancers. Stat Biosci 8, 1–7 (2016). https://doi.org/10.1007/s12561-014-9111-7

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