Expectations, validity, and reality in gene expression profiling
- PMID: 20579843
- PMCID: PMC2910173
- DOI: 10.1016/j.jclinepi.2010.02.018
Expectations, validity, and reality in gene expression profiling
Abstract
Objective: To provide a critical overview of gene expression profiling methodology and discuss areas of future development.
Results: Gene expression profiling has been used extensively in biological research and has resulted in significant advances in the understanding of the molecular mechanisms of complex disorders, including cancer, heart disease, and metabolic disorders. However, translating this technology into genomic medicine for use in diagnosis and prognosis faces many challenges. In addition, gene expression profile analysis is frequently controversial, because its conclusions often lack reproducibility and claims of effective dissemination into translational medicine have, in some cases, been remarkably unjustified. In the last decade, a large number of methodological and technical solutions have been offered to overcome the challenges.
Study design and setting: We consider the strengths, limitations, and appropriate applications of gene expression profiling techniques, with particular reference to the clinical relevance.
Conclusion: Some studies have demonstrated the ability and clinical utility of gene expression profiling for use as diagnostic, prognostic, and predictive molecular markers. The challenges of gene expression profiling lie with the standardization of analytic approaches and the evaluation of the clinical merit in broader heterogeneous populations by prospective clinical trials.
Similar articles
-
Clinical pharmacogenomics and transcriptional profiling in early phase oncology clinical trials.Curr Mol Med. 2005 Feb;5(1):83-102. doi: 10.2174/1566524053152933. Curr Mol Med. 2005. PMID: 15720272 Review.
-
Overview of various techniques/platforms with critical evaluation of each.Curr Treat Options Oncol. 2013 Dec;14(4):623-33. doi: 10.1007/s11864-013-0259-z. Curr Treat Options Oncol. 2013. PMID: 24243164 Review.
-
Large scale data mining approach for gene-specific standardization of microarray gene expression data.Bioinformatics. 2006 Dec 1;22(23):2898-904. doi: 10.1093/bioinformatics/btl500. Epub 2006 Oct 10. Bioinformatics. 2006. PMID: 17032674
-
Molecular profiling techniques and bioinformatics in cancer research.Eur J Surg Oncol. 2007 Apr;33(3):255-65. doi: 10.1016/j.ejso.2006.09.002. Epub 2006 Oct 27. Eur J Surg Oncol. 2007. PMID: 17071042 Review.
-
[Microarray data analysis].Ugeskr Laeger. 2006 May 29;168(22):2159-62. Ugeskr Laeger. 2006. PMID: 16768955 Danish.
Cited by
-
Finding Correlations Between mRNA and Protein Levels in Leishmania Development: Is There a Discrepancy?Front Cell Infect Microbiol. 2022 Jul 12;12:852902. doi: 10.3389/fcimb.2022.852902. eCollection 2022. Front Cell Infect Microbiol. 2022. PMID: 35903202 Free PMC article. Review.
-
Bariatric surgery: the challenges with candidate selection, individualizing treatment and clinical outcomes.BMC Med. 2013 Jan 10;11:8. doi: 10.1186/1741-7015-11-8. BMC Med. 2013. PMID: 23302153 Free PMC article. Review.
-
RNA-seq research landscape in Africa: systematic review reveals disparities and opportunities.Eur J Med Res. 2023 Jul 22;28(1):244. doi: 10.1186/s40001-023-01206-3. Eur J Med Res. 2023. PMID: 37480073 Free PMC article.
-
Discovery of potential biomarkers for human atherosclerotic abdominal aortic aneurysm through untargeted metabolomics and transcriptomics.J Zhejiang Univ Sci B. 2021 Sept 15;22(9):733-745. doi: 10.1631/jzus.B2000713. J Zhejiang Univ Sci B. 2021. PMID: 34514753 Free PMC article.
-
Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets.BMC Syst Biol. 2014 Jan 20;8:7. doi: 10.1186/1752-0509-8-7. BMC Syst Biol. 2014. PMID: 24444313 Free PMC article.
References
-
- Baliga NS. Systems biology. The scale of prediction. Science. 2008 Jun 6;320(5881):1297–8. - PubMed
-
- Kim K, Perroud B, Espinal G, Kachinskas D, Austrheim-Smith I, Wolfe BM, Warden CH. Genes and networks expressed in perioperative omental adipose tissue are correlated with weight loss from Roux-en-Y gastric bypass. Int J Obes (Lond) 2008;32(9):1395–406. - PubMed
-
- van't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415:530–536. - PubMed
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources