Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy
- PMID: 15908672
- DOI: 10.1200/JCO.2005.02.509
Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy
Abstract
Mapping tumor cell protein networks in vivo will be critical for realizing the promise of patient-tailored molecular therapy. Cancer can be defined as a dysregulation or hyperactivity in the network of intracellular and extracellular signaling cascades. These protein signaling circuits are the ultimate targets of molecular therapy. Each patient's tumor may be driven by a distinct series of molecular pathogenic defects. Thus, for any single molecular targeted therapy, only a subset of cancer patients may respond. Individualization of therapy, which tailors a therapeutic regimen to a tumor molecular portrait, may be the solution to this dilemma. Until recently, the field lacked the technology for molecular profiling at the genomic and proteomic level. Emerging proteomic technology, used concomitantly with genomic analysis, promises to meet this need and bring to reality the clinical adoption of molecular stratification. The activation state of kinase-driven signal networks contains important information relative to cancer pathogenesis and therapeutic target selection. Proteomic technology offers a means to quantify the state of kinase pathways, and provides post-translational phosphorylation data not obtainable by gene arrays. Case studies using clinical research specimens are provided to show the feasibility of generating the critical information needed to individualize therapy. Such technology can reveal potential new pathway interconnections, including differences between primary and metastatic lesions. We provide a vision for individualized combinatorial therapy based on proteomic mapping of phosphorylation end points in clinical tissue material.
Similar articles
-
Technology insight: pharmacoproteomics for cancer--promises of patient-tailored medicine using protein microarrays.Nat Clin Pract Oncol. 2006 May;3(5):256-68. doi: 10.1038/ncponc0485. Nat Clin Pract Oncol. 2006. PMID: 16683004 Review.
-
Clinical proteomics: from biomarker discovery and cell signaling profiles to individualized personal therapy.Biosci Rep. 2005 Feb-Apr;25(1-2):107-25. doi: 10.1007/s10540-005-2851-3. Biosci Rep. 2005. PMID: 16222423 Review.
-
Modeling of protein signaling networks in clinical proteomics.Cold Spring Harb Symp Quant Biol. 2005;70:517-24. doi: 10.1101/sqb.2005.70.022. Cold Spring Harb Symp Quant Biol. 2005. PMID: 16869790 Review.
-
Array-based proteomics: mapping of protein circuitries for diagnostics, prognostics, and therapy guidance in cancer.J Pathol. 2006 Apr;208(5):595-606. doi: 10.1002/path.1958. J Pathol. 2006. PMID: 16518808 Review.
-
Reverse phase protein microarrays for theranostics and patient-tailored therapy.Methods Mol Biol. 2008;441:113-28. doi: 10.1007/978-1-60327-047-2_8. Methods Mol Biol. 2008. PMID: 18370315
Cited by
-
The micro-RNA 199b-5p regulatory circuit involves Hes1, CD15, and epigenetic modifications in medulloblastoma.Neuro Oncol. 2012 May;14(5):596-612. doi: 10.1093/neuonc/nos002. Epub 2012 Mar 12. Neuro Oncol. 2012. PMID: 22411914 Free PMC article.
-
Network-based classification of breast cancer metastasis.Mol Syst Biol. 2007;3:140. doi: 10.1038/msb4100180. Epub 2007 Oct 16. Mol Syst Biol. 2007. PMID: 17940530 Free PMC article.
-
Reverse phase protein microarrays advance to use in clinical trials.Mol Oncol. 2010 Dec;4(6):461-81. doi: 10.1016/j.molonc.2010.09.003. Epub 2010 Oct 16. Mol Oncol. 2010. PMID: 20974554 Free PMC article. Review.
-
Pathway biomarker profiling of localized and metastatic human prostate cancer reveal metastatic and prognostic signatures.J Proteome Res. 2009 Jun;8(6):3044-54. doi: 10.1021/pr8009337. J Proteome Res. 2009. PMID: 19275204 Free PMC article.
-
Tissue is alive: New technologies are needed to address the problems of protein biomarker pre-analytical variability.Proteomics Clin Appl. 2009 Aug 1;3(8):874-882. doi: 10.1002/prca.200800001. Proteomics Clin Appl. 2009. PMID: 20871745 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources