Literature DB >> 16991194

Strategies for plasma proteomic profiling of cancers.

Gilbert S Omenn1.   

Abstract

Despite a voluminous literature on potential protein biomarkers and a compelling need for diagnostic tests based on biomarkers to detect cancers at much earlier, more treatable stages, progress has been limited. New methods and new instruments for analysis of differences in gene expression, gene methylation, and proteomics are being employed to try to accelerate the discovery phase. Given the heterogeneity of tumor mechanisms and the limitations of analytical methods, it is likely that a variety of strategies will be needed and will be complementary. That is the basis of this review of proteomic approaches. This article adopts a systems biology view, starting with mRNA transcripts in tumors and cultured tumor cells to detect mRNA overexpression, some of which will be correlated with protein overexpression. Some of those proteins may be secreted or released into proximal biofluids and plasma. Detection of low-abundance tumor proteins in the complex and dynamic mixture that is plasma requires combinations of increasingly powerful technologies. The biological amplification of protein signals through the immune system offers autoantibodies as potential biomarkers. Higher abundance proteins, including acute-phase reactants, may have practical value, especially if the proteins are modified as part of the cancer processes. Low molecular weight proteins, fragments, and peptides may offer complementary biomarkers. Promising biomarker candidates must be confirmed in independent studies. Then they must be submitted to higher-throughput methods practical for large-scale validation studies and, hopefully, for clinical and epidemiological applications. Standardized operating procedures for specimen handling, design and use of various reference standards, care to avoid bias and confounding, and guidelines for reporting findings and contributing datasets should enhance the prospects for predictive proteomic profiling of people at risk for cancers.

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Year:  2006        PMID: 16991194     DOI: 10.1002/pmic.200600331

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  12 in total

1.  Multistrip Western blotting to increase quantitative data output.

Authors:  Edita Aksamitiene; Jan B Hoek; Boris Kholodenko; Anatoly Kiyatkin
Journal:  Electrophoresis       Date:  2007-09       Impact factor: 3.535

2.  Multistrip western blotting to increase quantitative data output.

Authors:  Anatoly Kiyatkin; Edita Aksamitiene
Journal:  Methods Mol Biol       Date:  2009

Review 3.  Proteomic strategies and challenges in tumor metastasis research.

Authors:  Petra Hudler; Masa Gorsic; Radovan Komel
Journal:  Clin Exp Metastasis       Date:  2010-07-07       Impact factor: 5.150

4.  Identification of IMPDH2 as a tumor-associated antigen in colorectal cancer using immunoproteomics analysis.

Authors:  Yujun He; Zhirong Mou; Wanlin Li; Baohua Liu; Tao Fu; Shong Zhao; Debing Xiang; Yuzhang Wu
Journal:  Int J Colorectal Dis       Date:  2009-07-14       Impact factor: 2.571

5.  An LC-IMS-MS platform providing increased dynamic range for high-throughput proteomic studies.

Authors:  Erin Shammel Baker; Eric A Livesay; Daniel J Orton; Ronald J Moore; William F Danielson; David C Prior; Yehia M Ibrahim; Brian L LaMarche; Anoop M Mayampurath; Athena A Schepmoes; Derek F Hopkins; Keqi Tang; Richard D Smith; Mikhail E Belov
Journal:  J Proteome Res       Date:  2010-02-05       Impact factor: 4.466

Review 6.  Institutional shared resources and translational cancer research.

Authors:  Paolo De Paoli
Journal:  J Transl Med       Date:  2009-06-29       Impact factor: 5.531

Review 7.  Challenges of deciphering gastric cancer heterogeneity.

Authors:  Petra Hudler
Journal:  World J Gastroenterol       Date:  2015-10-07       Impact factor: 5.742

8.  Proteomic patterns analysis with multivariate calculations as a promising tool for prompt differentiation of early stage lung tissue with cancer and unchanged tissue material.

Authors:  Piotr Waloszczyk; Tomasz Janus; Jacek Alchimowicz; Tomasz Grodzki; Krzysztof Borowiak
Journal:  Diagn Pathol       Date:  2011-03-21       Impact factor: 2.644

Review 9.  Epigenetic aberrations and cancer.

Authors:  Miryam Ducasse; Mark A Brown
Journal:  Mol Cancer       Date:  2006-11-08       Impact factor: 27.401

Review 10.  Translational systems biology of inflammation.

Authors:  Yoram Vodovotz; Marie Csete; John Bartels; Steven Chang; Gary An
Journal:  PLoS Comput Biol       Date:  2008-04-25       Impact factor: 4.475

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