Proteomic profiling of cancer biomarkers

Revlon/UCLA Breast Center, 90095-7028, USA.
Briefings in Functional Genomics and Proteomics (Impact Factor: 3.67). 08/2003; 2(2):147-58.
Source: PubMed


Early detection and correct diagnosis are essential for effective treatment of cancer and patient survival. Complete sequencing of the human genome, and the genomes of other species, provides valuable tools for discerning the genetic abnormalities in cancer. However, differences between cancerous and normal cells reflect more than variations in genetic sequences and abundance of transcribed RNA. Many cancer biomarkers are manifestation of differences in post-transcriptional splicing and/or post-translational modifications. Thus, proteomic tools are being increasingly utilised in the post-genomic era for discovery of new cancer biomarkers. In this paper we will provide an overview of the biomarker discovery process from the proteomic profiling point of view, with emphasis given to the principles that are involved in the process, including the protein identification strategies, and how surface enhanced laser desorption ionisation mass spectrometry fits into the picture. The aim is to provide a resource for the experimental practitioner seeking awareness of the analytical tools that are now available in contemporary cancer research.

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    • "Proteomics has been employed recently to identify new disease related biomarkers for cancer diagnosis and development of targeted treatment (He et al., 2007; Shau et al., 2003; He et al., 2009; Whelan et al., 2009). Since tumor tissues and tumor cell lines are rich in cancer related proteins, they were selected to study the hydrophobic sub-proteome of human breast cancer. "
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    ABSTRACT: It is widely believed that discovery of specific, sensitive and reliable tumor biomarkers can improve the treatment of cancer. The goal of this study was to develop a novel fractionation protocol targeting hydrophobic proteins as possible cancer cell membrane biomarkers. Hydrophobic proteins of breast cancer tissues and cell lines were enriched by polymeric reverse phase columns. The retained proteins were eluted and digested for peptide identification by nano-liquid chromatography with tandem mass spectrometry using a hybrid linear ion-trap Orbitrap.Hundreds of proteins were identified from each of these three specimens: tumors, normal breast tissue, and breast cancer cell lines. Many of the identified proteins defined key cellular functions. Protein profiles of cancer and normal tissues from the same patient were systematically examined and compared. Stem cell markers were overexpressed in triple negative breast cancer (TNBC) compared with non-TNBC samples. Because breast cancer stem cells are known to be resistant to radiation and chemotherapy, and can be the source of metastasis frequently seen in patients with TNBC, our study may provide evidence of molecules promoting the aggressiveness of TNBC.The initial results obtained using a combination of hydrophobic fractionation and nano-LC mass spectrometry analysis of these proteins appear promising in the discovery of potential cancer biomarkers. When sufficiently refined, this approach may prove useful for early detection and better treatment of breast cancer.
    Full-text · Article · Jan 2010 · Journal of Proteomics & Bioinformatics
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    • "pressed protein in the disease state versus the control state . A usable biomarker must be both sensitive ( % of diseased subjects with marker ) and specific ( % of non - diseased subjects without the marker ) in a population with normal prevalence . The majority of reports on proteomic discovery of serum biomarkers have been in the cancer field ( Shau et al . , 2003 ) . We have chosen to classify protein biomarkers into three potential types : binary , single , and pattern ."
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    ABSTRACT: There are currently no consistent objective biochemical markers of alcohol abuse and alcoholism. Development of reliable diagnostic biomarkers that permit accurate assessment of alcohol intake and patterns of drinking is of prime importance to treatment and research fields. Diagnostic biomarker development in other diseases has demonstrated the utility of both open, systems biology, screening for biomarkers and more rational focused efforts on specific biomolecules or families of biomolecules. Long-term alcohol consumption leads to altered inflammatory cell and adaptive immune responses with associated pathologies and increased incidence of infections. This has led researchers to focus attention on identifying cytokine biomarkers in models of alcohol abuse. Alcohol is known to alter cytokine levels in plasma and a variety of tissues including lung, liver, and very importantly brain. A number of cytokine biomarker candidates have been identified, including: tumor necrosis factor-alpha, interleukin (IL)-1-alpha, IL-1-beta, IL-6, IL-8, IL-12, and monocyte chemoattractant protein-1. This is an emerging and potentially exciting avenue of research in that circulating cytokines may contribute to diagnostic biomarker panels, and a combination of multiple biomarkers may significantly increase the sensitivity and specificity of the biochemical tests aiding reliable and accurate detection of excessive alcohol intake.
    Full-text · Article · Dec 2009 · Journal of Neuroimmune Pharmacology
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    • "A classical proteomics approach includes 2D polyacrylamide gel electrophoresis (PAGE) and mass spectrometry in which proteins are identified by their expression profile and peptide sequencing (Hale et al., 2003; Shankar et al., 2005). Comparative protein profiling has been developed for the detection of specific protein expression patterns as a reflection of biological statuses (Shau et al., 2003; Rocken et al., 2004). "
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    ABSTRACT: Polycystic ovary syndrome (PCOS) is the most common cause of anovulatory infertility, affecting 5-10% of females of reproductive age. Currently, little is known about the changes in whole proteins between PCOS and normal ovaries. In the present study, a proteomic approach comprised two-dimensional gel electrophoresis (2DE) analysis and mass spectroscopy was used to identify proteins and examine expression patterns in three PCOS and normal ovaries. One hundred and ten protein spots were separated and showed different intensities between PCOS and normal ovaries. Sixty-nine proteins associated with cellular metabolism and physiological process were identified from 72 spots. Fifty-four proteins were up-regulated in PCOS ovaries and 15 other proteins were up-regulated in normal ovaries. These data demonstrate, for the first time, the complexity in the regulation of ovarian protein expression in human PCOS, and will provide important insight for a better understanding of the pathogenetic mechanisms underlying this clinical disorder.
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