Recent developments in proteomic methods and disease biomarkers

Abstract

Proteomic methodologies for identification and analysis of biomarkers have gained more attention during recent years and have evolved rapidly. Identification and detection of disease biomarkers are important to foresee outbreaks of certain diseases thereby avoiding surgery and other invasive and expensive medical treatments for patients. Thus, more research into discovering new biomarkers and new methods for faster and more accurate detection is needed. It is often difficult to detect and measure biomarkers because of their low concentrations and the complexity of their respective matrices. Therefore it is hard to find and validate methods for accurate screening methods suitable for clinical use. The most recent developments during the last three years and also some historical considerations of proteomic methodologies for identification and validation of disease biomarkers are presented in this review.

Optimization of ultrasound-assisted extraction of protein from egg white using response surface methodology (RSM) and its proteomic study by MALDI-TOF-MS

“…Proteomic methodologies for identica-tion of proteins by MS can provide reliable identication of the different proteins in comparison with other methods and have gained more attention during recent years. 7 Guérin-Dubiard et al, 8 11 have doubled the number of proteins (to 148) found in egg white by exploiting a peptide ligand libraries technology. Omana et al 12 determined the changes of proteins in egg white from white-shell eggs during storage to further understand the biochemical basis of egg white thinning.…”

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

“…[5– 8] However, due to the wide dynamic range of protein abundances, the potential presence of an array of post-translational modifications (PTMs) and the absence of protein amplification methods, candidate protein biomarkers pose tremendous challenges for the reliable and robust measurement of low-abundance protein biomarkers. [9,10] Therefore, new developments in protein quantification technologies that provide higher sensitivity and specificity are expected to greatly accelerate protein biomarker discovery and verification.…”

Principal Component Analysis with Linear and Quadratic Discriminant Analysis for Identification of Cancer Samples Based on Mass Spectrometry

“…18,[20][21][22][23][24] One of the main fields using MS data is metabolomics, which aims to identify and quantify small molecules involved in metabolic reactions. 25 Metabolomics studies have been applied in several areas, especially cancer.…”

“…5 Some examples of MS applications includes toxicology screening and toxic drug quantification using quadrupole MS/MS; 10 identification of inborn errors in metabolism or genetic defects in newborns for prenatal screening programs using electrospray tandem MS; 11 detection of drug-induced hepatotoxicity using MS-based metabolomics; 12 and identification and quantification of bleomycin in serum and tumor tissue by high resolution LC-MS. 13 MS-based techniques have been largely employed for cancer identification, such as for breast cancer, 14 prostate cancer, 15,16 ovarian cancer, 17 lung cancer, 18 and pancreatic cancer; 19 as well as for identifying many biomarkers. 18,[20][21][22][23][24] One of the main fields using MS data is metabolomics, which aims to identify and quantify small molecules involved in metabolic reactions. 25 Metabolomics studies have been applied in several areas, especially cancer.…”