Current perspectives in cancer proteomics

Breast cancer and protein biomarkers

Breast cancer is a healthcare concern of women worldwide. Despite procedures being available for diagnosis, prognosis and treatment of breast cancer, researchers are working intensively on the disease in order to improve the life quality of breast cancer patients. At present, there is no single treatment known to bring a definite cure for breast cancer. One of the possible solutions for combating breast cancer is through identification of reliable protein biomarkers that can be effectively used for early detection, prognosis and treatments of the cancer. Therefore, the task of identification of biomarkers for breast cancer has become the focus of many researchers worldwide.

Strategies for analysis of the glycosylation of proteins: current status and future perspectives

More than half of human proteins are glycosylated by a bewildering array of complex and heterogeneous N- and O-linked glycans. They function in myriad biological processes, including cell adhesion and signalling and influence the physical characteristics, stability, function, activity and immunogenicity of soluble glycoproteins. A single protein may be glycosylated differently to yield heterogenous glycoforms. Glycosylation analysis is of increasing interest in biomedical and biological research, the pharmaceutical and healthcare industry and biotechnology. This is because it is increasingly apparent that glycosylation changes in diseases, such as cancer, making it a promising target for development of clinically useful biomarkers and therapeutics. Furthermore, as the non-human cells employed in expression systems glycosylate their proteins very differently to human cells, and as glycosylation changes unpredictably under changing environmental conditions, glycans analysis for quality control, optimum efficacy and safety of recombinant glycoproteins destined for human therapeutic use is paramount. The complexities of carbohydrate chemistry make analysis challenging and while there are a variety of robust methodologies available for glycan analysis, there is currently a pressing need for the development of new, streamlined, high throughput approaches accessible to non-specialist laboratories.

Use of Legendre moments for the fast comparison of two-dimensional polyacrylamide gel electrophoresis maps images

In this paper, Legendre moments are calculated to extract the global information from a set of two-dimensional polyacrylamide gel electrophoresis map images. The dataset contains 18 samples belonging to two different cell lines (PACA44 and T3M4) of control (untreated) and drug-treated pancreatic ductal carcinoma cells. The aim of this work was to obtain the correct classification of the 18 samples, using the Legendre moments as discriminant variables. For each image the Legendre moments up to a maximum order of 100 were computed. The stepwise linear discriminant analysis (LDA) was performed in order to select the moments with the highest discriminating power. The results demonstrate that the Legendre moments can be successfully applied for fast classification purposes and similarity analysis.

Study of proteomic changes associated with healthy and tumoral murine samples in neuroblastoma by principal component analysis and classification methods

BACKGROUND

The adrenal gland is the election organ forming primary neuroblastoma (NB) tumours, the most common extracranial solid tumours of infancy and childhood.

METHODS

Samples of adrenal gland belonging to healthy and diseased nude mouse were analysed by 2D gel-electrophoresis. The resulting 2D-PAGE maps were digitized by PDQuest and investigated by principal component analysis (PCA).

RESULTS

The analysis of the loadings of the first principal component (PC) permitted the evaluation of the spots characterising each class of samples. Moreover, the soft-independent model of class analogy (SIMCA) method confirmed the separation of the samples in the two classes and allowed the identification of the modelling and discriminating spots. Very good correlation was found between the data obtained by analysis of 2D maps via the commercial software PDQuest and the present PCA analysis. In both cases, the comparison between such maps showed up- and down-regulation of 84 polypeptide chains, out of a total of 700 spots detected by a fluorescent stain, Sypro Ruby. Spots that were differentially expressed between the two groups were analysed by matrix-assisted laser desorption time-of-flight (MALDI-TOF) mass spectrometry and 14 of these spots were identified so far.

The potentials of MS-based subproteomic approaches in medical science: the case of lysosomes and breast cancer

Because of the great number of women who are diagnosed with breast cancer each year, and though this disease presents the lowest mortality rate among cancers, breast cancer remains a major public health problem. As for any cancer, the tumorigenic and metastatic processes are still hardly understood, and the biochemical markers that allow either a precise monitoring of the disease or the classification of the numerous forms of breast cancer remain too scarce. Therefore, great hopes are put on the development of high-throughput genomic and proteomic technologies. Such comprehensive techniques should help in understanding the processes and in defining steps of the disease by depicting specific genes or protein profiles. Because techniques dedicated to the current proteomic challenges are continuously improving, the probability of the discovery of new potential protein biomarkers is rapidly increasing. In addition, the identification of such markers should be eased by lowering the sample complexity; e.g., by sample fractionation, either according to specific physico-chemical properties of the proteins, or by focusing on definite subcellular compartments. In particular, proteins of the lysosomal compartment have been shown to be prone to alterations in their localization, expression, or post-translational modifications (PTMs) during the cancer process. Some of them, such as the aspartic protease cathepsin D (CatD), have even been proven as participating actively in the disease progression. The present review aims at giving an overview of the implication of the lysosome in breast cancer, and at showing how subproteomics and the constantly refining MS-based proteomic techniques may help in making breast cancer research progress, and thus, hopefully, in improving disease treatment.