Biomarkers – Multimedia

Current presentation is dedicated to case studies and illustrates diversity of the projects. Cases representing different projects combine the same analytical platform we utilize for metabolomics study of blood plasma and urine. While pattern recognition presents certain challenges but rather ones that can be resolved, identification of low abundant unknown biomarkers is critical for the field and offers significant technical challenge in spite of considerable progress in modern analytical techn

We used Ciphergen technology based on SELDI TOF-MS (Surface Enhanced Laser Desorption/Ionisation Time-of-Flight Mass Spectrometry) for analysis of protein expression profiles of 105 breast cancer tissue samples. The aim of this study was the identification of single proteins or protein patterns specific for different tumour subgroups, which should take advantage of the biomarker as an alternative to commonly used diagnostic and prognostic characteristics.

Plasma proteins serve as good indicators of disease as there are representative proteins from several cellular processes and thus a potential source for biomarker discovery. The large dynamic range of plasma proteins makes the analysis very challenging, as a large number of low abundance proteins are masked by a few high abundance proteins.

The presence of albumin in the urine of healthy subjects presents a stumbling block in diagnostics putting a question mark on the validity of albumin test for the detection of diabetic nephropathy. Therefore there arises a dire need to hunt for the proteins in the pertinent bio- fluids which can serve as biomarkers.

Proteome Systems has identified TB proteins in sputa and blood of people diagnosed with TB. Several of these proteins have been prioritised for ongoing validation. This involves generation of sensitive antibodies and optimisation of assays for detection of TB antigens in clinical samples. This presentation will discuss our progress in this program and our strategy for incorporation of these markers into a diagnostic test format.

LC-MS based proteomic experiments are used to compare complex biological samples across multiple conditions. Fast, powerful computational tools are needed to explore and detect differences in the areas of Expression Proteomics and Biomarker Discovery. In general, specialized steps are necessary to solve these difficult problems (binning, alignment & normalization, peak picking, relative quantitation, etc.). MS-Xelerator is a collection of software tools dedicated to all of the above tasks.

Caveolin1 (Cav-1) function either as a tumor supressor or as a promoter of metastasis. Overexpresion of cav-1 was correlated with: tumoral grading, proliferration markers (Ki67, p53), serum tumor markers (CEA, CA19.9) and angiogenic markers (VEGF, bFGF).

This study aims to identify protein profiles in breast cancer cells as predictors of chemoresistance by using two-dimensional gel electrophoresis and MALDI-TOF peptide mass fingerprinting. Our findings provide further insights into the complex mechanisms of chemoresistance, as well as representing an attractive starting point for the identification of potential protein biomarkers to predict response to chemotherapy in breast cancer in vivo.

We introduce a unique tool for the determination of relative abundances for human serum biomarkers. Conceptually similar to DNA microarrays, the S&S® Serum Biomarker Chip (SBC) is a single capture antibody array that was developed for comparative analysis of serum samples in order to identify differences or similarities in protein expression profiles.

MicroRNAs (miRNAs) comprise a recently identified class of small, non-protein-coding regulatory molecules that play important roles in many physiologic and pathologic processes, including differentiation, viral infection, and oncogenesis. In cancer, abnormal miRNA expression suggests that these molecules may serve as valuable diagnostic and prognostic molecular signatures.