‘Proteomics’ is the study of the proteome. Proteome, also known as protein profile is used as the technology to identify the functionality of the proteins expressed in certain conditions or diseases. The proteomic technology also enables us to understand the underlying effect of the protein-protein and protein-nucleic acid interactions as well as the post-translational modifications (Hewick et al., 2003).
Recent proteomic technologies have evolved from a very conventional two dimensional electrophoresis,found by O’Farrell and Klose in 1975,to computational methods coupled with other complementary techniques. These recent upgrades of proteomic technology enables the researchers to identify the potential proteins that is clinically significant.The recent tool of proteomic technology, Mass spectrometry techniques such as nanoflow liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) along with other techniques such as immunocapture platforms have enabled high-throughput analysis of a proteome or functional subsets of the proteome. Protein array technology are also used to study the interaction of proteins with standardized antibodies specific for total and activated protein targets allowing for investigation of pre-selected functional signaling outputs. These tools enables the discovery of novel biomarkers, identify drug targets, design effective drugs, assess drug efficacy and patient response to the therapyn short understanding the underlying activity of proteins by the means of proteomic permits us to intensify the discovery and development of drugs ( Walgen et al, 2004).
Traditionally, drug discovery and development has been sculptured based on “one drug for all”. These method targets the disease condition rather than individual patient management. However, the clinical prognosis manifest different profiles for majority of patients. These opens a new paradigm on target therapy which required development and discovery of new target therapy drugs.In conclusion, proteome analysis during preclinical or clinical development may allow the discovery of candidate markers for the prediction of drugs efficacy (Kelloff et al., 2005). Table 1 shows examples of a few disease related biomarkers.
Disease Clinical Biomarker
Alzheimer’s Disease Sulfatide, amyloid precursor, glycerophosphocholine and Tau proteins in CSF; Cystatin C and peptic fragment of the neurosecretory protein VGF Protein kinase C in red blood cells
Multiple Sclerosis CSF cystatin C and matrix metalloproteinases in serum
Breast Cancers HER-2/neu oncoprotein and tumor-specific glycoproteins Gefitinib Resistance Hypoxia-inducible factor-1 in head and neck cancer, epithelial membrane protein-1
Traumatic Brain Injury C-tau, hyperphosphorylated axonal neuro-filment protein and serum S100B
Advanced Breast Cancer Cdk6 and serum CA 15-3 for prognosis
Metastasic Breast Cancer Protein kinase C
Stroke Lipoprotein associated phospholipase-A2, intracellular adhesion molecule 1, PARK7 and nucleoside diphosphate kinase-A
Gliomas Receptor protein tyrosine phosphatase-B
Ischemic Heart Disease Troponin, natriuretic peptide, creatine kinase, myoglobin and fatty acid binding protein
Congestive Heart Failure G protein-coupled receptor kinase-2
Table. 1: List of biomarkers identified for diagnosis of several diseases (Chen et al., 2004; Meuwis et al., 2007; Ornstein et al., 2006; Sinha et al., 2007).
Examples of studies conducted to prove the co-relation of drug development with biomarkers are well establishedd. Carey et al examined 80 validated proteins from signaling pathways in advanced-stage ovarian carcinoma cases using the Reverse Phase Protein Array to identify expression of proteins associated with response to primary chemotherapy drug. Normalization of CA125, an established biomarker, by the 3rd cycle of platinum-based chemotherapy was chosen as the primary outcome measure of response. The outcome of the study indicates the secretion of cytokine Tumour Growth Factor-? pathway signaling strongly with chemoresistance. These indications are crucial for individual patient target and asses better therapeutic prognosis.
Another example would be HER2. HER2 is a successful target for three FDA-approved agents, trastuzumab, pertuzumab, and lapatinib. These targets have been proved to fulfil all 4 FDA criteria; identification of target, activation of the target, alteration of target by intervention and lastly target alteration associated with the clinical outcome (refer table 2).Hence, it is proven that when HER2 is amplified in most cases, it also is activated. The agents inhibit this activation and have been shown to be clinically valuable.A few trials are being conducted to evaluate selective targets using proteomic profiling to develop the knowledge required to optimally direct biomarker and therapeutic development.HER2 is regarded as one of the the most successful molecular targets.
Table 2: Four criteria and examples for credentialing therapeutic targets.
The target was present. Rheumatoid arthritis
TNF? overexpression was present and was etiologic in driving local inflammation and tissue destruction
The target was activated. Crohn’s disease
TNF? overexpression was a driving event.
The target was altered by the intervention. Ovarian cancer
Ras/Raf/ERK pathway was altered by sorafenib, a c-RAF kinase inhibitor.
The target alteration was associated with the clinical outcome. Breast cancer
HER2 amplification was associated with improved survival by trastuzumab, an anti-HER2 neutralizing antibody.