Proteomics-based anticancer drug discovery and development

Pectolinarigenin regulates the tumor-associated proteins in AGS-xenograft BALB/c nude mice

BACKGROUND

Pectolinarigenin (PEC) is a flavone extracted from Cirsium, and because it has anti-inflammatory properties, anti-cancer research is also being conducted. The objective of this work was to find out if PEC is involved in tumor control and which pathways it regulates in vivo and in vitro.

METHODS

AGS cell lines were xenografted into BALB/c nude mice to create tumors, and PEC was administered intraperitoneally to see if it was involved in tumor control. Once animal testing was completed, tumor proteins were isolated and identified using LC-MS analysis, and gene ontology of the found proteins was performed.

RESULTS

Body weight and hematological measurements on the xenograft mice model demonstrated that PEC was not harmful to non-cancerous cells. We found 582 proteins in tumor tissue linked to biological reactions such as carcinogenesis and cell death signaling. PEC regulated 6 out of 582 proteins in vivo and in vitro in the same way.

CONCLUSION

Our findings suggested that PEC therapy may inhibit tumor development in gastric cancer (GC), and proteomic research gives fundamental information about proteins that may have great promise as new therapeutic targets in GC.

Exploring different approaches to improve the success of drug discovery and development projects: a review

Background

There has been a significant increase in the cost and timeline of delivering new drugs for clinical use over the last three decades. Despite the increased investments in research infrastructure by pharmaceutical companies and technological advances in the scientific tools available, efforts to increase the number of molecules coming through the drug development pipeline have largely been unfruitful.

Main body

A non-systematic review of the current literature was undertaken to enumerate the various strategies employed to improve the success rates in the pharmaceutical research and development. The review covers the exploitation of genomics and proteomics, complementarity of target-based and phenotypic efficacy screening platforms, drug repurposing and repositioning, collaborative research, focusing on underserved therapeutic fields, outsourcing strategy, and pharmaceutical modeling and artificial intelligence. Examples of successful drug discoveries achieved through application of these strategies are highlighted and discussed herein.

Conclusions

Genomics and proteomics have uncovered a wide array of potential drug targets and are facilitative of enhanced scrupulous target identification and validation thus reducing efficacy-related drug attrition. When used complementarily, phenotypic and target-based screening platforms would likely allow serendipitous drug discovery while increasing rationality in drug design. Drug repurposing and repositioning reduces financial risks in drug development accompanied by cost and time savings, while prolonging patent exclusivity hence increased returns on investment to the innovator company. Equally important, collaborative research is facilitative of cross-fertilization and refinement of ideas, while sharing resources and expertise, hence reducing overhead costs in the early stages of drug discovery. Underserved therapeutic fields are niche drug discovery areas that may be used to experiment and launch novel drug targets, while exploiting incentivized benefits afforded by drug regulatory authorities. Outsourcing allows the pharma industries to focus on their core competencies while deriving greater efficiency of specialist contract research organizations. The existing and emerging pharmaceutical modeling and artificial intelligence softwares and tools allow for in silico computation enabling more efficient computer-aided drug design. Careful selection and application of these strategies, singly or in combination, may potentially harness pharmaceutical research and innovation.

Differential expression of proteomics models of colorectal cancer, colorectal benign disease and healthy controls

BACKGROUND

Colorectal cancer (CRC) is often diagnosed at a late stage with concomitant poor prognosis. The hypersensitive analytical technique of proteomics can detect molecular changes before the tumor is palpable. The surface-enhanced laser desorption/ionization-time of flight-mass spectra (SELDI-TOF-MS) is a newly-developed technique of evaluating protein separation in recent years. The protein chips have established the expression of tumor protein in the serum specimens and become the newly discovered markers for tumor diagnosis. The objective of this study was to find new markers of the diagnosis among groups of CRC, colorectal benign diseases (CBD) and healthy controls. The assay of SELDI-TOF-MS with analytical technique of protein-chip bioinformatics was used to detect the expression of protein mass peaks in the sera of patients or controls. One hundred serum samples, including 52 cases of colorectal cancer, 27 cases of colorectal benign disease, and 21 cases of healthy controls, were examined by SELDI-TOF-MS with WCX2 protein-chips.

RESULTS

The diagnostic models (I, II and III) were setup by analyzed the data and sieved markers using Ciphergen - Protein-Chip-Software 5.1. These models were combined with 3 protein mass peaks to discriminate CRC, CBD, and healthy controls. The accuracy, the sensitivity and the particularity of cross verification of these models are all highly over 80%.

CONCLUSIONS

The SELDI-TOF-MS is a useful tool to help diagnose colorectal cancer, especially during the early stage. However, identification of the significantly differentiated proteins needs further study.

Candidate protein biodosimeters of human exposure to ionizing radiation

PURPOSE

To conduct a literature review of candidate protein biomarkers for individual radiation biodosimetry of exposure to ionizing radiation.

MATERIALS AND METHODS

Reviewed approximately 300 publications (1973 - April 2006) that reported protein effects in mammalian systems after either in vivo or in vitro radiation exposure.

RESULTS

We found 261 radiation-responsive proteins including 173 human proteins. Most of the studies used high doses of ionizing radiation (>4 Gy) and had no information on dose- or time-responses. The majority of the proteins showed increased amounts or changes in phosphorylation states within 24 h after exposure (range: 1.5- to 10-fold). Of the 47 proteins that are responsive at doses of 1 Gy and below, 6 showed phosphorylation changes at doses below 10 cGy. Proteins were assigned to 9 groups based on consistency of response across species, dose- and time-response information and known role in the radiation damage response.

CONCLUSIONS

ATM (Ataxia telengiectasia mutated), H2AX (histone 2AX), CDKN1A (Cyclin-dependent kinase inhibitor 1A), and TP53 (tumor protein 53) are top candidate radiation protein biomarkers. Furthermore, we recommend a panel of protein biomarkers, each with different dose and time optima, to improve individual radiation biodosimetry for discriminating between low-, moderate-, and high-dose exposures. Our findings have applications for early triage and follow-up medical assessments.

A useful model to audit liver resolution from cirrhosis in rats using functional proteomics

BACKGROUND

We conducted a rat cirrhosis and recovery model, on the basis of which proteomics was used to audit liver resolution from cirrhosis.

MATERIALS AND METHODS

Micronodular cirrhosis was established using Sprague-Dawley rats fed thioacetamide, and spontaneous recovery from cirrhosis was acquired after thioacetamide withdrawal.

RESULTS

Over the course of a 2-, 3-, and 6-week recovery, macronodular cirrhosis, uneven liver surface, and nearly normal liver surface were acquired, respectively. Specific liver enzymes, hepatitis activity index, hepatocytes apoptosis index, number of activated Kupffer cells and hepatic stellate cells, and area of fibrosis bands consistently peaked at the end of thioacetamide administration and decreased progressively during the recovery period. mRNA expression of proinflammatory cytokines and proapoptotic molecules peaked around the end of thioacetamide administration and decreased thereafter. Using two-dimensional gel electrophoresis, the seven most upregulated and six most downregulated protein spots were analyzed by matrix-assisted laser desorption/ionization time-of-flight. Of these, GST-P2 and its isoforms, GST-alpha and GST-M, were chosen for further validation using immunohistochemistry. Expression of GST-P peaked at the 2-week recovery, whereas GST-alpha and GST-M remained at strong levels at the 6-week recovery.

CONCLUSIONS

The mechanism of resolution from cirrhosis can be extensively investigated using the presented model which, for example, showed GST isoforms performing their roles at different time phases.

Protein nanotechnology - A powerful futuristic diagnostic technique

Healthcare can be maintained well, when diagnosis is quick, accurate, cost-effective and painless. DNA and RNA based diagnosis may not reveal the right information for certain diseases. Identification and quantification of proteins and their folding mechanism are very important in diagnosis of diseases. Small quantities of proteins, which generally escape from detection and are responsible for the diseases, now can be quantified by protein nanotechniques which aids in the diagnosis. In this review, we have summarized the recent developments in nanotechnologies such as protein microarrays, biosensors etc. and their application in diagnosis of diseases at proteomics level have also been discussed.

Proteomic technologies for cancer target validation

Genomic and proteomic technologies have produced an abundance of drug targets, which is creating a bottleneck in drug development process. There is an increasing need for better target validation for cancer drug development and proteomic technologies are contributing to it. These technologies are compared to enable the selection of the one by matching the needs of a particular project. There are prospects for further improvement, and proteomics technologies will form an important addition to the existing genomic and chemical technologies for target validation.