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Innovative Solutions for Biomarker Discovery
RayBiotech's Innovative and cost-effective solutions for biomarker discovery
RayBiotech has developed an innovative platform for biomarker discovery and validation. The cost, specialized equipment and training and required for biomarker discovery using mass spectrometry and 2-D gel electrophoresis is prohibitive to most researchers. However, using our high-density arrays, researchers with modest budgets can screen for hundreds of potential cytokine biomarker candidates to find the most promising ones for further investigation, much faster than with traditional proteomic methods and at a fraction of the cost.
Biomarker Discovery: Traditional vs. Array-based Workflow
Limitations of Traditional Proteomic Approaches
Traditional proteomic approaches are often called “unbiased” because they detect peptide fragments from a wide range of proteins, with no pre-determined hypothesis as to which proteins may be differentially expressed. In reality, the sensitivity of LC/MS/MS assays is poor (>1,000 pg/ml), and detection is therefore biased toward more abundant proteins. Additionally, mass spec-based proteomics require expensive instruments and highly trained personnel to operate them. Moreover, these approaches are low throughput and have extremely high costs per sample tested.
Most biomarkers identified using traditional proteomic approaches are novel proteins, many of which have no commercially available antibody or immunoassay. Most biomarker candidates are validated and intended for clinical testing with antibody-based techniques, primarily single-target ELISAs, which are considered the gold standard of protein detection and commonly used in clinical diagnostics. While much effort has been made to develop mass-spec based assays, progress in implementation of these assays into the clinical setting has been slow and without much success.
RayBiotech’s Antibody Arrays Represent a Unique Approach to Biomarker Development
In contrast to 2-D gels and LC/MS, antibody arrays are much more sensitive (>1 pg/ml), making them ideal for identifying cytokines, chemokines, growth factors and other secreted molecules that would be missed by these traditional proteomic techniques. RayBiotech’s antibody arrays are also easily adaptable to high-throughput applications. Moreover, since the same antibodies in our screening arrays are also used in our quantitative arrays, there is no need to create an antibody or develop a new immunoassay to validate your biomarker candidates. Thus, antibody arrays can speed up the transition from biomarker discovery to biomarker validation.
RayBiotech offers more choices of array platforms and detectable targets than any of our competitors. Most of them only offer a single platform with limited choices of targets. Few of them offer antibody array panels suitable for biomarker screening In addition to our screening arrays, we offerquantitative multiplex arrays as well as single target ELISAs that (in most cases) use the same antibodies, making RayBiotech’s approach ideal for effective and efficient discovery and validation of biomarker candidates.
Examples of Biomarker Discovery with RayBiotech’s Antibody Arrays
More and more, researchers are relying on RayBiotech’s antibody arrays to accelerate their biomarker research. Unique cytokine “biosignatures” have been identified as being associated with various cancers using our antibody array technologies, including cancers of the breast (Vasquez-Martin 2008), lung (Cai 2009), bladder (Perez-Gracia 2009), stomach (Cui 2011; Hong, 2011), colon (Matsushita 2011) and prostate (Fujita 2008), as well as glioblastoma (Crocker 2010) and renal cell carcinoma (Vasquez-Martin 2008) and HBV-related hepatocellular carcinoma.
In a seminal article in Nature Medicine (Ray 2007), the authors demonstrated the use of our C-Series 1000 arrays to identify a panel of 18 plasma proteins that could distinguish, in blinded samples, those patients with Alzheimer’s disease from those with other types of dementia with nearly 90% accuracy. The authors used the same antibody arrays to test plasma samples taken from patients with mild cognitive impairment presenting 2-6 years before a clinical diagnosis of dementia, some due to Alzheimer’s, some not. Using the 18-marker panel, they were able to correctly identify those patients who ultimately were diagnosed with Alzheimer’s with 80% accuracy. This article provided an excellent example of the techniques of using antibody arrays in biomarker discovery, making it a road map for others to follow.
Similarly, researchers have reported success in finding biomarker candidates with our antibody arrays for many other diseases, including asthma (Hastie 2010; Matsunaga 2009) ), chronic obstructive pulmonary disease (Chen 2012), abdominal aortic aneurysms (Ramos-Mozo 2012), end-stage heart failure (Wei 2011), traumatic brain injury (Hergenroeder 2010) and graft-versus-host disease.
RayBiotech is also demonstrating the effectiveness of our antibody arrays in our own biomarker discovery investigations. In 2010, we published an article in which we describe the use of our own Biotin Label-based Human Cytokine Array 1, which contains antibodies to 507 human proteins, to discover a 5-marker panel that was able to distinguish serum samples that came from patients with ovarian cancer or normal controls with 94% accuracy (Huang 2010).
These are but a few examples of the power of our antibody array technologies in biomarker discovery. If you would like more information on our products and services for biomarker discovery, please contact us (firstname.lastname@example.org)
Cai Z, Chen Q, Chen J, Lu Y, Xiao G, Wu Z, et al. Monocyte chemotactic protein 1 promotes lung cancer-induced bone resorptive lesions in vivo. Neoplasia 11(3): 228-236. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2647725/
Chen H, Wang Y, Bai C, Wang X. (2012) Alterations of plasma inflammatory biomarkers in healthy and chronic obstuctive pulmonary disease patients with or without acute exacerbation. J Proteom. http://dx.doi.org/10.1016/j.jprot.2012.01.027 http://www.sciencedirect.com/science/article/pii/S187439191200067X
Cui J, Chen, Y, Chou W-C, Sun L, Chen L, Suo J, et al. (2011). An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer. Nucl Acids Res. 39(4):1197-1207. http://nar.oxfordjournals.org/content/39/4/1197.full
Crocker M, Ashley S, Giddings I, Petrik V, Hardcastle A, Aherne W, et al. (2011). Serum angiogenic profile of patients with glioblastoma identifies distinct tumor subtypes and shows that TIMP-1 is a prognostic factor. Neuro Oncol. 13(1): 99-108. http://neuro-oncology.oxfordjournals.org/content/13/1/99.short
Fujita K, Ewing CM, Sokoll LJ, Elliott DJ, Cunningham M, De Marzo AM, Isaacs WB, Pavlovich CP. (2008). Cytokine profiling of prostatic fluid from cancerous prostate glands identifies cytokines associated with the extent of tumor and inflammation. The Prostate. 68(8): 872-882. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2562260/
Hastie AT, Moore WC, Meyers DA, Vestal MS, Li H, Peters SP, Bleecker ER. (2010). Analysis of asthma severity phenotypes by sputum granulocytes. J Allerg Clin Immunol. 125(5): 1028-1036.e13. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2878277/
Hergenroeder GW, Moore AN, McCoy JP, Samsel L, Ward NH, Clifton GL, Dash PK. Serum IL-6: a candidate biomarker for intracranial pressure elevation following isolated traumatic brain injury. J Neuroinflamm. 7:19. http://www.jneuroinflammation.com/content/7/1/19
Hong CS, Cui J, Ni Z, Su Y, Puett D, Li F, Xu Y. (2011). A computational method for prediction of excretory proteins and application to identification of gastric cancer markers in urine. PLoS ONE. 6(2): e16875. doi:10.1371/journal.pone.0016875. http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0016875
Huang R, Jiang W, Yang J, Mao YQ, Zhange Y, Yang W, et al. (2010). A biotin label-based antibody array for high content profiling of protein expression. Cancer Genom Proteom. 7(3): 129-141. http://cgp.iiarjournals.org/content/7/3/129.short
Matsunaga K, Ichikawa T, Tanagisawa S, Akamatsu K, Koarai A, Hirano T, et al. (2009). Clinical application of exhaled breath condensate analysis in asthma: Prediction of FEV1 improvement by steroid therapy. Respiration. 78(4); 393-398. http://content.karger.com/ProdukteDB/produkte.aspAktion=ShowFulltext&ArtikelNr=243551&Ausgabe=253620&ProduktNr=224278
Matsushita K, Toiyama Y, Tanaka K, Sigusa S, Hiro J, Uchida K, Inoue Y, Kusunoki M. (2011). Soluble CXCL16 in preoperative serum is a novel prognostic marker and predicts recurrence of liver metastases in colorectal cancer patients. Ann Surg Oncol. doi: 10.1245/s10434-011-1993-8 http://www.springerlink.com/content/h1m6214096776381/
Perez-Gracia JL, Prior C, Guillen-Grima F, Segura V, Gonzalez A, Panizo A, et al. (2009). Identification of TNF-α and MMP-9 as potential baseline predictive serum markers of sunitinib activity in patients with renal cell carcinoma using a human cytokine array. Brit J Cancer. 101; 1876-1883. http://www.nature.com/bjc/journal/v101/n11/abs/6605409a.html
Ramos-Mozo P, Rodriquez C, Pastor-Vargas C, Blanco-Colio LM, Martinez-Gonzalez J, Meilhac O, et al. (2012). Plasma profiling by a protein array approach identifies IGFBP-1 as a novel biomarker of abdominal aortic aneurysm. Atheroscler. http://dx.doi.org/10.1016/j.atherosclerosis.2012.01.009 http://www.sciencedirect.com/science/article/pii/S0021915012000135
Vasquez-Martin A, Colomer R, Menendez JA. (2008). Her2/neu-induced “cytokine signature in breast cancer. In: Li JJ, Li SA, Mohla S, Rochefort and Maudelonde T, eds. Hormonal Carcinogenesis V. Advances in Experimental Medicine and Biology, volume 617, part 10. New York, NY; Springer; 311-319. http://www.springerlink.com/content/n30tr422275103x6/
Wei Y, Chi C, Lainscak M, Zhang X, Li J, Huang J, et al. (2011). Type-specific dysregulation of matrix metalloproteinases and their tissue inhibitors in end-stage heart failure patients : relationship between MMP-10 and LV remodeling. J Cell Mol Med. 15(4): 773-782. http://onlinelibrary.wiley.com/doi/10.1111/j.1582-4934.2010.01049.x/abstract