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BIOMARKER DISCOVERY: AN ARRAY OF POTENTIAL

Page 3 Page 4 Page 5 Page 6 Candidate Screening: Journey of a A Multiplexed Overcoming Low Abundance with Candidate Approach Bottlenecks in High Sensitivity Cancer Treatment BROADEN YOUR PERSPECTIVE See up to 2000 proteins at a glance.

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Explore an extensive panel of metabolic enzymes, structural proteins, epigenetic markers, hormones, and neuroregulatory factors – in addition to our popular list of cytokines, growth factors, receptors, adipokines, proteases, and signaling proteins.

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Candidate Screening: Low Abundance with High Sensitivity

hen processes regulating life – such as growth, of mass spectrometry instruments. Large-panel arrays allow reproduction, and movement – go awry, disease researchers with modest budgets to screen for hundreds Wcan result. Chemical moieties become imbalanced of potential , including cytokines, chemokines, in these disease states, often resulting in measurable levels of and other secreted molecules that could be missed through certain signature molecules, termed biomarkers. Biomarker traditional proteomics approaches. discovery has traditionally been performed through A Streamlined Workflow: From Discovery to proteomic approaches. However, these techniques have been limited in their ability to detect low abundance molecules. Validation Moreover, they are generally unable to scan for chemokines, Once thought of as being too narrow in scope for the biomarker cytokines, growth factors, and other secreted molecules. discovery phase, arrays containing a thousand or more Antibody arrays can overcome many of these issues and are now routinely used, enabling the researcher have become a more utilized proteomics approach in recent to target a broad selection of candidate markers with known years, thanks largely to intensified efforts to test and validate importance in many key cellular pathways and diseases. Thus, antibody pairs, facilitating the development of broad, high- antibody arrays may be used either alone or in tandem with throughput screens. MS data to perform the initial biomarker screen. The array offers an additional advantage: the ability to streamline the Complementing Traditional Biomarker Discovery biomarker workflow, from discovery to validation, by making Techniques use of common antibodies across multiple assays.

Traditional proteomic methods, such as 2-D gel MS-based biomarker verification usually involves a targeted electrophoresis and mass spectrometry (MS, including liquid approach, such as multiple-reaction-monitoring (MRM). chromatography-MS; LC-MS), have become indispensable Array-based biomarker verification instead makes use of tools in biomarker discovery. These techniques have smaller quantitative arrays (multiplex ELISAs) containing particularly advanced discovery. The a panel of analytes identified by the initial screening array. unbiased nature of mass spectrometry-based screens makes Because smaller antibody arrays are relatively quick to them ideal techniques for mining protein targets that don't produce, and the antibodies don’t need to be developed from have antibodies or other affinity reagents available. In recent scratch, the verification stage can begin quickly. years, significant efforts have been made to improve MS-based approaches in an effort to overcome associated biomarker- The final step in the biomarker journey, validation, requires discovery challenges (e.g., the need to perform high- assessment of biomarker performance in a large cohort study throughput assays and the wide dynamic range of biomarker in the target population. Array-based technology again allows candidate concentrations in the human body)1. this stage to be simplified, permitting the use of the same antibodies employed in the verification stage. However, due to ion suppression, certain secreted and low abundance biomarkers can be missed using MS- or 2-D gel- Sensitive and High-Throughput techniques, and different approaches and equipment are required to fully mine the proteome for these biomarkers. Furthermore, Multiplex immunoassays offer high detection sensitivity (as the cost of equipment, need for highly trained personnel, low as 1 pg/ml). Furthermore, antibody arrays are adaptable and high costs per sample tested can be prohibitive to many to high-throughput analysis, and the choice of array platforms researchers wanting to use traditional proteomic methods. offered is large and always expanding. The development of high-density arrays has placed the technique securely into the High-density antibody array screening, that is, using antibody spotlight when it comes to antibody discovery and validation, panels with more than 200 markers, requires minimal training making antibody arrays a perfect complement to traditional to use; moreover, capital equipment requirements (microarray proteomic techniques. scanners or CCD cameras) represent a fraction of the cost For references, please see page 7.

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Potential biomarkers for a particular disease or condition must first be discovered: high-density screening antibody arrays are an excellent tool for this stage, allowing researchers to profile hundreds of disease-related proteins simultaneously with minimal material and cost.

For biomarker candidate validation and verification, multiplex antibody arrays or single-target ELISAs are a logical choice: there is no need to develop new antibodies or immunoassays for validation or clinical applications using an antibody array approach.

HIGH-DENSITY SCREENING ARRAY • Phosphoproteins ANTIGENS FROM PATIENT SERA • Glycoproteins • Proteins (Antigens)

candidate identification

Multiplex antibody array • Quantitative

clinical Application • Diagnose and monitor disease • Potential therapeutic target

candidate Validation candidate Verification • No need to develop new assay BIOMARKER DISCOVERY: AN ARRAY OF POTENTIAL

A Multiplexed Approach

ore and more studies are finding that a single (antigens), glycoproteins, phosphoproteins, and many other cytokine or other chemical moiety is insufficient moieties. With the number of validated antibodies growing every Mfor use as a true disease biomarker, and that a more year, the gap in target throughput between arrays and mass global perspective is needed to truly understand the presence spectrometry continues to narrow. Antibody arrays are designed or development, of disease. High-density multiplexed with a pre-selected panel of antibodies that target markers antibody arrays that can now contain 2,000 antibodies or having known or suspected relevance in many disease processes. more in a single panel, combined with an ever-increasing Thus, this targeted approach can efficiently identify proteins pool of validated antibodies, puts arrays at the forefront of that are more likely to be effective biomarkers. Furthermore, biomarker discovery and development, and makes finding their high sensitivity makes them ideal for identifying secreted multiple biomarkers more accessible than ever before. molecules that may, in combination with other moieties, provide the global perspective necessary to tailor therapeutic regimes. Evolution of the Antibody Array Arrays in Precision Medicine Microarrays were first conceptualized in the early 1980s by Dr. Tse Wen Chang, who demonstrated that 20x20 grids of For precision medicine, antibody arrays are proving to be antibody spots could be placed on a small surface1. Antibody fundamental for the diagnosis and treatment of disease. For array models were further developed by Dr. Roger Ekins and example, high-density arrays were used to better characterize colleagues in the late 1980s when they created a model that the expression levels of 200 human cytokines, leading to the permitted simultaneous screening of an analyte panel2. Initial identification of a common cytokine signature and guiding concepts tried to miniaturize immunological assays and were the diagnosis of a patient with idiopathic uveitis. Personalized normally performed in 96-well plates. However, glass slides and treatment reversed the vision loss, illustrating how arrays may membranes were soon found to be better substrates for placing assist in individualizing therapy4. Using a similar approach, minute antibody spots, as they could accommodate larger arrays. another study identified serum proteins that could potentially identify patients who would respond to ipilimumab, a targeted In late 2000, the idea of simultaneously detecting multiple melanoma therapy5. cytokines came to fruition in the mind of Dr. Ruo-Pan Huang at Emory University, who developed nitrocellulose membrane- Uncovering New Drug Targets based antibody arrays as a strategy to increase the efficiency of profiling blood proteins. Dr. Huang began developing antibody Antibody arrays, with their high-throughput multiplexed design, arrays to replace cumbersome and expensive biochemical are a tool for biomarker discovery and not only offer insight into techniques such as single-target ELISAs and Western blots, disease, but also help mine potential new drug targets. From first publishing a paper about the new technique in 2001 asthma6 to renal cell carcinoma7, neurological dysfunction8 to titled “Simultaneous detection of multiple cytokines from end-stage heart failure9, antibody arrays have been successful in conditioned media and patient’s sera by an antibody-based discovering biomarkers in many disease areas. protein array system3." Multiplexed immunoassays can be applied in multiple aspects Following this publication, Dr. Huang received numerous of the drug discovery process, including in target identification, requests for his antibody arrays from other researchers, leading investigating mechanisms of drug resistance, elucidating the him to found RayBiotech, which provided the first commercially molecular mechanisms of drug action, understanding drug side available cytokine arrays to the research community. effects, and in clinical trials and managing patient care10.

The Growth of Arrays For references, please see page 7. Today, antibody arrays containing 2,000 antibodies in a single panel are available. Screening antibody arrays can target proteins

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Overcoming Bottlenecks in Cancer Treatment

ince their introduction into mainstream research labs, antibody Cancer-Drug Resistance: Overcoming Bottlenecks arrays have accelerated biomarker research. Array-based Sbiomarker discovery has shown particular promise in the field Drug resistance is a bottleneck in cancer treatment, that is sometimes of cancer research, where unique cytokine “biosignatures” have been caused by innate resistance within the tumor microenvironment linked with certain cancers. Antibody arrays have also proven useful (TME). Although the growth- and metastasis-promoting effects of the in providing insight into cancer mechanisms and in overcoming the TME have been well documented, its role in drug resistance has only bottleneck associated with innate resistance. been partially explored. Antibody arrays have been used to identify secreted factors in stromal cell culture that contributed to cancer drug Accelerating Cancer Biomarker Discovery resistance, revealing targets for combination therapies with increased Protein and antibody arrays represent new opportunities to profile efficacy. protein expression levels in patients suffering from various cancers. In a study by Straussman et al., 45 different cancer cell lines treated with Arrays are used to identify protein panels, which can be used as 35 distinct anti-cancer drugs were cultured with 23 different stromal biosignatures for clinical diagnosis, disease classification, disease cell lines12. Strikingly, the researchers found that 16 of the 35 drugs prediction, drug development, and for optimizing patient care. tested were rendered ineffective by the presence of stromal cells; the Arrays have already proven their worth in the cancer biomarker field effect was particularly pronounced for targeted drugs as opposed to for a myriad of cancers. In a study by Jiang et al., arrays were used conventional cytotoxic agents. From here, they further studied RAF to identify five serum protein markers (MSPa, TIMP-4, PDGF-Ra, inhibitor PLX4720 and its resistance in BRAF-mutant melanoma OPG, and CA125) that could effectively detect ovarian cancer with cell lines, discovering that the stromal cell-preconditioned medium high specificity and high sensitivity1. Vasquez-Martin et al. identified was sufficient to confer resistance to melanoma cells, suggesting a a panel of cytokine biomarkers from the IL-8 and GRO chemokine secreted factor was driving resistance. Using a custom label-based families, which may be useful for monitoring breast cancer responses array that detected 567 proteins, the researchers identified a single to endocrine treatments and/or HER2-targeted therapies2. A stomach factor, hepatocyte growth factor (HGF), that was confirmed to be cancer biosignature was put forward by Cui et al., where antibody implicated in melanoma drug resistance. These findings support arrays were used to identify 67 out of 136 computationally predicted the clinical relevance of HGF-mediated resistance to BRAF (proto- potential serum biomarkers, of which 24 were found to be abundant oncogene B-Raf) inhibitors; the authors suggest that combination in cancer patients versus the control group3. Hong et al. also used therapy with MET and RAF inhibitors could be effective for BRAF- 12 antibody arrays to validate computationally predicted markers mutant melanomas . excreted into urine for gastric cancer patients4. Other cancers for The TME is an important but understudied source of anti-cancer drug which antibody arrays have helped to discover biomarker signatures resistance, but high-density arrays are incredibly useful tools for further include lung5, colon6, prostate7, glioblastoma8, renal cell carcinoma9, uncovering the TME’s secrets. With further insights into the secretion and HBV-related hepatocellular carcinoma10. profiles of the tumor stroma, more effective targeted therapies can be Phosphorylated Proteins: Insight into Cancer developed and prescribed to the right patient. Mechanisms For references, please see page 7. Antibody arrays are not only pivotal in helping to discover biomarkers for cancers, but also in elucidating cancer mechanisms. In a study by Al-Aidaroos et al., antibody arrays against 71 unique tyrosine kinases (RTK activation study) and 41 unique growth factors (secreted growth factor analysis) were used to help identify PRL-3-driven EGFR hyperactivation and consequential to EGFR signaling, opening new avenues for inhibiting PRL-3-driven cancer progression11. The authors propose that elevated PRL-3 expression is an important clinical predictive biomarker for favorable anti-EGFR cancer therapy.

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References serum is a novel prognostic marker and predicts recurrence Article 1 - Candidate Screening: Low of liver metastases in patients,” Ann Surg Abundance with High Sensitivity Oncol, 19(3):518-527, 2012. 7. K. Fujita et al., “Cytokine profiling of prostatic fluid from 1. H. Wang et al., “The clinical impact of recent advances in cancerous prostate glands identifies cytokines associated LC-MS for cancer biomarker discovery and verification,” with the extent of tumor and ,” The Prostate, Expert Rev Proteomics, 13(1):99-114, 2016. 68(8):872-882, 2008. 8. M. Crocker et al., “Serum angiogenic profile of patients with Article 2 - A Multiplexed Approach glioblastoma identifies distinct tumor subtypes and shows that TIMP-1 is a prognostic factor,” Neuro Oncol, 13(1):99- 1. T.W. Chang, “Binding of cells to matrixes of distinct 108, 2011. antibodies coated on solid surface,” J Immunol Methods, 65(1– 9. J.L. Perez-Garcia et al., “Identification of TNF-α and MMP- 2): 217-223, 1983. 9 as potential baseline predictive serum markers of sunitinib 2. R.P. Ekins, “Multi-analyte immunoassay,” J Pharm Biomed activity in patients with renal cell carcinoma using a human , 7(2):155-168, 1989. Anal cytokine array,” Brit J Cancer, 101:1876-1883, 2009. 3. R-P. Huang et al., “Simultaneous detection of multiple 10. T. Liu et al., “Rapid determination of serological cytokine cytokines from conditioned media and patient's sera by an biomarkers for hepatitis B virus-related hepatocellular antibody-based protein array system,” , 294.1: Anal Biochem carcinoma using antibody microarrays,” Acta Biochim Biophys 55-62, 2001. Sin (Shanghai), 43(1):45-51, 2011. 4. G. Velez et al., “Precision medicine: personalized proteomics 11. A.Q. Al-Aidaroos et al., “Metastasis-associated PRL-3 for the diagnosis and treatment of idiopathic inflammatory induces EGFR activation and addiction in cancer cells,” J disease,” , 134(4):444-448, 2016. JAMA Ophthalmol Clin Invest, 123(8):3459-3471, 2013. 5. K. Homicsko et al., “Baseline serum predictors of clinical 12. R. Straussman et al., “Tumor micro-environment elicits response to CTLA4 inhibitor therapy in melanoma innate resistance to RAF inhibitors through HGF patients”, ,33:15_suppl, 3025-3025, 2015. J Clin Oncol secretion,” Nature, 487:500-504, 2012. 6. A.T. Hastie et al., “Analysis of asthma severity phenotypes by sputum granulocytes,” J Allerg Clin Immunol, 125(5):1028- 1036.e13, 2010. 7. J.L. Perez-Gracia et al., “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, 2009. 8. G.W. Hergenroeder et al., “Serum IL-6: a candidate biomarker for intracranial pressure elevation following isolated traumatic brain injury,” J Neuroinflamm, 7:19, 2010. 9. Y. Wei et al., “Type-specific dysregulation of matrix metalloproteinases and their tissue inhibitors in end-stage patients: relationship between MMP-10 and LV remodeling,” J Cell Mol Med, 15(4):773-782, 2011. 10. W. Huang et al.,“Integration of antibody array technology into drug discovery and development,” Assay Drug Dev Technol, 16(2):74-95, 2018.

Article 3 - Overcoming Bottlenecks in Cancer Treatment 1. W. Jiang et al., “Identification of five serum protein markers for detection of ovarian cancer by antibody arrays,” PLoS ONE, 8(10): e76795, 2013. 2. A. Vazquez-Martin et al., “Her-2/neu-induced “Cytokine Signature” in Breast Cancer,” in: Hormonal Carcinogenesis V, editor: Springer New York, pp. 311-319, 2008. 3. J. Cui et al., “An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer,” Nucl Acids Res, 39(4):1197-1207, 2011. 4. C.S. Hong et al., “A computational method for prediction of excretory proteins and application to identification of gastric cancer markers in urine,” PLoS ONE, 6(2): e16875, 2011. 5. Z. Cai et al., “Monocyte chemotactic protein 1 promotes lung cancer-induced bone resorptive lesions in vivo,” Neoplasia, 11(3):228-236, 2009. 6. K. Matsushita et al., “Soluble CXCL16 in preoperative

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