Use of high density antibody arrays to validate and discover cancer serum biomarkers

Multi-Omic Biomarkers Improve Indeterminate Pulmonary Nodule Malignancy Risk Assessment

The clinical management of patients with indeterminate pulmonary nodules is associated with unintended harm to patients and better methods are required to more precisely quantify lung cancer risk in this group. Here, we combine multiple noninvasive approaches to more accurately identify lung cancer in indeterminate pulmonary nodules. We analyzed 94 quantitative radiomic imaging features and 41 qualitative semantic imaging variables with molecular biomarkers from blood derived from an antibody-based microarray platform that determines protein, cancer-specific glycan, and autoantibody-antigen complex content with high sensitivity. From these datasets, we created a PSR (plasma, semantic, radiomic) risk prediction model comprising nine blood-based and imaging biomarkers with an area under the receiver operating curve (AUROC) of 0.964 that when tested in a second, independent cohort yielded an AUROC of 0.846. Incorporating known clinical risk factors (age, gender, and smoking pack years) for lung cancer into the PSR model improved the AUROC to 0.897 in the second cohort and was more accurate than a well-characterized clinical risk prediction model (AUROC = 0.802). Our findings support the use of a multi-omics approach to guide the clinical management of indeterminate pulmonary nodules.

Differences in Serum Biomarkers Between Combined Glucosamine and Chondroitin Versus Celecoxib in a Randomized, Double-blind Trial in Osteoarthritis Patients

BACKGROUND

Non-steroidal anti-inflammatory drugs, e.g., celecoxib, are commonly used for inflammatory conditions, but can be associated with adverse effects. Combined glucosamine hydrochloride plus chondroitin sulfate (GH+CS) are commonly used for joint pain and have no known adverse effects. Evidence from in vitro, animal and human studies suggest that GH+CS have anti-inflammatory activity, among other mechanisms of action.

OBJECTIVE

We evaluated the effects of GH+CS versus celecoxib on a panel of 20 serum proteins involved in inflammation and other metabolic pathways.

METHODS

Samples were from a randomized, parallel, double-blind trial of pharmaceutical grade 1500 mg GH + 1200 mg CS (n=96) versus 200 mg celecoxib daily (n=93) for 6- months in knee osteoarthritis (OA) patients. Linear mixed models adjusted for age, sex, body mass index, baseline serum protein values, and rescue medicine use assessed the intervention effects of each treatment arm adjusting for multiple testing.

RESULTS

All serum proteins except WNT16 were lower after treatment with GH+CS, while about half increased after celecoxib. Serum IL-6 was significantly reduced (by 9%, P=0.001) after GH+CS, and satisfied the FDR<0.05 threshold. CCL20, CSF3, and WNT16 increased after celecoxib (by 7%, 9% and 9%, respectively, P<0.05), but these serum proteins were no longer statistically significant after controlling for multiple testing.

CONCLUSION

The results of this study using samples from a previously conducted trial in OA patients, demonstrate that GH+CS reduces circulating IL-6, an inflammatory cytokine, but is otherwise comparable to celecoxib with regard to effects on other circulating protein biomarkers.

Proteomic Analysis of Plasma Reveals Fat Mass Influences Cancer-Related Pathways in Healthy Humans Fed Controlled Diets Differing in Glycemic Load

Increased adiposity and diets high in glycemic load (GL) are associated with increased risk of many chronic diseases including cancer. Using plasma from 80 healthy individuals [40 men/40 women, 29 with DXA-derived low fat mass (FM) and 51 with high FM] in a randomized cross-over-controlled feeding trial and arrays populated with 3,504 antibodies, we measured plasma proteins collected at baseline and end of each of two 28-day controlled diets: a low GL diet high in whole grains, legumes, fruits, and vegetables (WG) and a high GL diet high in refined grains and added sugars (RG). Following univariate testing for proteins differing by diet, we evaluated pathway-level involvement. Among all 80 participants, 172 proteins were identified as differing between diets. Stratifying participants by high and low FM identified 221 and 266 proteins, respectively, as differing between diets (unadjusted P < 0.05). These candidate proteins were tested for overrepresentation in Reactome pathways, corresponding to 142 (of 291) pathways in the high-FM group and 72 (of 274) pathways in the low-FM group. We observed that the cancer-related pathways, DNA Repair, DNA Replication, and Cell Cycle, were overrepresented in the high-FM participants while pathways involved in post-translational protein modification were overrepresented in participants with either FM. Although high-GL diets are associated with increased risk of some cancers, our study further suggests that biology associated with consumption of GL diets is variable depending on an individual's adiposity and dietary recommendations related to cancer prevention be made with the additional consideration of an individual's FM.

Tumor-derived Autoantibodies Identify Malignant Pulmonary Nodules

Rationale: Screening for non-small cell lung cancer is associated with earlier diagnosis and reduced mortality but also increased harm caused by invasive follow-up of benign pulmonary nodules. Lung tumorigenesis activates the immune system, components of which could serve as tumor-specific biomarkers. Objectives: To profile tumor-derived autoantibodies as peripheral biomarkers of malignant pulmonary nodules. Methods: High-density protein arrays were used to define the specificity of autoantibodies isolated from B cells of 10 resected lung tumors. These tumor-derived autoantibodies were also examined as free or complexed to antigen in the plasma of the same 10 patients and matched benign nodule control subjects. Promising autoantibodies were further analyzed in an independent cohort of 250 nodule-positive patients. Measurements and Main Results: Thirteen tumor B-cell-derived autoantibodies isolated ex vivo showed greater than or equal to 50% sensitivity and greater than or equal to 70% specificity for lung cancer. In plasma, 11 of 13 autoantibodies were present both complexed to and free from antigen. In the larger validation cohort, 5 of 13 tumor-derived autoantibodies remained significantly elevated in cancers. A combination of four of these autoantibodies could detect malignant nodules with an area under the curve of 0.74 and had an area under the curve of 0.78 in a subcohort of indeterminate (8-20 mm in the longest diameter) pulmonary nodules. Conclusions: Our novel pipeline identifies tumor-derived autoantibodies that could effectively serve as blood biomarkers for malignant pulmonary nodule diagnosis. This approach has future implications for both a cost-effective and noninvasive approach to determine nodule malignancy for widespread low-dose computed tomography screening.

Protein and glycomic plasma markers for early detection of adenoma and colon cancer

OBJECTIVE

To discover and confirm blood-based colon cancer early-detection markers.

DESIGN

We created a high-density antibody microarray to detect differences in protein levels in plasma from individuals diagnosed with colon cancer <3 years after blood was drawn (ie, prediagnostic) and cancer-free, matched controls. Potential markers were tested on plasma samples from people diagnosed with adenoma or cancer, compared with controls. Components of an optimal 5-marker panel were tested via immunoblotting using a third sample set, Luminex assay in a large fourth sample set and immunohistochemistry (IHC) on tissue microarrays.

RESULTS

In the prediagnostic samples, we found 78 significantly (t-test) increased proteins, 32 of which were confirmed in the diagnostic samples. From these 32, optimal 4-marker panels of BAG family molecular chaperone regulator 4 (BAG4), interleukin-6 receptor subunit beta (IL6ST), von Willebrand factor (VWF) and CD44 or epidermal growth factor receptor (EGFR) were established. Each panel member and the panels also showed increases in the diagnostic adenoma and cancer samples in independent third and fourth sample sets via immunoblot and Luminex, respectively. IHC results showed increased levels of BAG4, IL6ST and CD44 in adenoma and cancer tissues. Inclusion of EGFR and CD44 sialyl Lewis-A and Lewis-X content increased the panel performance. The protein/glycoprotein panel was statistically significantly higher in colon cancer samples, characterised by a range of area under the curves from 0.90 (95% CI 0.82 to 0.98) to 0.86 (95% CI 0.83 to 0.88), for the larger second and fourth sets, respectively.

CONCLUSIONS

A panel including BAG4, IL6ST, VWF, EGFR and CD44 protein/glycomics performed well for detection of early stages of colon cancer and should be further examined in larger studies.

Exploratory plasma proteomic analysis in a randomized crossover trial of aspirin among healthy men and women

Long-term use of aspirin is associated with lower risk of colorectal cancer and other cancers; however, the mechanism of chemopreventive effect of aspirin is not fully understood. Animal studies suggest that COX-2, NFκB signaling and Wnt/β-catenin pathways may play a role, but no clinical trials have systematically evaluated the biological response to aspirin in healthy humans. Using a high-density antibody array, we assessed the difference in plasma protein levels after 60 days of regular dose aspirin (325 mg/day) compared to placebo in a randomized double-blinded crossover trial of 44 healthy non-smoking men and women, aged 21-45 years. The plasma proteome was analyzed on an antibody microarray with ~3,300 full-length antibodies, printed in triplicate. Moderated paired t-tests were performed on individual antibodies, and gene-set analyses were performed based on KEGG and GO pathways. Among the 3,000 antibodies analyzed, statistically significant differences in plasma protein levels were observed for nine antibodies after adjusting for false discoveries (FDR adjusted p-value<0.1). The most significant protein was succinate dehydrogenase subunit C (SDHC), a key enzyme complex of the mitochondrial tricarboxylic acid (TCA) cycle. The other statistically significant proteins (NR2F1, MSI1, MYH1, FOXO1, KHDRBS3, NFKBIE, LYZ and IKZF1) are involved in multiple pathways, including DNA base-pair repair, inflammation and oncogenic pathways. None of the 258 KEGG and 1,139 GO pathways was found to be statistically significant after FDR adjustment. This study suggests several chemopreventive mechanisms of aspirin in humans, which have previously been reported to play a role in anti- or pro-carcinogenesis in cell systems; however, larger, confirmatory studies are needed.

Proteomic Analysis, Immune Dysregulation, and Pathway Interconnections with Obesity

Proteomic studies can offer information on hundreds to thousands of proteins and potentially provide researchers with a comprehensive understanding of signaling response during stress and disease. Large data sets, such as those obtained in high-dimensional proteomic studies, can be leveraged for pathway analysis to discover or describe the biological implications of clinical disease states. Obesity is a worldwide epidemic that is considered a risk factor for numerous other diseases. We performed analysis on plasma proteomic data from 3 separate sample sets of postmenopausal women to identify the pathways that are altered in subjects with a high body mass index (BMI) compared to normal BMI. We found many pathways consistently and significantly associated with inflammation dysregulated in plasma from obese/overweight subjects compared to plasma from normal BMI subjects. These pathways indicate alterations of soluble inflammatory regulators, cellular stress, and metabolic dysregulation. Our results highlight the importance of high-dimensional pathway analysis in complex diseases as well as provide information on the interconnections between pathways that are dysregulated with obesity. Specifically, overlap of obesity related pathways with those activated during cancer and infection could help describe why obesity is a risk factor for disease and help devise treatment options that mitigate its effect.

MAPRE1 as a plasma biomarker for early-stage colorectal cancer and adenomas

Blood-based biomarkers for early detection of colorectal cancer could complement current approaches to colorectal cancer screening. We previously identified the APC-binding protein MAPRE1 as a potential colorectal cancer biomarker. Here, we undertook a case-control validation study to determine the performance of MAPRE1 in detecting early colorectal cancer and colon adenoma and to assess the potential relevance of additional biomarker candidates. We analyzed plasma samples from 60 patients with adenomas, 30 with early colorectal cancer, 30 with advanced colorectal cancer, and 60 healthy controls. MAPRE1 and a set of 21 proteins with potential biomarker utility were assayed using high-density antibody arrays, and carcinoembryonic antigen (CEA) was assayed using ELISA. The biologic significance of the candidate biomarkers was also assessed in colorectal cancer mouse models. Plasma MAPRE1 levels were significantly elevated in both patients with adenomas and patients with colorectal cancer compared with controls (P < 0.0001). MAPRE1 and CEA together yielded an area under the curve of 0.793 and a sensitivity of 0.400 at 95% specificity for differentiating early colorectal cancer from controls. Three other biomarkers (AK1, CLIC1, and SOD1) were significantly increased in both adenoma and early colorectal cancer patient plasma samples and in plasma from colorectal cancer mouse models at preclinical stages compared with controls. The combination of MAPRE1, CEA, and AK1 yielded sensitivities of 0.483 and 0.533 at 90% specificity and sensitivities of 0.350 and 0.467 at 95% specificity for differentiating adenoma and early colorectal cancer, respectively, from healthy controls. These findings suggest that MAPRE1 can contribute to the detection of early-stage colorectal cancer and adenomas together with other biomarkers.

Candidate early detection protein biomarkers for ER+/PR+ invasive ductal breast carcinoma identified using pre-clinical plasma from the WHI observational study

Estrogen receptor (ER)-positive/progesterone receptor (PR)-positive invasive ductal carcinoma accounts for ~45 % of invasive breast cancer (BC) diagnoses in the U.S. Despite reductions in BC mortality attributable to mammography screening and adjuvant hormonal therapy, an important challenge remains the development of clinically useful blood-based biomarkers for risk assessment and early detection. The objective of this study was to identify novel protein markers for ER+/PR+ ductal BC. A nested case-control study was conducted within the Women's Health Initiative observational study. Pre-clinical plasma specimens, collected up to 12.5 months before diagnosis from 121 cases and 121 matched controls, were equally divided into training and testing sets and interrogated using a customized antibody array targeting >2000 proteins. Statistically significant differences (P < 0.05) in matched case versus control signals were observed for 39 candidates in both training and testing sets, and four markers (CSF2, RYBP, TFRC, ITGB4) remained significant after Bonferroni correction (P < 2.03 × 10(-5)). A multivariate modeling procedure based on elastic net regression with Monte Carlo cross-validation achieved an estimated AUC of 0.75 (SD 0.06). Most candidates did not overlap with those described previously for triple-negative BC, suggesting sub-type specificity. Gene set enrichment analyses identified two GO gene sets as upregulated in cases-microtubule cytoskeleton and response to hormone stimulus (P < 0.05, q < 0.25). This study has identified a pool of novel candidate plasma protein biomarkers for ER+/PR+ ductal BC using pre-diagnostic biospecimens. Further validation studies are needed to confirm these candidates and assess their potential clinical utility for BC risk assessment/early detection.

Cross-species antibody microarray interrogation identifies a 3-protein panel of plasma biomarkers for early diagnosis of pancreas cancer

PURPOSE

Pancreatic ductal adenocarcinoma (PDA) is the fourth leading cause of cancer-related death in the United States, and its incidence is on the rise. Advanced disease is nearly uniformly lethal, emphasizing the need to identify PDA at its earliest stages. To discover early biomarkers of PDA, we evaluated the circulating proteome in murine preinvasive and invasive plasma samples and human prediagnostic and diagnostic samples.

EXPERIMENTAL DESIGN

Using a customized antibody microarray platform containing >4,000 features, we interrogated plasma samples spanning preinvasive and invasive disease from a highly faithful mouse model of PDA. In parallel, we mined prediagnostic plasma from women in the Women's Health Initiative (WHI) who would later succumb to PDA together with matched, cancer-free control samples. Samples collected after an establishing diagnosis of PDA were also interrogated to further validate markers.

RESULTS

We identified ERBB2 and TNC in our cross-species analyses, and multiple antibodies identified ESR1 in prediagnostic plasma from people that succumb to PDA. This 3-marker panel had an AUC of 0.86 (95% confidence interval [CI], 0.76-0.96) for the diagnostic cohort that increased to 0.97 (95% CI, 0.92-1.0) with CA19-9 included. The 3-marker panel also had an AUC of 0.68 (95% CI, 0.58-0.77) for the prediagnostic cohort.

CONCLUSIONS

We identified potential disease detection markers in plasma up to 4 years before death from PDA with superior performance to CA19-9. These markers might be especially useful in high-risk cohorts to diagnose early, resectable disease, particularly in patients that do not produce CA19-9.

Randomized trial of glucosamine and chondroitin supplementation on inflammation and oxidative stress biomarkers and plasma proteomics profiles in healthy humans

BACKGROUND

Glucosamine and chondroitin are popular non-vitamin dietary supplements used for osteoarthritis. Long-term use is associated with lower incidence of colorectal and lung cancers and with lower mortality; however, the mechanism underlying these observations is unknown. In vitro and animal studies show that glucosamine and chondroitin inhibit NF-kB, a central mediator of inflammation, but no definitive trials have been done in healthy humans.

METHODS

We conducted a randomized, double-blind, placebo-controlled, cross-over study to assess the effects of glucosamine hydrochloride (1500 mg/d) plus chondroitin sulfate (1200 mg/d) for 28 days compared to placebo in 18 (9 men, 9 women) healthy, overweight (body mass index 25.0-32.5 kg/m2) adults, aged 20-55 y. We examined 4 serum inflammatory biomarkers: C-reactive protein (CRP), interleukin 6, and soluble tumor necrosis factor receptors I and II; a urinary inflammation biomarker: prostaglandin E2-metabolite; and a urinary oxidative stress biomarker: F2-isoprostane. Plasma proteomics on an antibody array was performed to explore other pathways modulated by glucosamine and chondroitin.

RESULTS

Serum CRP concentrations were 23% lower after glucosamine and chondroitin compared to placebo (P = 0.048). There were no significant differences in other biomarkers. In the proteomics analyses, several pathways were significantly different between the interventions after Bonferroni correction, the most significant being a reduction in the "cytokine activity" pathway (P = 2.6 x 10-16), after glucosamine and chondroitin compared to placebo.

CONCLUSION

Glucosamine and chondroitin supplementation may lower systemic inflammation and alter other pathways in healthy, overweight individuals. This study adds evidence for potential mechanisms supporting epidemiologic findings that glucosamine and chondroitin are associated with reduced risk of lung and colorectal cancer.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01682694.

Spatiotemporal proteomic analyses during pancreas cancer progression identifies serine/threonine stress kinase 4 (STK4) as a novel candidate biomarker for early stage disease

Pancreas cancer, or pancreatic ductal adenocarcinoma, is the deadliest of solid tumors, with a five-year survival rate of <5%. Detection of resectable disease improves survival rates, but access to tissue and other biospecimens that could be used to develop early detection markers is confounded by the insidious nature of pancreas cancer. Mouse models that accurately recapitulate the human condition allow disease tracking from inception to invasion and can therefore be useful for studying early disease stages in which surgical resection is possible. Using a highly faithful mouse model of pancreas cancer in conjunction with a high-density antibody microarray containing ∼2500 antibodies, we interrogated the pancreatic tissue proteome at preinvasive and invasive stages of disease. The goal was to discover early stage tissue markers of pancreas cancer and follow them through histologically defined stages of disease using cohorts of mice lacking overt clinical signs and symptoms and those with end-stage metastatic disease, respectively. A panel of seven up-regulated proteins distinguishing pancreas cancer from normal pancreas was validated, and their levels were assessed in tissues collected at preinvasive, early invasive, and moribund stages of disease. Six of the seven markers also differentiated pancreas cancer from an experimental model of chronic pancreatitis. The levels of serine/threonine stress kinase 4 (STK4) increased between preinvasive and invasive stages, suggesting its potential as a tissue biomarker, and perhaps its involvement in progression from precursor pancreatic intraepithelial neoplasia to pancreatic ductal adenocarcinoma. Immunohistochemistry of STK4 at different stages of disease revealed a dynamic expression pattern further implicating it in early tumorigenic events. Immunohistochemistry of a panel of human pancreas cancers confirmed that STK4 levels were increased in tumor epithelia relative to normal tissue. Overall, this integrated approach yielded several tissue markers that could serve as signatures of disease stage, including early (resectable), and therefore clinically meaningful, stages.

Plasma protein analysis of patients with different B-cell lymphomas using high-content antibody microarrays

PURPOSE

In this study, plasma samples from a multicentric case-control study on lymphoma were analyzed for the identification of proteins useful for diagnosis.

EXPERIMENTAL DESIGN

The protein content in the plasma of 100 patients suffering from the three most common B-cell lymphomas and 100 control samples was studied with antibody microarrays composed of 810 antibodies that target cancer-associated proteins. Sample pools were screened for an identification of marker proteins. Then, the samples were analyzed individually to validate the usability of these markers.

RESULTS

More than 200 proteins with disease-associated abundance changes were found. The evaluation on individual patients confirmed some molecules as robust informative markers while others were inadequate for this purpose. In addition, the analysis revealed distinct subgroups for each of the three investigated B-cell lymphoma subtypes. With this information, we delineated a classifier that discriminates the different lymphoma entities.

CONCLUSIONS AND CLINICAL RELEVANCE

Variations in plasma protein abundance permit discrimination between different patient groups. After validation on a larger study cohort, the findings could have diagnostic as well as differential diagnostic potential. Beside this, methodological aspects were critically evaluated, such as the value of sample pooling for the identification of biomarkers that are useful for a diagnosis on individual patients.

High-Throughput Analysis of Plasma Hybrid Markers for Early Detection of Cancers

Biomarkers for the early detection of cancer in the general population have to perform with high sensitivity and specificity in order to prevent the costs associated with over-diagnosis. There are only a few current tissue or blood markers that are recommended for generalized cancer screening. Despite the recognition that combinations of multiple biomarkers will likely improve their utility, biomarker panels are usually limited to a single class of molecules. Tissues and body fluids including plasma and serum contain not only proteins, DNA and microRNAs that are differentially expressed in cancers but further cancer specific information might be gleaned by comparing different classes of biomolecules. For example, the level of a certain microRNA might be related to the level of a particular protein in a cancer specific manner. Proteins might have cancer-specific post-translational modifications (e.g., phosphorylation or glycosylation) or lead to the generation of autoantibodies. Most currently approved biomarkers are glycoproteins. Autoantibodies can be produced as a host's early surveillance response to cancer-specific proteins in pre-symptomatic and pre-diagnostic stages of cancer. Thus, measurement of the level of a protein, the level of its glycosylation or phosphorylation and whether autoantibodies are produced to it can yield multi-dimensional information on each protein. We consider specific proteins that show consistent cancer-specific changes in two or three of these measurements to be "hybrid markers". We hypothesize these markers will suffer less variation between different individuals since one component can act to "standardize" the other measurement. As a proof of principle, a 180 plasma sample set consisting of 120 cases (60 colon cancers and 60 adenomas) and 60 controls were analyzed using our high-density antibody array for changes in their protein, IgG-complex and sialyl-Lewis A (SLeA) modified proteins. At p < 0.05, expression changes in 1,070 proteins, 49 IgG-complexes (11 present in the protein list) and 488 Lewis X-modified proteins (57 on the protein list) were observed. The biomarkers significant on both lists are potential hybrid markers. Thus, plasma hybrid markers have the potential to create a new class of early detection markers of cancers.

Discovery of sialyl Lewis A and Lewis X modified protein cancer biomarkers using high density antibody arrays

We report on a high-dimensional method to globally profile glycoproteins that are modified with sialyl Lewis A or Lewis X glycans. Specifically, glycoproteins in serum or plasma are fractionated on a high-density antibody microarray (i.e., each are localized to their specific antibody spot) and are specifically detected via fluorescently labeled anti-sialyl Lewis A or anti-Lewis X antibodies with quantification in a microarray scanner. Non-glycosylated proteins or glycoproteins with other glycan motifs do not interfere with this assay. The whole process is very rapid and applicable for high-throughput screening without the need for purification of glycoproteins from the samples. Using these methods, sialyl Lewis A or Lewis X moieties were found to be expressed on many previously unreported secreted or membrane associated proteins. Furthermore, the combination of sialyl Lewis A or Lewis X content with protein level increased the ability of certain glycoproteins to distinguish 30 patients with stage III and IV colon cancer from 60 control samples. Thus, this highly sensitive method is capable of discovering novel specific glycan modifications on proteins, many of which will likely be useful for disease detection and monitoring.

BIOLOGICAL SIGNIFICANCE

In this paper, we show that we can detect cancer-specific glycan modifications on thousands of proteins using a high-density antibody array paired with a glycan specific antibody to probe the bound glycoproteins. To our knowledge, our array is by far the largest and densest that has ever been used for global profiling of specific glycan modification on proteins. Analysis of colon cancer patient plasma for sialyl Lewis A and Lewis X modifications revealed previously unknown protein carriers of these modifications and significant increases in these specific glycans on some proteins in people with cancer versus healthy controls, suggesting this method could be used to discover novel biomarkers.

High-throughput screening for native autoantigen-autoantibody complexes using antibody microarrays

We report on a novel, high-dimensional method to detect autoantibodies that are complexed with their natural autoantigens. Specifically, autoantibody-autoantigen complexes in serum or plasma are directly incubated onto a high-density antibody microarray. Detection of the bound autoantibody-antigen complex is made via fluorescently labeled antihuman immunoglobulin G or other immunoglobulin isotype secondary antibodies and quantification in a microarray scanner. Uncomplexed antibodies do not interfere with this assay. The whole process is very rapid and applicable for high-throughput screening without the need for production of proteins or immunoglobulin purification from the samples. Using these methods, we found that plasma from healthy individuals contains hundreds of autoantibodies complexed with cellular proteins. Thus, this highly sensitive, multiplex method is capable of discovering new autoantibody-antigen or circulating immune complexes, many of which will likely be useful for disease detection and characterization.

Discovery and preliminary confirmation of novel early detection biomarkers for triple-negative breast cancer using preclinical plasma samples from the Women's Health Initiative observational study

Triple-negative breast cancer is a particularly aggressive and lethal breast cancer subtype that is more likely to be interval-detected rather than screen-detected. The purpose of this study is to discover and initially validate novel early detection biomarkers for triple-negative breast cancer using preclinical samples. Plasma samples collected up to 17 months before diagnosis from 28 triple-negative cases and 28 matched controls from the Women's Health Initiative Observational Study were equally divided into a training set and a test set and interrogated by a customized antibody array. Data were available on 889 antibodies; in the training set, statistically significant differences in case versus control signals were observed for 93 (10.5 %) antibodies at p < 0.05. Of these 93 candidates, 29 were confirmed in the test set at p < 0.05. Areas under the curve for these candidates ranged from 0.58 to 0.79. With specificity set at 98 %, sensitivity ranged from 4 to 68 % with 20 candidates having a sensitivity ≥ 20 % and 6 having a sensitivity ≥ 40 %. In an analysis of KEGG gene sets, the pyrimidine metabolism gene set was upregulated in cases compared to controls (p = 0.004 in the testing set) and the JAK/Stat signaling pathway gene set was downregulated (p = 0.003 in the testing set). Numerous potential early detection biomarkers specific to triple-negative breast cancer in multiple pathways were identified. Further research is required to followup on promising candidates in larger sample sizes and to better understand their potential biologic importance as our understanding of the etiology of triple-negative breast cancer continues to grow.

Protein microarrays for the identification of praja1 e3 ubiquitin ligase substrates

Although they are the primary determinants of substrate specificity, few E3-substrate pairs have been positively identified, and few E3's profiled in a proteomic fashion. Praja1 is an E3 implicated in bone development and highly expressed in brain. Although it has been well studied relative to the majority of E3's, little is known concerning the repertoire of proteins it ubiquitylates. We sought to identify high confidence substrates for Praja1 from an unbiased proteomic profile of thousands of human proteins using protein microarrays. We first profiled Praja1 activity against a panel of E2's to identify its optimal partner in vitro. We then ubiquitylated multiple, identical protein arrays and detected putative substrates with reagents that vary in ubiquitin recognition according to the extent of chain formation. Gene ontology clustering identified putative substrates consistent with information previously known about Praja1 function, and provides clues into novel aspects of this enzyme's function.

State of the art in tumor antigen and biomarker discovery

Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology.

Use of a single-chain antibody library for ovarian cancer biomarker discovery

The discovery of novel early detection biomarkers of disease could offer one of the best approaches to decrease the morbidity and mortality of ovarian and other cancers. We report on the use of a single-chain variable fragment antibody library for screening ovarian serum to find novel biomarkers for the detection of cancer. We alternately panned the library with ovarian cancer and disease-free control sera to make a sublibrary of antibodies that bind proteins differentially expressed in cancer. This sublibrary was printed on antibody microarrays that were incubated with labeled serum from multiple sets of cancer patients and controls. The antibodies that performed best at discriminating disease status were selected, and their cognate antigens were identified using a functional protein microarray. Overexpression of some of these antigens was observed in cancer serum, tumor proximal fluid, and cancer tissue via dot blot and immunohistochemical staining. Thus, our use of recombinant antibody microarrays for unbiased discovery found targets for ovarian cancer detection in multiple sample sets, supporting their further study for disease diagnosis.

Dual-color proteomic profiling of complex samples with a microarray of 810 cancer-related antibodies

Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses.

Up-regulated proteins in the fluid bathing the tumour cell microenvironment as potential serological markers for early detection of cancer of the breast

Breast cancer is by far the most common diagnosed form of cancer and the leading cause of cancer death in women today. Clinically useful biomarkers for early detection of breast cancer could lead to a significant reduction in mortality. Here we describe a detailed analysis using gel-based proteomics in combination with mass spectrometry and immunohistochemistry (IHC) of the tumour interstitial fluids (TIF) and normal interstitial fluids (NIF) collected from 69 prospective breast cancer patients. The goal of this study was to identify abundant cancer up-regulated proteins that are externalised by cells in the tumour microenvironment of most if not all these lesions. To this end, we applied a phased biomarker discovery research strategy to the analysis of these samples rather than comparing all samples among each other, with inherent inter and intra-sample variability problems. To this end, we chose to use samples derived from a single tumour/benign tissue pair (patient 46, triple negative tumour), for which we had well-matched samples in terms of epithelial cell numbers, to generate the initial dataset. In this first phase we found 110 proteins that were up-regulated by a factor of 2 or more in the TIF, some of which were confirmed by IHC. In the second phase, we carried out a systematic computer assisted analysis of the 2D gels of the remaining 68 TIF samples in order to identify TIF 46 up-regulated proteins that were deregulated in 90% or more of all the available TIFs, thus representing common breast cancer markers. This second phase singled out a set of 26 breast cancer markers, most of which were also identified by a complementary analysis using LC-MS/MS. The expression of calreticulin, cellular retinoic acid-binding protein II, chloride intracellular channel protein 1, EF-1-beta, galectin 1, peroxiredoxin-2, platelet-derived endothelial cell growth factor, protein disulfide isomerase and ubiquitin carboxyl-terminal hydrolase 5 were further validated using a tissue microarray containing 70 malignant breast carcinomas of various grades of atypia. A significant number of these proteins have already been detected in the blood/plasma/secretome by others. The next steps, which include biomarker prioritization based on the hierarchal evaluation of these markers, antibody and antigen development, assay development, analytical validation, and preliminary testing in the blood of healthy and breast cancer patients, are discussed.

Oncoproteomic profiling with antibody microarrays

The incidence of cancer and its associated mortality are increasing globally, indicating an urgent need to develop even more effective and sensitive sets of biomarkers that could help in early diagnosis and consequent intervention. Given that many cellular processes are carried out by proteins, cancer research has recently shifted toward an exploration of the full proteome for such discovery. Among the advanced methodologies that are being developed for analyzing the proteome, antibody microarrays have become a prominent tool for gathering the information required for a better understanding of disease biology, early detection, discrimination of tumors and monitoring of disease progression. Here, we review the technical aspects and challenges in the development and use of antibody microarray assays and examine recently reported applications in oncoproteomics.

Targeted proteomic strategy for clinical biomarker discovery

The high complexity and large dynamic range of blood plasma proteins currently prohibit the sensitive and high-throughput profiling of disease and control plasma proteome sample sets large enough to reliably detect disease indicating differences. To circumvent these technological limitations we describe here a new two-stage strategy for the mass spectrometry (MS) assisted discovery, verification and validation of disease biomarkers. In an initial discovery phase N-linked glycoproteins with distinguishable expression patterns in primary normal and diseased tissue are detected and identified. In the second step the proteins identified in the initial phase are subjected to targeted MS analysis in plasma samples, using the highly sensitive and specific selected reaction monitoring (SRM) technology. Since glycosylated proteins, such as those secreted or shed from the cell surface are likely to reside and persist in blood, the two-stage strategy is focused on the quantification of tissue derived glycoproteins in plasma. The focus on the N-glycoproteome not only reduces the complexity of the analytes, but also targets an information-rich subproteome which is relevant for remote sensing of diseases in the plasma. The N-glycoprotein based biomarker discovery and validation workflow reviewed here allows for the robust identification of protein candidate panels that can finally be selectively monitored in the blood plasma at high sensitivity in a reliable, non-invasive and quantitative fashion.

A single lysis solution for the analysis of tissue samples by different proteomic technologies

Cancer, being a major healthcare concern worldwide, is one of the main targets for the application of emerging proteomic technologies and these tools promise to revolutionize the way cancer will be diagnosed and treated in the near future. Today, as a result of the unprecedented advances that have taken place in molecular biology, cell biology and genomics there is a pressing need to accelerate the translation of basic discoveries into clinical applications. This need, compounded by mounting evidence that cellular model systems are unable to fully recapitulate all biological aspects of human dissease, is driving scientists to increasingly use clinically relevant samples for biomarker and target discovery. Tissues are heterogeneous and as a result optimization of sample preparation is critical for generating accurate, representative, and highly reproducible quantitative data. Although a large number of protocols for preparation of tissue lysates has been published, so far no single recipe is able to provide a "one-size fits all" solubilization procedure that can be used to analyse the same lysate using different proteomics technologies. Here we present evidence showing that cell lysis buffer 1 (CLB1), a lysis solution commercialized by Zeptosens [a division of Bayer (Schweiz) AG], provides excellent sample solubilization and very high 2D PAGE protein resolution both when using carrier ampholytes and immobilized pH gradient strips. Moreover, this buffer can also be used for array-based proteomics (reverse-phase lysate arrays or direct antibody arrays), allowing the direct comparison of qualitative and quantitative data yielded by these technologies when applied to the same samples. The usefulness of the CLB1 solution for gel-based proteomics was further established by 2D PAGE analysis of a number of technically demanding specimens such as breast carcinoma core needle biopsies and problematic tissues such as brain cortex, cerebellum, skeletal muscle, kidney cortex and tongue. This solution when combined with a specific sample preparation technique - cryostat sectioning of frozen specimens - simplifies tissue sample preparation and solves most of the difficulties associated with the integration of data generated by different proteomic technologies.

Use of cancer-specific yeast-secreted in vivo biotinylated recombinant antibodies for serum biomarker discovery

BACKGROUND

Strategies to discover circulating protein markers of ovarian cancer are urgently needed. We developed a novel technology that permits us to isolate recombinant antibodies directed against the potential serum biomarkers, to facilitate the further development of affinity reagents necessary to construct diagnostic tests.

METHODS

This study presents a novel discovery approach based on serum immunoprecipitation with cancer-specific in vivo biotinylated recombinant antibodies (biobodies) derived from differentially selected yeast-display scFv, and analysis of the eluted serum proteins by electrophoresis and/or mass spectrometry.

RESULTS

Using this strategy we identified catabolic fragments of complement factors, EMILIN2, Von Willebrand factor and phosphatidylethanolamine-binding protein 1 (PEBP1 or RKIP) in patient sera. To our knowledge, this is the first report of a soluble form of PEBP1 in human. Independent evidence for ovarian cancer-specific expression of PEBP1 in patient sera was found by ELISA assays and antibody arrays with anti-PEBP1 antibodies. PEBP1 was detected in 29 out of 30 ascites samples and discriminated ovarian cancer sera from controls (p = 0.02). Finally, we confirmed by western blots the presence of a 21-23 kDa fragment corresponding to the expected size of PEBP1 but we also showed additional bands of 38 kDa and 50-52 kDa in various tissues and cell lines.

CONCLUSION

We conclude that the novel strategy described here allows the identification of candidate biomarkers that can be variants of normally expressed proteins or that display cancer-specific post-translational modifications.

Use of high density antibody arrays to validate and discover cancer serum biomarkers

Perhaps the greatest barrier to translation of serum biomarker discoveries is the inability to evaluate putative biomarkers in high throughput validation studies. Here we report on the development, production, and implementation of a high-density antibody microarray used to evaluate large numbers of candidate ovarian cancer serum biomarkers. The platform was shown to be useful for evaluation of individual antibodies for comparative analysis, such as with disease classification, and biomarker validation and discovery. We demonstrate its performance by showing that known tumor markers behave as expected. We also identify several promising biomarkers from a candidate list and generate hypotheses to support new discovery studies.