Protein profiling in human sera for identification of potential lung cancer biomarkers using antibody microarray

To identify potential biomarkers of lung cancer (LC), profiling of proteins in sera obtained from healthy and LC patients was determined using an antibody microarray. Based on our previous study on mRNA expression profiles between patients with LC and healthy persons, 19 proteins of interest were selected as targets for fabrication of an antibody microarray. Antibody to each protein and five nonspecific control antibodies were spotted onto a hydrogel‐coated glass slide and used for profiling of proteins in sera of LC patients in a two‐color fluorescence assay. Forty‐eight human sera samples were analyzed, and expression profiling of proteins were represented by the internally normalized ratio method. Six proteins were distinctly down‐regulated in sera of LC patients; this observation was validated by Wilcoxon test, false discovery rate, and Western blotting. Blind test of other 32 human sera using the antibody microarray followed by hierarchical clustering analysis revealed an approximate sensitivity of 88%, specificity of 80%, and an accuracy of 84%, respectively, in classifying the sera, which supports the potential of the six identified proteins as biomarkers for the prognosis of lung cancer.     

Development of a "reverse capture" autoantibody microarray for studies of antigen-autoantibody profiling

Diagnosing cancers based on serum profiling is a particularly attractive concept. However, the technical challenges to analysis of the serum proteome arise from the dynamic range of protein amounts. Cancer sera contain antibodies that react with a unique group of autologous cellular antigens, which affords a dramatic amplification of signal in the form of antibodies relative to the amount of the corresponding antigens. The serum autoantibody repertoire from cancer patients might, therefore, be exploited for antigen-antibody profiling. To date, studies of antigen-antibody reactivity using microarrays have relied on recombinant proteins or synthetic peptides as arrayed features. However, recombinant proteins and/or synthetic peptides may fail to accurately detect autoantibody binding due to the lack of proper PTMs. Here we describe the development and use of a "reverse capture" autoantibody microarray. Our "reverse capture" autoantibody microarray is based on the dual-antibody sandwich immunoassay platform of ELISA, which allows the antigens to be immobilized in their native configuration. As "proof-of-principle", we demonstrate its use for antigen-autoantibody profiling with sera from patients with prostate cancer and benign prostate hyperplasia.     

Quantum dot-based protein micro- and nanoarrays for detection of prostate cancer biomarkers

In this article, we demonstrate the fabrication and detection of cancer protein biochips consisting of micro- and nanoarrays whereby pegylated quantum dots (QDs) conjugated to antibodies (Abs) of prostate specific antigens (PSA) were used for the detection of clinical biomarkers such as PSA. BSA which acts as an efficient blocking layer in microarrays, tends to show an interaction with QDs. In view of this fact, we investigated two series of samples which were fabricated in the presence and absence of BSA blocking layer. Variation in the incubation time required for the antigen-antibody interaction to take place, different proteins as controls and the effect of bare QDs on these microarrays, were the three main parameters which were studied in these two series. Samples fabricated in the absence of BSA blocking layer exhibited an extremely high specificity in the detection of cancer proteins and were also marked by negligible nonspecific binding effects of QDs, in stark contrast to the samples fabricated using BSA as a blocking layer. Fabrication of nanoarrays of QD-conjugated PSA Abs having a spot size of nearly 900 nm has also been demonstrated. Thus, we show the potential offered by QDs in in vitro analysis of cancer biomarker imaging.     

Evaluation of microarray surfaces and arraying parameters for autoantibody profiling

Autoantigen microarrays are being used increasingly to study autoimmunity. Significant variation has been observed when comparing microarray surfaces, printing methods, and probing conditions. In the present study, 24 surfaces and several arraying parameters were analyzed using >500 feature autoantigen microarrays printed with quill pins. A small subset of slides, including FAST, PATH, and SuperEpoxy2, performed well while maintaining the sensitivity and specificity of autoantigen microarrays previously demonstrated by our laboratory. By optimizing the major variables in our autoantigen microarray platform, subtle differences in serum samples can be identified that will shed light on disease pathogenesis.     

Mass profiling-directed isolation and identification of a stage-specific serologic protein biomarker of advanced prostate cancer

Carcinoma of the prostate (CaP) is the second leading cause of cancer-related mortality among American men. While high cure rates are associated with localized CaP, no cure exists for advanced recurrent disease. At present there are no known serologic biomarkers specific to this stage of the disease. Several groups have used mass spectrometry (MS) based mass profiling (MP) combined with multivariate analysis to identify diagnostically predictive protein peaks for CaP in serum and tissues. Nevertheless, an appreciable level of skepticism exists for MP attributed primarily to a lack of definitive protein characterization. To address this problem, we have applied an approach that combines MP with a whole-protein based top-down separation strategy for the identification of a stage-specific marker in a group comprising 16 patients with CaP (metastatic and localized disease) and 15 healthy individuals. MP, combined with multivariate analysis, yielded 17 serum proteins specific to metastatic disease. A single protein detected at m/z 7771 was found to be significantly decreased in the sera of all the metastatic CaP patients but not in localized CaP or healthy individuals. This protein was therefore chosen as the primary candidate for further analysis. The complex nature of the serologic proteome necessitated an isolation strategy that included a C18 prefractionation, followed by multidimensional liquid chromatography and, finally, two-dimensional gel electrophoresis. The separation process was monitored by UV-Vis and matrix-assisted laser desorption/ionization-time of flight MS analysis. This strategy was found to greatly facilitate subsequent MS characterization of the unknown protein, which was identified as platelet factor 4, a chemokine with prothrombolytic and antiangiogenic activities. Confirmation was achieved using both Western blot analysis and enzyme-linked immunosorbent assay. With the growing interest in using MP for patient classification and diagnosis, our approach and its variations should be powerful in the separation and characterization of proteins following MP.     

Prediction of recurrence of non muscle‐invasive bladder cancer by means of a protein signature identified by antibody microarray analyses

About 70% of newly diagnosed cases of bladder cancer are low‐stage, low‐grade, non muscle‐invasive. Standard treatment is transurethral resection. About 60% of the tumors will recur, however, and in part progress to become invasive. Therefore, surveillance cystoscopy is performed after resection. However, in the USA and Europe alone, about 54 000 new patients per year undergo repeated cystoscopies over several years, who do not experience recurrence. Analysing in a pilot study resected tumors from patients with (n = 19) and without local recurrence (n = 6) after a period of 5 years by means of an antibody microarray that targeted 724 cancer‐related proteins, we identified 255 proteins with significantly differential abundance. Most are involved in the regulation and execution of apoptosis and cell proliferation. A multivariate classifier was constructed based on 20 proteins. It facilitates the prediction of recurrence with a sensitivity of 80% and a specificity of 100%. As a measure of overall accuracy, the area under the curve value was found to be 91%. After validation in additional sample cohorts with a similarly long follow‐up, such a signature could support decision making about the stringency of surveillance or even different treatment options.     

Protein chip-based microarray profiling of oxidized low density lipoprotein-treated cells

Commercially available high-content Ab380 and extensively validated DLM26 homemade protein microarrays were used to profile the effects of the pro-atherogenic molecule, oxidized low density lipoprotein (OxLDL), on human aortic smooth muscle cells. Protein microarrays detected 298 proteins in cell lysates and 54 of these were differentially regulated. Microarray data were validated by immunoblotting for a selected set of up- and down-regulated proteins. The protein microarray data sets were compared with our recent cDNA microarray-based gene expression results in order to characterize the global effect of OxLDL on smooth muscle cell functions. A group of cell-cell interaction molecules was classified as up-regulated by OxLDL, whereas nucleic acid/protein biosynthesis, structural and humoral response proteins/genes were under-expressed in cells treated by OxLDL. These findings reveal the major pattern of OxLDL-induced effects on the human aortic smooth muscle cells functions and also demonstrate that protein chip-based microarrays could be a useful proteomic tool to profile disease-related states of muscle cells.     

Antibody microarray-based profiling of complex specimens: systematic evaluation of labeling strategies

Antibody microarrays have often had limited success in detection of low abundant proteins in complex specimens. Signal amplification systems improve this situation, but still are quite laborious and expensive. However, the issue of sensitivity is more likely a matter of kinetically appropriate microarray design as demonstrated previously. Hence, we re-examined in this study the suitability of simple and inexpensive detection approaches for highly sensitive antibody microarray analysis. N-hydroxysuccinimidyl ester (NHS)- and Universal Linkage System (ULS)-based fluorescein and biotin labels used as tags for subsequent detection with anti-fluorescein and extravidin, respectively, as well as fluorescent dyes were applied for analysis of blood plasma. Parameters modifying strongly the performance of microarray detection such as labeling conditions, incubation time, concentrations of anti-fluorescein and extravidin and extent of protein labeling were analyzed and optimized in this study. Indirect detection strategies whether based on NHS- or ULS-chemistries strongly outperformed direct fluorescent labeling and enabled detection of low abundant cytokines with many dozen-fold signal-to-noise ratios. Finally, particularly sensitive detection chemistry was applied to monitoring cytokine production of stimulated peripheral T cells. Microarray data were in accord with quantitative cytokine levels measured by ELISA and Luminex, demonstrating comparable reliability and femtomolar range sensitivity of the established microarray approach.     

Protein subcellular localization profiling of breast cancer cells by dissociable antibody microarray staining

We have developed dissociable antibody microarray (DAMA) staining technology that provides a new approach to the global analysis of protein subcellular localization (SCL) in fixed cells. We have developed and optimized this technology for protein SCL profiling, generated ChipView, a program for management and analysis of molecular image database, and utilized the technique to identify proteins with unique SCL in breast cancer cell lines. We compared the SCL profiles of 325 proteins among nine different breast cell lines, and have identified one protein, Cyclin B1, with distinctively different SCLs between normal and cancer cell lines. With classic individual immunostaining, Cyclin B1 was confirmed to localize to the cytoplasm of seven breast cancer cell lines and in both cytoplasm and nuclei of two normal breast cell lines, and to have higher expression levels in the cancer cell lines tested.     

Application of mass spectrometry to the discovery of biomarkers for detection of prostate cancer

There has been an impressive emergence of mass spectrometry based technologies applied toward the study of proteins. Equally notable is the rapid adaptation of these technologies to biomedical approaches in the realm of clinical proteomics. Concerted efforts toward the elucidation of the proteomes of organ sites or specific disease state are proliferating and from these efforts come the promise of better diagnostics/prognostics and therapeutic intervention. Prostate cancer has been a focus of many such studies with the promise of improved care to patients via biomarkers derived from these proteomic approaches. The newer technologies provide higher analytical capabilities, employ automated liquid handling systems, fractionation techniques and bioinformatics tools for greater sensitivity and resolving power, more robust and higher throughput sample processing, and greater confidence in analytical results. In this prospects, we summarize the proteomic technologies applied to date in prostate cancer, along with their respective advantages and disadvantages. The development of newer proteomic strategies for use in future applications is also discussed.     

Characterization of serum biomarkers for detection of early stage ovarian cancer

We have previously reported the identification of three ovarian cancer biomarker panels comprised of SELDI-TOF-MS peaks representing 14 differentially expressed serum proteins for the diagnosis of ovarian cancer. Using micro-LC-MS/MS, we identified five m/z peaks as transthyretin (TTR 13.9 kDa, TTR fragment 12.9 kDa), beta-hemoglobin (Hb, 15.9 kDa), apolipoprotein AI (ApoAI, 28 kDa) and transferrin (TF, 79 kDa). Western and/or ELISA methods confirmed the differential expression of TTR, Hb, and TF, and multivariate analyses resulted in improving the detection of early stage ovarian tumors (low malignant potential and malignant; receiver operating characteristic, ROC 0.933) as compared to cancer antigen CA125 alone (ROC 0.833). Interestingly, when CA125 was included with our markers in the multivariate analysis, the ROC increased to 0.959. Furthermore, multivariate analysis with only the mucinous subtype of early stage ovarian tumors, showed our markers to greatly improve the detection of disease (ROC 0.959) as compared to CA125 alone (ROC 0.613). Interestingly, the combination of CA125 with our markers did not seem to further improve the detection of mucinous tumors (ROC 0.955). We conclude that TTR, Hb, ApoAI and TF, when combined with CA125 should significantly improve the detection of early stage ovarian cancer.     

miRNA expression profiling for identification of potential breast cancer biomarkers

To identify micro RNA (miRNA) biomarker candidates for early detection of breast cancer and detection of minimal residual breast cancer, we performed miRNA expression profiling in pooled RNA samples from breast tumors, and from bone marrow mononuclear cells, peripheral blood mononuclear cells and plasma from healthy controls. We found substantially higher levels of five miRNAs in the breast tumors compared to the normal samples. However, validation of these miRNA levels, and seven other candidates selected from the literature, in individual samples from healthy controls and patients with non-metastatic breast cancer did not suggest further examination of their biomarker potential.     

Complex interaction between serum folate levels and genetic polymorphisms in folate pathway genes: biomarkers of prostate cancer aggressiveness

Little is known about the role of folate and polymorphisms associated with folate metabolism on prostate cancer risk in populations of African origin. We examined the relationship between serum folate and prostate cancer and whether any association was modified by genetic polymorphisms for folate metabolism. The study was case–control in design and consisted of 218 men 40–80 years old with newly diagnosed, histologically confirmed prostate cancer and 236 cancer-free men attending the same urology clinics in Jamaica, March 2005–July 2007. Serum folate was measured by an immunoassay method and genomic DNA evaluated for MTHR (C677T and A1298C), MTRR A66G, and MTR A2756G polymorphisms. Mean serum folate concentration was higher among cases (12.3 ± 4.1 nmol/L) than controls (9.7 ± 4.2 nmol/L). Serum folate concentration showed a positive association with prostate cancer (OR, 4.41; CI, 2.52–7.72 per 10 nmol/L) regardless of grade. No interactions were observed between genotype and folate concentration, but a weak gene effect was observed for MTHFR A1298C and low-grade prostate cancer. Larger studies to investigate the role of gene–gene/gene–diet interactions in Black men are needed.     

Design of recombinant antibody microarrays for membrane protein profiling of cell lysates and tissue extracts

Generating global protein expression profiles, including also membrane proteins, will be crucial for our understanding of biological processes in health and disease. In this study, we have expanded our antibody microarray technology platform and designed the first human recombinant antibody microarray for membrane proteins targeting crude cell lysates and tissue extracts. We have optimized all key technological parameters and successfully developed a setup for extracting, labeling and analyzing non-fractionated membrane proteomes under non-denaturing conditions. Finally, the platform was also extended and shown to be compatible with simultaneous profiling of both membrane proteins and water-soluble proteins.     

Comparative protein profiling of serum and plasma using an antibody suspension bead array approach

In the pursuit towards a systematic analysis of human diseases, array‐based approaches within antibody proteomics offer high‐throughput strategies to discover protein biomarkers in serum and plasma. To investigate the influence of sample preparation on such discovery attempts, we report on a systematic effort to compare serum and plasma protein profiles determined with an antibody suspension bead array. The intensity levels were used to define protein profiles and no significant differences between serum and plasma were observed for 79% of the 174 antibodies (targeting 156 proteins). By excluding 36 antibodies giving rise to differential intensity levels, cluster analysis revealed donor‐specific rather than preparation‐dependent grouping. With a cohort from a clinically relevant medical condition, the metabolic syndrome, the influence of the sample type on a multiplexed biomarker discovery approach was further investigated. Independent comparisons of protein profiles in serum and plasma revealed an antibody targeting ADAMTSL‐4, a protein that would qualify to be studied further in association with the condition. In general, the preparation type had an impact on the results of the applied antibody suspension bead array, and while the technical variability was equal, plasma offered a greater biological variability and allowed to give rise to more discoveries than serum.     

Biocompatibility of surfaces for antibody microarrays: design of macroporous silicon substrates

Major efforts to develop antibody microarray technology to enable global proteome analysis to be performed in a facile manner are under way. In this process, the design and the properties of the substrate will play crucial roles. In the present study, we have developed novel, highly biocompatible solid supports for microarrays, using adsorbed recombinant human single-framework antibody fragments as probes. Several silicon-based supports, including planar silicon, micro- and macroporous silicon, and nitrocellulose-coated variants thereof, were designed and evaluated in a stepwise procedure. The surfaces were scored based on biocompatibility and probe binding capacity as judged by spot morphology, signal intensities, signal to noise ratios, dynamic range, sensitivity, and reproducibility. A set of five commercially available substrates, selected to represent a set of supports providing different surface and coupling chemistries, was used as reference surfaces. The results showed that several well-performing silicon-based supports could be designed; in particular, a nitrocellulose-coated macroporous variant, MAP3-NC7, received the highest scores. In comparison, MAP3-NC7 displayed properties equal to or better than those of the reference substrates. Taken together, designed surfaces based on silicon can undoubtedly meet the requirements of the next generation of solid supports for antibody microarrays.     

Antibody‐based profiling of cerebrospinal fluid within multiple sclerosis

Antibody suspension bead arrays have proven to enable multiplexed and high‐throughput protein profiling in unfractionated plasma and serum samples through a direct labeling approach. We here describe the development and application of an assay for protein profiling of cerebrospinal fluid (CSF). While setting up the assay, systematic intensity differences between sample groups were observed that reflected inherent sample specific total protein amounts. Supplementing the labeling reaction with BSA and IgG diminished these differences without impairing the apparent sensitivity of the assay. We also assessed the effects of heat treatment on the analysis of CSF proteins and applied the assay to profile 43 selected proteins by 101 antibodies in 339 CSF samples from a multiple sclerosis (MS) cohort. Two proteins, GAP43 and SERPINA3 were found to have a discriminating potential with altered intensity levels between sample groups. GAP43 was detected at significantly lower levels in secondary progressive MS compared to early stages of MS and the control group of other neurological diseases. SERPINA3 instead was detected at higher levels in all MS patients compared to controls. The developed assay procedure now offers new possibilities for broad‐scale protein profiling of CSF within neurological disorders.     

Towards a human proteome atlas: high-throughput generation of mono-specific antibodies for tissue profiling

A great need exists for the systematic generation of specific antibodies to explore the human proteome. Here, we show that antibodies specific to human proteins can be generated in a high-throughput manner involving stringent affinity purification using recombinant protein epitope signature tags (PrESTs) as immunogens and affinity-ligands. The specificity of the generated affinity reagents, here called mono-specific antibodies (msAb), were validated with a novel protein microarray assay. The success rate for 464 antibodies generated towards human proteins was more than 90% as judged by the protein array assay. The antibodies were used for parallel profiling of patient biopsies using tissue microarrays generated from 48 human tissues. Comparative analysis with well-characterized monoclonal antibodies showed identical or similar specificity and expression patterns. The results suggest that a comprehensive atlas containing extensive protein expression and subcellular localization data of the human proteome can be generated in an efficient manner with mono-specific antibodies.     

Detection of pre-neoplastic and neoplastic prostate disease by MALDI profiling of urine

The heterogeneous progression to the development of prostate cancer (PCa) has precluded effective early detection screens. Existing prostate cancer screening paradigms have relatively poor specificity for cancer relative to other prostate diseases, commonly benign prostatic hyperplasia (BPH). A method for discrimination of BPH, HGPIN, and PCa urine proteome was developed through testing 407 patient samples using matrix assisted laser desorption-mass spectrometry time of flight (MALDI-TOF). Urine samples were adsorbed to reverse phase resin, washed, and the eluant spotted directly for MALDI-TOF analysis of peptides. The processing resolved over 130 verifiable signals of a mass range of 1000-5000 m/z to suggest 71.2% specificity and 67.4% sensitivity in discriminating PCa vs. BPH. Comparing BPH and HGPIN resulted in 73.6% specificity and 69.2% sensitivity. Comparing PCa and HGPIN resulted in 80.8% specificity and 81.0% sensitivity. The high throughput, low-cost assay method developed is amenable for large patient numbers required for supporting biomarker identification.