The current status of cancer biomarker research using tumour-associated antigens for minimal invasive and early cancer diagnostics

Antibody Profiling and In Silico Functional Analysis of Differentially Reactive Antibody Signatures of Glioblastomas and Meningiomas

Studies on tumor-associated antigens in brain tumors are sparse. There is scope for enhancing our understanding of molecular pathology, in order to improve on existing forms, and discover new forms, of treatment, which could be particularly relevant to immuno-oncological strategies. To elucidate immunological differences, and to provide another level of biological information, we performed antibody profiling, based on a high-density protein array (containing 8173 human transcripts), using IgG isolated from the sera of n = 12 preoperative and n = 16 postoperative glioblastomas, n = 26 preoperative and n = 29 postoperative meningiomas, and n = 27 healthy, cancer-free controls. Differentially reactive antigens were compared to gene expression data from an alternate public GBM data set from OncoDB, and were analyzed using the Reactome pathway browser. Protein array analysis identified approximately 350-800 differentially reactive antigens, and revealed different antigen profiles in the glioblastomas and meningiomas, with approximately 20-30%-similar and 10-15%-similar antigens in preoperative and postoperative sera, respectively. Seroreactivity did not correlate with OncoDB-derived gene expression. Antigens in the preoperative glioblastoma sera were enriched for signaling pathways, such as signaling by Rho-GTPases, COPI-mediated anterograde transport and vesicle-mediated transport, while the infectious disease, SRP-dependent membrane targeting cotranslational proteins were enriched in the meningiomas. The pre-vs. postoperative seroreactivity in the glioblastomas was enriched for antigens, e.g., platelet degranulation and metabolism of lipid pathways; in the meningiomas, the antigens were enriched in infectious diseases, metabolism of amino acids and derivatives, and cell cycle. Antibody profiling in both tumor entities elucidated several hundred antigens and characteristic signaling pathways that may provide new insights into molecular pathology and may be of interest for the development of new treatment strategies.

State of the Art of Chemosensors in a Biomedical Context

Healthcare is undergoing large transformations, and it is imperative to leverage new technologies to support the advent of personalized medicine and disease prevention. It is now well accepted that the levels of certain biological molecules found in blood and other bodily fluids, as well as in exhaled breath, are an indication of the onset of many human diseases and reflect the health status of the person. Blood, urine, sweat, or saliva biomarkers can therefore serve in early diagnosis of diseases such as cancer, but also in monitoring disease progression, detecting metabolic disfunctions, and predicting response to a given therapy. For most point-of-care sensors, the requirement that patients themselves can use and apply them is crucial not only regarding the diagnostic part, but also at the sample collection level. This has stimulated the development of such diagnostic approaches for the non-invasive analysis of disease-relevant analytes. Considering these timely efforts, this review article focuses on novel, sensitive, and selective sensing systems for the detection of different endogenous target biomarkers in bodily fluids as well as in exhaled breath, which are associated with human diseases.

Identification of tumor-associated antigens of lung cancer: SEREX combined with bioinformatics analysis

The aim of this study is to identify novel tumor-associated antigens (TAAs) of lung cancer by using serological analysis of recombinant cDNA expression library (SEREX) and bioinformatics analysis as well as to explore their humoral immune response. SEREX and pathway enrichment analysis were used to immunoscreen TAAs of lung cancer and elaborate their function in biological pathways, respectively. Subsequently, the sera level of autoantibodies against the selected TAAs (TOP2A, TRIM37, HSP90AB1, EEF1G and TPP1) was detected by immunoserological analysis to explore the immune response of these antigens. The Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) database were applied to explore the mRNA and protein expression level of TOP2A, TRIM37 and HSP90AB1 in tissues, respectively. Seventy positive clones were identified by SEREX which contain 63 different genes, and 35 genes of them have been reported. These 35 genes were mainly related to regulation of different transcription factor and performed enrichment in legionellosis, RNA transport, IL-17 signaling pathway via enrichment analysis. Additionally, the positive rate of autoantibodies against TOP2A, TRIM37 and HSP90AB1 in lung cancer patients were typically higher than normal control (NC; P < 0.05). Moreover, the combination of the autoantibodies against TOP2A, TRIM37 and HSP90AB1 possessed an excellent diagnostic performance with sensitivity of 84% and specificity of 60%. The mRNA expression level of TOP2A was obviously unregulated in squamous cell carcinoma (SCC) tissues and adenocarcinoma (ADC) tissues compared to normal tissues (P < 0.05). In addition, TRIM37 and HSP90AB1 also showed a significant difference between SCC and NC at the mRNA expression level (P < 0.05). This study combining comprehensive autoantibody and gene expression assays has added to the growing list of lung cancer antigens, which may aid the development of diagnostic and immunotherapeutic targets for lung cancer patients.

Application of Phage-Displayed Peptides in Tumor Imaging Diagnosis and Targeting Therapy

Phage display is an effective and powerful technique that provides a route to discovery unique peptides targeting to tumor cells. Specifically binding peptides are considered as the valuable target directing molecule fragments with potential efficiency to improve the current tumor clinic, and offer new approaches for tumor prevention, diagnosis and treatment. We focus on the recent advances in the isolation of tumor-targeting peptides by biopanning methods, with particular emphasis on molecular imaging, and pharmaceutical targeting therapy.

Biomolecular Sensing at the Interface between Chiral Metasurfaces and Hyperbolic Metamaterials

In recent times, biomolecular sensing to recognize genetic fragments and proteins is spurring unprecedented interest as a diagnostic protocol for cancer and infectious diseases. Significant efforts have been made to design nanomaterials able to control the light-matter interaction at the single nanometer scale, where genes and proteins bind specifically to receptors. Here, we numerically show how the interface between a chiral metasurface and hyperbolic metamaterials can enable both high sensitivity and specificity for low-molecular-weight nucleic acids and proteins. As we have recently reported, hyperbolic dispersion metamaterials allow molecular biorecognition with extreme sensitivity because of coupled and highly confined plasmon polaritons. Specificity is almost exclusively achieved by receptor-ligand interaction at the in-plane sensing surface. Interestingly, an adapted out-of-plane chiral metasurface enables three key functionalities of the hyperbolic metamaterial sensor. Computational effort reveals that helicoidal metasurfaces can act as (i) efficient diffractive elements to excite surface and bulk plasmon polaritons; (ii) out-of-plane sensing branches to reduce the diffusion limit and increase the sensing surface; and (iii) biorecognition assay also via circular dichroism and chiral selectivity.

Using gold nanoparticles to detect single-nucleotide polymorphisms: toward liquid biopsy

The possibility of detecting genetic mutations rapidly in physiological media through liquid biopsy has attracted the attention within the materials science community. The physical properties of nanoparticles combined with robust transduction methods ensure an improved sensitivity and specificity of a given assay and its implementation into point-of-care devices for common use. Covering the last twenty years, this review gives an overview of the state-of-the-art of the research on the use of gold nanoparticles in the development of colorimetric biosensors for the detection of single-nucleotide polymorphism as cancer biomarker. We discuss the main mechanisms of the assays that either are assisted by DNA-based molecular machines or by enzymatic reactions, summarize their performance and provide an outlook towards future developments.

IgG based immunome analyses of breast cancer patients reveal underlying signaling pathways

Background: Breast cancer is the most frequent and one of the most fatal malignancies among women. Within the concept of personalized medicine, molecular characterization of tumors is usually performed by analyzing somatic mutations, RNA gene expression signatures or the proteome by mass-spectrometry. Alternatively, the immunological fingerprint of the patients can be analyzed by protein microarrays, which is able to provide another layer of molecular pathological information without invasive intervention.

Results: We have investigated the immune signature of breast cancer patients and compared them with healthy controls, using protein microarray-based IgG profiling. The identified differentially reactive antigens (n=517) were further evaluated by means of various pathway analysis tools. Our results indicate that the immune signature of breast cancer patients shows a clear distinction from healthy individuals characterized by differentially reactive antigens involved in known disease relevant signaling pathways, such as VEGF, AKT/PI3K/mTOR or c-KIT, which is in close agreement with the findings from RNA-based expression profiles.

Conclusion: Differential antigenic properties between breast cancer patients and healthy individual classes can be defined by serum-IgG profiling on protein microarrays. These immunome profiles provide an additional layer of molecular pathological information, which has the potential to refine and complete the systems biological map of neoplastic disease.

Plasma membrane localization of CYP4Z1 and CYP19A1 and the detection of anti-CYP19A1 autoantibodies in humans

It is thought that autoantibody (aAb) production can be caused by (aberrant) protein targeting to the plasma surface of cells. We recently demonstrated the presence of the human cytochrome P450 enzyme CYP4Z1 on the plasma membrane of MCF-7 breast cancer cells and the detection of high titers of anti-CYP4Z1 aAbs in breast cancer patients, but not in healthy controls. In the present study we show that cells of the normal breast cell line MCF-10A do not display CYP4Z1 on their surface. By contrast, we detected CYP19A1 (aromatase) on the plasma membrane of both cell lines. Interestingly, the presence of CYPs on the cell surface did not correlate with their relative expression levels in these cell lines. Indirect ELISA experiments demonstrated the presence of anti-CYP19A1 aAbs in female breast cancer patient sera as well as in male and female controls, respectively; aAb titers in all three groups varied considerably and overall, the results obtained for each group were not significantly different from those of either of the other two groups. Based on these data we propose the hypothesis that CYP translocation to the plasma membrane, but not the intracellular expression level, is the crucial precondition for the generation of anti-CYP aAbs.

Advanced methods for microRNA biosensing: a problem-solving perspective

MicroRNAs (miRNAs) present several features that make them more difficult to analyze than DNA and RNA. For this reason, efforts have been made in recent years to develop innovative platforms for the efficient detection of microRNAs. The aim of this review is to provide an overview of the sensing strategies able to deal with drawbacks and pitfalls related to microRNA detection. With a critical perspective of the field, we identify the main challenges to be overcome in microRNA sensing, and describe the areas where several innovative approaches are likely to come for managing those issues that put limits on improvement to the performances of the current methods. Then, in the following sections, we critically discuss the contribution of the most promising approaches based on the peculiar properties of nanomaterials or nanostructures and other hybrid strategies which are envisaged to support the adoption of these new methods useful for the detection of miRNA as biomarkers of practical clinical utility. Graphical abstract ᅟ.

A diagnostic autoantibody signature for primary cutaneous melanoma

Melanoma is an aggressive form of skin cancer that is curable by surgical excision in the majority of cases, if detected at an early stage. To improve early stage melanoma detection, the development of a highly sensitive diagnostic test is of utmost importance. Here we aimed to identify antibodies to a panel of tumour associated antigens that can differentiate primary melanoma patients and healthy individuals. A total of 245 sera from primary melanoma patients and healthy volunteers were screened against a high-throughput microarray platform containing 1627 functional proteins. Following rigorous statistical analysis, we identified a combination of 10 autoantibody biomarkers that, as a panel, displays a sensitivity of 79%, specificity of 84% and an AUC of 0.828 for primary melanoma detection. This melanoma autoantibody signature may prove valuable for the development of a diagnostic blood test for routine population screening that, when used in conjunction with current melanoma diagnostic techniques, could improve the early diagnosis of this malignancy and ultimately decrease the mortality rate of patients.

Autoantibodies as Potential Biomarkers in Breast Cancer

Breast cancer is a major cause of mortality in women; however, technologies for early stage screening and diagnosis (e.g., mammography and other imaging technologies) are not optimal for the accurate detection of cancer. This creates demand for a more effective diagnostic means to replace or be complementary to existing technologies for early discovery of breast cancer. Cancer neoantigens could reflect tumorigenesis, but they are hardly detectable at the early stage. Autoantibodies, however, are biologically amplified and hence may be measurable early on, making them promising biomarkers to discriminate breast cancer from healthy tissue accurately. In this review, we summarized the recent findings of breast cancer specific antigens and autoantibodies, which may be useful in early detection, disease stratification, and monitoring of treatment responses of breast cancer.

The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling

Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC) patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A) and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 “CRC genes.” These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology.

Selecting analytical biomarkers for diagnostic applications: a first principles approach

INTRODUCTION

Biomarkers are objective indications of a medical state that can be measured accurately and reproducibly. Traditional biomarkers enable diagnosis of disease through detection of disease-specific molecules, disease-mediated molecular changes, or distinct physiological or anatomical signatures. Areas covered: This work provides a framework for selecting biomarkers that are most likely to provide useful information about a patient's disease state. Though the authors emphasize markers related to disease, this work is also applicable to biomarkers for monitoring physiological changes such as ovulation or pregnancy. Additionally, the scope was restricted to biomarkers that are amenable to analytical detection across a range of health care levels, including low resource settings. The authors describe trade-offs between biomarkers' sensitivity/specificity for a disease-causing agent, the complexity of detection, and how this knowledge can be applied to the development of diagnostic tests. This report also details additional assessment criteria for successful tests. Expert commentary: Biomarker selection should primarily be driven by an attempt to answer an explicit clinical question (preferably causative relationship of the biomarker to disease-state), and only then by test development expediency (ease of detection). This framework is useful for stakeholders from test developers to clinicians to identify the trade-offs for diagnostic biomarkers for any use case.

Peptide Nucleic Acid-Based Biosensors for Cancer Diagnosis

The monitoring of DNA and RNA biomarkers freely circulating in the blood constitutes the basis of innovative cancer detection methods based on liquid biopsy. Such methods are expected to provide new opportunities for a better understanding of cancer disease at the molecular level, thus contributing to improved patient outcomes. Advanced biosensors can advance possibilities for cancer-related nucleic acid biomarkers detection. In this context, peptide nucleic acids (PNAs) play an important role in the fabrication of highly sensitive biosensors. This review provides an overview of recently described PNA-based biosensors for cancer biomarker detection. One of the most striking features of the described detection approaches is represented by the possibility to detect target nucleic acids at the ultra-low concentration with the capability to identify single-base mutations.

Innate immune mediators in cancer: between defense and resistance

Chronic inflammation in the tumor microenvironment and evasion of the antitumor effector immune response are two of the emerging hallmarks required for oncogenesis and cancer progression. The innate immune system not only plays a critical role in perpetuating these tumor-promoting hallmarks but also in developing antitumor adaptive immune responses. Thus, understanding the dual role of the innate system in cancer immunology is required for the design of combined immunotherapy strategies able to tackle established tumors. Here, we review recent advances in the understanding of the role of cell populations and soluble components of the innate immune system in cancer, with a focus on complement, the adapter molecule Stimulator of Interferon Genes, natural killer cells, myeloid cells, and B cells.

A Model-Based Personalized Cancer Screening Strategy for Detecting Early-Stage Tumors Using Blood-Borne Biomarkers

An effective cancer blood biomarker screening strategy must distinguish aggressive from nonaggressive tumors at an early, intervenable time. However, for blood-based strategies to be useful, the quantity of biomarker shed into the blood and its relationship to tumor growth or progression must be validated. To study how blood biomarker levels correlate with early-stage viable tumor growth in a mouse model of human cancer, we monitored early tumor growth of engineered human ovarian cancer cells (A2780) implanted orthotopically into nude mice. Biomarker shedding was monitored by serial blood sampling, whereas tumor viability and volume were monitored by bioluminescence imaging and ultrasound imaging. From these metrics, we developed a mathematical model of cancer biomarker kinetics that accounts for biomarker shedding from tumor and healthy cells, biomarker entry into vasculature, biomarker elimination from plasma, and subject-specific tumor growth. We validated the model in a separate set of mice in which subject-specific tumor growth rates were accurately predicted. To illustrate clinical translation of this strategy, we allometrically scaled model parameters from mouse to human and used parameters for PSA shedding and prostate cancer. In this manner, we found that blood biomarker sampling data alone were capable of enabling the detection and discrimination of simulated aggressive (2-month tumor doubling time) and nonaggressive (18-month tumor doubling time) tumors as early as 7.2 months and 8.9 years before clinical imaging, respectively. Our model and screening strategy offers broad impact in their applicability to any solid cancer and associated biomarkers shed, thereby allowing a distinction between aggressive and nonaggressive tumors using blood biomarker sampling data alone. Cancer Res; 77(10); 2570-84. ©2017 AACR.

Biosensors for liquid biopsy: circulating nucleic acids to diagnose and treat cancer

The detection of cancer biomarkers freely circulating in blood offers new opportunities for cancer early diagnosis, patient follow-up, and therapy efficacy assessment based on liquid biopsy. In particular, circulating cell-free nucleic acids released from tumor cells have recently attracted great attention also because they become detectable in blood before the appearance of other circulating biomarkers, such as circulating tumor cells. The detection of circulating nucleic acids poses several technical challenges that arise from their low concentration and relatively small size. Here, possibilities offered by innovative biosensing approaches for the detection of circulating DNA in peripheral blood and blood-derived products such as plasma and serum blood are discussed. Different transduction principles are used to detect circulating DNAs and great advantages are derived from the combined use of nanostructured materials.

Fluorescent/magnetic micro/nano-spheres based on quantum dots and/or magnetic nanoparticles: preparation, properties, and their applications in cancer studies

The study of cancer is of great significance to human survival and development, due to the fact that cancer has become one of the greatest threats to human health. In recent years, the rapid progress of nanoscience and nanotechnology has brought new and bright opportunities to this field. In particular, the applications of quantum dots (QDs) and magnetic nanoparticles (MNPs) have greatly promoted early diagnosis and effective therapy of cancer. In this review, we focus on fluorescent/magnetic micro/nano-spheres based on QDs and/or MNPs (we may call them "nanoparticle-sphere (NP-sphere) composites") from their preparation to their bio-application in cancer research. Firstly, we outline and compare the main four kinds of methods for fabricating NP-sphere composites, including their design principles, operation processes, and characteristics (merits and limitations). The NP-sphere composites successfully inherit the unique fluorescence or magnetic properties of QDs or MNPs. Moreover, compared with the nanoparticles (NPs) alone, the NP-sphere composites show superior properties, which are also discussed in this review. Then, we summarize their recent applications in cancer research from three aspects, that is: separation and enrichment of target tumor cells or biomarkers; cancer diagnosis mainly through medical imaging or tumor biomarker detection; and cancer therapy via targeted drug delivery systems. Finally, we provide some perspectives on the future challenges and development trends of the NP-sphere composites.

Printed peptide arrays identify prognostic TNC serumantibodies in glioblastoma patients

Liquid biopsies come of age offering unexploited potential to monitor and react to tumor evolution. We developed a cost-effective assay to non-invasively determine the immune status of glioblastoma (GBM) patients. Employing newly developed printed peptide microarrays we assessed the B-cell response against tumor-associated antigens (TAAs) in 214 patients. Firstly, sera of long-term (36+ months, LTS, n=10) and short-term (6-10 months, STS, n=14) surviving patients were screened for prognostic antibodies against 1745 13-mer peptides covering known TAAs (TNC, EGFR, GLEA2, PHF3, FABP5, MAGEA3). Next, survival associations were investigated in two retrospective independent multicenter validation sets (n=61, n=129, all IDH1-wildtype). Reliability of measurements was tested using a second array technology (spotted arrays). LTS/STS screening analyses identified 106 differential antibody responses. Evaluating the Top30 peptides in validation set 1 revealed three prognostic peptides. Prediction of TNC peptide VCEDGFTGPDCAE was confirmed in a second set (p=0.043, HR=0.66 [0.44-0.99]) and was unrelated to TNC protein expression. Median signals of printed arrays correlated with pre-synthesized spotted microarrays (p<0.0002, R=0.33). Multiple survival analysis revealed independence of age, gender, KPI and MGMT status. We present a novel peptide microarray immune assay that identified increased anti-TNC VCEDGFTGPDCAE serum antibody titer as a promising non-invasive biomarker for prolonged survival.

The prostate cancer immunome: In silico functional analysis of antigenic proteins from microarray profiling with IgG

The study of the immunome of prostate cancer (PCa) and characterization of autoantibody signature from differentially reactive antigens can uncover disease stage proteins, reveal enriched networks and even expose aberrant cellular mechanisms during the disease process. By conducting plasma IgG profiling on protein microarrays presenting 5449 unique human proteins expressed in 15 417 E. coli human cDNA expression clones, we elucidated 471 (21 higher reactive in PCa) differentially reactive antigens in 50 PCa versus 49 patients with benign prostate hyperplasia (BPH) at initial diagnosis. Functional analyzes show that the immune-profile of PCa compared to BPH control samples is significantly enriched in features targeting Cellular assembly, Cell death and pathways involved in Cell cycle, translation, and assembly of proteins as EIF2 signaling, PCa related genes as AXIN1 and TP53, and ribosomal proteins (e.g. RPS10). An overlap of 61 (out of 471) DIRAGs with the published 1545 antigens from the SEREX database has been found, however those were higher reactive in BPH. Clinical relevance is shown when antibody-reactivities against eight proteins were significantly (p < 0.001) correlated with Gleason-score. Herewith we provide a biological and pathophysiological characterization of the immunological layer of cancerous (PCa) versus benign (BPH) disease, derived from antibody profiling on protein microarrays.

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.

Non-invasive glioblastoma immunoprofiling by printed peptide arrays

Immune monitoring assays for patient stratification and treatment efficacy in clinical trials are in demand. We have recently described a cost-effective non-invasive assay to determine the immune status of glioblastoma patients. Profiling antitumor serum antibodies by customized printed peptide arrays identified response against a tenascin-C (TNC) peptide as a robust prognostic biomarker.

Cancer proteomics: developments in technology, clinical use and commercialization

In the last two decades, advances in genomic, transcriptomic and proteomic methods have enabled us to identify and classify cancers by their molecular profiles. Many anticipate that a molecular taxonomy of cancer will not only lead to more effective subtyping of cancers but also earlier diagnoses, more informative prognoses and more targeted treatments. This article reviews recent technological developments in the field of proteomics, recent discoveries in proteomic cancer biomarker research and trends in clinical use. Readers are also informed of examples of successful commercialization, and the future of proteomics in cancer diagnostics.

Up-to-Date Applications of Microarrays and Their Way to Commercialization

This review addresses up-to-date applications of Protein Microarrays. Protein Microarrays play a significant role in basic research as well as in clinical applications and are applicable in a lot of fields, e.g., DNA, proteins and small molecules. Additionally they are on the way to enter clinics in routine diagnostics. Protein Microarrays can be powerful tools to improve healthcare. An overview of basic characteristics to mediate essential knowledge of this technique is given. To reach this goal, some challenges still have to be addressed. A few applications of Protein Microarrays in a medical context are shown. Finally, an outlook, where the potential of Protein Microarrays is depicted and speculations how the future of Protein Microarrays will look like are made.

Elevated levels of the complement activation product C4d in bronchial fluids for the diagnosis of lung cancer

Molecular markers in bronchial fluids may contribute to the diagnosis of lung cancer. We previously observed a significant increase of C4d-containing complement degradation fragments in bronchoalveolar lavage (BAL) supernatants from lung cancer patients in a cohort of 50 cases and 22 controls (CUN cohort). The present study was designed to determine the diagnostic performance of these complement fragments (hereinafter jointly referred as C4d) in bronchial fluids. C4d levels were determined in BAL supernatants from two independent cohorts: the CU cohort (25 cases and 26 controls) and the HUVR cohort (60 cases and 98 controls). A series of spontaneous sputum samples from 68 patients with lung cancer and 10 controls was also used (LCCCIO cohort). Total protein content, complement C4, complement C5a, and CYFRA 21-1 were also measured in all cohorts. C4d levels were significantly increased in BAL samples from lung cancer patients. The area under the ROC curve was 0.82 (95%CI = 0.71-0.94) and 0.67 (95%CI = 0.58-0.76) for the CU and HUVR cohorts, respectively. In addition, unlike the other markers, C4d levels in BAL samples were highly consistent across the CUN, CU and HUVR cohorts. Interestingly, C4d test markedly increased the sensitivity of bronchoscopy in the two cohorts in which cytological data were available (CUN and HUVR cohorts). Finally, in the LCCCIO cohort, C4d levels were higher in sputum supernatants from patients with lung cancer (area under the ROC curve: 0.7; 95%CI = 0.56-0.83). In conclusion, C4d is consistently elevated in bronchial fluids from lung cancer patients and may be used to improve the diagnosis of the disease.

The pre-analytical processing of blood samples for detecting biomarkers on protein microarrays

Specimen collection method and quality insurance are pivotal in biomarker discovery. Pre-analytical variables concerning blood collection and sample handling might affect analytical results and should be standardised prior application. In this study, we examine pre-analytical characteristics of blood samples using protein microarray. The influences of 1) standby times until centrifugation (1 h, 4 h, 24 h and 48 h), 2) four blood collection methods, and 3) IgG purified from those samples on differentially reactive antigens between samples ("DIRAGs") were investigated. Spearman correlation analyses of intra-individual arrays demonstrated remarkable differences (0.75-0.98 vs. 0.5-0.75) of antibody reactivities within and between serum and plasma samples. Class comparison showed that reactive antigen profiles were best preserved using IgG purified samples of serum tubes without separation gel as after 24h 83% of the 1h baseline DIRAGs were re-found. Testing dilution series with protein microarrays and Luminex xMap® Technology, we found linear correlations (R(2) = 0.94-0.99) between IgG concentration and read-out when using purified IgG instead of serum. Therefore, we highly recommend standardising pre-analytics and proposing the use of purified IgG for autoantibody immune-profiling with protein microarrays to reduce potential unspecific binding of matrix proteins abundant in serum and plasma samples.

SIGNIFICANCE

Although purified IgG cannot completely compensate the influence of pre-analytics, in highly parallel immune-profiling IgG enables reduction of unspecific effects, which occur when using serum or plasma for analysis on protein microarrays. Reproducibility problems due to pre-analytical processing of blood samples might explain discrepant results reported in various biomarker studies.

Autoantibodies in breast cancer

In addition to their historical role, autoantibodies appear promising as biomarkers to facilitate diagnosis, improve patient outcome and decrease mortality in cancer. Autoantibodies may also be useful in the identification of subjects at risk for cancer, that is, those bearing premalignant changes. Numerous studies have demonstrated that cancer serum contains a variety of autoantibodies that react with autologous cellular antigens, that is, tumor-associated antigens. Interestingly, some of these antigens are involved in signal transduction, cell cycle regulation, cell proliferation, and apoptosis. As such, identification of these molecules has additional importance for development of novel anticancer drugs and vaccines. This review focuses on the use of autoantibodies in breast cancer, a major public health problem. We also address the need for additional research to validate this approach in cancer diagnostics and therapeutics in general.

A multiparametric serum marker panel as a complementary test to mammography for the diagnosis of node-negative early-stage breast cancer and DCIS in young women

BACKGROUND

The sensitivity of mammography for the detection of small lesions, including node-negative early-stage (T1N0) primary breast cancer (PBC) and ductal carcinoma in situ (DCIS), is significantly decreased in young patients. From a clinical standpoint, an inconclusive mammogram reflects the inability of clinicians to confidently decide whether patients should be referred for biopsy or for follow-up with repeat imaging.

METHODS

Specific ELISAs were developed for a panel of 13 well-recognized breast autoantigens (HSP60, FKBP52, PRDX2, PPIA, MUC1, GAL3, PAK2, P53, CCNB1, PHB2, RACK1, RUVBL1, and HER2). Circulating autoantibody levels were measured in a cohort of 396 serum samples from histologically confirmed DCIS (n = 87) or T1N0 PBC (n = 153) and healthy controls (n = 156).

RESULTS

Individually, antibodies against CCNB1, FKBP52, GAL3, PAK2, PRDX2, PPIA, P53, and MUC1 demonstrated discriminatory power between breast cancer and healthy control groups. At 90% sensitivity, the overall combined specificity of the autoantibody serum screening test was 42%. Adjustment for higher sensitivities of 95% and 99% resulted in 30% and 21% specificities, respectively (33% and 18% in T1N0 PBC and 28% and 21% in DCIS). Finally, in patients with node-negative early-stage breast cancer younger than 50 years, the autoantibody assay exhibited 59% specificity with a fixed sensitivity at 90%.

CONCLUSIONS

Our autoantibody panel allows accurate detection of early breast cancer and DCIS, notably in younger patients.

IMPACT

Clinical assessment of this autoantibody panel displays a potential to facilitate clinical management of early-stage breast cancer detection in cases of inconclusive mammogram.

Early lung cancer diagnosis by biosensors

Lung cancer causes an extreme threat to human health, and the mortality rate due to lung cancer has not decreased during the last decade. Prognosis or early diagnosis could help reduce the mortality rate. If microRNA and tumor-associated antigens (TAAs), as well as the corresponding autoantibodies, can be detected prior to clinical diagnosis, such high sensitivity of biosensors makes the early diagnosis and prognosis of cancer realizable. This review provides an overview of tumor-associated biomarker identifying methods and the biosensor technology available today. Laboratorial researches utilizing biosensors for early lung cancer diagnosis will be highlighted.

Glycoproteomic analysis of tissues from patients with colon cancer using lectin microarrays and nanoLC-MS/MS

The current study evaluated the glycoproteomic profile of tissues from colon cancer patients. The lectin microarray was first performed to compare the glycoprotein profiles between colon cancer and matched normal tissues. Level of N-acetylglucosamine (GlcNAc) that Solanum tuberosum lectin (STL) bound was found to be elevated in colon cancer, which was verified through lectin histochemistry. The subsequent glycoproteomic analysis based on STL enrichment of glycoproteins followed by label-free quantitative nano liquid chromatography-mass spectrometry/mass spectrometry (nanoLC-MS/MS) analysis identified 72 proteins in high confidence. Among these proteins, 17 were exclusively detected in cancer tissues, and 14 were significantly upregulated in tumor tissues. Annexin A1 and HSP90β were chosen for further investigation by immunoprecipitation coupled with lectin blots, western blots and tissue microarrays. Both Annexin A1 and HSP90β were GlcNAcylated, and their protein expressions were elevated in colon cancer, compared to normal tissues. Moreover, specific changes of GlcNAc abundances in Annexin A1 and HSP90β suggested that tumor-specific glycan patterns could serve as candidate biomarkers of colon cancer for distinguishing cancer patients from healthy individuals.

Functionalized magnetic nanoparticles for the detection and quantitative analysis of cell surface antigen

Cell surface antigens as biomarkers offer tremendous potential for early diagnosis, prognosis, and therapeutic response in a variety of diseases such as cancers. In this research, a simple, rapid, accurate, inexpensive, and easily available in vitro assay based on magnetic nanoparticles and magnetic cell separation principle was applied to identify and quantitatively analyze the cell surface antigen expression in the case of prostate cancer cells. Comparing the capability of the assay with flow cytometry as a gold standard method showed similar results. The results showed that the antigen-specific magnetic cell separation with antibody-coated magnetic nanoparticles has high potential for quantitative cell surface antigen detection and analysis.