María González-González

Nanotechniques in proteomics: Protein microarrays and novel detection platforms

The field of proteomics has undergone rapid advancements over the last decade and protein microarrays have emerged as a promising technological platform for the challenging tasks of studying complex proteomes. Researchers have gone beyond traditional techniques and approached promising disciplines like nanotechnology to satisfy the growing demands of studying proteins in high-throughput format. Applications of nanotechnology in proteomics came from the need to detect low-abundant proteins in complex mixtures for sensitive, real-time and multiplexed detection platform. The scope of this article is to outline the current status and key technological advances of nanotechniques in protein microarrays.

Biomarker Discovery by Novel Sensors Based on Nanoproteomics Approaches

During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors.

New technologies in cancer. Protein microarrays for biomarker discovery

The emergence of proteomic techniques and methodological approaches to study disease has kindled the quest for new biomarkers. Thus, the use of protein microarrays has surged as a powerful tool for large-scale testing of biological samples. In this mini-review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.

Self-assembled protein arrays from an Ornithodoros moubata salivary gland expression library.

Protein interactions play a critical role in the regulation of many biological events and their study in a high-throughput format has become a key area of proteomic research. Nucleid Acid Programmable Protein Arrays (NAPPA) technology allows the construction of protein arrays from cDNA expression libraries in high-throughput cell-free systems to study protein interaction and functions. Tick saliva contains antihemostatic, anti-inflammatory, and immunosuppressive proteins that counteract the host hemostatic, immune, and inflammatory responses allowing the ingestion of host blood and facilitating its infection by the tick-borne pathogens. Identification of such proteins and their functions could help in the selection of antigenic targets for the development of antitick and transmission-blocking vaccines. With that aim, we have prepared a cDNA expression library from the salivary glands of Ornithodoros moubata and subsequently produced a self-assembled protein microarray using 480 randomly selected clones from that library. The reproducibility of the array, its representativeness of the tick salivary protein repertoire, and the functionality of the in situ expressed proteins have been checked, demonstrating that it is a suitable tool for the identification and functional characterization of soft tick salivary molecules that interact with host proteins. Several clones in the array were shown to bind to human recombinant P-selectin. One of them was a likely secreted tick phospholipase A2, which may represent a potential new ligand for P-selectin. As these salivary molecules are likely involved in blood meal acquisition through the modulation of the host immune and hemostatic responses, this new high-throughput tool could open new avenues for development of new therapeutic agents and control strategies against ticks and tick-borne pathogens.

Intratumoural cytogenetic heterogeneity of sporadic colorectal carcinomas suggests several pathways to liver metastasis

Much has been learned about the chromosomal abnormalities of colorectal carcinomas but the cytogenetic relationship between the neoplastic clones present in primary versus metastatic tumour samples remains unclear. We analyse the frequency of abnormalities for 47 chromosome regions using the interphase fluorescence in situ hybridization technique in a group of 48 tumours, including 24 primary colorectal tumours and 24 paired liver metastases. All tumours showed complex karyotypes with numerical/structural abnormalities for seven or more different chromosomes/chromosome regions both in the primary tumours and in their paired metastases. Chromosome 8 was the most frequently altered (22/24 primary tumours), consistently showing del(8p22) and/or gains/amplification of 8q24, followed by abnormalities of the entire chromosome 7 (21/24 primary tumours) and of chromosomes 17p and 20q (20/24 primary tumours). Simultaneous staining for multiple chromosome probes revealed the presence of two or more tumour cell clones in 23/24 cases (46/48 tumour samples). Interestingly, the liver metastases typically contained tumour cell clones similar to those found in the primary tumours, suggesting the absence of selective selection of specific tumour clones. Despite this, additional chromosomal abnormalities were detected in 23/24 metastatic tumours, which preferentially consisted of del(17p13) and gains/amplification of 11q13 and 20q13; moreover, compared to primary tumours, metastases showed an increased number of abnormalities of chromosomes 1p, 7q, 8q, 13q, and 18q, and new chromosomal abnormalities involving chromosomes 6, 10q23, 14q32, 15q22, and 19q13. Owing to the high frequency of numerical abnormalities of the entire chromosome 7 and loss and/or gain/amplification of specific regions of chromosome 8, eg del(8p22) and/or gains/amplification of 8q24 in primary colorectal tumours with associated metastases, it is suggested that their assessment at diagnosis could be of great clinical utility for the identification of colorectal cancer patients at higher risk of developing liver metastases. Copyright

Analysis of autoantibody profiles in osteoarthritis using comprehensive protein array concepts.

Osteoarthritis (OA) is the most common rheumatic disease and one of the most disabling pathologies worldwide. To date, the diagnostic methods of OA are very limited, and there are no available medications capable of halting its characteristic cartilage degeneration. Therefore, there is a significant interest in new biomarkers useful for the early diagnosis, prognosis, and therapeutic monitoring. In the recent years, protein microarrays have emerged as a powerful proteomic tool to search for new biomarkers. In this study, we have used two concepts for generating protein arrays, antigen microarrays, and NAPPA (nucleic acid programmable protein arrays), to characterize differential autoantibody profiles in a set of 62 samples from OA, rheumatoid arthritis (RA), and healthy controls. An untargeted screen was performed on 3840 protein fragments spotted on planar antigen arrays, and 373 antigens were selected for validation on bead-based arrays. In the NAPPA approach, a targeted screening was performed on 80 preselected proteins. The autoantibody targeting CHST14 was validated by ELISA in the same set of patients. Altogether, nine and seven disease related autoantibody target candidates were identified, and this work demonstrates a combination of these two array concepts for biomarker discovery and their usefulness for characterizing disease-specific autoantibody profiles.

Unique genetic profile of sporadic colorectal cancer liver metastasis versus primary tumors as defined by high-density single-nucleotide polymorphism arrays

Most genetic studies in colorectal carcinomas have focused on those abnormalities that are acquired by primary tumors, particularly in the transition from adenoma to carcinoma, whereas few studies have compared the genetic abnormalities of primary versus paired metastatic samples. In this study, we used high-density 500K single-nucleotide polymorphism arrays to map the overall genetic changes present in liver metastases (n=20) from untreated colorectal carcinoma patients studied at diagnosis versus their paired primary tumors (n=20). MLH1, MSH2 and MSH6 gene expression was measured in parallel by immunohistochemistry. Overall, metastatic tumors systematically contained those genetic abnormalities observed in the primary tumor sample from the same subject. However, liver metastases from many cases (up to 8 out of 20) showed acquisition of genetic aberrations that were not found in their paired primary tumors. These new metastatic aberrations mainly consisted of (1) an increased frequency of genetic lesions of chromosomes that have been associated with metastatic colorectal carcinoma (1p, 7p, 8q, 13q, 17p, 18q, 20q) and, more interestingly, (2) acquisition of new chromosomal abnormalities (eg, losses of chromosomes 4 and 10q and gains of chromosomes 5p and 6p). These genetic changes acquired by metastatic tumors may be associated with either the metastatic process and/or adaption of metastatic cells to the liver microenvironment. Further studies in larger series of patients are necessary to dissect the specific role of each of the altered genes and chromosomal regions in the metastatic spread of colorectal tumors.

Mapping of Genetic Abnormalities of Primary Tumours from Metastatic CRC by High-Resolution SNP Arrays

Background For years, the genetics of metastatic colorectal cancer (CRC) have been studied using a variety of techniques. However, most of the approaches employed so far have a relatively limited resolution which hampers detailed characterization of the common recurrent chromosomal breakpoints as well as the identification of small regions carrying genetic changes and the genes involved in them. Methodology/Principal Findings Here we applied 500K SNP arrays to map the most common chromosomal lesions present at diagnosis in a series of 23 primary tumours from sporadic CRC patients who had developed liver metastasis. Overall our results confirm that the genetic profile of metastatic CRC is defined by imbalanced gains of chromosomes 7, 8q, 11q, 13q, 20q and X together with losses of the 1p, 8p, 17p and 18q chromosome regions. In addition, SNP-array studies allowed the identification of small (<1.3 Mb) and extensive/large (>1.5 Mb) altered DNA sequences, many of which contain cancer genes known to be involved in CRC and the metastatic process. Detailed characterization of the breakpoint regions for the altered chromosomes showed four recurrent breakpoints at chromosomes 1p12, 8p12, 17p11.2 and 20p12.1; interestingly, the most frequently observed recurrent chromosomal breakpoint was localized at 17p11.2 and systematically targeted the FAM27L gene, whose role in CRC deserves further investigations. Conclusions/Significance In summary, in the present study we provide a detailed map of the genetic abnormalities of primary tumours from metastatic CRC patients, which confirm and extend on previous observations as regards the identification of genes potentially involved in development of CRC and the metastatic process.

Data Analysis Strategies for Protein Microarrays.

Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation.

Association between Genetic Subgroups of Pancreatic Ductal Adenocarcinoma Defined by High Density 500 K SNP-Arrays and Tumor Histopathology

The specific genes and genetic pathways associated with pancreatic ductal adenocarcinoma are still largely unknown partially due to the low resolution of the techniques applied so far to their study. Here we used high-density 500 K single nucleotide polymorphism (SNP)-arrays to define those chromosomal regions which most commonly harbour copy number (CN) alterations and loss of heterozygozity (LOH) in a series of 20 PDAC tumors and we correlated the corresponding genetic profiles with the most relevant clinical and histopathological features of the disease. Overall our results showed that primary PDAC frequently display (>70%) extensive gains of chromosomes 1q, 7q, 8q and 20q, together with losses of chromosomes 1p, 9p, 12q, 17p and 18q, such chromosomal regions harboring multiple cancer- and PDAC-associated genes. Interestingly, these alterations clustered into two distinct genetic profiles characterized by gains of the 2q14.2, 3q22.1, 5q32, 10q26.13, 10q26.3, 11q13.1, 11q13.3, 11q13.4, 16q24.1, 16q24.3, 22q13.1, 22q13.31 and 22q13.32 chromosomal regions (group 1; n = 9) versus gains at 1q21.1 and losses of the 1p36.11, 6q25.2, 9p22.1, 9p24.3, 17p13.3 and Xp22.33 chromosomal regions (group 2; n = 11). From the clinical and histopathological point of view, group 1 cases were associated with smaller and well/moderately-differentiated grade I/II PDAC tumors, whereas and group 2 PDAC displayed a larger size and they mainly consisted of poorly-differentiated grade III carcinomas. These findings confirm the cytogenetic complexity and heterogenity of PDAC and provide evidence for the association between tumor cytogenetics and its histopathological features. In addition, we also show that the altered regions identified harbor multiple cancer associate genes that deserve further investigation to determine their relevance in the pathogenesis of PDAC.