Special Issue "Applications of Microarrays in Diagnostics"

A special issue of High-Throughput (ISSN 2571-5135).

Deadline for manuscript submissions: closed (15 September 2018)

Special Issue Editors

Guest Editor
Prof. Dr. Pierosandro Tagliaferri

Department of Experimental and Clinical Medicine, Magna Graecia University, Salvatore Venuta University Campus, Catanzaro Italy
Website | E-Mail
Interests: cancer; clinical trials; immunotherapy; translational research; biomarker discovery; pharmacogenomics, biostatistics, microarrays
Guest Editor
Dr. Maria Teresa Di Martino

Department of Experimental and Clinical Medicine, Magna Graecia University, Salvatore Venuta University Campus, Catanzaro Italy
Website | E-Mail
Interests: cellular and molecular biology of human cancer; gene expression profiling; pharmacogenomics; microarrays; integrative genomics
Guest Editor
Prof. Dr. Pierfrancesco Tassone

Department of Experimental and Clinical Medicine, Magna Graecia University, Salvatore Venuta University Campus, Catanzaro Italy
Website | E-Mail
Interests: cancer; clinical trials; immunotherapy; translational research; animal models of human cancer; biomarker discovery; pharmacogenomics

Special Issue Information

Dear Colleagues,

The use of microarray-based assays for gene expression and genomic DNA analysis has rapidly expanded in various fields of molecular biology, including life sciences, translational research and molecular diagnostics. The success of the microarray technologies derives from their ability to perform multiplex analysis of biological systems at the cellular, protein, and genetic levels in a massively parallel way. The recent advances in array technology, bioinformatics, and statistics, as well as the reductions in costs, have reinforced the clinical utility of microarrays for diagnostic, prognostic, or therapeutic purposes in healthcare. For this Special Issue, we invite submissions on the applications of microarray analysis in disease diagnostics and personalized medicine. These include biomarker discovery, diagnosis and classification of human cancers, pharmacogenetics, proteomics, and chromosomal analysis, as well as analytical tools for data processing and analysis.

Prof. Dr. Pierosandro Tagliaferri
Prof. Dr. Pierfrancesco Tassone
Dr. Maria Teresa Di Martino
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. High-Throughput is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 350 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • microarray
  • disease diagnosis
  • cancer
  • pharmacogenetics
  • biomarkers discovery
  • personalized medicine

Published Papers (5 papers)

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Research

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Open AccessArticle Development and Assessment of a Diagnostic DNA Oligonucleotide Microarray for Detection and Typing of Meningitis-Associated Bacterial Species
High-Throughput 2018, 7(4), 32; https://doi.org/10.3390/ht7040032
Received: 13 August 2018 / Revised: 11 September 2018 / Accepted: 21 September 2018 / Published: 16 October 2018
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Abstract
Meningitis is commonly caused by infection with a variety of bacterial or viral pathogens. Acute bacterial meningitis (ABM) can cause severe disease, which can progress rapidly to a critical life-threatening condition. Rapid diagnosis of ABM is critical, as this is most commonly associated [...] Read more.
Meningitis is commonly caused by infection with a variety of bacterial or viral pathogens. Acute bacterial meningitis (ABM) can cause severe disease, which can progress rapidly to a critical life-threatening condition. Rapid diagnosis of ABM is critical, as this is most commonly associated with severe sequelae with associated high mortality and morbidity rates compared to viral meningitis, which is less severe and self-limiting. We have designed a microarray for detection and diagnosis of ABM. This has been validated using randomly amplified DNA targets (RADT), comparing buffers with or without formamide, in glass slide format or on the Alere ArrayTubeTM (Alere Technologies GmbH) microarray platform. Pathogen-specific signals were observed using purified bacterial nucleic acids and to a lesser extent using patient cerebral spinal fluid (CSF) samples, with some technical issues observed using RADT and glass slides. Repurposing the array onto the Alere ArrayTubeTM platform and using a targeted amplification system increased specific and reduced nonspecific hybridization signals using both pathogen nucleic and patient CSF DNA targets, better revealing pathogen-specific signals although sensitivity was still reduced in the latter. This diagnostic microarray is useful as a laboratory diagnostic tool for species and strain designation for ABM, rather than for primary diagnosis. Full article
(This article belongs to the Special Issue Applications of Microarrays in Diagnostics)
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Open AccessArticle A Parallel Software Pipeline for DMET Microarray Genotyping Data Analysis
High-Throughput 2018, 7(2), 17; https://doi.org/10.3390/ht7020017
Received: 31 March 2018 / Revised: 21 May 2018 / Accepted: 7 June 2018 / Published: 14 June 2018
Cited by 1 | PDF Full-text (2490 KB) | HTML Full-text | XML Full-text
Abstract
Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory) based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and [...] Read more.
Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory) based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and needs of each subject, according to the study of diseases at different scales from genotype to phenotype scale. To make concrete the goal of personalized medicine, it is necessary to employ high-throughput methodologies such as Next Generation Sequencing (NGS), Genome-Wide Association Studies (GWAS), Mass Spectrometry or Microarrays, that are able to investigate a single disease from a broader perspective. A side effect of high-throughput methodologies is the massive amount of data produced for each single experiment, that poses several challenges (e.g., high execution time and required memory) to bioinformatic software. Thus a main requirement of modern bioinformatic softwares, is the use of good software engineering methods and efficient programming techniques, able to face those challenges, that include the use of parallel programming and efficient and compact data structures. This paper presents the design and the experimentation of a comprehensive software pipeline, named microPipe, for the preprocessing, annotation and analysis of microarray-based Single Nucleotide Polymorphism (SNP) genotyping data. A use case in pharmacogenomics is presented. The main advantages of using microPipe are: the reduction of errors that may happen when trying to make data compatible among different tools; the possibility to analyze in parallel huge datasets; the easy annotation and integration of data. microPipe is available under Creative Commons license, and is freely downloadable for academic and not-for-profit institutions. Full article
(This article belongs to the Special Issue Applications of Microarrays in Diagnostics)
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Review

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Open AccessReview Pharmacogenomic Profiling of ADME Gene Variants: Current Challenges and Validation Perspectives
High-Throughput 2018, 7(4), 40; https://doi.org/10.3390/ht7040040
Received: 5 October 2018 / Revised: 29 November 2018 / Accepted: 13 December 2018 / Published: 18 December 2018
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Abstract
In the past decades, many efforts have been made to individualize medical treatments, taking into account molecular profiles and the individual genetic background. The development of molecularly targeted drugs and immunotherapy have revolutionized medical treatments but the inter-patient variability in the anti-tumor drug [...] Read more.
In the past decades, many efforts have been made to individualize medical treatments, taking into account molecular profiles and the individual genetic background. The development of molecularly targeted drugs and immunotherapy have revolutionized medical treatments but the inter-patient variability in the anti-tumor drug pharmacokinetics (PK) and pharmacodynamics can be explained, at least in part, by genetic variations in genes encoding drug metabolizing enzymes and transporters (ADME) or in genes encoding drug receptors. Here, we focus on high-throughput technologies applied for PK screening for the identification of predictive biomarkers of efficacy or toxicity in cancer treatment, whose application in clinical practice could promote personalized treatments tailored on individual’s genetic make-up. Pharmacogenomic tools have been implemented and the clinical utility of pharmacogenetic screening could increase safety in patients for the identification of drug metabolism-related biomarkers for a personalized medicine. Although pharmacogenomic studies were performed in adult cohorts, pharmacogenetic pediatric research has yielded promising results. Additionally, we discuss the current challenges and theoretical bases for the implementation of pharmacogenetic tests for translation in the clinical practice taking into account that pharmacogenomics platforms are discovery oriented and must open the way for the setting of robust tests suitable for daily practice. Full article
(This article belongs to the Special Issue Applications of Microarrays in Diagnostics)
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Open AccessReview From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology
High-Throughput 2018, 7(4), 33; https://doi.org/10.3390/ht7040033
Received: 24 September 2018 / Revised: 9 October 2018 / Accepted: 22 October 2018 / Published: 26 October 2018
Cited by 1 | PDF Full-text (1313 KB) | HTML Full-text | XML Full-text
Abstract
Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, [...] Read more.
Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, a large number of multidimensional data can be derived from analysis of health and disease systems. Comprehensive analysis of multi-omics data in an integrated framework, which includes cumulative effects in the context of biological pathways, is therefore eagerly awaited. This strategy could allow the identification of pathway-addiction of cancer cells that may be amenable to therapeutic intervention. However, translation into clinical settings requires an optimized integration of omics data with clinical vision to fully exploit precision cancer medicine. We will discuss the available technical approach and more recent developments in the specific field. Full article
(This article belongs to the Special Issue Applications of Microarrays in Diagnostics)
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Open AccessReview The Cytoscan HD Array in the Diagnosis of Neurodevelopmental Disorders
High-Throughput 2018, 7(3), 28; https://doi.org/10.3390/ht7030028
Received: 30 July 2018 / Revised: 6 September 2018 / Accepted: 6 September 2018 / Published: 14 September 2018
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Abstract
Submicroscopic chromosomal copy number variations (CNVs), such as deletions and duplications, account for about 15–20% of patients affected with developmental delay, intellectual disability, multiple congenital anomalies, and autism spectrum disorder. Most of CNVs are de novo or inherited rearrangements with clinical relevance, but [...] Read more.
Submicroscopic chromosomal copy number variations (CNVs), such as deletions and duplications, account for about 15–20% of patients affected with developmental delay, intellectual disability, multiple congenital anomalies, and autism spectrum disorder. Most of CNVs are de novo or inherited rearrangements with clinical relevance, but there are also rare inherited imbalances with unknown significance that make difficult the clinical management and genetic counselling. Chromosomal microarrays analysis (CMA) are recognized as the first-line test for CNV detection and are now routinely used in the clinical diagnostic laboratory. The recent use of CMA platforms that combine classic copy number analysis with single-nucleotide polymorphism (SNP) genotyping has increased the diagnostic yields. Here we discuss the application of the Cytoscan high-density (HD) SNP-array for the detection of CNVs. We provide an overview of molecular analyses involved in identifying pathogenic CNVs and highlight important guidelines to establish pathogenicity of CNV. Full article
(This article belongs to the Special Issue Applications of Microarrays in Diagnostics)
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