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Microarrays
Special Issues
Diagnostic, Prognostic and Predictive Cancer Biomarkers
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Diagnostic, Prognostic and Predictive Cancer Biomarkers

A special issue of Microarrays (ISSN 2076-3905).

Deadline for manuscript submissions: closed (30 June 2016) | Viewed by 21105

Special Issue Editor

Prof. Dr. Massimo Negrini

E-Mail Website
Guest Editor
Department of Morphology, Surgery and Experimental Medicine, University of Ferrara, Ferrara, Italy
Interests: cancer genomics; microRNA; non-coding RNA; RNA-based diagnostic approaches; RNA-based therapeutic approaches; expression profiling

Special Issue Information

Dear Colleagues,

Microarray approaches opened the way for high-throughput analyses of gene expression, copy number variations, and DNA polymorphisms that were expected to have an impact in the characterization of human cancer. These studies improved our understanding of cancer molecular pathogenesis and potentially useful applications were developed. More recently, Next Generation Sequencing approaches have further widened the potential of high throughput methods by allowing the nucleotide sequencing of large panels of genes or even entire genomes. Cancer genomics is in the position of translating the large amount of knowledge acquired in the past ten years into clinically useful applications, through the development of innovative and highly informative approaches that may improve the management of cancer patients.

This Special Issue invites contributions on the use of high-throughput approaches aimed at the identification of cancer biomarkers. Original manuscripts or reviews on genomics, transcriptomics, and proteomics studies are welcomed. Topics may range from molecular tumorigenesis to diagnosis, prognostic stratification, patients’ follow-up, treatment indicators, and prediction of therapy response. New high-throughput approaches or devices and methods for data analysis are also welcomed subjects. We wish to provide a wide presentation of available or potentially innovative approaches and the achieved results that originate from high-throughput approaches.

Dr. Massimo Negrini
Guest Editor

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 submissions that pass pre-check are 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. Microarrays 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

  • cancer research
  • viral oncogenesis
  • biomarkers
  • diagnosis
  • prognosis
  • screening
  • gene expression profiling
  • proteomic microarray
  • copy number variations
  • next generation sequencing
  • single-nucleotide polymorphisms
  • data analysis
  • network analysis
  • high-throughput approaches

Published Papers (4 papers)

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Research

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764 KiB  
Article
MicroRNA Profile of Lung Tumor Tissues Is Associated with a High Risk Plasma miRNA Signature
by Orazio Fortunato, Carla Verri, Ugo Pastorino, Gabriella Sozzi and Mattia Boeri
Microarrays 2016, 5(3), 18; https://doi.org/10.3390/microarrays5030018 - 05 Jul 2016
Cited by 6 | Viewed by 5140
Abstract
Lung cancer is the most common cause of cancer deaths worldwide. MicroRNAs (miRNAs) are short, non-coding RNAs that regulate gene expression. Many studies have reported that alterations in miRNA expression are involved in several human tumors. We have previously identified a circulating miRNA [...] Read more.
Lung cancer is the most common cause of cancer deaths worldwide. MicroRNAs (miRNAs) are short, non-coding RNAs that regulate gene expression. Many studies have reported that alterations in miRNA expression are involved in several human tumors. We have previously identified a circulating miRNA signature classifier (MSC) able to discriminate lung cancer with more aggressive features. In the present work, microarray miRNA profiling of tumor tissues collected from 19 lung cancer patients with an available MSC result were perform in order to find a possible association between miRNA expression and the MSC risk level. Eleven tissue mature miRNAs and six miRNA precursors were observed to be associated with the plasma MSC risk level of patients. Not one of these miRNAs was included in the MSC algorithm. A pathway enrichment analysis revealed a role of these miRNA in the main pathways determining lung cancer aggressiveness. Overall, these findings add to the knowledge that tissue and plasma miRNAs behave as excellent diagnostic and prognostic biomarkers, which may find rapid application in clinical settings. Full article
(This article belongs to the Special Issue Diagnostic, Prognostic and Predictive Cancer Biomarkers)
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1408 KiB  
Article
Small-Molecule Inhibition of Rho/MKL/SRF Transcription in Prostate Cancer Cells: Modulation of Cell Cycle, ER Stress, and Metastasis Gene Networks
by Chris R. Evelyn, Erika M. Lisabeth, Susan M. Wade, Andrew J. Haak, Craig N. Johnson, Elizabeth R. Lawlor and Richard R. Neubig
Microarrays 2016, 5(2), 13; https://doi.org/10.3390/microarrays5020013 - 28 May 2016
Cited by 14 | Viewed by 5250
Abstract
Metastasis is the major cause of cancer deaths and control of gene transcription has emerged as a critical contributing factor. RhoA- and RhoC-induced gene transcription via the actin-regulated transcriptional co-activator megakaryocytic leukemia (MKL) and serum response factor (SRF) drive metastasis in breast cancer [...] Read more.
Metastasis is the major cause of cancer deaths and control of gene transcription has emerged as a critical contributing factor. RhoA- and RhoC-induced gene transcription via the actin-regulated transcriptional co-activator megakaryocytic leukemia (MKL) and serum response factor (SRF) drive metastasis in breast cancer and melanoma. We recently identified a compound, CCG-1423, which blocks Rho/MKL/SRF-mediated transcription and inhibits PC-3 prostate cancer cell invasion. Here, we undertook a genome-wide expression study in PC-3 cells to explore the mechanism and function of this compound. There was significant overlap in the genes modulated by CCG-1423 and Latrunculin B (Lat B), which blocks the Rho/MKL/SRF pathway by preventing actin polymerization. In contrast, the general transcription inhibitor 5,6-dichloro-1-β-d-ribofuranosyl-1H-benzimidazole (DRB) showed a markedly different pattern. Effects of CCG-1423 and Lat B on gene expression correlated with literature studies of MKL knock-down. Gene sets involved in DNA synthesis and repair, G1/S transition, and apoptosis were modulated by CCG-1423. It also upregulated genes involved in endoplasmic reticulum stress. Targets of the known Rho target transcription factor family E2F and genes related to melanoma progression and metastasis were strongly suppressed by CCG-1423. These results confirm the ability of our compound to inhibit expression of numerous Rho/MKL-dependent genes and show effects on stress pathways as well. This suggests a novel approach to targeting aggressive cancers and metastasis. Full article
(This article belongs to the Special Issue Diagnostic, Prognostic and Predictive Cancer Biomarkers)
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2439 KiB  
Article
Stromal Activation by Tumor Cells: An in Vitro Study in Breast Cancer
by Giuseppe Merlino, Patrizia Miodini, Biagio Paolini, Maria Luisa Carcangiu, Massimiliano Gennaro, Matteo Dugo, Maria Grazia Daidone and Vera Cappelletti
Microarrays 2016, 5(2), 10; https://doi.org/10.3390/microarrays5020010 - 18 May 2016
Cited by 5 | Viewed by 5181
Abstract
Background: The tumor microenvironment participates in the regulation of tumor progression and influences treatment sensitivity. In breast cancer, it also may play a role in determining the fate of non-invasive lesions such as ductal carcinoma in situ (DCIS), a non-obligate precursor of invasive [...] Read more.
Background: The tumor microenvironment participates in the regulation of tumor progression and influences treatment sensitivity. In breast cancer, it also may play a role in determining the fate of non-invasive lesions such as ductal carcinoma in situ (DCIS), a non-obligate precursor of invasive diseases, which is aggressively treated despite its indolent nature in many patients since no biomarkers are available to predict the progression of DCIS to invasive disease. In vitro models of stromal activation by breast tumor cells might provide clues as to specific stromal genes crucial for the transition from DCIS to invasive disease. Methods: normal human dermal fibroblasts (NHDF) were treated under serum-free conditions with cell culture media conditioned by breast cancer cell lines (SkBr3, MDA-MB-468, T47D) for 72 h and subjected to gene expression profiling with Illumina platform. Results: TGM2, coding for a tissue transglutaminase, was identified as candidate gene for stromal activation. In public transcriptomic datasets of invasive breast tumors TGM2 expression proved to provide prognostic information. Conversely, its role as an early biosensor of tumor invasiveness needs to be further investigated by in situ analyses. Conclusion: Stromal TGM2 might probably be associated with precancerous evolution at earlier stages compared to DCIS. Full article
(This article belongs to the Special Issue Diagnostic, Prognostic and Predictive Cancer Biomarkers)
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Review

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921 KiB  
Review
Genomic-Wide Analysis with Microarrays in Human Oncology
by Kenichi Inaoka, Yoshikuni Inokawa and Shuji Nomoto
Microarrays 2015, 4(4), 454-473; https://doi.org/10.3390/microarrays4040454 - 16 Oct 2015
Cited by 4 | Viewed by 5108
Abstract
DNA microarray technologies have advanced rapidly and had a profound impact on examining gene expression on a genomic scale in research. This review discusses the history and development of microarray and DNA chip devices, and specific microarrays are described along with their methods [...] Read more.
DNA microarray technologies have advanced rapidly and had a profound impact on examining gene expression on a genomic scale in research. This review discusses the history and development of microarray and DNA chip devices, and specific microarrays are described along with their methods and applications. In particular, microarrays have detected many novel cancer-related genes by comparing cancer tissues and non-cancerous tissues in oncological research. Recently, new methods have been in development, such as the double-combination array and triple-combination array, which allow more effective analysis of gene expression and epigenetic changes. Analysis of gene expression alterations in precancerous regions compared with normal regions and array analysis in drug-resistance cancer tissues are also successfully performed. Compared with next-generation sequencing, a similar method of genome analysis, several important differences distinguish these techniques and their applications. Development of novel microarray technologies is expected to contribute to further cancer research. Full article
(This article belongs to the Special Issue Diagnostic, Prognostic and Predictive Cancer Biomarkers)
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