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Genes
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Bioinformatic Approaches in Cancer
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Bioinformatic Approaches in Cancer

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 4160

Special Issue Editors

Dr. Adriane F. Evangelista

E-Mail Website
Guest Editor
Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos 14784-400, Brazil
Interests: bioinformatics; cancer genome; multi-omics analysis; mutational signatures; next-generation sequencing
Dr. Rui Manuel Reis

E-Mail Website
Guest Editor
1. Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos 14784400, SP, Brazil
2. Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710057 Braga, Portugal
3. ICVS/3B's - PT Government Associate Laboratory, 4806909 Braga/Guimaraes, Portugal
Interests: cancer biomarkers; brain tumors; cancer mutations; copy number aberrations; genomic analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

You are invited to contribute to a Special Issue of Genes that will focus on a Multi-omics Approach in Cancer. The advent of high-throughput technologies has enabled the development of methods for genome-wide characterization and detection of global transcript levels. Recently, bioinformatics tools have been developed and applied to the integration of the massive amount of data across multiple omics layers. Each type of omics data provides high-dimensional and meaningful information on the molecular mechanisms underlying the disease. An integrative approach provides a basis for the development of targeted cancer therapies.

In this Special Issue of Genes, we welcome reviews, new methods, and original research articles that apply different layers of multi-omics data (i.e., genome, transcriptome, epigenome, proteome, metabolome) for cancer research.

We look forward to receiving your contributions.

Dr. Adriane F. Evangelista
Dr. Rui Manuel Reis
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 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. Genes is an international peer-reviewed open access monthly 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 2600 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 genome
  • bioinformatics in cancer
  • multi-omics approach
  • integrative analysis
  • next-generation sequencing

Published Papers (2 papers)

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Research

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15 pages, 1999 KiB  
Article
Identification of MicroRNA Expression Profiles Related to the Aggressiveness of Salivary Gland Adenoid Cystic Carcinomas
by Maicon Fernando Zanon, Cristovam Scapulatempo-Neto, Ricardo Ribeiro Gama, Márcia Maria Chiquitelli Marques, Rui Manuel Reis and Adriane Feijó Evangelista
Genes 2023, 14(6), 1220; https://doi.org/10.3390/genes14061220 - 2 Jun 2023
Cited by 1 | Viewed by 1439
Abstract
Adenoid cystic carcinoma (ACC) has been reported as the second most common carcinoma of the salivary glands. Few studies have associated miRNA expression with ACC aggressiveness. In this study, we evaluated the miRNA profile of formalin-fixed, paraffin-embedded (FFPE) samples of salivary gland ACC [...] Read more.
Adenoid cystic carcinoma (ACC) has been reported as the second most common carcinoma of the salivary glands. Few studies have associated miRNA expression with ACC aggressiveness. In this study, we evaluated the miRNA profile of formalin-fixed, paraffin-embedded (FFPE) samples of salivary gland ACC patients using the NanoString platform. We studied the miRNA expression levels associated with the solid growth pattern, the more aggressive histologic feature of ACCs, compared with the tubular and cribriform growth patterns. Moreover, the perineural invasion status, a common clinicopathological feature of the disease that is frequently associated with the clinical progression of ACC, was investigated. The miRNAs showing significant differences between the study groups were selected for target prediction and functional enrichment, which included associations with the disease according to dedicated databases. We observed decreased expression of miR-181d, miR-23b, miR-455, miR-154-5p, and miR-409 in the solid growth pattern compared with tubular and cribriform growth patterns. In contrast, miR-29c, miR-140, miR-195, miR-24, miR-143, and miR-21 were overexpressed in patients with perineural invasion. Several target genes of the miRNAs identified have been associated with molecular processes involved in cell proliferation, apoptosis, and tumor progression. Together, these findings allowed the characterization of miRNAs potentially associated with aggressiveness in salivary gland adenoid cystic carcinoma. Our results highlight important new miRNA expression profiles involved in ACC carcinogenesis that could be associated with the aggressive behavior of this tumor type. Full article
(This article belongs to the Special Issue Bioinformatic Approaches in Cancer)
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Review

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23 pages, 2503 KiB  
Review
Single-Cell Analysis in the Omics Era: Technologies and Applications in Cancer
by Michele Massimino, Federica Martorana, Stefania Stella, Silvia Rita Vitale, Cristina Tomarchio, Livia Manzella and Paolo Vigneri
Genes 2023, 14(7), 1330; https://doi.org/10.3390/genes14071330 - 24 Jun 2023
Viewed by 2354
Abstract
Cancer molecular profiling obtained with conventional bulk sequencing describes average alterations obtained from the entire cellular population analyzed. In the era of precision medicine, this approach is unable to track tumor heterogeneity and cannot be exploited to unravel the biological processes behind clonal [...] Read more.
Cancer molecular profiling obtained with conventional bulk sequencing describes average alterations obtained from the entire cellular population analyzed. In the era of precision medicine, this approach is unable to track tumor heterogeneity and cannot be exploited to unravel the biological processes behind clonal evolution. In the last few years, functional single-cell omics has improved our understanding of cancer heterogeneity. This approach requires isolation and identification of single cells starting from an entire population. A cell suspension obtained by tumor tissue dissociation or hematological material can be manipulated using different techniques to separate individual cells, employed for single-cell downstream analysis. Single-cell data can then be used to analyze cell–cell diversity, thus mapping evolving cancer biological processes. Despite its unquestionable advantages, single-cell analysis produces massive amounts of data with several potential biases, stemming from cell manipulation and pre-amplification steps. To overcome these limitations, several bioinformatic approaches have been developed and explored. In this work, we provide an overview of this entire process while discussing the most recent advances in the field of functional omics at single-cell resolution. Full article
(This article belongs to the Special Issue Bioinformatic Approaches in Cancer)
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