Special Issue "State-of-the-Art of Gene Regulation for Cancer Cell"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Biological Processes and Systems".

Deadline for manuscript submissions: 21 December 2021.

Special Issue Editors

Prof. Dr. Yi-Jang Lee
E-Mail Website
Guest Editor
Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei 112, Taiwan
Interests: molecular radiation biology and oncology; molecular and cell biology; cancer biology; molecular imaging
Dr. Chun-Yuan Chang
E-Mail Website
Guest Editor
Radiation oncology, Rutgers Cancer Institute of New Jersey, Rutgers university, New Brunswick, NJ 08903, USA
Interests: Cellular biology, Cancer biology, Cancer immunology. To investigate the regulation of p53 and its signaling pathway in promoting CRC tumorigenesis.

Special Issue Information

Dear Colleagues,

Manipulation of gene regulation is the most common and critical technique in various fields of molecular and cell biological research. It is not only essential for elucidation of mechanisms of cell behaviors in the molecular level, but it is also a fundamental operation for multi-disciplinary research. For instance, gene regulatory technology could integrate with nanotechnology, pharmacology, theranostic technology, drug delivery, molecular imaging, immunology, and neuroscience to approach the biomedical questions from benchside to the bedside. Although gene therapy has not been fully regarded as a modern approach for cancer treatment, the investigation of gene regulation remains essential for evalulating the prognosis of therapeutic efficacy. The genes of interest are also verstile, including coding RNA and non-coding RNA with various lengths. The technologies for gene regulation are also greatly improved for the purposes of stable and general expression, low immunogenicity, target specific editing, low or high cell selectivity, cliinical intension, combining cell therapy, and development of cancer vaccines. Drug discovery is also largely related to the technology of gene regulation to validate the potent drug mechanisms and precise medicine. Therefore, we enthusiastically invite papers presenting novel developments and inventions of gene expression technology with the values of basic research and clinical applications for cancer therapy. The appropriate topics may include but are not limited to the following:

  • Genomic editing technology for expression of cancer targeting genes
  • Biocompatible vehicles for cancer specific delivery of genes
  • Advanced techniques for expression and regulation of coding RNA and non-coding RNA
  • Bioinformatics-based design of technology for expression and regulation of genes in cancers and therapeutic implications

Prof. Dr. Yi-Jang Lee
Dr. Chun-Yuan Chang
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. Processes 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 2000 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

  • CRISPR/Cas9
  • system biology
  • transposon based gene delivery
  • foamy virus, lentivirus, adenovirus and AAV
  • coding RNA and non-coding RNA
  • cancer
  • Genomic editing

Published Papers (1 paper)

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Review

Review
Estimation of Gene Regulatory Networks from Cancer Transcriptomics Data
Processes 2021, 9(10), 1758; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9101758 - 30 Sep 2021
Viewed by 305
Abstract
Cancer is a genetic disease in which multiple genes are perturbed. Thus, information about the regulatory relationships between genes is necessary for the identification of biomarkers and therapeutic targets. In this review, methods for inference of gene regulatory networks (GRNs) from transcriptomics data [...] Read more.
Cancer is a genetic disease in which multiple genes are perturbed. Thus, information about the regulatory relationships between genes is necessary for the identification of biomarkers and therapeutic targets. In this review, methods for inference of gene regulatory networks (GRNs) from transcriptomics data that are used in cancer research are introduced. The methods are classified into three categories according to the analysis model. The first category includes methods that use pair-wise measures between genes, including correlation coefficient and mutual information. The second category includes methods that determine the genetic regulatory relationship using multivariate measures, which consider the expression profiles of all genes concurrently. The third category includes methods using supervised and integrative approaches. The supervised approach estimates the regulatory relationship using a supervised learning method that constructs a regression or classification model for predicting whether there is a regulatory relationship between genes with input data of gene expression profiles and class labels of prior biological knowledge. The integrative method is an expansion of the supervised method and uses more data and biological knowledge for predicting the regulatory relationship. Furthermore, simulation and experimental validation of the estimated GRNs are also discussed in this review. This review identified that most GRN inference methods are not specific for cancer transcriptome data, and such methods are required for better understanding of cancer pathophysiology. In addition, more systematic methods for validation of the estimated GRNs need to be developed in the context of cancer biology. Full article
(This article belongs to the Special Issue State-of-the-Art of Gene Regulation for Cancer Cell)
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