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Computational Biology in Cancer Genomics and Proteomics
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Computational Biology in Cancer Genomics and Proteomics

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".

Deadline for manuscript submissions: closed (20 January 2023) | Viewed by 6454

Special Issue Editors

Prof. Dr. Jing Zhang

E-Mail Website
Guest Editor
School of Engineering Medicine, Beihang University, Beijing, China
Interests: bioinformatics; cancer genomics; neoantigen; tumorigenesis
Dr. Wei Chen

E-Mail Website
Guest Editor
School of Engineering Medicine, Beihang University, Beijing, China
Interests: computational biology; cancer; genomics; genetics
Dr. Dake Zhang

E-Mail Website
Guest Editor
School of Engineering Medicine, Beihang University, Beijing, China
Interests: cancer genomics; genetics; epigenetics; biomarkers

Special Issue Information

Dear Colleagues,

Genomics and proteomics are emerging technologies which accelerate the rate and number of discoveries in cancer research. Fueled by the huge number of genomic and proteomic data, computational biology is dealing with the challenges of technically and statistically understanding these complex data, translating the information to fit cancer studies.

This Special Issue aims to provide insight into some of the cutting-edge technologies in computational biology/bioinformatics and their potential applications in the field of cancer research. Contributions may illuminate the new bioinformatics methods, explore genotype–phenotype correlations through datamining, and apply machine learning methods to characterize tumors from diverse perspectives (including but not limited to genetic pathology, diagnostic biomarkers, and single cells). To progress in the knowledge of such intricate issues, contributions by experts in the field in the form of research papers and critical reviews are required.

Prof. Dr. Jing Zhang
Dr. Wei Chen
Dr. Dake Zhang
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

  • computational biology
  • cancer genomics
  • bioinformatics
  • cancer clonal evolution
  • single-cell RNA sequencing
  • cancer proteomics

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

20 pages, 6212 KiB  
Article
EGFRvIII Promotes the Proneural–Mesenchymal Transition of Glioblastoma Multiforme and Reduces Its Sensitivity to Temozolomide by Regulating the NF-κB/ALDH1A3 Axis
by Zhong-Fang Shi, Guan-Zhang Li, You Zhai, Chang-Qing Pan, Di Wang, Ming-Chen Yu, Chi Liu, Wei Zhang and Xiao-Guang Yu
Genes 2023, 14(3), 651; https://doi.org/10.3390/genes14030651 - 4 Mar 2023
Cited by 9 | Viewed by 3235
Abstract
(1) Background: Glioblastoma multiforme (GBM) is the most common and malignant intracranial tumor in adults. At present, temozolomide (TMZ) is recognized as the preferred chemotherapeutic drug for GBM, but some patients have low sensitivity to TMZ or chemotherapy resistance to TMZ. Our previous [...] Read more.
(1) Background: Glioblastoma multiforme (GBM) is the most common and malignant intracranial tumor in adults. At present, temozolomide (TMZ) is recognized as the preferred chemotherapeutic drug for GBM, but some patients have low sensitivity to TMZ or chemotherapy resistance to TMZ. Our previous study found that GBM patients with EGFRvIII (+) have low sensitivity to TMZ. However, the reasons and possible mechanisms of the chemoradiotherapy resistance in GBM patients with EGFRvIII (+) are not clear. (2) Methods: In this study, tissue samples of patients with GBM, GBM cell lines, glioma stem cell lines, and NSG mice were used to explore the causes and possible mechanisms of low sensitivity to TMZ in patients with EGFRvIII (+)-GBM. (3) Results: The study found that EGFRvIII promoted the proneural–mesenchymal transition of GBM and reduced its sensitivity to TMZ, and EGFRvIII regulated of the expression of ALDH1A3. (4) Conclusions: EGFRvIII activated the NF-κB pathway and further regulated the expression of ALDH1A3 to promote the proneural–mesenchymal transition of GBM and reduce its sensitivity to TMZ, which will provide an experimental basis for the selection of clinical drugs for GBM patients with EGFRvIII (+). Full article
(This article belongs to the Special Issue Computational Biology in Cancer Genomics and Proteomics)
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20 pages, 1043 KiB  
Article
Identification and Characterization of Glycine- and Arginine-Rich Motifs in Proteins by a Novel GAR Motif Finder Program
by Yi-Chun Wang, Shang-Hsuan Huang, Chien-Ping Chang and Chuan Li
Genes 2023, 14(2), 330; https://doi.org/10.3390/genes14020330 - 27 Jan 2023
Cited by 4 | Viewed by 2416
Abstract
Glycine- and arginine-rich (GAR) motifs with different combinations of RG/RGG repeats are present in many proteins. The nucleolar rRNA 2′-O-methyltransferase fibrillarin (FBL) contains a conserved long N-terminal GAR domain with more than 10 RGG plus RG repeats separated by specific amino acids, mostly [...] Read more.
Glycine- and arginine-rich (GAR) motifs with different combinations of RG/RGG repeats are present in many proteins. The nucleolar rRNA 2′-O-methyltransferase fibrillarin (FBL) contains a conserved long N-terminal GAR domain with more than 10 RGG plus RG repeats separated by specific amino acids, mostly phenylanalines. We developed a GAR motif finder (GMF) program based on the features of the GAR domain of FBL. The G(0,3)-X(0,1)-R-G(1,2)-X(0,5)-G(0,2)-X(0,1)-R-G(1,2) pattern allows the accommodation of extra-long GAR motifs with continuous RG/RGG interrupted by polyglycine or other amino acids. The program has a graphic interface and can easily output the results as .csv and .txt files. We used GMF to show the characteristics of the long GAR domains in FBL and two other nucleolar proteins, nucleolin and GAR1. GMF analyses can illustrate the similarities and also differences between the long GAR domains in the three nucleolar proteins and motifs in other typical RG/RGG-repeat-containing proteins, specifically the FET family members FUS, EWS, and TAF15 in position, motif length, RG/RGG number, and amino acid composition. We also used GMF to analyze the human proteome and focused on the ones with at least 10 RGG plus RG repeats. We showed the classification of the long GAR motifs and their putative correlation with protein/RNA interactions and liquid–liquid phase separation. The GMF algorithm can facilitate further systematic analyses of the GAR motifs in proteins and proteomes. Full article
(This article belongs to the Special Issue Computational Biology in Cancer Genomics and Proteomics)
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