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Molecular Research of Multi-omics in Cancer

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Oncology".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 1598

Special Issue Editor


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Guest Editor
Department of Microbiology, Immunology, and Physiology: Bioinformatics Core, Meharry Medical College, Nashville, TN 37208, USA
Interests: bioinformatics; genomics; transcriptomics; proteomics; biomedical informatics; health disparities

Special Issue Information

Dear Colleagues,

Bioinformatics and “omics”-level technologies have revolutionized cancer research by utilizing computational methods to analyze large-scale biological data. High-throughput sequencing (HTS), such as DNA-Seq and RNA-Seq, combined with advances in proteomics-scale mass spectrometry have significantly contributed to molecular biology methods in discovering novel pathways in cancer. Advanced algorithms have facilitated the discovery of biomarkers for early detection and personalized treatment strategies. Bioinformatics contributes to precision medicine, allowing researchers to uncover molecular intricacies and develop targeted therapies, significantly advancing our understanding and treatment of cancer.

This Special Issue aims to contribute to the evolving landscape of cancer research by leveraging advanced bioinformatics and molecular biology techniques. By focusing on bioinformatics utilizing high-throughput sequencing techniques (DNA-Seq, RNA-Seq, ChIP-Seq) and/or proteomics, we hope to uncover novel perspectives that will advance our understanding of cancer and its potential implications in research and treatment. Researchers are encouraged to submit review and original research articles that contribute to the collective knowledge in this critical and rapidly evolving field.

Dr. Siddharth Pratap
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.

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Keywords

  • bioinformatics
  • biomedical informatics
  • high-throughput sequencing (HTS)/next-generation sequencing (NGS)
  • DNA-Seq/genomics
  • RNA-Req/transcriptomics
  • mass spectrometry/proteomics

 

Published Papers (1 paper)

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Research

21 pages, 9299 KiB  
Article
The Proteomic Analysis of Cancer-Related Alterations in the Human Unfoldome
by Victor Paromov, Vladimir N. Uversky, Ayorinde Cooley, Lincoln E. Liburd II, Shyamali Mukherjee, Insung Na, Guy W. Dayhoff II and Siddharth Pratap
Int. J. Mol. Sci. 2024, 25(3), 1552; https://doi.org/10.3390/ijms25031552 - 26 Jan 2024
Viewed by 1455
Abstract
Many proteins lack stable 3D structures. These intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains with intrinsically disordered protein regions (IDPRs) often carry out regulatory functions related to molecular recognition and signal transduction. IDPs/IDPRs constitute a substantial portion of the human [...] Read more.
Many proteins lack stable 3D structures. These intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains with intrinsically disordered protein regions (IDPRs) often carry out regulatory functions related to molecular recognition and signal transduction. IDPs/IDPRs constitute a substantial portion of the human proteome and are termed “the unfoldome”. Herein, we probe the human breast cancer unfoldome and investigate relations between IDPs and key disease genes and pathways. We utilized bottom-up proteomics, MudPIT (Multidimensional Protein Identification Technology), to profile differentially expressed IDPs in human normal (MCF-10A) and breast cancer (BT-549) cell lines. Overall, we identified 2271 protein groups in the unfoldome of normal and cancer proteomes, with 148 IDPs found to be significantly differentially expressed in cancer cells. Further analysis produced annotations of 140 IDPs, which were then classified to GO (Gene Ontology) categories and pathways. In total, 65% (91 of 140) IDPs were related to various diseases, and 20% (28 of 140) mapped to cancer terms. A substantial portion of the differentially expressed IDPs contained disordered regions, confirmed by in silico characterization. Overall, our analyses suggest high levels of interactivity in the human cancer unfoldome and a prevalence of moderately and highly disordered proteins in the network. Full article
(This article belongs to the Special Issue Molecular Research of Multi-omics in Cancer)
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