Technological Development for Advances in Cancer Research and Precision Oncology

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Molecular Cancer Biology".

Deadline for manuscript submissions: 23 December 2024 | Viewed by 844

Special Issue Editors


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Co-Guest Editor
Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, PA 17033-0850, USA
Interests: bioinformatics; genomics; machine learning
Special Issues, Collections and Topics in MDPI journals

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Co-Guest Editor
College of Information Sciences and Technology, Institute for Computational and Data Sciences, Pennsylvania State University, University Park, State College, PA 16802, USA
Interests: data mining; healthcare informatics; machine learning; natural language processing

Special Issue Information

Dear Colleagues,

Innovations in a wide variety of technologies have accelerated cancer research and transformed clinical oncology. Applications of machine learning and advanced bioinformatics have made progressive breakthroughs in high-dimensional data analytics for cancer prediction. Novel methodologies for the isolation and analysis of extracellular vesicles, cell-free DNA/RNA/protein, circulating tumor cells, and molecular ty** have emerged for clinical utility in detection and monitoring of cancer. Advances in single-cell profiling, genome editing, three-dimensional printing, and organoid technology have enhanced our understanding of cancer biology and the development of diagnostic tools and therapeutics. Multi-platform molecular analyses along with the development of targeted agents have led to achievement of personalized cancer therapy. Molecular, cellular, and organismal engineering have had a major impact on basic and translational cancer research. Advances in nanotechnology, molecular probes, spectrometry, and cryo-electron microscopy, as well as applications of biosensors, robotics, and radiation sciences, have accelerated the progress against cancer.

In this Special Issue, we aim to showcase recent advances and innovations in technologies for cancer research and precision oncology. We invite the submission of manuscripts covering all cancer types, from basic laboratory research to translational and clinical research. Narrated reviews describing the history and significant contributions of technology in cancer research are also welcome.

Dr. Nelson Yee
Dr. Ilias Georgakopoulos-Soares
Dr. Fenglong Ma
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at mdpi.longhoe.net 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. Cancers is an international peer-reviewed open access semimonthly 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 2900 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

  • bioengineering
  • bioinformatics
  • biosensor
  • extracellular vesicles
  • genome editing
  • machine learning
  • molecular profiling
  • nanoparticles
  • organoids
  • robotics

Published Papers (1 paper)

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Research

14 pages, 1973 KiB  
Article
3D Chromatin Alteration by Disrupting β-Catenin/CBP Interaction Is Enriched with Insulin Signaling in Pancreatic Cancer
by Yufan Zhou, Zhi**g He, Tian Li, Lavanya Choppavarapu, **aohui Hu, Ruifeng Cao, Gustavo W. Leone, Michael Kahn and Victor X. **
Cancers 2024, 16(12), 2202; https://doi.org/10.3390/cancers16122202 - 12 Jun 2024
Viewed by 470
Abstract
The therapeutic potential of targeting the β-catenin/CBP interaction has been demonstrated in a variety of preclinical tumor models with a small molecule inhibitor, ICG-001, characterized as a β-catenin/CBP antagonist. Despite the high binding specificity of ICG-001 for the N-terminus of CBP, this β-catenin/CBP [...] Read more.
The therapeutic potential of targeting the β-catenin/CBP interaction has been demonstrated in a variety of preclinical tumor models with a small molecule inhibitor, ICG-001, characterized as a β-catenin/CBP antagonist. Despite the high binding specificity of ICG-001 for the N-terminus of CBP, this β-catenin/CBP antagonist exhibits pleiotropic effects. Our recent studies found global changes in three-dimensional (3D) chromatin architecture in response to disruption of the β-catenin/CBP interaction in pancreatic cancer cells. However, an understanding of how the functional crosstalk between the antagonist and the β-catenin/CBP interaction affects changes in 3D chromatin architecture and, thereby, gene expression and downstream effects remains to be elucidated. Here, we perform Hi-C analyses on canonical and patient-derived pancreatic cancer cells before and after treatment with ICG-001. In addition to global alteration of 3D chromatin domains, we unexpectedly identify insulin signaling genes enriched in the altered chromatin domains. We further demonstrate that the chromatin loops associated with insulin signaling genes are significantly weakened after ICG-001 treatment. We finally elicit the deletion of a loo** of IRS1—a key insulin signaling gene—significantly impeding pancreatic cancer cell growth, indicating that loo**-mediated insulin signaling might act as an oncogenic pathway to promote pancreatic cancer progression. Our work shows that targeting aberrant insulin chromatin loo** in pancreatic cancer might provide a therapeutic benefit. Full article
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