Molecular Mechanisms and Therapeutic Resistance in Cancer: Insights from Transcriptional Regulation and Immune Modulation
A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Pharmacology".
Deadline for manuscript submissions: 20 November 2024 | Viewed by 47
Special Issue Editor
Interests: RNA-processing; alternative polyadenylation and splicing; 3D-genomics and gene regulation; multi-modal single-cell integration; lung premalignancy and repairment mechanisms; EPI-genenomic regulators in the immune system
Special Issue Information
Dear Colleagues,
Cancer is a complex and multifaceted disease that has long been a major challenge for healthcare systems worldwide. Despite significant advances in cancer diagnosis and treatment, therapeutic resistance remains a significant obstacle to effective cancer management.
To address this challenge, we bring together experts from diverse backgrounds in translational oncology, bioinformatics, artificial intelligence, and biostatistics to share knowledge and expertise. This Special Issue aims to delve into the intricate relationship between transcriptional dysregulation in immune and other systems and its role in therapeutic resistance in cancer. Topics of interest include, but are not limited to, exploring epigenomic mechanisms, translational regulators, cell-to-cell communication, cancer microenvironmental evolution, and spatio-single-cell level interpretation. These investigations will shed light on the core factors operating at the transcriptional layer and their implications for therapeutic strategies in combating cancer resistance. Contributors to this Special Issue are encouraged to utilize state-of-the-art genomic technologies and computational methodologies to identify novel therapeutic targets and develop personalized cancer therapies. We expect contributions to be grounded in reproducible and transparent methodologies, ensuring that the provided data resources are reusable by the scientific community. This commitment to robust methodology and data sharing will facilitate the advancement of cancer research and the development of effective treatments.
Join us in this Special Issue as we explore the intersection of transcriptional dysregulation and therapeutic resistance in cancer, and discover innovative solutions to overcome this major challenge in cancer management.
Dr. Hyunmin Kim
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.
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. Pharmaceuticals 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 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
- cancer
- therapeutic resistance
- transcriptional dysregulation
- bioinformatics
- artificial intelligence
- machine learning
- cancer therapy
- resistance mechanisms
- cancer treatment
- gene regulation
- multi-omics multi-modal single cell
- cancer cell heterogeneity
