Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.1
3.0
Journals
JPM
Special Issues
Advances of Precision Medicine in Oncology
share announcement

Advances of Precision Medicine in Oncology

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Personalized Therapy and Drug Delivery".

Deadline for manuscript submissions: 25 December 2024 | Viewed by 4091

Special Issue Editors

Dr. Panagiota Filippou

E-Mail Website
Guest Editor
1. School of Health and Life Sciences, Teesside University, Middlesbrough TS1 3BX, UK
2. National Horizons Centre, Teesside University, Darlington DL1 1HG, UK
Interests: extracellular proteolysis; proteolytic enzymes; tumor microenvironment; cytokines; chemotherapy; clinical biomarkers
Special Issues, Collections and Topics in MDPI journals
Dr. Anastasia Constantinidou

E-Mail Website
Guest Editor
1. Medical School, University of Cyprus, Nicosia 1678, Cyprus
2. Bank of Cyprus Oncology Centre, Strovolos 2011, Cyprus
3. Cyprus Cancer Research Institute (CCRI), Nicosia 2116, Cyprus
Interests: targeted therapy; translational research; cancer biomarkers; medical oncology

Special Issue Information

Dear Colleagues,

Precision medicine is an emerging medical field, representing the future for individual diagnostics and therapeutic interventions. Targeted to the molecular basis of cancer, precision oncology uses individual differences to create personalized treatment plans. Consequently, it is of significance to develop a deeper understanding of molecular portraits and advance personalized diagnostics and therapeutic interventions accordingly.

This Special Issue focuses on the identification and elucidation of the role of novel biomolecules implicated in cancer progression and the tumor- and metastasis-promoting microenvironment, their clinical applications as cancer biomarkers and the development of novel personalized treatments.

We welcome authors to submit original research and reviews on malignancies. Submissions should focus on (but are not limited to) the following areas:

  • Emerging technologies for cancer biomarker discovery.
  • Identification of novel proteins and other biomolecules as cancer biomarkers in diagnostics and the tumour pathways for therapeutics.
  • Molecular diagnostic approaches and bioinformatics to guide cancer diagnosis and treatment.
  • Clinical applications in precision cancer medicine.
  • Circulating tumor cells and circulating tumor DNA in liquid biopsies.

Dr. Panagiota Filippou
Dr. Anastasia Constantinidou
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. Journal of Personalized Medicine 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

  • precision medicine
  • personalized cancer care
  • circulating tumor cells
  • biomolecules
  • liquid biopsies
  • omics technologies
  • biomarkers

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

26 pages, 7080 KiB  
Article
Integrative Analysis of Multi-Omics Data to Identify Deregulated Molecular Pathways and Druggable Targets in Chronic Lymphocytic Leukemia
by Dimitra Mavridou, Konstantina Psatha and Michalis Aivaliotis
J. Pers. Med. 2024, 14(8), 831; https://doi.org/10.3390/jpm14080831 - 6 Aug 2024
Viewed by 1437
Abstract
Chronic Lymphocytic Leukemia (CLL) is the most common B-cell malignancy in the Western world, characterized by frequent relapses despite temporary remissions. Our study integrated publicly available proteomic, transcriptomic, and patient survival datasets to identify key differences between healthy and CLL samples. We exposed [...] Read more.
Chronic Lymphocytic Leukemia (CLL) is the most common B-cell malignancy in the Western world, characterized by frequent relapses despite temporary remissions. Our study integrated publicly available proteomic, transcriptomic, and patient survival datasets to identify key differences between healthy and CLL samples. We exposed approximately 1000 proteins that differentiate healthy from cancerous cells, with 608 upregulated and 415 downregulated in CLL cases. Notable upregulated proteins include YEATS2 (an epigenetic regulator), PIGR (Polymeric immunoglobulin receptor), and SNRPA (a splicing factor), which may serve as prognostic biomarkers for this disease. Key pathways implicated in CLL progression involve RNA processing, stress resistance, and immune response deficits. Furthermore, we identified three existing drugs—Bosutinib, Vorinostat, and Panobinostat—for potential further investigation in drug repurposing in CLL. We also found limited correlation between transcriptomic and proteomic data, emphasizing the importance of proteomics in understanding gene expression regulation mechanisms. This generally known disparity highlights once again that mRNA levels do not accurately predict protein abundance due to many regulatory factors, such as protein degradation, post-transcriptional modifications, and differing rates of translation. These results demonstrate the value of integrating omics data to uncover deregulated proteins and pathways in cancer and suggest new therapeutic avenues for CLL. Full article
(This article belongs to the Special Issue Advances of Precision Medicine in Oncology)
►▼ Show Figures

Figure 1

23 pages, 11038 KiB  
Article
A Multi-Omics Analysis of an Exhausted T Cells’ Molecular Signature in Pan-Cancer
by Christos Rigopoulos, Ilias Georgakopoulos-Soares and Apostolos Zaravinos
J. Pers. Med. 2024, 14(7), 765; https://doi.org/10.3390/jpm14070765 - 18 Jul 2024
Viewed by 2148
Abstract
T cells are essential tumor suppressors in cancer immunology, but their dysfunction induced by cancer cells can result in T cell exhaustion. Exhausted T cells (Tex) significantly influence the tumor immune environment, and thus, there is a need for their thorough investigation across [...] Read more.
T cells are essential tumor suppressors in cancer immunology, but their dysfunction induced by cancer cells can result in T cell exhaustion. Exhausted T cells (Tex) significantly influence the tumor immune environment, and thus, there is a need for their thorough investigation across different types of cancer. Here, we address the role of Tex cells in pan-cancer, focusing on the expression, mutations, methylation, immune infiltration, and drug sensitivity of a molecular signature comprising of the genes HAVCR2, CXCL13, LAG3, LAYN, TIGIT, and PDCD1across multiple cancer types, using bioinformatics analysis of TCGA data. Our analysis revealed that the Tex signature genes are differentially expressed across 14 cancer types, being correlated with patient survival outcomes, with distinct survival trends. Pathway analysis indicated that the Tex genes influence key cancer-related pathways, such as apoptosis, EMT, and DNA damage pathways. Immune infiltration analysis highlighted a positive correlation between Tex gene expression and immune cell infiltration in bladder cancer, while mutations in these genes were associated with specific immune cell enrichments in UCEC and SKCM. CNVs in Tex genes were widespread across cancers. We also highlight high LAYN methylation in most tumors and a negative correlation between methylation levels and immune cell infiltration in various cancers. Drug sensitivity analysis identified numerous correlations, with CXCL13 and HAVCR2 expressions influencing sensitivity to several drugs, including Apitolisib, Belinostat, and Docetaxel. Overall, these findings highlight the importance of reviving exhausted T cells to enhance the treatment efficacy to significantly boost anti-tumor immunity and achieve better clinical outcomes. Full article
(This article belongs to the Special Issue Advances of Precision Medicine in Oncology)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop