Novel Prognostic Biomarkers in Human Cancers: From Discovery to Application
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Biomarkers".
Deadline for manuscript submissions: 15 May 2024 | Viewed by 1042
Special Issue Editor
Interests: tumor biomarkers; investigational markers; prognosis; biochemical relapse; overall survival; clinical trials; advancement in biomarker discovery; bioinformatics and marker discovery; AI and biomarker discovery
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Cancer is the leading cause of death among men and women worldwide, with an estimated 19.3 million new cases and approximately 10 million cancer deaths each year. Reliable molecular biomarkers can serve as accurate tools for monitoring the clinical progression of the disease, the aggressiveness of the tumor, the drug response and the overall survival of cancer patients. Non-invasive biological materials such as DNA, coding and non-coding RNA, lipids and proteins could represent an abundant source of tumor markers. Because human tumor tissue is a biologically and clinically heterogeneous matter, the molecular biomarkers currently employed do not sufficiently address the wide variety of human specimens, the state of the disease, the reproducibility of results and patients’ clinical outcomes. Researchers should further endeavor to standardize biological biomarker sources, the various methodologies utilized, the interpretation of data, and the model of analysis and multicenter studies employed in order to ensure the reliability and specificity of tumor biomarkers. Unfortunately, the current application of some routine biomarkers is limited by the occurrence of false positive results, which can lead to the overtreatment of indolent disease and mislead treatment decisions at relapse. Therefore, the development of novel strategies for more specific and reliable prognostic tumor markers is needed.
In this Special Issue, we will highlight the most recent techniques used for investigational biomarker discovery, validation and clinical studies in order to promote next-generation human tumor biomarkers that can meet the clinical needs. This Special Issue particularly welcomes the submission of full manuscripts or review articles focusing on the development and evaluation of prognostic markers.
Dr. Zakaria Y. Abd Elmageed
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. 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
- tumor biomarkers
- investigational markers
- prognosis
- biochemical relapse
- overall survival
- clinical trials
- advancement in biomarker discovery
- bioinformatics and marker discovery
- AI and biomarker discovery
