Special Issue "Biomarkers in Cancer"
Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 28140
Interests: cancer genetics; cancer biomarkers; cancer-related germline variants; cancer risk; radiation
Cancer biomarkers are any measurable indicator of risk of cancer, occurrence of cancer, or patient outcome. They may include, among other things, germline or somatic genetic variants, epigenetic signatures, transcriptional changes (in mRNA, microRNA, or other non-coding RNA), and proteomic signatures. These indicators are based on biomolecules, such as nucleic acids and proteins, that can be detected in samples obtained easily and non-invasively from blood (or serum or plasma), saliva, buccal swabs, stool, urine, or sputum. They can also be detected in samples from tissues, but in this case a biopsy is necessary. Detection technologies have advanced tremendously over the last few decades, including techniques such as next-generation sequencing, single-cell genomics, and methods for studying circulating tumor DNA or exosomes released or secreted by tumor cells, respectively.
The clinical applications of biomarkers are extensive. They can be used as tools for cancer risk assessment, screening and early detection of cancer, accurate diagnosis, patient prognosis, and prediction of response to chemotherapy or radiotherapy. Therefore, they can help to optimize decision-making in clinical practice. For example, cancer patients identified as patients with a favorable prognosis can benefit from therapy optimization and avoid side effects and even treatment toxicity. Moreover, newly developed targeted therapies are functional only on patients with specific genetic mutations in cancer cells and cancer biomarkers are the tools used for the identification of these subsets of patients. This is known as precision oncology. However, there remains room for improvement in the field of cancer biomarkers. Nowadays, a scientific challenge for researchers is the identification of new biomarkers with greater sensitivity and specificity and a positive predictive value.
This Special Issue will contain original research articles and reviews describing the background on cancer biomarkers and providing updated knowledge of recent advances. We welcome articles that focus on biomarkers for cancer predisposition, screening/early detection, or diagnosis confirmation, as well as biomarkers for personalized cancer treatment.
Dr. Gemma Armengol
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. Biomolecules 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 2700 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.
- cancer biomarkers
- cancer predisposition
- cancer risk
- early detection
- response to therapy
- personalized cancer treatment
- precision oncology