Special Issue "Patient-Derived Cancer Models from Basic Study to Clinical Application"
A special issue of Cells (ISSN 2073-4409).
Deadline for manuscript submissions: closed (31 May 2019).
Interests: Rare cancer research; sarcoma; proteogenomics; applications of patient-derived cancer model
Special Issues and Collections in MDPI journals
Patient-derived cancer models are essential tools in both basic cancer research and pre-clinical studies. Such models are generated either by inoculating tumor tissues into experimental animals, such as mouse and chicken egg, or by maintaining tumor cells under in vitro tissue culture conditions. Patient-derived cancer models have been used extensively in cancer research, and our current understanding of tumor biology is largely based on the results of experiments using these models. Moreover, based on the assumption that patient-derived cancer models can faithfully reflect the therapeutic response of human cancers, these models have been used in the screening and evaluation of drug candidates and in the investigation of novel drugs’ indications. These models may also be potent to predict the response of individual patients to various treatments, thereby facilitating clinical trials and contributing to precision medicine. Although the utility of such models is obvious in basic research and seems promising in clinical applications, they have several limitations. For example, global gene and protein studies have revealed significant similarities but also dissimilarities between clinical tumors and their models. This suggests that the models may not represent the clinical and biological characteristics of each cancer sufficiently. Moreover, the take rate of common subcutaneous xenografts varies across different cancers and is less than 50% on average. Therefore, the current cancer models may not be applicable to routine clinical practice. Taken together, we need to understand the characteristics of cancer, optimize the specifics of cancer models, and generate novel models that faithfully reproduce the critical clinical features of various cancers. This Special Issue of Cells should improve our understanding of the possibilities and limitations of patient-derived cancer models by including works from investigators both performing cancer research using patient-derived cancer models and engaged in developing novel cancer models. I hope that this Special issue of Cells will contribute to the advance of cancer research through patient-derived cancer models and lead to the development of novel therapies for patients with cancer in the future.
Dr. Tadashi Kondo
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 papers will be 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. Cells 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 2000 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.
- patient-derived cancer model
- cell line
- omics study
- drug sensitivity
- clinical trial