PDX Finder: A Portal for Patient-Derived tumor Xenograft Model Discovery
Preprint posted on 5 April 2018 https://www.biorxiv.org/content/early/2018/04/05/291443
Article now published in Nucleic Acids Research at http://dx.doi.org/10.1093/nar/gky984
An open information resource for patient-derived tumor models: PDX Finder as a searchable portal to improve visibility, transparency and communication in cutting-edge cancer research.
Selected by Carmen Adriaens
Categories: cancer biology, cell biology, clinical trials, genetics, genomics
Background
In the past 15 years, tens of laboratories all over the world have implemented patient-derived tumor xenograft (PDX) models as a powerful tool to study cancer. The principle is simple: upon biopsy in the clinic, a piece or a suspension of the resected tumorous tissue is engrafted either orthotopically or subcutaneously in an immunocompromised mouse. If the graft is successful, the grown tumor can be re-transplanted (expanded) into another set of mice (2nd generation) and so on, until several mice bear the same parent tumor and can be used for experiments. Over generations of host mice, the human tumor stroma is usually replaced by mouse stroma, but the cancerous tissue retains its principal molecular and histological characteristics.
PDX models have several advantages over in vitro– or cell line graft- based techniques. For instance, they retain well the cellular heterogeneity found in the original tumors and they usually respond to a treatment in a manner similar to the donor. They can even be predictive of resistance development or response rate. Moreover, as opposed to genetically engineered mouse models (GEMMs), the cells are of human origin, and data generated for the models is directly relevant to the study of human cancer biology.
PDX models are used for several cancer-related applications. For instance, the engraftment rate and success of a tumor can be examined diagnostically to determine stage and aggressiveness. They are employed to resolve important biological questions such as what the tumor heterogeneity is, whether a cell-of-origin exists, or if certain tumor cells are intrinsically resistant to therapy. Recently, the field has imagined a more clinically relevant application: although expensive and not devoid of risk (and if anything, still in a very controversial light), PDX models could be used as “avatars” for cancer patients. In such a scenario, several drug combinations and treatment courses can be tested and characterized before an actual therapy scheme is established in the clinic.
The problem
“Alone, we can do so little; together, we can do so much.” — Helen Keller
Although many labs have developed PDX models, the techniques to do so are not standardized and the reporting and availability of data, especially, are limited and scattered, or very heterogeneous among different groups. In a community effort, several world-wide consortia recently established PDX-MI, a Minimal Information set of guidelines that recommends PDX users to report “essential” and “desirable” data modules when new models or research is published (Meehan, Conte et al. Cancer Research, 2017). Since the use of PDX is rapidly expanding, there is a pressing need for a centralized database containing the available models and their minimal information. A such, they can be shared globally to prevent redundant studies and the perfect PDX and associated data can be easily found for the specific research question asked.
The preprint
In this preprint, Conte et al. present PDX Finder (www.PDXfinder.org), an online database aiming to solve the decentralization of available models and the information about them. For now, seven PDX centers (one in Italy, six in the US) have joined the database. The authors invite all other centers from around the world to participate.
PDX finder provides a searchable platform for PDX models of different cancer types, and searches can be narrowed to the geographical location of the model, the anatomical system, collection site, molecular characteristics, type of host and patient, mouse generation etc. It will be updated with clinically and biologically relevant information, where available, and aims to improve the visibility of cancer models for future studies.
My opinion
Overall, I think this preprint is a clear and concise description of the website and serves its citation and dissemination purposes well. Importantly, I believe this manuscript is a worthy attempt to address a recurrent issue in modern science: the lack of transparency, standardization, data availability, and mobility of reagents and skills.
This preprint and the PDX Finder website is a small but important step forward by aiming to centralize the information. It may help to increase the visibility of available models and stimulate communication between biologists, clinicians, and informaticians. Hopefully, the platform will encourage exchange among different centers and laboratories, which will be especially valuable when done within the framework of the PDX-MI. Furthermore, the use of animal models for research and clinical purpose is obviously not without controversy. This database may hence contribute to the three R’s – Replace, Reduce, Refine. A central platform can help to avoid duplicate models for fundamental research, and in contrast, may reveal gaps in molecular subtypes for individual tumor type PDX models.
In conclusion, I believe that, although as with all animal models their use needs reasonable caution, overall PDX models are an excellent and robust tool to study cancer. In past years they appear to have taken center stage successfully and seem ready to revolutionize cancer research. I like to think we all strive towards the same objective of understanding and trying to cure cancer, and we will need to bundle our efforts to succeed. Ultimately, PDX Finder may help to achieve that goal in an effective and transparent manner.
Posted on: 20 April 2018
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