At any time, most cancer patients are receiving a treatment that does not significantly benefit them while enduring bodily and financial toxicity. Aiming to guide each patient to the most optimal treatment, precision medicine has been expanding from genetic mutations to other drivers of clinical outcome. There has been a concerted effort to create “avatars” of patient tumors for testing and selecting therapies before administering them into patients.

A recently published Cancer Cell paper, which represents several National Cancer Institute consortia and includes key opinion leaders from both the research and clinical sectors in the United States and Europe, laid out the vision for next-generation, functional precision medicine by recommending measures to enable 3D patient tumor avatars (3D-PTAs) to guide treatment decisions in the clinic. 

According to Xiling Shen, PhD, the corresponding author of this article and the chief scientific officer of the Terasaki Institute for Biomedical Innovation, the power of 3D-PTAs, which include patient-derived organoids, 3D bioprinting, and microscale models, lie in their accurate real-life depiction of a tumor with its microenvironment and their speed and scalability to test and predict the efficacy of prospective therapeutic drugs. 

To fully realize this aim and maximize clinical accuracy, however, many steps are needed to standardize methods and criteria, design clinical trials, and incorporate complete patient data for the best possible outcome in personalized care.

The use of such tools and resources can involve a great variety of materials, methods, and handling of data, however, and to ensure the accuracy and integrity for any clinical decision making, major efforts are needed to aggregate, standardize, and validate the uses of 3D-PTAs. Attempts by the National Cancer Institute’s Patient-Derived Models of Cancer Consortium and other groups have initiated official protocol standardizations, and much work needs to be done.

The authors emphasize that in addition to unifying and standardizing protocols over a widespread number of research facilities, there must be quantification using validated software pipelines, and information must be codified and shared amongst all the research groups involved. They also recommend that more extensive and far-reaching clinical patient profile be compiled, which encompass every facet of a patient’s history, including not only medical, but demographic information as well; these are important factors in patient outcome. 

To achieve standardization in this regard, regulatory infrastructure provided by the National Institutes of Health and other institutes and journals must also be included to allow reliable global data sharing and access.

Clinical trials are also a major part of the 3D-PTA effort, and to date, studies have been conducted to examine clinical trial workflows and turnaround times using 3D-PTA. The authors advise innovative clinical trial designs that can help with selecting patients for specific trials or custom treatments, especially when coupled with the patient’s clinical and demographic information.

Combining these patient omics profiles with information in 3D-PTA functional data libraries can be facilitated by well-defined computational pipelines, and the authors advocate the utilization of relevant consortia, such as NCI Patient-Derived Model of Cancer Program, PDXnet, Tissue Engineering Collaborative, and Cancer Systems Biology Centers as well as European research infrastructure such as INFRAFRONTIER, EuroPDX)

Integrating data from existing 3D-PTA initiatives, consortia, and biobanks with omics profiles can bring precision medicine to a new level, providing enhanced vehicles for making optimum choices among approved therapeutic drugs, as well as investigational, alternative, non-chemotherapeutic drugs. It can also provide solutions for patients experiencing drug resistance and expand opportunities for drug repurposing.

“The integration of the 3D-PTA platform is a game-changing tool for oncological drug development,” says Ali Khademhosseini, PhD, director and CEO for the Terasaki Institute for Biomedical Innovation. “We must combine it in a robust fashion with existing cancer genomics to produce the most powerful paradigm for precision oncology.”