Develop New Cancer Technologies

NCI has announced several funding opportunities that align with the Cancer Moonshot.

See Funding Opportunities

While experimental models have greatly improved the understanding of basic cancer biology, there has historically been a lack of technologies available sophisticated enough to account for the heterogeneity and complexity of tumors. This has limited the ability to accurately predict the success of various anticancer agents in patients and hindered the high-throughput development of new cancer treatments.

This recommendation supports the development, testing, and validation of emerging technologies that have the potential to transform cancer research and/or clinical care. New enabling technologies that represent the heterogeneity of tumor biology and integrate with computational platforms are critically important to help scientists discover new research directions and predict therapeutic responses.

Projects aligning with the recommendation will focus on enhancing experimental and analytical capabilities addressing complexities of cancer, designing new capabilities for advancing clinical diagnostic measurements in cancer patients, developing new technologies to improve biospecimen and data quality, and improving predictive modeling approaches.

Ultimately, the goal is to use these new enabling technologies to improve cancer research across the continuum of care.

NCI has awarded funding for several projects that align with this recommendation to develop new enabling technologies.

Patient-Derived Xenografts Development Network (PDXNet)

Patient-derived xenografts (PDX) models describe an experimental method where tissue from a cancer patient’s tumor is implanted into a mouse. These models are emerging as an important approach for translational cancer research. For example, scientists can perform PDX trials where they test drug treatments in mice to understand a tumor’s response to therapy and potential biomarkers of an effective treatment. These PDX trials can help researchers determine the most promising cancer drugs or drug combinations to test in specific populations of cancer patients.

However, PDX models are often developed in isolated programs, leading to a lack of standardization in these systems and issues of validating and replicating results. Also, isolated collections of PDX models are often too small to reflect the diversity of patient tumors found in large-scale clinical trials.

This led to NCI’s creation of a collaborative network of Patient-Derived Xenografts Centers (PDTCs) for the large-scale development of PDX models, advancement of standardization procedures for these experimental systems, and design of model validation methods to advance the translation of PDX findings to clinical cancer treatments. The PDTCs are determining the best PDX trial approaches for the experimental testing of cancer drugs in molecularly defined tumors.

The M-PDTCs of PDXNet are developing racially and ethnically diverse PDX models that can be used to test cancer treatments. These centers aim to advance the understanding of disparities observed in the outcomes of cancer treatments among racially and ethnically diverse populations.

NCI also supports interdisciplinary collaborative projects between PDXNet and researchers outside the network to accelerate drug testing in PDX model collections.

Along with investigators developing PDX models, the Patient-Derived Models Repository at the Frederick National Laboratory for Cancer Research plays an important role in the PDTCs. This repository is developing PDX models from tissue samples across the country. It’s creating a PDX bank that can be shared with investigators in the PDTCs and the cancer research community.

Activities to Promote Technology Research Collaborations (APTRC) for Cancer Research

There are two different NCI programs that focus on supporting technology development for advancing cancer research. The Innovative Molecular Analysis Technologies (IMAT) program supports innovative, data-generating platforms and methods while the Informatics Technologies for Cancer Research (ITCR) program supports data processing and visualization technologies.

NCI is accelerating the development of new enabling cancer technologies by leveraging expertise in IMAT and ITCR through multidisciplinary collaborations between investigators in these programs. These collaborative projects bring together complementary technology platforms and approaches to enhance their capabilities for studies of cancer.

Integration and Validation of Emerging Technologies to Accelerate Cancer Research

These exploratory and developmental projects are advancing the development and validation of new enabling technologies and tools for basic and clinical cancer research. The focus of these projects includes: enhancing experimental and analytical capabilities to understand the complexities of cancer, developing new technologies to advance cancer diagnosis, designing predictive models of cancer progression and responses to treatment, and generating new approaches to improve cancer-related data quality. The projects also include technology validation to ensure that new approaches could be readily adopted by the cancer research community.

These projects are working to overcome persistent challenges in cancer research and have the potential to lead to new capabilities in cancer research areas.

Small Business Innovation Research (SBIR) and Small Business Technology Transfer Research (STTR) Contracts for Enabling Technologies

NCI supports contracts with small businesses performing research and development for new enabling technologies in cancer research. Some of the current projects are focusing on the development experimental models to study cancer disparities and researching new cancer detection technologies.

Evaluation of Prostate Specific Membrane Antigen (PMSA)-Based PET Imaging of High Risk Prostate Cancer

There are very limited ways to stratify high risk prostate cancer patients. To address this issue, researchers with NCI’s Center for Cancer Research are investigating the clinical use of PET imaging on patients with high risk prostate cancer. They are focusing on using PET to image Prostate Specific Membrane Antigen (PSMA), which is a protein that is expressed in prostate cancer tissue and associated with cancer aggressiveness. By comparing the PSMA PET scans with complication-free survival outcomes, the researchers hope to understand if PSMA imaging could be used to identify subsets of prostate cancer patients and guide treatment decisions.

Cancer Technology Projects Awarded Cancer Moonshot Funding

Awarded Projects
Funding Opportunity Project Title Institution Principal Investigator(s)
PDX Data Commons and Coordinating Center (PDCCC) for the PDX Development and Trial Centers Research Network (PDXNet) (U24) Data Coordination Center for PDXNet Jackson Laboratory Chuang, Jeffrey Hsu-Min; Davis-Dusenbery, Brandi Nicole
PDX Development and Trial Centers (PDTCS) (U54) Washington University PDX Development and Trial Center Washington University Govindan, Ramaswamy; Ding, Li; Li, Shunqiang
Rational Approaches to Melanoma Therapy Wistar Institute Herlyn, Meenhard F; Davies, Michael
University of Texas PDX Development and Trial Center University of Texas MD Anderson Cancer Center Roth, Jack; Meric-Bernstam, Funda
PDX Trial Center for Breast Cancer Therapy University of Utah Welm, Alana L; Lewis, Michael T; Welm, Bryan E
Minority-Patient Derived Xenograft (PDX) Development and Trial Center (PDTC) Network (U54) Minority PDX Development and Trial Center: Baylor College of Medicine and MD Anderson Cancer Center Collaboration on Mechanistic Studies to Dissect and Combat Health Disparities in Cancer Baylor College of Medicine Mitsiades, Nicholas
University of California Minority Patient-Derived Xenograft (PDX) Development and Trial Center (UCaMP) to Reduce Cancer Health Disparities University of California at Davis Pan, Chong-Xian; Carvajal Carmona, Luis Guillermo; Chen, Moon Shao-Chuang
Integration and Validation of Emerging Technologies to Accelerate Cancer Research (R33) Advanced Cancer Classification via Single-Cell Electrophoretic Cytopathology University of California Berkeley Herr, Amy Elizabeth
Development of Genetically Tractable, Driver Gene-syngeneic Brain Tumor Models for Pre-clinical Adoptive TCR-T Therapy Duke University Li, Qijing; Yan, Hai
High Precision Single Cell Genomes: Linear Amplification and Digital Haplotypes Harvard University Xie, Xiaoliang Sunney
In-Depth Proteome Mapping of the Tumor Microenvironment with Single-Cell Resolution Battelle Pacific Northwest Laboratories Kelly, Ryan T
Multi-Tracer Volumetric PET (MTV-PET) to Measure Tumor Glutamine and Glucose Metabolic Rates in a Single Imaging Session University of Pennsylvania Mankoff, David; Karp, Joel
Minimally Intrusive Colorectal Cancer Risk Stratification with Nanocytology: Targeting Underscreened Populations Boston Medical Center Roy, Hemant; Backman, Vadim
Precise DCE-MRI Assessment of Brain Tumors University of Southern California Nayak, Krishna S
Functional Microscale Organotypic Assays to Predict Patient Response to Anti-angiogenesis Therapies University of Wisconsin-Madison

Beebe, David J; Abel, E Jason; Cho, Steve Yoon-Ho; Huang, Wei; Kim, Kyungmann; Kyriakopoulos, Christos

Genome-wide Identification and Targeting of Resistance to Cancer Therapy University of Maryland, College Park

Ruppin, Eytan; Gutkind, J Silvio

Molecular Beacon Based Extracellular mRNA and Protein Detection for Early Cancer Diagnosis Ohio State University Lee, Ly James; Fleisher, Martin
  • Posted: October 22, 2018

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