Develop New Enabling Cancer Technologies
NCI has announced several funding opportunities that align with the Cancer Moonshot.See Funding Opportunities
This recommendation supports the development, adaption, and validation of emerging technologies that have the potential to transform cancer research and/or clinical care.
Projects aligning with the recommendation will focus on enhancing experimental and analytical capabilities addressing the 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.
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. Investigators in this program are also performing technology validation to ensure that new approaches could be readily adopted by the cancer research community.
These projects are being funded to overcome persistent challenges in cancer research and have the potential to lead to new capabilities in cancer research areas.
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 in 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, as well as issues validating and replicating the results. Also, isolated collections of PDX models are often too small to reflect the diversity of patient tumors found in large-scale clinical trials.
PDXNet is addressing research challenges related to PDX models. PDX Development and Trial Centers (PDTCs) are developing PDX models on a large scale, advancing standardization procedures for these experimental systems and designing 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.
Minority (M)-PDTCs 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.
Interactions and collaborations across PDXNet, as well as data sharing with the broader community, are supported by the PDXNet Data Commons and Coordinating Center (PDCCC).
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 PDXNet. This repository is developing PDX models from tissue samples across the country, stored in a PDX bank that can be shared with investigators in the PDTCs and the cancer research community.
More information about the network can be found at the PDXNet website.
Activities to Promote Technology Research Collaborations (APTRC) for Cancer Research
There are two unique NCI programs related to APTRC 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.
Novel Technologies to Facilitate Research Using Next Generation Patient-Derived Cancer Models
Research projects in this program are developing technology tools to accelerate and enhance studies across the spectrum of cancer research using advanced human-derived next-generation cancer models, including 3D organoids and conditionally reprogrammed cells. These projects are specifically advancing cancer models developed as part of the Human Cancer Models Initiative (HCMI). The technology tools being examined by investigators of the program include new laboratory methods and reagents for screening studies and computational approaches for data analysis from experiments using next-generation cancer models. The goal of these research projects is to enhance the adoption, sharing, and use of next generation cancer models to advance cancer research progress.
Small Business Innovation Research (SBIR) and Small Business Technology Transfer Research (STTR) Grants and Contracts for Enabling Technologies
NCI supports grants and contracts with small businesses developing new enabling technologies for cancer research. The range of projects supported through these investments span the breadth of Cancer Moonshot, with some of the currently active projects focusing on the development of experimental models to study cancer disparities and the design of new cancer detection technologies, for example.
Evaluation of Prostate Specific Membrane Antigen (PMSA)-Based PET Imaging of High-Risk Prostate Cancer
At this time, there are 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 positron emission tomography (PET) imaging on patients with high-risk prostate cancer. PET offers the opportunity to develop an approach to image Prostate Specific Membrane Antigen (PSMA), 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.
NCI Program for Natural Products Discovery (NPNPD)
NPNPD is advancing natural product research and the discovery of new molecules in nature that impact biological processes of cancer. The NCI Natural Products Repository of the NPNPD has over 230,000 extracts of plants, microbes, algae, and marine species, which are being used for the generation of more than a million research-ready, partially purified natural product samples. The NPNPD collection of natural product extracts and partially purified samples is being sent to research centers performing drug screens around the world. Once researchers identify an extract with potential anticancer activity, the NPNPD uses automated techniques to quickly identify and isolate the active compound for more detailed studies.
Cancer Technology Projects Awarded Cancer Moonshot Funding
|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|