Fast-Track proposals will be accepted.
Direct-to-Phase II proposals will NOT be accepted
Number of anticipated awards: 3-5
Budget (total costs, per award):
Phase I: up to $400,000 for up to 9 months
Phase II: up to $2,000,000 for up to 2 years
PROPOSALS THAT EXCEED THE BUDGET OR PROJECT DURATION LISTED ABOVE MAY NOT BE FUNDED.
Public large-scale molecular-level datasets have facilitated sophisticated secondary data analysis leading to new biological discovery. These data sources provide rich, multi-omic molecular level data on bulk or single-cell populations, but most measurements do not preserve the spatial relationships between tumor cells and thus limit the ability to discover important and targetable cell-cell and cell-microenvironment interactions. To address this shortcoming, several programs supported by NIH, NCI and beyond have undertaken the construction of spatiotemporal single cell resolution atlases of normal and diseased tissues.
Examples of technologies currently employed to build spatial atlases include multiplex microscopy and mass cytometry-based imaging modalities that provide information on multiple (10s-1000s) of biological molecules (genes, proteins, metabolites, etc.) in a single two-dimensional thin tissue section. While imaging of sequential tissue sections provides a way to re-construct the three-dimensional (3D) tumor microenvironment, most high content imaging modalities require multiple rounds of tissue staining and manipulation that can be destructive to any one tissue section making it difficult to reconstruct accurate 3D views. Therefore, technologies that provide imaging workflows that deliver cellular to sub-cellular resolution -omics level data in three dimensions (i.e. in thick tissue resections or whole biopsy samples) are likely to more faithfully conserve the architectural or structural components within the tumor microenvironment that could be destroyed or altered during multiple rounds of tissue processing. It is possible that approaches such as light sheet microscopy could fill this need, but the current protocols for tissue clearing, multiple rounds of target labeling to facilitate highly multiplexed omics measurement, and subsequent image processing make the overall workflow for an individual tissue prohibitively slow (days to weeks) and difficult to employ in atlas building activities where a large number of normal and tumor maps is required for a representative normal tissue or tumor atlas.
The goal is to advance the development and dissemination of imaging workflows capable of omics-level measurements in thick tissue resections or whole biopsy cores that can scale for use in atlas building initiatives. Proposals should enable interrogation in a manner that combines high resolution (preferably single-cell) -omics level data (i.e. genomics, transcriptomic, proteomic, metabolomic, etc.) with information about 3D native tumor architecture (i.e. extracellular matrix, vasculature, higher order structure, etc.).
Proposals that are within scope of this solicitation may combine existing, new, or improved assay components into an improved imaging workflow. Examples of existing, new, or improved components include imaging technologies or modalities, tissue clearing methodologies, imaging probes and/or detection reagents, cyclic staining or targeting procedures, and/or unique combinations of imaging and multi-omic measurement platforms. A minimal workflow will provide a 3D view of multiplexed omics data without the need for reconstruction from 2D tissue slices. The ability to concurrently acquire additional information regarding native tumor architecture would be considered a strength (e.g. second harmonic imaging or alternative technology). Offerors should benchmark their proposed workflow against current state-of-the-art imaging workflows and demonstrate a decrease in overall assay time while maintaining a similar or increased capacity for omic-scale analysis.
It is anticipated that proposals may include the development of new algorithms, visualization tools, and analysis software to facilitate data handling, analysis and visualization of results. However, applications that are solely software-based will be considered not responsive.
• Establish a project team with proven expertise in development of high-resolution cellular imaging systems and multi-modal data analysis, including subject matter experts in the tumor(s) being imaged and the -omics measurements being proposed.
• Define relevant use cases for the technology including, but not limited to, what tissues can be analyzed, what imaging resolution can be expected, what -omic measurement(s) will be completed, desired throughput of the system, and identification of benchmark technologies.
• Prepare a report that specifies quantitative technical and commercially relevant milestones that can be used to evaluate the success of the technology versus current state-of-the-art 3D high resolution imaging platforms. Quantitative milestones may be relevant metrics (i.e. compared to benchmarks, alternative assays) or absolute metrics (i.e. minimum number of proteins or genes detected, metrics related to repeatability of the assay). Metrics regarding total assay time (including tissue preparation, cyclic staining (if relevant), and imaging processing/analysis) are expected.
• Generate proof-of-concept dataset that addresses the use case above using resection tissue or biopsy cores from solid human cancers or from a generally accepted mammalian cancer model (i.e. PDX, xenograft, GEMM) that demonstrates the ability to capture and visualize molecular -omics measurements in 3D.
• Prepare a report summarizing the performance of the system against the quantitative technical milestones indicated above. Include any plans to modify the platform based upon performance against stated milestones.
• Develop and provide preliminary Standard Operating Procedures for system use, including a validated list of reagents addressing the use case identified above.
• Present phase I findings and demonstrate the functional prototype system to an NCI evaluation panel via webinar.
• Generate proof-of-concept dataset that demonstrates the ability to quantify the 3D native tumor architecture (i.e. extracellular matrix, vasculature, higher order structure, etc) in addition to the capabilities optimized in Phase I.
• Generate datasets representative of at least three solid tumor types (thick resections or whole biopsies).
• Provide a report that documents the reliability, robustness and usability of the system for the purpose of generating large scale molecular and cellular atlas building.
• Provide a report to benchmark system performance (including total assay time) and functionality against the commercially relevant quantitative milestones proposed in Phase I. Report should demonstrate feasibility for scale up at a price point that is compatible with market success.
• Provide Standard Operating Procedures for system use, including a validated list of reagents for each of the three demonstration tumor types. Include documentation for troubleshooting new tumor or tissue types to demonstrate the system can be utilized beyond the tumor types proposed.
• Provide a roadmap for development of a turnkey system.
Receipt date: October 26, 2020, 5:00 p.m. Eastern Daylight Time
Apply for this topic on the Contract Proposal Submission (eCPS) website.
For full PHS2021-1 Contract Solicitation, CLICK HERE.