3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors
About This Grant
SUMMARY/ABSTRACT Optical microscopy plays an essential role in cancer research by providing detailed information on single cell and organelle phenotypes. The recent development of spatial profiling approaches based on highly multiplexed tissue imaging makes it possible to perform detailed analysis of human and murine cells within a preserved tumor environment. This enables a precise analysis of tumor phenotypes and tumor-immune interaction, mechanism-of-action studies on approved and investigational drugs (as part of clinical trials) and promises to advance diagnostics for precision cancer care. As an NCI Research Specialist (Core-based), Clarence Yapp PhD will continue to support NCI-funded investigators and trainees involved in both classical and emerging microscopy applications and the use of machine learning/AI methods to convert complex images into quantitative single cell data. Yapp has extensive experience in microscopy and image analysis core facilities and currently serves as the Director of Microscopy and Computer Vision for the Laboratory of Systems Pharmacology (LSP) at Harvard Medical School (HMS). The LSP is an interdisciplinary multi-investigator laboratory that hosts about 100 core and affiliated faculty, students, and staff from multiple hospitals and universities in Eastern Massachusetts (seven institutions currently). It also provides instrumentation, software support, and methods development to several dozen other cancer biology groups in Boston and beyond. Yapp works at the interface between wet bench science, data analysis, and visualization, making him an unusually effective resource for a range of basic, translational, and clinical studies. He has served as co-chair of image- focused working groups for multiple NCI programs including the Cancer Systems Biology Consortium (CSBC), the Human Tumor Atlas Network (HTAN), and the Cellular Cancer Biology Imaging Research Program (CCBIR) and developed an international reputation for 3D tissue imaging. Yapp has published on a wide range of topics, often as first or senior author, with a current focus on imaging human tumors using multiplexed super-resolution 3D confocal and light sheet microscopy (LSFM). These 3D methods reveal single cell phenotypes and organelle morphologies not discernable in conventional 2D images and show that many multicellular structures are more extended and interconnected than hitherto thought. As a research specialist Yapp will: First, continue development and documentation of innovative 3D tissue imaging methods by working with trainees, faculty, and other LSP staff; Second, coordinate the development of software tools able to quantify the morphologies of individual cells and multi-cellular structures in 3D and use these to study immune cell states during cancer progression; Third, promote dissemination and uptake of 3D imaging methods by creating educational materials and disseminating these to microscopy core facility directors nationwide. Yapp’s research and training program will thereby provide essential support for Unit Director Prof. Sandro Santagata and two dozen other NCI-supported cancer biologists at HMS and beyond.
Grant Summary
3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors is a NCI - National Cancer Institute grant providing up to $195K for university, nonprofit, healthcare org. Applications are due 2031-07-31 (open). Check eligibility and apply with FindGrants.
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How to Apply
Up to $195K
2031-07-31
- 1Confirm your organization is eligible for 3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors from NCI - National Cancer Institute, checking organization type, location, and any population or project requirements.
- 2Gather the required documents and information, including your organization details, project plan, and budget figures.
- 3Draft your application narrative and budget addressing the funder's priorities and review criteria. FindGrants can draft each section for you to review and edit.
- 4Review every section against the requirements checklist, then export a submission-ready application pack and submit it to NCI - National Cancer Institute before the deadline.
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3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors: Frequently Asked Questions
Who is eligible for the 3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors?
3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors is offered by NCI - National Cancer Institute and is generally open to university, nonprofit, healthcare org. It is open to organizations nationwide unless the funder specifies otherwise. Review the specific eligibility terms before applying, since funders set their own requirements around organization type, location, and the population or project being served.
How much funding does the 3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors provide?
3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors provides up to $195K per award from NCI - National Cancer Institute. Actual award sizes depend on the scope of your project, available program funds, and the number of applicants, so build a budget that reflects realistic, allowable costs rather than the maximum figure.
When is the 3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors deadline?
Applications for 3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors are due 2031-07-31 (open). Because deadlines can change, verify the date with the funder, NCI - National Cancer Institute, and give yourself enough time to prepare a complete, competitive application before the close date.
How do you apply for the 3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors?
To apply for 3D highly-multiplexed imaging and machine learning for immunoprofiling of human and murine tumors, confirm your eligibility, gather the required documents, and prepare a narrative and budget that address the funder's priorities. FindGrants guides you step by step and can draft each section, then exports a submission-ready application pack for this grant from NCI - National Cancer Institute.