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Active NON-SBIR/STTR RPGS NIH (US)

IMAT-ITCR Collaboration: Multiplexed Spatial Data calibration and analysis using micro-capsules

$847.5K USD

Funder NATIONAL CANCER INSTITUTE
Recipient Organization Harvard Medical School
Country United States
Start Date Sep 12, 2023
End Date Aug 31, 2026
Duration 1,084 days
Number of Grantees 2
Roles Principal Investigator; Co-Investigator
Data Source NIH (US)
Grant ID 11136707
Grant Description

PROJECT SUMMARY Highly multiplexed imaging methods such as CycIF, CODEX, mxIF, MIBI, and IMC are providing remarkable insight into tumor micro-environments, but they suffer from substantial variability between runs and substantial differences from one technology to the next. The reasons for changes in staining

intensity with cycle number are not fully known, but it appears that it is absolute intensity rather than morphology that is variable. Variability in staining intensity severely limits the ability to create large multi-specimen datasets within a single lab (due to batch effects) and it precludes comparison across

laboratories and institutions. A central goal of this proposal is to leverage micro-capsule technology to develop reliable calibration standards and software algorithms that use these standards for data normalization. A set of standards would allow systematic comparison between experimental methods,

which has been a persistent problem in the field. Quality control and calibration are also essential elements in the implementation of CLIA-compatible workflows for clinical use. Thus, we propose that developing calibration standards is urgently needed to accelerate development of both antibody and nucleic-acid based spatial profiling methods for studying tumors.

To achieve this goal, this administrative supplement will build a new collaboration between the labs of Drs. Klein, Pfister and Santagata who are supported by an R33 IMAT grant (Klein) and a U01 ITCR grant (Pfister and Santagata). The proposal brings together two efforts: micro-capsule technology, and spatial multi-omic computational image analysis. The project proposes to use micro-capsule

technology to develop these much-needed imaging calibration standards. The goal is realized through two aims. In the first aim, we adapt computational image analysis tools from Pfister and Santagata labs to register, detect, segment, and normalize data from sequential imaging of capsules. This aim is stand-alone, as it directly advances the original goals of Klein’s IMAT

grant. In the second aim, we generate imaging calibration standards using cell lysates in micro- particles, then evaluate them as standards for multiplexed imaging, and building on Aim 1 we establish computational tools for building calibration into imaging tasks.

All Grantees

Harvard Medical School

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