# A robust platform for multiplexed, subcellular proteomic imaging in human tissue

> **NIH NIH UH3** · STANFORD UNIVERSITY · 2021 · $547,000

## Abstract

Project Summary
Multiplexed Ion Beam Imaging by Time of Flight (MIBI-TOF) uses secondary ion mass spectrometry and metal
conjugated primary antibodies to simultaneously visualize dozens of proteins at subcellular resolution in a single
tissue section. This technology is back compatible with archival formalin fixed, paraffin embedded tissue (FFPE)
and has been used in peer-reviewed work to simultaneously visualize and quantify 36 proteins in retrospective
human tissue cohorts. In line with the stated goals of the HuBMAP consortium to develop both “High-sensitivity,
high-resolution imaging techniques that can rapidly provide spectral data over large areas of tissue” and
“Quantitative imaging analysis tools, including automated 3D image segmentation, feature extraction, and image
annotation,” the work outlined here will create a standardized, high throughput, and user-friendly workflow for
using MIBI-TOF in basic and translational research to gain insight into how single cell phenotype and tissue
structure are functionally-linked in health and disease. To achieve this, we will validate 100 FFPE antibodies
and optimize ready-to-use multiplexed staining panels in lyophilized format that will permit storage for at least
two years. Protocols and reagents for multiplexed signal amplification of protein and mRNA targets will be further
refined, while next generation instrumentation will increase sample throughput to permit full tissue section
imaging of up to 40 proteins in 1 hour. Standardized reagents and more robust instrumentation will be
accompanied by an automated computational pipeline that utilizes a standard set of segmentation markers and
machine learning to accurately identify nuclei and cell borders in any non-neural human tissue. This data will be
used to cluster single cell events into functionally distinct populations according to morphology, protein
expression, and histological distribution. The reagents and computational pipeline proposed here synergize with
existing HuBMAP-funded platforms and could be readily generalized to virtually any high dimensional imaging
modality. Thus, this work will not only provide a practical, back compatible imaging platform for high throughput
multiplexed imaging, but will also accelerate development of other complimentary imaging technologies as well.

## Key facts

- **NIH application ID:** 10247827
- **Project number:** 5UH3CA246633-03
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Robert michael Angelo
- **Activity code:** UH3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $547,000
- **Award type:** 5
- **Project period:** 2019-09-11 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10247827

## Citation

> US National Institutes of Health, RePORTER application 10247827, A robust platform for multiplexed, subcellular proteomic imaging in human tissue (5UH3CA246633-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10247827. Licensed CC0.

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