# In situ protein analysis of laser dissected cell ensembles

> **NIH NIH R21** · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · 2020 · $431,750

## Abstract

Project Summary
Many diseases are caused by a large number of combined effects, from genetic predisposition, to lifestyle and
environmental factors; which makes understanding, treating, and curing these multifactorial diseases still a
considerable challenge. Some of the unsolved questions can only be addressed in human tissue specimens.
The availability of clinically annotated human tissue samples from banks and clinical repositories provides a
golden opportunity to unravel cellular pathways that may lead to viable therapies. The investigation of numerous
cell types and subtypes within their native tissue context calls for technologies to enable the analysis of single
cells or small cell subpopulations from tissue.
 Current available technologies do not simultaneously fulfill the requisites of cellular resolution, minimum
sample preparation, minimized sample loss, sample native state preservation, high sensitivity and specificity,
and high throughput. As a result, to date, there is no commercial method extracting and analyzing the minute
amounts of protein from a few cells procured from tissue through laser capture microdissection. We propose to
develop a robust, quantitative, and sensitive assay, designated Laser-Capture Microdissection combined with
Microfluidic Mass Spectrometry (LCM-MIMAS), to overcome the bottlenecks of current technology for quantifying
peptides and proteins in single cells or small cellular ensembles that combines the power of LCM (cell selectivity
and spatial organization), MALDI-TOF mass spectrometry (high mass accuracy, high speed data acquisition),
and immunocapture (for high targeted sensitivity). For proof-of-principle, we will detect the peptide hormones
insulin, glucagon, and somatostatin in cells from archived human pancreatic tissue (Aim 1), and amyloid beta
(Aβ) in cells from archived human brain (Aim 2). We have chosen these two models because both have a high
cellular complexity, are representative of two multifactorial diseases - diabetes and Alzheimer’s disease - for
which there is no cure and where new technologies to assess molecular pathways could lead to novel or
improved therapeutic approaches.
 Successful LCM-MIMAS will allow protein quantification with unprecedented detail on a vast array of biological
systems within small cellular ensembles (1-100 cells) including neurodegenerative diseases, but also cancer,
cardiovascular disease, diabetes, microorganism-host interactions, and many other diseases.

## Key facts

- **NIH application ID:** 9957708
- **Project number:** 1R21AG067488-01
- **Recipient organization:** ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
- **Principal Investigator:** Alexandra Ros
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $431,750
- **Award type:** 1
- **Project period:** 2020-05-01 → 2024-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9957708

## Citation

> US National Institutes of Health, RePORTER application 9957708, In situ protein analysis of laser dissected cell ensembles (1R21AG067488-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9957708. Licensed CC0.

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