# Spectroscopy Assisted Laser Microdissection

> **NIH NIH R21** · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · 2023 · $159,706

## Abstract

Abstract
Molecular understanding of tumors relies greatly on appropriate samples to be prepared from epithelial cells in
tissues. Epithelial cells, however, are often surrounded by other cell types and extracting pure populations of
these cells is crucial for correct biospecimen preparation and resulting accuracy of molecular assays. Laser
microdissection (LM) has contributed immensely in this effort due to its high spatial specificity in the extraction
of defined cell populations and ease of use. While LM has enhanced the precision of biochemical analysis,
several drawbacks remain. The necessity of staining and human supervision limits throughput, molecular yield
and purity of samples. There is little explicit control or confidence in the purity of extracted cell populations
while it is difficult to extract multiple cells from the same sample. Combining the morphologic specificity of
microscopy and molecular sensitivity of spectroscopy, infrared (IR) spectroscopic imaging been employed to
automate histopathologic recognition in complex tissues using artificial intelligence algorithms applied of
spectral data. This project will demonstrate a completely automated instrument by coupling LM with IR
microscopy. Termed spectroscopy-assisted laser microdissection (SLaM), the developed prototype will be
validated using state of the art IR imaging systems and commercial LCM in terms of accuracy, speed and type
fidelity. Last, the approach will be applied to extract cells of different types from the same prostate sample to
demonstrate the capability to multiplex LM (muxLM) from the same tissue. The project directly addresses the
need to reduce the time- and labor-intensive nature of LM. SLaM can maximize the quality and utility of
biological samples used for downstream analyses by automation, high throughput and precision while enabling
a comprehensive acquisition of cells without user fatigue or error, thereby providing a sample of higher integrity
and quality for cancer molecular analysis.

## Key facts

- **NIH application ID:** 10689945
- **Project number:** 5R21CA263147-03
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
- **Principal Investigator:** Rohit Bhargava
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $159,706
- **Award type:** 5
- **Project period:** 2021-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10689945

## Citation

> US National Institutes of Health, RePORTER application 10689945, Spectroscopy Assisted Laser Microdissection (5R21CA263147-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10689945. Licensed CC0.

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