# Investigating Spectral Biomarker Candidates for Migratory Potential in Cancer Cells Using Micro-FTIR and O‑PTIR Spectroscopy

## TL;DR

This paper explores new methods using infrared spectroscopy to identify cancer cell migration traits without traditional staining techniques.

## Contribution

The study introduces O-PTIR spectroscopy as a novel method for label-free cancer cell analysis with improved spatial resolution.

## Key findings

- O-PTIR spectroscopy shows potential for identifying IR tumor markers with better spatial resolution than FTIR.
- Machine learning models were developed to classify cells based on spectral features related to migratory properties.
- The custom-built O-PTIR instrument outperformed commercial FTIR in microfluidic channel measurements.

## Abstract

Routine diagnostic practice for cancer and metastasis
relies on
a time-consuming staining process and the use of antibodies to detect
selected molecular markers and is hence limited by a lack of real-time
data and the availability of molecular information. Against this background,
techniques based on rapid chemical analysis to identify migratory
properties are highly desirable. Fourier-Transform Infrared (FTIR)
microspectroscopy has a long history in the label-free identification
of infrared marker bands for cancer detection. However, it requires
extensive postprocessing of the acquired spectra, is of limited suitability
for analysis in aqueous environments, and has poor spatial resolution.
To overcome these challenges, we are using a new method termed Optical
Photothermal Infrared (O-PTIR) spectroscopy to detect local absorption
to establish potential IR tumor markers and classification models.
We report on experimental outcomes using machine learning and FTIR
microspectroscopy for the classification of cells and the analysis
of spectral features reflecting cancer and migratory properties, comparing
a commercial FTIR microspectrometer to a custom-built O-PTIR instrument
dedicated to spectroscopic measurement and imaging in microfluidic
channels.