# Molecularly Imprinted Polymer Nanoparticles for Lung-Cancer-Cell-Surface Proteomics

## TL;DR

This study uses synthetic nanoparticles to identify proteins on lung cancer cells that could be targets for diagnosis and treatment.

## Contribution

A novel 'snapshot imprinting' method is introduced to identify cell-surface proteins in lung cancer cells.

## Key findings

- Mass spectrometry identified 2381 proteins, with hundreds of differentially expressed proteins in cancer cell lines.
- Five hub proteins (NPM1, TOP2A, EZH2, PRKDC, HNRNPK) were found to be clinically relevant for diagnostics and therapy.
- NanoMIP-based imprinting shows promise as an alternative to traditional methods for identifying protein targets.

## Abstract

The identification and targeting of lung-cancer-cell-surface proteins are important for drug development. Molecularly imprinted polymer nanoparticles (nanoMIPs) offer a synthetic approach for the recognition of proteins on the cell surfaces. This work outlines the use of a novel ‘snapshot imprinting’ approach to characterize differences in the cell-surface proteomes of lung cancer cell lines (A549, H460, H522) and a non-cancerous cell line (BEAS-2B) to potential protein targets for diagnostic and therapeutic applications. The mass spectrometry-based quantitative proteomics identified 2381 proteins. Fold change and p-value thresholds were used to define statistically and biologically significant differentially expressed proteins (DEPs) across cell lines, yielding 353, 426, and 274 DEPs for A549, H460, and H522, respectively, when compared to BEAS-2B. The DEPs identified across overlapping cell line comparisons were analyzed using Gene Ontology enrichment and a protein–protein network to identify hub proteins. Among these hub proteins, five proteins (NPM1, TOP2A, EZH2, PRKDC, and HNRNPK) were identified as clinically relevant when cross-referenced with the Human Protein Atlas database and the literature, highlighting their potential as diagnostic and therapeutic targets. These findings highlight the potential of nanoMIP-based snapshot imprinting as an alternative to ‘classical’ approaches for identifying potential protein targets for diagnostic and therapeutic applications.