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

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 <i>p</i>-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.

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Publication Details

Journal
Polymers
Published
2026-01-20
DOI
https://doi.org/10.3390/polym18020281
Primary Topic
Analytical chemistry methods development
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Kirabo Magumba, Salvador Macip, Sergey Piletsky, Thong Huy Cao et al.
Polymers
Analytical chemistry methods development
article

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

Kirabo Magumba, Salvador Macip, Sergey Piletsky, Thong Huy Cao, Elena Piletska, Donald Jones
article en

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 <i>p</i>-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.

PolymersVol. 18(2)
Universitat Oberta de Catalunya (ES), University of Leicester (GB), Leicester College (GB), Glenfield Hospital (GB), University Hospitals of Leicester NHS Trust (GB), Pasqual Maragall Foundation (ES)
National Institute for Health and Care Research, University of Leicester, NIHR Leicester Biomedical Research Centre
Good health and well-being
Openalex Percentile: Top 83%
Analytical chemistry methods development
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