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Potential of SERS and proteomics for biomarker detection in cancer cells.

Title: Potential of SERS and proteomics for biomarker detection in cancer cells.
Authors: Lilek D; Biotech Campus Tulln, University of Applied Sciences Wiener Neustadt, Konrad-Lorenz Straße 10, 3430, Tulln, Austria. david.lilek@fhwn.ac.at.; Department of Chemistry and Physics of Materials, Paris Lodron University Salzburg, Jakob-Haringer-Str. 2a, 5020, Salzburg, Austria. david.lilek@fhwn.ac.at.; Mayr A; Biotech Campus Tulln, University of Applied Sciences Wiener Neustadt, Konrad-Lorenz Straße 10, 3430, Tulln, Austria.; Grossinger C; Biotech Campus Tulln, University of Applied Sciences Wiener Neustadt, Konrad-Lorenz Straße 10, 3430, Tulln, Austria.; Rechthaler J; Biotech Campus Tulln, University of Applied Sciences Wiener Neustadt, Konrad-Lorenz Straße 10, 3430, Tulln, Austria.; Steininger L; Biotech Campus Tulln, University of Applied Sciences Wiener Neustadt, Konrad-Lorenz Straße 10, 3430, Tulln, Austria.; Zimmermann D; Biotech Campus Tulln, University of Applied Sciences Wiener Neustadt, Konrad-Lorenz Straße 10, 3430, Tulln, Austria.; Gamsjaeger S; Ludwig Boltzmann Institute of Osteology at the Hanusch Hospital of OEGK and AUVA Trauma Centre Meidling, 1st Medical Department, Hanusch Hospital, Heinrich Collin Str. 30, A-1140, Vienna, Austria.; Wilts BD; Department of Chemistry and Physics of Materials, Paris Lodron University Salzburg, Jakob-Haringer-Str. 2a, 5020, Salzburg, Austria.; Musso M; Department of Chemistry and Physics of Materials, Paris Lodron University Salzburg, Jakob-Haringer-Str. 2a, 5020, Salzburg, Austria.; Wiesner C; Institute Biotechnology, IMC Krems University of Applied Sciences, Krems an der Donau, Austria.; Grünfelder A; Biotech Campus Tulln, University of Applied Sciences Wiener Neustadt, Konrad-Lorenz Straße 10, 3430, Tulln, Austria.; Herbinger B; Biotech Campus Tulln, University of Applied Sciences Wiener Neustadt, Konrad-Lorenz Straße 10, 3430, Tulln, Austria.; Prohaska K; Biotech Campus Tulln, University of Applied Sciences Wiener Neustadt, Konrad-Lorenz Straße 10, 3430, Tulln, Austria. katerina.prohaska@fhwn.ac.at.
Source: Analytical and bioanalytical chemistry [Anal Bioanal Chem] 2026 Mar 27. Date of Electronic Publication: 2026 Mar 27.
Publication Model: Ahead of Print
Publication Type: Journal Article
Language: English
Journal Info: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 101134327 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1618-2650 (Electronic) Linking ISSN: 16182642 NLM ISO Abbreviation: Anal Bioanal Chem Subsets: MEDLINE
Imprint Name(s): Original Publication: Heidelberg : Springer-Verlag, 2002-
Abstract: This study investigates the use of quantitative LC-MS/MS-based proteomics and surface-enhanced Raman spectroscopy (SERS) for biomarker detection in classical Hodgkin lymphoma (HL). Two HL cell models with distinct TP53 status were utilized to evaluate the effects of etoposide, a DNA-damaging chemotherapeutic agent, and resveratrol, a polyphenolic compound with known chemosensitizing activity. For SERS, the best performance was achieved by applying logistic regression to classify different treatment conditions and identify discriminative spectral features in the data. Proteomics showed highly reproducible and accurate results with relative standard deviations of below 5% for the sample preparation and about 2% for the measurements. Proteomic profiling revealed a TP53-dependent organization of metabolic and stress-response pathways and demonstrated that cryopreserved aliquots yielded the most consistent proteomic signatures. Treatment-dependent regulation of key biomarker proteins showed direct correspondence to specific SERS features, such as reduced nucleotide/cytochrome-associated signals and enhanced amide and aromatic amino acid signals. Our findings highlight the strength of applying reproducible proteomic profiling with machine learning-guided SERS analysis to improve molecular interpretation and to validate potential biomarkers in cancer research. Future work will focus on refining the analytical workflow and extending it toward integrative multi-omics applications, enabling more comprehensive biomarker detection and mechanistic insight into classical Hodgkin lymphoma. This strategy will be extended to additional model systems-such as metastatic melanoma, melanocytes, and ultimately patient-derived leukemia cells-to help bridge the gap toward clinical translation.; (© 2026. The Author(s).)
Competing Interests: Declarations. Conflict of interest: The authors declare no competing interests.
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Grant Information: GLF21-1-019 Gesellschaft für Forschungsförderung Niederösterreich
Contributed Indexing: Keywords: Biomarker detection; Hodgkin lymphoma; Machine learning; Multi-omics; Proteomics; SERS (surface-enhanced Raman spectroscopy)
Entry Date(s): Date Created: 20260328 Latest Revision: 20260328
Update Code: 20260328
DOI: 10.1007/s00216-026-06459-5
PMID: 41896432
Database: MEDLINE

Journal Article

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