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Updated: Dec 30, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Proteomic Determination of Metabolic Protein Expression in Ten Different Tumor Cell Lines
Mariella Gruber-Olipitz1, Leila Afjehi-Sadat1, Maureen Felizardo1
1Department of Pediatrics, Division of Basic Sciences, Medical University of Vienna, Vienna, Austria.
Abstract:
Alterations in different metabolic pathways are a prerequisite to facilitate malignant features such as invasiveness, metastasis, progression and resistance mechanisms to therapy in tumor cells. To generate metabolic protein expression patterns of tumor cells, and in order to provide an analytical tool for establishing metabolic maps, "metabolomes", we applied two-dimensional electrophoresis (2-DE) followed by mass spectrometry (MALDI-TOF-TOF with LIFT technology) in ten individual tumor cell lines (Saos-2; SK-N-SH; HCT-116; Caov3; A-549; HL60; A-673; A-375; MCF-7; Hela) widely used in tumor research. A series of 124 metabolic proteins, represented by 432 spots, was unambiguously identified by this proteomic approach. The proteins detected comprise a multitude of pathways including intermediary, energy, lipid, nucleic acid, amino acid, carbohydrate, redox, phosphate, iron and folate metabolism. Fifty-six enzymes were present in a single tumor cell line exclusively, whereas only enolase-1, a key component of the glycolytic cascade, was found in all cell lines investigated, thereby underscoring the heterogeneous protein expression profile in different cancer types. Construction of individual protein maps provides an analytical tool and reference base for studying the "metabolome" of tumor cells, forming the basis for designing studies in tumor metabolism, and reveals proteins that can be used as pharmaceutical targets in experimental therapies.
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