Hoja-Lukowicz, D. | Search bioRxiv

bioRxiv2025

Type 1 LacNAc and LacdiNAc on N-glycans as molecular biomarkers of human melanoma cells

Melanoma, the most dangerous form of skin cancer, is characterized by its high potential to spread or metastasize. Tumor progression is associated with changes in glycosylation that occur early in carcinogenesis and evolve as the cancer develops and spreads. To identify new melanoma transformation markers, we analyzed N-glycans from melanocytes and melanoma cell lines at different progression stages. We performed analyses using matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry (MS) and hydrophilic interaction liquid chromatography (HILIC)-high performance liquid chromatography (HPLC) techniques on N-glycans without and after digestion with exoglycosidase arrays. Our results showed that, unlike melanocytes, melanoma cells express higher levels of type 1 LacNAc units and triantennary complex type glycans instead of high-mannose type glycans. Our results revealed that the N-glycomes of all analyzed cell lines possess Lewis X/A epitopes and, for the first time, demonstrate the presence of Gal{beta}1-4Gal{beta}1-4GlcNAc and Gal{beta}1-3Gal{beta}1-3GlcNAc units. The characteristic feature of melanoma cells is the presence of LacdiNAc structures. Our study provides the first comprehensive characterization of the N-glycome of melanocytes and suggests novel glyco-biomarkers of melanoma progression.

cancer biology↗

bioRxiv2021

Suitable reference genes selection for reliable normalization of gene expression in melanoma: implementation of an innovative GenExpA software

The algorithms commonly used to select the best stable reference gene in RT-qPCR data analysis have their limitations. We showed that simple selection of the reference gene or pair of genes with the lowest stability value from the pool of potential reference genes - a commonly used approach - is not sufficient to accurately and reliably normalize the target gene transcript and can lead to biologically incorrect conclusions. For reliable assessment of changes in a target gene expression level, we propose our innovative GenExpA software, which works in a manner independent of the experimental model and the normalizer used. GenExpA software selects the best reference by combining the NormFinder algorithm with progressive removal of the least stable gene from the candidate genes in a given experimental model and in the set of daughter models assigned to it. The reliability of references is validated based on the consistency of the statistical analyses of normalized target gene expression levels through all models, described by the coherence score (CS). The use of the CS value imparts a new quality to qPCR analysis because it clarifies how low the stability value of reference must be in order for biologically correct conclusions to be drawn. We tested our method on qPCR data for the B4GALT genes family in melanoma, which is characterized by a high mutation rate, and in melanocytes. GenExpA is available at https://github.com/DorotaHojaLukowicz/GenExpA or https://www.sciencemarket.pl/baza-programow-open-source#oferty. HighlightsGenExpA - next-generation software for normalizer selection and validation The GenExpA tool defines how low the stability value of the reference should be The GenExpA tool determines the level of gene expression analysis robustness The GenExpA tool increases the speed of analysis and reduces cost

cancer biology↗