Labena (Slovenia)

Melanoma-associated antigens (MAGEs) are cancer-testis antigens (CTAs) aberrantly expressed in multiple cancer types, including hepatocellular carcinoma (HCC), and associated with aggressive phenotypes. Although MAGE proteins are widely studied as cancer immunotherapy targets, their roles in HCC and the regulation of their expression during liver pathogenesis in mouse models, including dietary effects, remain poorly understood. We analyzed Mage gene expression in liver tissues from 78 C3H/HeJ mice with chronic diet-induced obesity. While type I MAGE genes are frequently expressed in human HCC, we found no evidence of their expression in mouse liver tumors, suggesting species-specific regulation. In contrast, type II Maged2, previously reported to be upregulated in human HCC, was significantly increased in mouse liver tumors. Analysis of human HCC samples from The Cancer Genome Atlas (TCGA) database confirmed MAGED2 upregulation and its association with patient prognosis. Together, these findings identify MAGED2 as a conserved marker of liver cancer in both humans and mice and emphasize the importance of cross-species comparative approaches for selecting appropriate models and accurately interpreting results, particularly for CTAs, which often evolved recently and in a species-specific manner.

Traditional transcriptomic studies often overlook the complex heterogeneity of skeletal muscle, as they typically isolate RNA from mixed muscle fibre and cell populations, resulting in an averaged transcriptomic profile that obscures fibre type-specific differences. This study assessed the potential of the recently developed Xenium platform for high-resolution spatial transcriptomic analysis of human skeletal muscle histological sections. Human vastus lateralis muscle samples from two individuals were analysed using the Xenium platform and Human Multi-Tissue and Cancer Panel targeting 377 genes complemented by staining of successive sections for Myosin Heavy Chain isoforms to differentiate between type 1 and type 2 muscle fibres. Manual segmentation of muscle fibres allowed accurate comparisons of transcript densities across fibre types and subcellular regions, overcoming limitations in the platform's automated segmentation. The analysis revealed higher transcript density in type 1 fibres, particularly in nuclear and perinuclear areas, and identified 191 out of 377 genes with differential expression between muscle fibres and perimysium. Genes such as PROX1, S100A1, LGR5, ACTA2, and LPL exhibited higher expression in type 1 fibres, whereas PEBP4, CAVIN1, GATM, and PVALB in type 2 fibres. We demonstrated that the Xenium platform is capable of high-resolution spatial in situ transcriptomic analysis of skeletal muscle histological sections. This study demonstrates that, with manual segmentation, the Xenium platform effectively performs fibre type-specific transcriptomic analysis, providing new insights into skeletal muscle biology.