Dysregulated miRNAs in a canine model of haemangiosarcoma metastatic to the brain.

Haemangiosarcoma is a highly metastatic and lethal cancer of blood vessel-forming cells that commonly spreads to the brain in both humans and dogs. Dysregulations in phosphatase and tensin (PTEN) homologue have been identified in various types of cancers, including haemangiosarcoma. MicroRNAs (miRNAs) are short noncoding single-stranded RNA molecules that play a crucial role in regulating the gene expression. Some miRNAs can function as oncogenes or tumour suppressors, influencing important processes in cancer, such as angiogenesis. This study aimed to investigate whether miRNAs targeting PTEN were disrupted in canine haemangiosarcoma and its corresponding brain metastases (BM). The expression levels of miRNA-10b, miRNA-19b, miRNA-21, miRNA-141 and miRNA-494 were assessed in samples of primary canine cardiac haemangiosarcomas and their matched BM. Furthermore, the miRNA profile of the tumours was compared to samples of adjacent non-cancerous tissue and healthy control tissues. In primary cardiac haemangiosarcoma, miRNA-10b showed a significant increase in expression, while miRNA-494 and miRNA-141 exhibited downregulation. Moreover, the overexpression of miRNA-10b was retained in metastatic brain lesions. Healthy tissues demonstrated significantly different expression patterns compared to cancerous tissues. In particular, the expression of miRNA-10b was nearly undetectable in both control brain tissue and perimetastatic cerebral tissue. These findings can provide a rationale for the development of miRNA-based therapeutic strategies, aimed at selectively treating haemangiosarcoma.

Co-Density Distribution Maps for Advanced Molecule Colocalization and Co-Distribution Analysis.

Cellular and subcellular spatial colocalization of structures and molecules in biological specimens is an important indicator of their co-compartmentalization and interaction. Presently, colocalization in biomedical images is addressed with visual inspection and quantified by co-occurrence and correlation coefficients. However, such measures alone cannot capture the complexity of the interactions, which does not limit itself to signal intensity. On top of the previously developed density distribution maps (DDMs), here, we present a method for advancing current colocalization analysis by introducing co-density distribution maps (cDDMs), which, uniquely, provide information about molecules absolute and relative position and local abundance. We exemplify the benefits of our method by developing cDDMs-integrated pipelines for the analysis of molecules pairs co-distribution in three different real-case image datasets. First, cDDMs are shown to be indicators of colocalization and degree, able to increase the reliability of correlation coefficients currently used to detect the presence of colocalization. In addition, they provide a simultaneously visual and quantitative support, which opens for new investigation paths and biomedical considerations. Finally, thanks to the coDDMaker software we developed, cDDMs become an enabling tool for the quasi real time monitoring of experiments and a potential improvement for a large number of biomedical studies.