20.500.12556/DiRROS-31705 Decreased gene expression of antiangiogenic factors in endometrial cancer qPCR analysis and machine learning modelling Endometrial cancer (EC) is an increasing health concern, with its growth driven by an angiogenic switch that occurs early in cancer development. Our study used publicly available datasets to examine the expression of angiogenesis-related genes and proteins in EC tissues, and compared them with adjacent control tissues. We identified nine genes with significant differential expression and selected six additional antiangiogenic genes from prior research for validation on EC tissue in a cohort of 36 EC patients. Using machine learning, we built a prognostic model for EC, combining our data with The Cancer Genome Atlas (TCGA). Our results revealed a significant up-regulation of IL8 and LEP and down-regulation of eleven other genes in EC tissues. These genes showed differential expression in the early stages and lower grades of EC, and in patients without deep myometrial or lymphovascular invasion. Gene co-expressions were stronger in EC tissues, particularly those with lymphovascular invasion. We also found more extensive angiogenesis-related gene involvement in postmenopausal women. In conclusion, our findings suggest that angiogenesis in EC is predominantly driven by decreased antiangiogenic factor expression, particularly in EC with less favourable prognostic features. Our machine learning model effectively stratified EC based on gene expression, distinguishing between low and high-grade cases. endometrial cancer angiogenic factor tumour-adjacent tissue machine learning TCGA LEP rak endometrija angiogeni faktor tkivo ob tumorju strojno učenje TCGA LEP true false true Angleški jezik Slovenski jezik Neznano 2026-08-06 10:27:30 2026-08-06 10:27:30 2026-08-07 03:58:32 0000-00-00 00:00:00 2023 0 0 Nasl. z nasl. zaslona; Opis vira z dne 24. 7. 2023; str. 1-25 iss. 14, [article no.] 3661 Vol. 15 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 616-006 2072-6694 10.3390/cancers15143661 159457795 RAZ_Roskar_Luka_2023.pdf RAZ_Roskar_Luka_2023.pdf 1 5C3BE213D66798F8B2C7C71FBFF85775 5f1ec8be93e2acd5273064bd643c3ad9d4f1291fdc8fb8db2b1a934ecd0dafd2 c7e578af-9170-11f1-af5a-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=49212 https://www.mdpi.com/2072-6694/15/14/3661 1 abb1fa46-9170-11f1-af5a-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=49211 Univerzitetni klinični center Ljubljana 0 0 0