Assessment of the angiogenic potential of xenografted tumors by biomedical imaging techniques.
Tumor angiogenesis promotes tumor growth, metastasis and disease progression.
APA
Druzhkova I, Orlova A, et al. (2026). Assessment of the angiogenic potential of xenografted tumors by biomedical imaging techniques.. Biomedical optics express, 17(3), 1189-1204. https://doi.org/10.1364/BOE.577775
MLA
Druzhkova I, et al.. "Assessment of the angiogenic potential of xenografted tumors by biomedical imaging techniques.." Biomedical optics express, vol. 17, no. 3, 2026, pp. 1189-1204.
PMID
41970573
Abstract
Tumor angiogenesis promotes tumor growth, metastasis and disease progression. Different cancer types vary in their angiogenic potential, which may influence prognosis and response to therapy. In the present work, we established xenograft models of three of the most aggressive types of human cancers: glioblastoma U87MG, gastric cancer MKN-45, and pancreatic cancer MIA PaCa-2, in immunodeficient mice. The study of vascular network by optoacoustic microangiography revealed the highest degree of vascularization in U87MG xenografts, and the lowest in MIA PaCa-2 xenografts. As shown by PAS-CD31 dual staining, U87MG-derived tumors also showed the highest expression of the endothelial marker CD31 as well as the highest vasculogenic mimicry capacity. In line with this, metabolic imaging by fluorescence Lifetime Imaging Microscopy (FLIM) of nicotinamide adenine dinucleotide (NADH) revealed that MIA PaCa-2 xenografts were the most glycolytic, whereas U87MG had higher levels of oxidative phosphorylation, and MKN-45 showed intermediate values. Therefore, when creating animal models with xenografted tumors, it is important to understand the angiogenic potential of cancer cells, especially for studying drug candidates with an antiangiogenic effect. Also, the combination of optoacoustics and immunohistochemical analysis with FLIM imaging allows for a comprehensive assessment of both vascularization and the metabolic state of the tumor, which can help predict the therapeutic response.