Browsing by Author "Milovanović, Jelena (57197628471)"

Purpose: More than half of prostate cancer patients undergo radiation treatment which may be accompanied by acute or late side effects in genitourinary, GU, and/or gastrointestinal, GI tract, and radiotherapy-induced fatigue (RIF). The biological role of RNase L highlights its potential to be tested for association with the adverse effects of radiotherapy. Objectives: This study aims to investigate the associations among RNASEL gene variants, acute, late GI/GU toxicity events, and RIF to evaluate their potential to be used as biomarkers for prediction of response to radiation treatment. Methods: The DNA from peripheral blood mononuclear cells of 81 patients with prostate adenocarcinoma under RT was genotyped for RNASEL rs12757998, rs486907, and rs627928 by real-time quantitative PCR. The acute and late GU and GI adverse effects were evaluated during and up to 54 months after RT, as well as the occurrence or increase in fatigue grade. Results: rs12757998 RNASEL TT genotype was shown to be significantly associated with severity of acute GU toxicity while CT genotype with severity of late GI toxicity. Furthermore, CC genotype of rs12757998 and the AA genotype of rs627928 were shown to be potential independent predictive biomarkers of RIF. Conclusion: RNASEL gene polymorphisms are associated with a higher risk of radiotoxicity, which may be used for biological tests for the prediction of RT-related side effects and to develop strategies to fight against fatigue, to significantly improve the quality of life of cancer survivors. © Copyright © 2025 Taylor & Francis Group LLC.

Survival and life quality of breast cancer patients could be improved by more aggressive chemotherapy for those at high metastasis risk and less intense treatments for low-risk patients. Such personalized treatment cannot be currently achieved due to the insuffcient reliability of metastasis risk prognosis. The purpose of this study was therefore, to identify novel histopathological prognostic markers of metastasis risk through exhaustive computational image analysis of 80 size and shape subsets of epithelial clusters in breast tumors. The group of 102 patients had a follow-up median of 12.3 years, without lymph node spread and systemic treatments. Epithelial cells were stained by the AE1/AE3 pan-cytokeratin antibody cocktail. The size and shape subsets of the stained epithelial cell clusters were defined in each image by use of the circularity and size filters and analyzed for prognostic performance. Epithelial areas with the optimal prognostic performance were uniformly small and round and could be recognized as individual epithelial cells scattered in tumor stroma. Their count achieved an area under the receiver operating characteristic curve (AUC) of 0.82, total area (AUC = 0.77), average size (AUC = 0.63), and circularity (AUC = 0.62). In conclusion, by use of computational image analysis as a hypothesis-free discovery tool, this study reveals the histomorphological marker with a high prognostic value that is simple and therefore easy to quantify by visual microscopy. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Survival and life quality of breast cancer patients could be improved by more aggressive chemotherapy for those at high metastasis risk and less intense treatments for low-risk patients. Such personalized treatment cannot be currently achieved due to the insuffcient reliability of metastasis risk prognosis. The purpose of this study was therefore, to identify novel histopathological prognostic markers of metastasis risk through exhaustive computational image analysis of 80 size and shape subsets of epithelial clusters in breast tumors. The group of 102 patients had a follow-up median of 12.3 years, without lymph node spread and systemic treatments. Epithelial cells were stained by the AE1/AE3 pan-cytokeratin antibody cocktail. The size and shape subsets of the stained epithelial cell clusters were defined in each image by use of the circularity and size filters and analyzed for prognostic performance. Epithelial areas with the optimal prognostic performance were uniformly small and round and could be recognized as individual epithelial cells scattered in tumor stroma. Their count achieved an area under the receiver operating characteristic curve (AUC) of 0.82, total area (AUC = 0.77), average size (AUC = 0.63), and circularity (AUC = 0.62). In conclusion, by use of computational image analysis as a hypothesis-free discovery tool, this study reveals the histomorphological marker with a high prognostic value that is simple and therefore easy to quantify by visual microscopy. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.