The present studies were undertaken to evaluate by light and by electron microscopy the influence of Ukrain on the morphology of breast cancer. The studies were carried out on material obtained from ten patients with breast cancer, treated preoperatively with Ukrain. Control material for the studies was obtained from patients of similar age and advancement of the disease, who did not receive Ukrain. The data obtained in the present studies indicate that Ukrain is responsible for severe changes in morphology of tumour cells. Histological examination by both light and electron microscopy revealed cells characteristic of those undergoing apoptosis. The stromal changes of the tumour were characterized by intensive proliferation of the connective tissue accompanied by an immune reaction expressed by mononuclear infiltrates.
Download full-text PDF |
Source |
---|
Acta Oncol
January 2025
Psychological Aspects of Cancer, Cancer Survivorship, The Danish Cancer Institute, Copenhagen, Denmark.
Introduction: To target psychological support to cancer patients most in need of support, screening for psychological distress has been advocated and, in some settings, also implemented. Still, no prior studies have examined the appropriate 'dosage' and whether screening for distress before cancer treatment may be sufficient or if further screenings during treatment are necessary. We examined the development in symptom trajectories for breast cancer patients with low distress before surgery and explored potential risk factors for developing burdensome symptoms at a later point in time.
View Article and Find Full Text PDFCell Mol Biol Lett
January 2025
Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Arcavacata Di Rende, 87036, Cosenza, Italy.
Breast cancer is the most commonly diagnosed type of cancer and the leading cause of cancer-related death in women worldwide. Highly targeted therapies have been developed for different subtypes of breast cancer, including hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-positive breast cancer. However, triple-negative breast cancer (TNBC) and metastatic breast cancer disease are primarily treated with chemotherapy, which improves disease-free and overall survival, but does not offer a curative solution for these aggressive forms of breast cancer.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Genetics, The University of Alabama at Birmingham, Birmingham, AL, USA.
Nowadays, chemotherapy and immunotherapy remain the major treatment strategies for Triple-Negative Breast Cancer (TNBC). Identifying biomarkers to pre-select and subclassify TNBC patients with distinct chemotherapy responses is essential. In the current study, we performed an unbiased Reverse Phase Protein Array (RPPA) on TNBC cells treated with chemotherapy compounds and found a leading significant increase of phosphor-AURKA/B/C, AURKA, AURKB, and PLK1, which fall into the mitotic kinase group.
View Article and Find Full Text PDFSci Rep
January 2025
Chair of Obstetrics Development, Faculty of Health Sciences, Medical University of Lublin, Lublin, Poland.
The aim of the study is to analyze the relationship between personality traits of women with hereditary predisposition to breast/ovarian cancer and their obstetric history and cancer-preventive behaviors. A total of 357 women, participants of 'The National Program for Families With Genetic/Familial High Risk for Cancer', were included in the study. The Neo Five-Factor Inventory (NEO-FFI) and a standardized original questionnaire designed for the purpose of the study were used.
View Article and Find Full Text PDFSci Rep
January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!