Background: The incidence of breast carcinoma is increasing in developing countries due to adoption of western life-style. Fine-needle aspiration cytology is the initial method to evaluate the palpable breast lesions. The neoadjuvant therapy is helpful in treating high grade rather than low grade breast carcinomas. Masood cytologic index (MCI) delineates all the breast lesions into four groups. The carcinoma group is not graded further.
Aim: The present study proposes a method for the expansion of carcinoma group into three grades.
Materials And Methods: A total of 50 breast carcinoma cases were prospectively studied by comparing expansion of MCI with modified bloom Richardson (MBR) grading over a period of 3 years.
Results: Altogether 43/50 cases (86%) had concordance with histopathological grading. The analysis revealed a R2 value of 60%, which was significant. The P value of anisonucleosis, nucleoli and chromatin pattern were 0.001, 0.049 and 0.02 respectively, which were significant.
Conclusions: The present study with the expansion of carcinoma category of MCI into three grades similar to MBR will help the treating surgeon to plan the management accordingly. The results obtained in this study need to be subjected to multicentric study with a large number of cases.
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http://dx.doi.org/10.4103/0970-9371.126647 | DOI Listing |
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.
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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.
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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.
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