Ovarian cancer is the most common cause of death among gynecological malignancies. We discuss different types of clinical and nonclinical features that are used to study and analyze the differences between benign and malignant ovarian tumors. Computer-aided diagnostic (CAD) systems of high accuracy are being developed as an initial test for ovarian tumor classification instead of biopsy, which is the current gold standard diagnostic test. We also discuss different aspects of developing a reliable CAD system for the automated classification of ovarian cancer into benign and malignant types. A brief description of the commonly used classifiers in ultrasound-based CAD systems is also given.
Recent studies have identified causal links between altered gut microbiome, chronic inflammation, and inflammation-driven conditions such as diabetes and cardiovascular disease. Childhood cancer survivors (CCS) show late effects of therapy in the form of inflammaging-related disorders as well as microbial dysbiosis, supporting a hypothesis that the conditions are interconnected. Given the susceptibility of the gut microbiome to alteration, a number of therapeutic interventions have been investigated for the treatment of inflammatory conditions, though not within the context of cancer survivorship in children and adolescents. Here, we evaluate the potential for these interventions, which include probiotic supplementation, prebiotics/fiber-rich diet, exercise, and fecal microbiota transplantation for prevention and treatment of cancer treatment-related microbial dysbiosis in survivors. We also make recommendations to improve adherence and encourage long-term lifestyle changes for maintenance of healthy gut microbiome in CCS as a potential strategy to mitigate treatment-related late effects.
Breast cancer is the most common malignancy and the second most common cause of cancer-related mortality in women. Triple-negative breast cancers do not express estrogen receptors, progesterone receptors, or human epidermal growth factor receptor 2 and have a higher recurrence rate, greater metastatic potential, and lower overall survival rate than those of other breast cancers. Treatment of triple-negative breast cancer is challenging; molecular-targeted therapies are largely ineffective and there is no standard treatment. In this review, we evaluate current attempts to classify triple-negative breast cancers based on their molecular features. We also describe promising treatment methods with different advantages and discuss genetic biomarkers and other prediction tools. Accurate molecular classification of triple-negative breast cancers is critical for patient risk categorization, treatment decisions, and surveillance. This review offers new ideas for more effective treatment of triple-negative breast cancer and identifies novel targets for drug development.