A Two-Step Feature Selection Radiomic Approach to Predict Molecular Outcomes in Breast Cancer.

Breast Cancer (BC) is the most common cancer among women worldwide and is characterized by intra- and inter-tumor heterogeneity that strongly contributes towards its poor prognosis. The Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER2), and Ki67 antigen are the most examined markers depicting BC heterogeneity and have been shown to have a strong impact on BC prognosis. Radiomics can noninvasively predict BC heterogeneity through the quantitative evaluation of medical images, such as Magnetic Resonance Imaging (MRI), which has become increasingly important in the detection and characterization of BC. However, the lack of comprehensive BC datasets in terms of molecular outcomes and MRI modalities, and the absence of a general methodology to build and compare feature selection approaches and predictive models, limit the routine use of radiomics in the BC clinical practice. In this work, a new radiomic approach based on a two-step feature selection process was proposed to build predictors for ER, PR, HER2, and Ki67 markers. An in-house dataset was used, containing 92 multiparametric MRIs of patients with histologically proven BC and all four relevant biomarkers available. Thousands of radiomic features were extracted from post-contrast and subtracted Dynamic Contrast-Enanched (DCE) MRI images, Apparent Diffusion Coefficient (ADC) maps, and T2-weighted (T2) images. The two-step feature selection approach was used to identify significant radiomic features properly and then to build the final prediction models. They showed remarkable results in terms of F1-score for all the biomarkers: 84%, 63%, 90%, and 72% for ER, HER2, Ki67, and PR, respectively. When possible, the models were validated on the TCGA/TCIA Breast Cancer dataset, returning promising results (F1-score = 88% for the ER+/ER- classification task). The developed approach efficiently characterized BC heterogeneity according to the examined molecular biomarkers.

Could Kallikrein-Related Serine Peptidase 3 Be an Early Biomarker of Environmental Exposure in Young Women?

Bisphenols and phthalates affect androgen receptor-mediated signaling that directly regulates Kallikrein-Related serine Peptidase 3 (KLK3) secretion, indicating that environmental factors may play a role in KLK3 secretion. With the aim of obtaining preliminary data on whether KLK3 could serve as an early marker of environmental pollution effects, in 61 and 58 healthy women living in a high environmental impact (HEI) and low environmental impact (LEI) area, respectively, serum KLK3 levels at different phases of menstrual cycle were measured. KLK3 values resulted in always being higher in the HEI group with respect to the LEI group. These differences were particularly relevant in the ovulatory phase (cycle day 12°-13°) of the menstrual cycle. The differences in KLK3 values during the three phases of the menstrual cycle were significant in the LEI group differently from the HEI group. In addition, higher progesterone levels were observed in the LEI group with respect to the HEI group in the luteal phase, indicating an opposite trend of KLK3 and progesterone in this phase of the menstrual cycle. Although changes in KLK3 could also depend on other factors, these preliminary data could be an early indication of an expanding study of the role of biomarkers in assessing early environmental effects for female reproductive health.

Comparing different sperm separation techniques for ART, through quantitative evaluation of p53 protein.

CONTEXT: In the last 10 years, assisted reproductive technologies (ARTs) have offered infertile couples an opportunity to complete their reproductive project. However, the high failure rate could be explained with the complex human reproduction system. In ART, the decrease of the success is due to the conditions far from the natural ones. AIMS: The aim of this study is to evaluate deoxyribonucleic acid (DNA) damage of spermatozoa before and after selection procedures, using a new technique able to quantize sperm DNA damage. SETTINGS AND DESIGN: They were involved 43 males domiciled permanently in two areas with different Environmental Impact, HEI (high environmental impact) and LEI (Low environmental impact), they are aged between 24 and 31 years with various degrees of dyspermia. SUBJECTS AND METHODS: The 43 males were divided into two groups: 21 in Group A (EIL) and 22 in Group B (EIH). The samples must be aliquoted into parts of 0.5 mL: Group (a) Control, no processing; Group (b) Swim-up (SUP) from semen; Group (c) classic SUP; Group (d) density gradient centrifugation (DGC). All samples were subjected to a quantitative dosage of p53 protein, before and after processing. STATISTICAL ANALYSIS USED: For the development of the probability and significance of the data, the Student's t-test was used. RESULTS: From our data, it emerges that Groups D and B provide a superior quality about motility, vitality, and apoptosis indexes compared to other conventional techniques. In Group B, apoptosis is comparable to Group D, but they have slightly lower about motility and vitality. Group C is the one that has lower parameters than the other techniques. Regarding the evaluation of p53 protein, the results are conflicting with the evaluation of apoptosis; in fact, in Group D, the values are significantly higher than the other techniques. CONCLUSIONS: Sperm separation is an important moment in ART techniques. From our data, it emerges a greater fragility of DNA in the male spermatozoa who reside permanently in areas with high environmental impact.