Background: Residents in a large area of North-Eastern Italy were exposed to perfluoroalkyl substances (PFAS) via drinking water. Studies on the association between PFAS and blood pressure levels are limited, and results are inconsistent. Using cross-sectional data from the Regional health surveillance program, we aimed to quantify the associations between PFAS serum concentrations and blood pressure and hypertension prevalence. Methods: The study comprised 16,224 individuals aged 20–39 years. Pregnant women (n = 327), or individuals with missing information on the selected covariates (n = 111) were excluded, leaving 15,786 subjects for the analyses. Hypertension was defined as any self-reported diagnosis, use of antihypertensive drugs, or elevated systolic blood pressure (SBP ≥ 140 mmHg)/diastolic blood pressure (DBP ≥ 90 mmHg). Generalized additive models were used to investigate the relation between perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA)) natural log (ln) transformed and by decile, and SBP, DBP, hypertension, adjusted for potential confounders. Results: Both SBP and DBP increased significantly with an increase in the ln-transformed serum PFAS concentrations in a monotonic way. The predicted increase in SBP and DBP were 1.54 mmHg (95%CI 0.61–2.47), 1.60 mmHg (95%CI 0.92–2.27) from lowest to highest decile of PFOA. The associations were stronger for SBP in men and for DBP in women. One unit increase in each In-transformed PFAS was positively associated with an increased odd of hypertension in men: PFOA OR = 1.06 (1.01–1.11), PFOS OR = 1.13 (1.03–1.23), PFHxS OR = 1.08 (1.02–1.15), PFNA OR = 1.20 (1.02–1.40). Conclusions: Our findings suggest that serum PFAS concentrations were associated with increased systolic and diastolic blood pressure in a large highly exposed young adult population. Although the magnitude of the observed effect was relatively small, if confirmed it would be of public health relevance since even small increases in blood pressure levels at the population level may be associated to a raised risk of adverse outcomes such as cardiovascular disease and target organ damage.

Circulating HER2 extracellular domain (HER2 ECD) levels were proposed as a surrogate for HER2 tissue expression to monitor breast cancer patients for early relapse or responses to standard or HER2-targeted therapies, such as the monoclonal antibody (mAb) trastuzumab. Currently, available commercial ELISA assays for HER2 ECD rely on antibodies recognizing undisclosed or unknown epitopes. In this work, two ELISA assays employing MGR2 and MGR3 epitope-specific mAbs for HER2 ECD were developed and validated, showing good assay precision and linearity of the dose-response signal within the dynamic range of 0.19–12.50 ng mL⁻¹ and detection limits of 0.76 and 0.75 ng mL⁻¹ for the MGR2 and MGR3 assays, respectively. The developed assay showed a good agreement with two widely used commercial kits for HER2 ECD quantification in serum samples from breast cancer patients. A complete characterization of mAb-HER2 ECD interaction was performed by means of surface plasmon resonance using trastuzumab as control for both epitope mapping and kinetics analysis. The epitopes recognized by the two mAbs showed no overlap with trastuzumab, which was confirmed by trastuzumab interference analysis in serum samples. The method showed to be a practical approach to determine HER2 ECD with a high degree of sensitivity, reliability and recovery in samples containing mAbs-based therapies.

Primary breast cancer (PBC) is a heterogeneous disease at the clinical, histopathological, and molecular levels. The improved classification of PBC might be important to identify subgroups of the disease, relevant to patient management. Machine learning algorithms may allow a better understanding of the relationships within heterogeneous clinical syndromes. This work aims to show the potential of unsupervised learning techniques for improving classification in PBC. A dataset of 712 women with PBC is used as a motivating example. A set of variables containing biological prognostic parameters is considered to define groups of individuals. Four different clustering methods are used: K-means, self-organising maps, hierarchical agglomerative (HAC), and Gaussian mixture models clustering. HAC outperforms the other clustering methods. With an optimal partitioning parameter, the methods identify two clusters with different clinical profiles. Patients in the first cluster are younger and have lower values of the oestrogen receptor (ER) and progesterone receptor (PgR) than patients in the second cluster. Moreover, cathepsin D values are lower in the first cluster. The three most important variables identified by the HAC are: age, ER, and PgR. Unsupervised learning seems a suitable alternative for the analysis of PBC data, opening up new perspectives in the particularly active domain of dissecting clinical heterogeneity.

Purpose: Epidermal growth factor receptor (EGFR) is overexpressed in approximately 50% of invasive breast carcinomas and it is correlated with hormone resistance and poor prognosis. EGFR suppression by gefitinib, a quinazoline derivative that inhibits phosphorylation of the specific receptor, represents a novel therapeutic strategy. A dose-finding study was performed to evaluate the combination of gefitinib with weekly epirubicin in patients with pretreated metastatic breast cancer. Methods: Fifteen patients were enrolled at four sequential dose levels. Gefitinib was administered orally, at the fixed daily dose of 250 mg. The starting dose of epirubicin was 20 mg/m². Escalating dose levels of epirubicin were planned by increments of 5 mg/m² per level, up to the maximum tolerated dose (MTD). Pharmacodynamic studies were performed by determining serum and tissue ERBB2 and EGFR. Results: At the first three dose levels tested no patient experienced a dose-limiting toxicity (DLT). In cohort 4, two patients experienced DLTs (grade 4 dyspnea and asthenia, grade 3 diarrhea and thrombocytopenia) identifying the MTD of epirubicin as 35 mg/m². Of the 14 cases assessable for response, partial response was documented in two patients, and stable disease in seven, giving an overall disease control rate of 64.2%. The comparison of pre- and post-therapy ERBB2 and EGFR values was not statistically significant between the subgroups of patients regarding responsiveness to treatment. Conclusions: The recommended dose of epirubicin for phase II studies is 30 mg/m² in combination with gefitinib at the daily dose of 250 mg. Pharmacodynamic studies did not identify any biomarker predictive of response.

Despite the clear endocrine-metabolic relationship between androgenic activity and adiposity, the role of androgens in breast cancer prognosis according to patient’s adiposity is scarcely explored. Here, we aimed at investigating the prognostic value of circulating testosterone in association with patient’s body mass index (BMI). Circulating testosterone and BMI were evaluated at breast cancer diagnosis in 460 estrogen receptor (ER)-positive postmenopausal patients. Local relapse, distant metastasi(e)s and contralateral breast cancer were considered recurrence events. The Kruskal-Wallis test was performed to evaluate if testosterone levels differed within subgroups of categorical tumour characteristics. The Cox proportional hazard regression model was fitted to estimate the impact of standard prognostic factors on relapse-specific hazard ratio (HR). After backward selection, a model including continuous testosterone level, BMI categories (< 25, normal-weight; =25–30, overweight; ≥30 kg/m2, obese), tumour size and lymph nodes number was fitted. Furthermore, Cox models provided the relapse-specific HRs for median, third quartile and 95th percentile compared to the first quartile of testosterone levels, stratified by BMI categories. During a median follow up of 6.3 years, 45 patients relapsed. Testosterone levels significantly increased across BMI categories (p = 0.001). Both circulating testosterone and BMI were positively associated with disease free survival (p = 0.005 and p = 0.021, respectively). A significant interaction was found between testosterone and BMI (p = 0.006). For normal-weight women, testosterone concentration around median (0.403 ng/mL) or third quartile (0.532 ng/mL) showed a high significant HR of relapse (5.52; 95% CI:1.65–18.49 and 4.55; 95% CI:1.09–18.98, respectively). Overweight patients showed increased HR at increasing testosterone levels, reaching a significant high HR (4.68; 95% CI:1.39–15.70) for testosterone values of 0.782 ng/mL (95th percentile). For obese patients HR decreased (not significantly) at increased testosterone concentrations, explaining the interaction between testosterone levels and BMI categories. In ER-positive postmenopausal breast cancer patients, high testosterone levels are associated with worse prognosis in normal-weight and overweight women, whereas in obese seems to be associated with a better outcome. Although the results require further validation, they suggest that assessment of circulating testosterone and BMI could help to identify postmenopausal ER-positive patients at higher risk of relapse and potentially open new therapeutic strategies.