Biomedical subjects

Michelino De Laurentiis

Publications and source records attributed to Michelino De Laurentiis.

3 recordsLinked to original sources

PubMed2026

Transcriptomic signatures of mind-body transformations therapy in breast cancer: Downregulation of the interferon signaling pathway.

BACKGROUND: Growing evidence has shown that Mind-Body Transformations-Therapies (MBT-T) are able to modulate chronic inflammation, a well-known driver of cancer progression and drug resistance. In our previous work, we showed that a specific MBT-T protocol was able to reduce the release of various pro-inflammatory cytokines and chemokines in the sera of patients with breast cancer that completed adjuvant chemotherapy. Despite these clinical observations, the underlying molecular pathways through which this therapy exerts its effects remain unclear. This study aims to address this gap by characterizing genome-wide transcriptional profiles in patients undergoing a novel MBT-T protocol. METHODS: In this proof-of-concept study, patients with breast cancer were randomized into two groups: Group 1 (CTL), receiving standard follow-up care, and Group 2 (MBT-T), receiving standard follow-up plus biweekly MBT-T for 4 months. Blood samples were collected at different timepoints during the treatment. After RNA extraction from whole blood, gene expression was analyzed on twenty-one patients (CTL, n = 7; MBT-T, n = 14) using the nCounter® Human Inflammation Panel (249 genes). RESULTS: Patients undergoing MBT-T showed a significant global downregulation of inflammatory gene expression compared to the control group. The analysis revealed that the Interferon (IFN) signaling pathway was the most significantly suppressed, by downregulation of key genes such as IFIT1, IFIT3, IFI44, MX1 and OASL in the MBT-T group. CONCLUSIONS: MBT-T acts as a biological modulator capable of downregulating key inflammatory pathways at the transcriptional level. These findings provide a genomic basis for the clinical benefits of mind-body interventions in oncology.

Breast cancer↗

PubMed2004

Neural network analysis for evaluating cancer risk in thyroid nodules with an indeterminate diagnosis at aspiration cytology: identification of a low-risk subgroup.

Thyroid nodules with a predominant follicular structure are often diagnosed as indeterminate at fine-needle aspiration biopsy (FNAB). We studied 453 patients with a thyroid nodule diagnosed as indeterminate at FNAB by using a feed-forward artificial neural network (ANN) analysis to integrate cytologic and clinical data, with the goal of subgrouping patients into a high-risk and in a low-risk category. Three hundred seventy-one patients were used to train the network and 82 patients were used to validate the model. The cytologic smears were blindly reviewed and classified in a high-risk and a low-risk subgroup on the basis of standard criteria. Neural network analysis subdivided the 371 lesions of the first series into a high-risk group (cancer rate of approximately 33% at histology) and a low-risk group (cancer rate of 3%). Only cytologic parameters contributed to this classification. Analysis of the receiver operating characteristic (ROC) curves demonstrated that the ANN model discriminated with higher sensitivity and specificity between benign and malignant nodules compared to standard cytologic criteria (p < 0.001). This value did not show degradation when ANN predictions were applied to the validation series of 82 nodules. In conclusion, neural network analysis of cytologic data may be a useful tool to refine the risk of cancer in patients with lesions diagnosed as indeterminate by FNAB.

Adult↗

PubMed2003

Twenty-year results of the Naples GUN randomized trial: predictive factors of adjuvant tamoxifen efficacy in early breast cancer.

PURPOSE: Tamoxifen (TAM) is increasingly administered to new early breast cancer patients. Because it is not devoid of toxic effects, we studied factors potentially predictive of its efficacy. EXPERIMENTAL DESIGN: From 1978 to 1983, 433 patients were enrolled in the GUN randomized trial: 206 were assigned to TAM versus 227 controls (no-TAM). Premenopausal patients with axillary lymph node involvement (60 TAM versus 65 no-TAM) also received nine CMF cycles. Eight biological markers were retrospectively assayed for most patients: estrogen; progesterone; prolactin receptors (PrlRs); microvessel count (MVC); S-phase fraction; tumor ploidy; epidermal growth factor receptor (EGFR); and HER2. We performed a multivariate test of the TAM/covariate interactions to establish whether these variables predicted for TAM efficacy. Estimates of the TAM effect were expressed as hazard ratio (HR) of death of TAM over no-TAM patients with 95% confidence intervals (95% CIs). RESULTS: At a median follow-up of 15 years, PrlRs, MVC, S-phase fraction, ploidy, and EGFR did not influence TAM efficacy. Differently, HER2 had an overall significant predictive effect: HR = 0.59 (95% CI: 0.40-0.87) in HER2-negative subjects versus HR = 1.09 (95% CI: 0.63-1.87) in HER2-positive subjects (interaction test: P = 0.04). The predictive effect of HER2 was also evident in the subgroup of patients with steroid receptor-positive tumors (HER2 positive: HR = 1.33, 95% CI: 0.70-2.51; HER2 negative: HR = 0.73, 95% CI: 0.47-1.14). CONCLUSIONS: With the statistical power of the present randomized trial, S-phase, ploidy, EGFR, PrlR, and MVC do not seem to predict for TAM efficacy. Conversely, our data support the hypothesis that tumors overexpressing HER2 might not benefit from adjuvant TAM.

Adolescent↗