Prognostic value of circulating tumor cells in oligorecurrent hormone-sensitive prostate cancer patients undergoing stereotactic body radiation therapy.

Background: Stereotactic body radiation therapy (SBRT) is an effective metastasis-directed therapy for managing oligometastatic prostate cancer patients. However, it lacks reliable biomarkers for risk stratification. Circulating Tumor Cells (CTC) show promise as minimally invasive prognostic indicators.

A fully interpretable machine learning model for increasing the effectiveness of urine screening.

Objectives: This article addresses the need for effective screening methods to identify negative urine samples before urine culture, reducing the workload, cost, and release time of results in the microbiology laboratory. We try to overcome the limitations of current solutions, which are either too simple, limiting effectiveness (1 or 2 parameters), or too complex, limiting interpretation, trust, and real-world implementation ("black box" machine learning models).

Methods: The study analyzed 15,312 samples from 10,534 patients with clinical features and the Sysmex Uf-1000i automated analyzer data.

Anti-VEGF therapy selects for clones resistant to glucose starvation in ovarian cancer xenografts.

Background: Genetic and metabolic heterogeneity are well-known features of cancer and tumors can be viewed as an evolving mix of subclonal populations, subjected to selection driven by microenvironmental pressures or drug treatment. In previous studies, anti-VEGF therapy was found to elicit rewiring of tumor metabolism, causing marked alterations in glucose, lactate ad ATP levels in tumors. The aim of this study was to evaluate whether differences in the sensitivity to glucose starvation existed at the clonal level in ovarian cancer cells and to investigate the effects induced by anti-VEGF therapy on this phenotype by multi-omics analysis.

Integration of Cellular and Humoral Immune Responses as an Immunomonitoring Tool for SARS-CoV-2 Vaccination in Healthy and Fragile Subjects.

Cellular and humoral immunity are both required for SARS-CoV-2 infection recovery and vaccine efficacy. The factors affecting mRNA vaccination-induced immune responses, in healthy and fragile subjects, are still under investigation. Thus, we monitored the vaccine-induced cellular and humoral immunity in healthy subjects and cancer patients after vaccination to define whether a different antibody titer reflected similar rates of cellular immune responses and if cancer has an impact on vaccination efficacy.

Clinical relevance of the combined analysis of circulating tumor cells and anti-tumor T-cell immunity in metastatic breast cancer patients.

Background: Metastatic breast cancer (mBC) is a heterogeneous disease with varying responses to treatments and clinical outcomes, still requiring the identification of reliable predictive biomarkers. In this context, liquid biopsy has emerged as a powerful tool to assess in real-time the evolving landscape of cancer, which is both orchestrated by the metastatic process and immune-surveillance mechanisms. Thus, we investigated circulating tumor cells (CTCs) coupled with peripheral T-cell immunity to uncover their potential clinical relevance in mBC.

An antivenin resistant, IVIg-corticosteroids responsive viper induced thrombocytopenia.

In this case report the hospital management of an acute, severe thrombocytopenia in a 57-year-old man in the north-east of Italy is reported. Thrombocytopenia developed immediately after the viper bite, despite the absence of clinical signs of envenomation. No hemorrhage, ecchymoses or other signs of coagulopathy developed during the hospitalization; two doses of antivenin FAB-Fragments had no effect on thrombocytopenia, which instead responded promptly to intravenous immunoglobulins (IVIg) and glucocorticoids.

Image Analysis of Circulating Tumor Cells and Leukocytes Predicts Survival and Metastatic Pattern in Breast Cancer Patients.

Background: The purpose of the present work was to test whether quantitative image analysis of circulating cells can provide useful clinical information targeting bone metastasis (BM) and overall survival (OS >30 months) in metastatic breast cancer (MBC).

Methods: Starting from cell images of epithelial circulating tumor cells (eCTC) and leukocytes (CD45pos) obtained with DEPArray, we identified the most significant features and applied single-variable and multi-variable methods, screening all combinations of four machine-learning approaches (Naïve Bayes, Logistic regression, Decision Trees, Random Forest).

Results: Best predictive features were circularity (OS) and diameter (BM), in both eCTC and CD45pos.

IgG antibodies against SARS-CoV-2 decay but persist 4 months after vaccination in a cohort of healthcare workers.

Background And Aims: Monitoring the immune response against SARS-CoV-2 is pivotal in the evaluation of long-term vaccine efficacy. Immunoglobulin G (IgG) antibodies represent an advisable tool to reach this goal, especially for the still poorly defined antibody trend induced by the new class of mRNA vaccines against SARS-CoV-2.

Materials And Methods: Anti-Spike RBD IgG antibodies were monitored in a cohort of healthcare workers at CRO Aviano, National Cancer Institute, through MAGLUMI® chemiluminescence assay, at 1 and 4 months after full-schedule of BNT162b2 or mRNA-1273 vaccination.

Dysmetabolic Circulating Tumor Cells Are Prognostic in Metastatic Breast Cancer.

Circulating tumor cells (CTCs) belong to a heterogeneous pool of rare cells, and a unequivocal phenotypic definition of CTC is lacking. Here, we present a definition of metabolically-altered CTC (MBA-CTCs) as CD45-negative cells with an increased extracellular acidification rate, detected with a single-cell droplet microfluidic technique. We tested the prognostic value of MBA-CTCs in 31 metastatic breast cancer patients before starting a new systemic therapy (T0) and 3-4 weeks after (T1), comparing results with a parallel FDA-approved CellSearch (CS) approach.

Application of an Artificial Intelligence Algorithm to Prognostically Stratify Grade II Gliomas.

(1) Background: Recently, it has been shown that the extent of resection (EOR) and molecular classification of low-grade gliomas (LGGs) are endowed with prognostic significance. However, a prognostic stratification of patients able to give specific weight to the single parameters able to predict prognosis is still missing. Here, we adopt classic statistics and an artificial intelligence algorithm to define a multiparametric prognostic stratification of grade II glioma patients.

Sleeping beauty genetic screen identifies miR-23b::BTBD7 gene interaction as crucial for colorectal cancer metastasis.

Background: Metastatic colorectal cancer (CRC) remains a deadly disease. Identifying locally advanced CRC patients with high risk of developing metastasis and improving outcome of metastatic CRC patients require discovering master regulators of metastasis. In this context, the non-coding part of the human genome is still largely unexplored.

Microfluidic droplets content classification and analysis through convolutional neural networks in a liquid biopsy workflow.

In a recent paper we presented an innovative method of liquid biopsy, for the detection of circulating tumor cells (CTC) in the peripheral blood. Using microfluidics, CTC are individually encapsulated in water-in-oil droplets and selected by their increased rate of extracellular acidification (ECAR). During the analysis, empty or debris-containing droplets are discarded manually by screening images of positive droplets, increasing the operator-dependency and time-consumption of the assay.

Assessment of the Mutational Status of NSCLC Using Hypermetabolic Circulating Tumor Cells.

Molecular characterization is currently a key step in NSCLC therapy selection. Circulating tumor cells (CTC) are excellent candidates for downstream analysis, but technology is still lagging behind. In this work, we show that the mutational status of NSCLC can be assessed on hypermetabolic CTC, detected by their increased glucose uptake.

Emerging Technologies for Cancer Research: Towards Personalized Medicine with Microfluidic Platforms and 3D Tumor Models.

In the present review, we describe three hot topics in cancer research such as circulating tumor cells, exosomes, and 3D environment models. The first section is dedicated to microfluidic platforms for detecting circulating tumor cells, including both affinity-based methods that take advantage of antibodies and aptamers, and "label-free" approaches, exploiting cancer cells physical features and, more recently, abnormal cancer metabolism. In the second section, we briefly describe the biology of exosomes and their role in cancer, as well as conventional techniques for their isolation and innovative microfluidic platforms.

Dissecting the Heterogeneity of Circulating Tumor Cells in Metastatic Breast Cancer: Going Far Beyond the Needle in the Haystack.

Although the enumeration of circulating tumor cells (CTC) defined as expressing both epithelial cell adhesion molecule and cytokeratins (EpCAM⁺/CK⁺) can predict prognosis and response to therapy in metastatic breast, colon and prostate cancer, its clinical utility (i.e., the ability to improve patient outcome by guiding therapy) has not yet been proven in clinical trials.

A Method for Detecting Circulating Tumor Cells Based on the Measurement of Single-Cell Metabolism in Droplet-Based Microfluidics.

The number of circulating tumor cells (CTCs) in blood is strongly correlated with the progress of metastatic cancer. Current methods to detect CTCs are based on immunostaining or discrimination of physical properties. Herein, a label-free method is presented exploiting the abnormal metabolic behavior of cancer cells.

In patients with metastatic breast cancer the identification of circulating tumor cells in epithelial-to-mesenchymal transition is associated with a poor prognosis.

Background: Although recent models suggest that the detection of Circulating Tumor Cells (CTC) in epithelial-to-mesenchymal transition (EM CTC) might be related to disease progression in metastatic breast cancer (MBC) patients, current detection methods are not efficient in identifying this subpopulation of cells. Furthermore, the possible association of EM CTC with both clinicopathological features and prognosis of MBC patients has still to be demonstrated. Aims of this study were: first, to optimize a DEPArray-based protocol meant to identify, quantify and sort single, viable EM CTC and, subsequently, to test the association of EM CTC frequency with clinical data.

Glucose is a key driver for GLUT1-mediated nanoparticles internalization in breast cancer cells.

The mesenchymal state in cancer is usually associated with poor prognosis due to the metastatic predisposition and the hyper-activated metabolism. Exploiting cell glucose metabolism we propose a new method to detect mesenchymal-like cancer cells. We demonstrate that the uptake of glucose-coated magnetic nanoparticles (MNPs) by mesenchymal-like cells remains constant when the glucose in the medium is increased from low (5.