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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. We validated the method in 30 Stage IV NSCLC patients: peripheral blood samples were incubated with a fluorescent glucose analog (2-NBDG) and analyzed by flow cytometry. Cells with the highest glucose uptake were sorted out. EGFR and KRAS mutations were detected by ddPCR. In sorted cells, mutated DNA was found in 85% of patients, finding an exact match with primary tumor in 70% of cases. Interestingly, in two patients multiple KRAS mutations were detected. Two patients displayed different mutations with respect to the primary tumor, and in two out of the four patients with a wild type primary tumor, new mutations were highlighted: EGFR p.746_750del and KRAS p.G12V. Hypermetabolic CTC can be enriched without the need of dedicated equipment and their mutational status can successfully be assessed by ddPCR. Finally, the finding of new mutations supports the possibility of probing tumor heterogeneity.
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http://dx.doi.org/10.3390/cancers10080270 | DOI Listing |
Cancer
September 2025
Thoracic Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, New York, USA.
Background: Trials of neoadjuvant chemoimmunotherapy (chemoIO) have changed the standard of care for resectable nonsmall cell lung cancer (NSCLC). This study characterizes the outcomes of off-trial patients who received treatment with neoadjuvant chemoIO.
Methods: The authors analyzed records of patients with stage IB-III NSCLC who received neoadjuvant chemoIO with an intent to proceed to surgical resection at three US academic institutions.
Background: This study aims to gain further insights into the characteristics of the rare subtype of acute myeloid leukemia (AML) with BCR∷ABL by analyzing laboratory detection results of various gene mutations, such as NPM1.
Methods: Laboratory detection results of multiple gene missense mutations, including NPM1, were analyzed in a case of primary AML with BCR∷ABL.
Results: The patient exhibited morphological features of acute leukemia in the bone marrow.
Pediatr Dev Pathol
September 2025
The Hospital for Sick Children, Division of Pathology, Toronto, Canada.
Background: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of childhood. For stratification purposes, rhabdomyosarcoma is classified into fusion-positive RMS (alveolar rhabdomyosarcoma) and fusion-negative RMS (embryonal or spindle cell/sclerosing, FN-RMS) subtypes according to its fusion status. This study aims to highlight the pathologic and molecular characteristics of a cohort of FN-RMS using a targeted NGS RNA-Seq assay.
View Article and Find Full Text PDFCureus
August 2025
Clinical Microbiology, Prathima Institute of Medical Sciences, Karimnagar, IND.
Since its discovery, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has become the epicenter of public health concern. This was mainly attributed to the complexity of COVID-19 that resulted in variable disease progression with some developing asymptomatic infections, some suffering mild to moderate infections that resolved without the need for hospitalizations, and a few infected persons developing severe infections that required intensive care unit (ICU) admission and mechanical ventilation. The COVID-19 pandemic spread globally, affecting billions of people and killing millions.
View Article and Find Full Text PDFMov Disord Clin Pract
September 2025
Neurology Unit, Neuromotor and Rehabilitation Department, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
Background: GBA1 variants are the major genetic risk factor for Parkinson's Disease (PD) and account for 5-30% of PD cases depending on the population and age at onset of the disease.
Objectives: The aim of this study was to assess whether Artificial Intelligence (AI) could predict GBA1-mutated genotype in PD (GBA1-PD). Particularly, the main objective was to identify a Machine Learning (ML) model capable of accurately providing a pre-test estimate of GBA1-mutated status, relying on the clinical and demographic variables with the highest predictive value.