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Background: Sentinel lymph node biopsy (SLNB) is crucial for staging and managing melanoma, but selecting patients for SLNB is challenging, with around 80% of procedures yielding negative results. The clinicopathological and gene expression profile model (CP-GEP) was developed to identify low-risk melanoma patients who may forgo SLNB. CP-GEP combines Breslow thickness, patient age, and a gene expression analysis to classify patients as high- or low-risk for nodal metastasis. This study aimed to validate the performance of CP-GEP in a multicenter Danish cohort.
Method: Primary melanoma tissue from 536 T1-T3 patients who had undergone SLNB was retrospectively analyzed using CP-GEP. Results were compared with SLNB status and the Melanoma Institute Australia nomogram (MIA).
Results: T1, T2, and T3 melanomas comprised 32.8%, 46.8%, and 20.3% of cases, respectively. The SLNB positivity rate was 18.1%. Overall, 40.9% was classified as CP-GEP low-risk (NPV 91.3%). Among T1 and T2 subgroups, 72.7% and 35.5% were low-risk, with NPVs of 94.5% and 87.6%, respectively. For 507 patients with MIA scores, CP-GEP identified 42.4% as low-risk (NPV 91.2%) versus 8.1% by MIA (NPV 95.1%).
Conclusion: CP-GEP is a promising tool for supporting deselection of SLNB in melanoma patients, with a potential reduction rate of over 40%.
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http://dx.doi.org/10.1002/jso.70035 | DOI Listing |
Alzheimers Res Ther
September 2025
Department of Neurology, Saarland University, Kirrberger Straße, 66421, Homburg/Saar, Germany.
Background: Alzheimer's disease (AD) patients and animal models exhibit an altered gut microbiome that is associated with pathological changes in the brain. Intestinal miRNA enters bacteria and regulates bacterial metabolism and proliferation. This study aimed to investigate whether the manipulation of miRNA could alter the gut microbiome and AD pathologies.
View Article and Find Full Text PDFEur J Med Res
September 2025
Department of Zoology, Faculty of Science, Ain Shams University, Abbassia, Cairo, 11566, Egypt.
Nuclear receptors (NRs) are a superfamily of ligand-activated transcription factors that regulate gene expression in response to metabolic, hormonal, and environmental signals. These receptors play a critical role in metabolic homeostasis, inflammation, immune function, and disease pathogenesis, positioning them as key therapeutic targets. This review explores the mechanistic roles of NRs such as PPARs, FXR, LXR, and thyroid hormone receptors (THRs) in regulating lipid and glucose metabolism, energy expenditure, cardiovascular health, and neurodegeneration.
View Article and Find Full Text PDFGenome Biol
September 2025
Department of Clinical Pharmacy, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, 90089, USA.
Background: Recent advances in high-throughput sequencing technologies have enabled the collection and sharing of a massive amount of omics data, along with its associated metadata-descriptive information that contextualizes the data, including phenotypic traits and experimental design. Enhancing metadata availability is critical to ensure data reusability and reproducibility and to facilitate novel biomedical discoveries through effective data reuse. Yet, incomplete metadata accompanying public omics data may hinder reproducibility and reusability and limit secondary analyses.
View Article and Find Full Text PDFDiagn Pathol
September 2025
Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Background: Gastric cancer is one of the most common cancers worldwide, with its prognosis influenced by factors such as tumor clinical stage, histological type, and the patient's overall health. Recent studies highlight the critical role of lymphatic endothelial cells (LECs) in the tumor microenvironment. Perturbations in LEC function in gastric cancer, marked by aberrant activation or damage, disrupt lymphatic fluid dynamics and impede immune cell infiltration, thereby modulating tumor progression and patient prognosis.
View Article and Find Full Text PDFGenome Biol
September 2025
Department of Evolutionary Genetics, Max-Planck Institute for Evolutionary Biology, Plön, Germany.
Background: Most RNA-seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier gene expression to investigate whether they provide insights into the underlying biology.
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