Machine Learning Discoveries of FOXM1-X Synergy in ETC-1922159 Treated Colorectal Cancer Cells

Published: Jan. 1, 2025

Language: Английский

Expression Profile of Twelve Transcripts as a Supporting Tool for the Molecular Characterization of Canine Cutaneous Mast Cell Tumors at Diagnosis: Association with Histological Grading and Clinical Staging

Genes, Journal Year: 2025, Volume and Issue: 16(3), P. 340 - 340

Published: March 14, 2025

Background/Objectives: Mast cell tumors (MCTs) are the second most common malignant neoplasms in dogs. Histopathological grading and clinical staging main tools for estimating biological behavior disease extent; thus, both essential therapeutic decision-making prognostication. However, of MCTs dogs is variable, it sometimes deviates from expectations. In a previous study, we identified 12 transcripts whose expression profile allowed clear distinction between Kiupel low-grade high-grade cutaneous (cMCTs) was associated with prognosis. Building on these findings, this study evaluated predictive potential transcripts’ profiles classifying cMCTs into high-grade. Methods: A logistic regression classifier based able to classify as low- or developed subsequently tested novel dataset 50 have been determined through qPCR. Results: The reaches an accuracy 67% area under receiver operating characteristic curve (AUC) 0.76. Interestingly, molecular classification clearly identifies stage-IV (90% true positive rate). Conclusions: qPCR analysis biomarkers combined machine learning-based might serve tool support cMCT management at diagnosis.

Language: Английский

The oncogenic role of FOXM1 in hepatocellular carcinoma: molecular mechanisms, clinical significance, and therapeutic potentials

Naunyn-Schmiedeberg s Archives of Pharmacology, Journal Year: 2025, Volume and Issue: unknown

Published: April 23, 2025

Language: Английский