AIMC Topic: Gene Expression Regulation, Neoplastic
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Integrating single-cell RNA sequencing, WGCNA, and machine learning to identify key biomarkers in hepatocellular carcinoma.
Scientific reports
Apr 1, 2025
The microarray and single-cell RNA-sequencing (scRNA-seq) datasets of hepatocellular carcinoma (HCC) were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis (W...
Machine learning based intratumor heterogeneity related signature for prognosis and drug sensitivity in breast cancer.
Scientific reports
Mar 28, 2025
Intratumor heterogeneity (ITH) is involved in tumor evolution and drug resistance. Drug sensitivity shows discrepancy in different breast cancer (BRCA) patients due to ITH. The genes mediating ITH in BRCA and their role in predicting prognosis and dr...
Unveiling the power of Treg.Sig: a novel machine-learning derived signature for predicting ICI response in melanoma.
Frontiers in immunology
Mar 28, 2025
BACKGROUND: Although immune checkpoint inhibitor (ICI) represents a significant breakthrough in cancer immunotherapy, only a few patients benefit from it. Given the critical role of Treg cells in ICI treatment resistance, we explored a Treg-associate...
scMalignantFinder distinguishes malignant cells in single-cell and spatial transcriptomics by leveraging cancer signatures.
Communications biology
Mar 27, 2025
Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterizing tumor heterogeneity, yet accurately identifying malignant cells remains challenging. Here, we propose scMalignantFinder, a machine learning tool specifically designed to dis...
Identification of CACNB1 protein as an actionable therapeutic target for hepatocellular carcinoma via metabolic dysfunction analysis in liver diseases: An integrated bioinformatics and machine learning approach for precise therapy.
International journal of biological macromolecules
Mar 25, 2025
In addition to histological evaluation for nonalcoholic fatty liver disease (NAFLD), a comprehensive analysis of the metabolic landscape is urgently needed to categorize patients into distinct subgroups for precise treatment. In this study, a total o...
Identification of prognostic subtypes and the role of FXYD6 in ovarian cancer through multi-omics clustering.
Frontiers in immunology
Mar 18, 2025
BACKGROUND: Ovarian cancer (OC), as a malignant tumor that seriously endangers the lives and health of women, is renowned for its complex tumor heterogeneity. Multi-omics analysis, as an effective method for distinguishing tumor heterogeneity, can mo...
Machine learning reveals glycolytic key gene in gastric cancer prognosis.
Scientific reports
Mar 13, 2025
Glycolysis is recognized as a central metabolic pathway in the neoplastic evolution of gastric cancer, exerting profound effects on the tumor microenvironment and the neoplastic growth trajectory. However, the identification of key glycolytic genes t...
Molecular structure and mechanism of protein MSMB, TPPP3, SPI1: Construction of novel 4 pancreatic cancer-related protein signatures model based on machine learning.
International journal of biological macromolecules
Mar 12, 2025
The high mortality rate of pancreatic cancer is closely related to its inconspicuous early symptoms and difficult diagnosis. In recent years, with the rapid development of proteomics and bioinformatics, the use of machine learning technology to analy...
Development of a MVI associated HCC prognostic model through single cell transcriptomic analysis and 101 machine learning algorithms.
Scientific reports
Mar 7, 2025
Hepatocellular carcinoma (HCC) is an exceedingly aggressive form of cancer that often carries a poor prognosis, especially when it is complicated by the presence of microvascular invasion (MVI). Identifying patients at high risk of MVI is crucial for...
Precision Medicine
Prognosis
Clinical Decision-Making
Biomarkers, Tumor
Humans
Machine Learning
Single-Cell Gene Expression Analysis
Immunotherapy
Gene Expression Regulation, Neoplastic
Treatment Outcome
Risk Assessment
Liver Neoplasms
Carcinoma, Hepatocellular
Microvessels
Immune Checkpoint Proteins
Mutation
Neoplasm Invasiveness
Datasets as Topic
Liver
Kaplan-Meier Estimate
Meta-Analysis as Topic
Breast cancer prediction based on gene expression data using interpretable machine learning techniques.
Scientific reports
Mar 4, 2025
Breast cancer remains a global health burden, with an increase in deaths related to this particular cancer. Accurately predicting and diagnosing breast cancer is important for treatment development and survival of patients. This study aimed to accura...
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