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Gene Expression Regulation, Neoplastic

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Unravelling tumour cell diversity and prognostic signatures in cutaneous melanoma through machine learning analysis.

Journal of cellular and molecular medicine Jul 1, 2024
Melanoma, a highly malignant tumour, presents significant challenges due to its cellular heterogeneity, yet research on this aspect in cutaneous melanoma remains limited. In this study, we utilized single-cell data from 92,521 cells to explore the tu...
Cell Line, Tumor Single-Cell Analysis Immunotherapy Gene Expression Regulation, Neoplastic Cell Proliferation Cluster Analysis Melanoma, Cutaneous Malignant Prognosis Melanoma Skin Neoplasms Biomarkers, Tumor Humans Machine Learning
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Deciphering lung adenocarcinoma prognosis and immunotherapy response through an AI-driven stemness-related gene signature.

Journal of cellular and molecular medicine Jul 1, 2024
Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic accuracy is vital for personalised treatment approaches, especially in the context of immunotherapy. In this study, we constructed an artificial intellig...
Transcriptome Cell Line, Tumor Lung Neoplasms Immunotherapy Artificial Intelligence Prognosis Biomarkers, Tumor Gene Expression Profiling Adenocarcinoma of Lung CDC2-CDC28 Kinases Gene Expression Regulation, Neoplastic Cell Proliferation Neoplastic Stem Cells Cell Movement Humans
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Deciphering the tumour microenvironment of clear cell renal cell carcinoma: Prognostic insights from programmed death genes using machine learning.

Journal of cellular and molecular medicine Jul 1, 2024
Clear cell renal cell carcinoma (ccRCC), a prevalent kidney cancer form characterised by its invasiveness and heterogeneity, presents challenges in late-stage prognosis and treatment outcomes. Programmed cell death mechanisms, crucial in eliminating ...
Humans Machine Learning Carcinoma, Renal Cell Single-Cell Analysis Prognosis Gene Expression Regulation, Neoplastic Tumor Microenvironment Apoptosis Biomarkers, Tumor Kidney Neoplasms Gene Expression Profiling
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Integrating machine learning and single-cell analysis to uncover lung adenocarcinoma progression and prognostic biomarkers.

Journal of cellular and molecular medicine Jul 1, 2024
The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (IAC) involves a complex evolution of tumour cell clusters, the mechanisms of which remain largely unknown. By integrating single-cel...
Humans Adenocarcinoma of Lung Machine Learning Single-Cell Analysis Prognosis Lung Neoplasms Tumor Microenvironment Immunotherapy Biomarkers, Tumor Gene Expression Regulation, Neoplastic Disease Progression Gene Expression Profiling
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Advancing lung adenocarcinoma prognosis and immunotherapy prediction with a multi-omics consensus machine learning approach.

Journal of cellular and molecular medicine Jul 1, 2024
Lung adenocarcinoma (LUAD) is a tumour characterized by high tumour heterogeneity. Although there are numerous prognostic and immunotherapeutic options available for LUAD, there is a dearth of precise, individualized treatment plans. We integrated mR...
Humans Machine Learning Prognosis Multiomics Gene Expression Regulation, Neoplastic MicroRNAs Adenocarcinoma of Lung Biomarkers, Tumor Gene Expression Profiling Lung Neoplasms Immunotherapy
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Study of prognostic splicing factors in cancer using machine learning approaches.

Human molecular genetics Jun 21, 2024
Splicing factors (SFs) are the major RNA-binding proteins (RBPs) and key molecules that regulate the splicing of mRNA molecules through binding to mRNAs. The expression of splicing factors is frequently deregulated in different cancer types, causing ...
Humans Machine Learning Prognosis Biomarkers, Tumor Neoplasms Liver Neoplasms Carcinoma, Hepatocellular RNA Splicing Alternative Splicing RNA Splicing Factors Computational Biology RNA, Messenger RNA-Binding Proteins Gene Expression Regulation, Neoplastic
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Unraveling the complexity of the senescence-associated secretory phenotype in adamantinomatous craniopharyngioma using multimodal machine learning analysis.

Neuro-oncology Jun 3, 2024
BACKGROUND: Cellular senescence can have positive and negative effects on the body, including aiding in damage repair and facilitating tumor growth. Adamantinomatous craniopharyngioma (ACP), the most common pediatric sellar/suprasellar brain tumor, p...
Machine Learning Cellular Senescence Craniopharyngioma Phenotype Male Humans Female Child Biomarkers, Tumor Gene Expression Regulation, Neoplastic Pituitary Neoplasms
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Validating linalool as a potential drug for breast cancer treatment based on machine learning and molecular docking.

Drug development research Jun 1, 2024
Breast cancer (BC) is a common cancer for women. This study aims to construct a prognostic risk model of BC and identify prognostic biomarkers through machine learning approaches, and clarify the mechanism by which linalool exerts tumor-suppressive f...
Gene Expression Regulation, Neoplastic Cell Proliferation Apoptosis Acyclic Monoterpenes Breast Neoplasms Humans Molecular Docking Simulation Machine Learning Antineoplastic Agents Prognosis Cell Line, Tumor Female
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Machine learning-based identification of a cell death-related signature associated with prognosis and immune infiltration in glioma.

Journal of cellular and molecular medicine Jun 1, 2024
Accumulating evidence suggests that a wide variety of cell deaths are deeply involved in cancer immunity. However, their roles in glioma have not been explored. We employed a logistic regression model with the shrinkage regularization operator (LASSO...
Myeloid Differentiation Factor 88 Nomograms Glioma Lymphocytes, Tumor-Infiltrating Cell Death Biomarkers, Tumor Brain Neoplasms Gene Expression Profiling Humans Male Transcriptome Machine Learning Middle Aged ROC Curve Prognosis Gene Expression Regulation, Neoplastic Female
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ctGAN: combined transformation of gene expression and survival data with generative adversarial network.

Briefings in bioinformatics May 23, 2024
Recent studies have extensively used deep learning algorithms to analyze gene expression to predict disease diagnosis, treatment effectiveness, and survival outcomes. Survival analysis studies on diseases with high mortality rates, such as cancer, ar...
Deep Learning Female Humans Computational Biology Breast Neoplasms Neural Networks, Computer Gene Expression Regulation, Neoplastic Neoplasms Algorithms Survival Analysis Gene Expression Profiling
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