AIMC Topic: Cell Line, Tumor
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Bayesian-optimized deep learning for identifying essential genes of mitophagy and fostering therapies to combat drug resistance in human cancers.
Journal of cellular and molecular medicine
Jan 1, 2025
Dysregulated mitophagy is essential for mitochondrial quality control within human cancers. However, identifying hub genes regulating mitophagy and developing mitophagy-based treatments to combat drug resistance remains challenging. Herein, BayeDEM (...
Artificial Intelligence-Guided Identification of IGFBP7 as a Critical Indicator in Lactic Metabolism Determines Immunotherapy Response in Stomach Adenocarcinoma.
Journal of cellular and molecular medicine
Jan 1, 2025
Due to considerable tumour heterogeneity, stomach adenocarcinoma (STAD) has a poor prognosis and varies in response to treatment, making it one of the main causes of cancer-related mortality globally. Recent data point to a significant role for metab...
TPD52 as a Therapeutic Target Identified by Machine Learning Shapes the Immune Microenvironment in Breast Cancer.
Journal of cellular and molecular medicine
Jan 1, 2025
Breast cancer (BRCA) is one of the most common malignancies and a leading cause of cancer-related mortality among women globally. Despite advances in diagnosis and treatment, the heterogeneity of BRCA presents significant challenges for effective man...
Deciphering the Role of SLFN12: A Novel Biomarker for Predicting Immunotherapy Outcomes in Glioma Patients Through Artificial Intelligence.
Journal of cellular and molecular medicine
Dec 1, 2024
Gliomas are the most prevalent form of primary brain tumours. Recently, targeting the PD-1 pathway with immunotherapies has shown promise as a novel glioma treatment. However, not all patients experience long-lasting benefits, underscoring the necess...
DD-PRiSM: a deep learning framework for decomposition and prediction of synergistic drug combinations.
Briefings in bioinformatics
Nov 22, 2024
Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and safety profiles of these therapies remains a significant challenge, primarily because of the complex i...
Unveiling Varied Cell Death Patterns in Lung Adenocarcinoma Prognosis and Immunotherapy Based on Single-Cell Analysis and Machine Learning.
Journal of cellular and molecular medicine
Nov 1, 2024
Programmed cell death (PCD) pathways hold significant influence in the etiology and progression of a variety of cancer forms, particularly offering promising prognostic markers and clues to drug sensitivity for lung adenocarcinoma (LUAD) patients. We...
Model ensembling as a tool to form interpretable multi-omic predictors of cancer pharmacosensitivity.
Briefings in bioinformatics
Sep 23, 2024
Stratification of patients diagnosed with cancer has become a major goal in personalized oncology. One important aspect is the accurate prediction of the response to various drugs. It is expected that the molecular characteristics of the cancer cells...
Identification of novel M2 macrophage-related molecule ATP6V1E1 and its biological role in hepatocellular carcinoma based on machine learning algorithms.
Journal of cellular and molecular medicine
Sep 1, 2024
Hepatocellular carcinoma (HCC) remains the most prevalent form of primary liver cancer, characterized by late detection and suboptimal response to current therapies. The tumour microenvironment, especially the role of M2 macrophages, is pivotal in th...
Multi-task deep latent spaces for cancer survival and drug sensitivity prediction.
Bioinformatics (Oxford, England)
Sep 1, 2024
MOTIVATION: Cancer is a very heterogeneous disease that can be difficult to treat without addressing the specific mechanisms driving tumour progression in a given patient. High-throughput screening and sequencing data from cancer cell-lines has drive...
Exploiting Metabolic Defects in Glioma with Nanoparticle-Encapsulated NAMPT Inhibitors.
Molecular cancer therapeutics
Aug 1, 2024
The treatment of primary central nervous system tumors is challenging due to the blood-brain barrier and complex mutational profiles, which is associated with low survival rates. However, recent studies have identified common mutations in gliomas [is...
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