AIMC Topic: Drug Resistance, Neoplasm
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Integrated multi-omics and machine learning reveal a gefitinib resistance signature for prognosis and treatment response in lung adenocarcinoma.
IUBMB life
Nov 29, 2024
Gefitinib resistance (GR) presents a significant challenge in treating lung adenocarcinoma (LUAD), highlighting the need for alternative therapies. This study explores the genetic basis of GR to improve prediction, prevention, and treatment strategie...
Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning.
Nature communications
Nov 29, 2024
Integrating diverse types of biological data is essential for a holistic understanding of cancer biology, yet it remains challenging due to data heterogeneity, complexity, and sparsity. Addressing this, our study introduces an unsupervised deep learn...
Integrating machine learning-predicted circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) in metastatic breast cancer: A proof of principle study on endocrine resistance profiling.
Cancer letters
Nov 20, 2024
The study explored endocrine resistance by leveraging machine learning to establish the prognostic stratification of predicted Circulating tumor cells (CTCs), assessing its integration with circulating tumor DNA (ctDNA) features and contextually eval...
Using bioinformatics and artificial intelligence to map the cyclin-dependent kinase 4/6 inhibitor biomarker landscape in breast cancer.
Future oncology (London, England)
Nov 12, 2024
A cyclin-dependent kinase 4/6 (CDK4/6) inhibitor combined with endocrine therapy is the standard-of-care for patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative advanced breast cancer. However, not all patients r...
Deep learning-based automatic image classification of oral cancer cells acquiring chemoresistance in vitro.
PloS one
Nov 1, 2024
Cell shape reflects the spatial configuration resulting from the equilibrium of cellular and environmental signals and is considered a highly relevant indicator of its function and biological properties. For cancer cells, various physiological and en...
Integrating machine learning and multi-omics analysis to develop an asparagine metabolism immunity index for improving clinical outcome and drug sensitivity in lung adenocarcinoma.
Immunologic research
Sep 25, 2024
Lung adenocarcinoma (LUAD) is a malignancy affecting the respiratory system. Most patients are diagnosed with advanced or metastatic lung cancer due to the fact that most of their clinical symptoms are insidious, resulting in a bleak prognosis. Given...
Machine learning-based integration develops a multiple programmed cell death signature for predicting the clinical outcome and drug sensitivity in colorectal cancer.
Anti-cancer drugs
Aug 9, 2024
Tumorigenesis and treatment are closely associated with various programmed cell death (PCD) patterns. However, the coregulatory role of multiple PCD patterns in colorectal cancer (CRC) remains unknown. In this study, we developed a multiple PCD index...
Artificial Intelligence-Driven Multiomics Network Analysis Reveals Resistance Mechanisms in Oral Cancer.
International dental journal
Aug 2, 2024
Comprehensive Bioinformatics Analysis and Machine Learning of TTK as a Transhepatic Arterial Chemoembolization Resistance Target in Hepatocellular Carcinoma.
Molecular biotechnology
Jul 2, 2024
Transhepatic arterial chemoembolization (TACE) is the standard treatment for intermediate-stage hepatocellular carcinoma (HCC). However, a significant proportion of patients are non-responders or poor responders to TACE. Therefore, our aim is to iden...
Biomarkers, Tumor
Gene Expression Profiling
Liver Neoplasms
Carcinoma, Hepatocellular
Humans
Machine Learning
Drug Resistance, Neoplasm
Prognosis
Protein Interaction Maps
Chemoembolization, Therapeutic
Computational Biology
Kaplan-Meier Estimate
Gene Expression Regulation, Neoplastic
Cell Cycle Proteins
Databases, Genetic
Artificial intelligence for small molecule anticancer drug discovery.
Expert opinion on drug discovery
Jun 18, 2024
INTRODUCTION: The transition from conventional cytotoxic chemotherapy to targeted cancer therapy with small-molecule anticancer drugs has enhanced treatment outcomes. This approach, which now dominates cancer treatment, has its advantages. Despite th...
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