AIMC Topic: Apoptosis
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Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth.
Cell communication and signaling : CCS
Dec 5, 2024
BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long durational erlotinib treatment of non-small cell lung cancer (NSCLC) patients, leading to drug resistance and disease progression. Identification of new selec...
Machine learning-based analysis of programmed cell death types and key genes in intervertebral disc degeneration.
Apoptosis : an international journal on programmed cell death
Dec 4, 2024
Intervertebral disc degeneration (IVDD) is intricately associated with various forms of programmed cell death (PCD). Identifying key PCD types and associated genes is essential for understanding the molecular mechanisms underlying IVDD and discoverin...
The diagnostic value investigation of programmed cell death genes in heart failure.
BMC cardiovascular disorders
Nov 22, 2024
BACKGROUND: We aimed to identify the potential diagnostic markers and associated molecular mechanisms based on programmed cell death (PCD)-related genes in patients with heart failure (HF).
Plasminogen Activator Inhibitor 1
Gene Expression Regulation
Apoptosis Regulatory Proteins
Apoptosis
Predictive Value of Tests
Genetic Markers
Heart Failure
Reproducibility of Results
Gene Expression Profiling
Transcriptome
Case-Control Studies
Protein Interaction Maps
Gene Regulatory Networks
Nomograms
Databases, Genetic
Humans
Machine Learning
Comprehensive analysis and validation of TP73 as a biomarker for calcium oxalate nephrolithiasis using machine learning and in vivo and in vitro experiments.
Urolithiasis
Nov 16, 2024
Calcium oxalate (CaOx) nephrolithiasis constitutes approximately 75% of nephrolithiasis cases, resulting from the supersaturation and deposition of CaOx crystals in renal tissues. Despite their prevalence, precise biomarkers for CaOx nephrolithiasis ...
Comprehensive multi-omics analysis identifies chromatin regulator-related signatures and TFF1 as a therapeutic target in lung adenocarcinoma through a 429-combination machine learning approach.
Frontiers in immunology
Oct 30, 2024
INTRODUCTION: Lung cancer is a leading cause of cancer-related deaths, with its incidence continuing to rise. Chromatin remodeling, a crucial process in gene expression regulation, plays a significant role in the development and progression of malign...
Integrating multi-omics and machine learning survival frameworks to build a prognostic model based on immune function and cell death patterns in a lung adenocarcinoma cohort.
Frontiers in immunology
Sep 13, 2024
INTRODUCTION: The programmed cell death (PCD) plays a key role in the development and progression of lung adenocarcinoma. In addition, immune-related genes also play a crucial role in cancer progression and patient prognosis. However, further studies...
Accurately identifying positive and negative regulation of apoptosis using fusion features and machine learning methods.
Computational biology and chemistry
Sep 11, 2024
Apoptotic proteins play a crucial role in the apoptosis process, ensuring a balance between cell proliferation and death. Thus, further elucidating the regulatory mechanisms of apoptosis will enhance our understanding of their functions. However, the...
A prognostic biomarker of disulfidptosis constructed by machine learning framework model as potential reporters of pancreatic adenocarcinoma.
Cellular signalling
Aug 28, 2024
BACKGROUND: Pancreatic adenocarcinoma (PAAD), known for its high lethality, has not been thoroughly explored in terms of its mechanisms and patterns of immune infiltration. Disulfidptosis, a newly identified mode of cell death, is likely associated w...
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...
Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns.
Scientific reports
Aug 2, 2024
Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant programmed cell death (PCD) implicated in AML pathogenesis suggests PCD-related signatures could serve as biomarkers to predict clinical outcomes and...
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