AIMC Topic: Drug Resistance, Neoplasm
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A robust multiplex-DIA workflow profiles protein turnover regulations associated with cisplatin resistance and aneuploidy.
Nature communications
May 30, 2025
Quantifying protein turnover is fundamental to understanding cellular processes and advancing drug discovery. Multiplex-DIA mass spectrometry (MS), combined with dynamic SILAC labeling (pulse-SILAC, or pSILAC) reliably measures protein turnover and d...
Emerging artificial intelligence-driven precision therapies in tumor drug resistance: recent advances, opportunities, and challenges.
Molecular cancer
Apr 23, 2025
Drug resistance is one of the main reasons for cancer treatment failure, leading to a rapid recurrence/disease progression of the cancer. Recently, artificial intelligence (AI) has empowered physicians to use its powerful data processing and pattern ...
Circumventing glioblastoma resistance to temozolomide through optimal drug combinations designed by systems pharmacology and machine learning.
British journal of pharmacology
Apr 14, 2025
BACKGROUND AND PURPOSE: Glioblastoma (GBM), the most frequent and aggressive brain tumour in adults, is associated with a dismal prognostic despite intensive treatment involving surgery, radiotherapy and temozolomide (TMZ)-based chemotherapy. The ini...
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...
Cancer Drug Sensitivity Prediction Based on Deep Transfer Learning.
International journal of molecular sciences
Mar 10, 2025
In recent years, many approved drugs have been discovered using phenotypic screening, which elaborates the exact mechanisms of action or molecular targets of drugs. Drug susceptibility prediction is an important type of phenotypic screening. Large-sc...
Machine learning identifies clinical tumor mutation landscape pathways of resistance to checkpoint inhibitor therapy in NSCLC.
Journal for immunotherapy of cancer
Mar 3, 2025
BACKGROUND: Immune checkpoint inhibitors (CPIs) have revolutionized cancer therapy for several tumor indications. However, a substantial fraction of patients treated with CPIs derive no benefit or have short-lived responses to CPI therapy. Identifyin...
Multi-omics and single-cell analysis reveals machine learning-based pyrimidine metabolism-related signature in the prognosis of patients with lung adenocarcinoma.
International journal of medical sciences
Feb 18, 2025
Pyrimidine metabolism is a hallmark of tumor metabolic reprogramming, while its significance in the prognostic and therapeutic implications of patients with lung adenocarcinoma (LUAD) still remains unclear. In this study, an integrated framework of...
Single-cell RNA sequencing and machine learning provide candidate drugs against drug-tolerant persister cells in colorectal cancer.
Biochimica et biophysica acta. Molecular basis of disease
Jan 25, 2025
Drug resistance often stems from drug-tolerant persister (DTP) cells in cancer. These cells arise from various lineages and exhibit complex dynamics. However, effectively targeting DTP cells remains challenging. We used single-cell RNA sequencing (sc...
Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer.
Breast cancer research : BCR
Jan 12, 2025
Recent evidence indicates that endocrine resistance in estrogen receptor-positive (ER+) breast cancer is closely correlated with phenotypic characteristics of epithelial-to-mesenchymal transition (EMT). Nonetheless, identifying tumor tissues with a m...
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