ArticleNature communications2024
AI-powered omics-based drug pair discovery for pyroptosis therapy targeting triple-negative breast cancer.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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Who cites it
22 citing papers in PubMed.
- Deciphering the rules of regulated cell death subroutines by in silico methods.Journal of advanced research · 2026Review
- The role of artificial intelligence in precision medicine for breast cancer.Discover oncology · 2026Review
- AI-genomics synergy for drug repurposing in breast cancer: an interpretability-driven framework.NPJ genomic medicine · 2026Review
- Structural evolution of carbon frameworks realizes in vitro interfacial transport in metabolically reprogrammed senescent cells for senolysis.Nature communications · 2026Article
- Harnessing pyroptosis in breast cancer therapy: immunological mechanisms and emerging biomaterial strategies.Cell death discovery · 2026Review
- Actinolactomycin fromMolecules (Basel, Switzerland) · 2026Article
- Traditional Chinese Medicine Modernization in Diagnosis and Treatment: Utilizing Artificial Intelligence and Nanotechnology.MedComm · 2026Review
- Article
- Decoding the molecular mechanisms of pyroptosis and its therapeutic development prospects.Frontiers in cell and developmental biology · 2026Review
- Integrating bulk, single-cell, and spatial transcriptomics to identify a novel pyroptosis-related gene signature for predicting prognosis and tumor immune landscape in triple-negative breast cancer.Frontiers in immunology · 2026Article
- Recent Advances and Emerging Directions in Machine Learning-Based Breast Cancer Drug Discovery: A Comprehensive Review.Breast cancer (Dove Medical Press) · 2026Review
- Cracking the code of cancer immunotherapy resistance: emerging roles of pyroptosis and necroptosis.Journal of experimental & clinical cancer research : CR · 2025Review
- Therapeutic targeting of cell death-immune crosstalk in cancer to rewire the tumor immune microenvironment.Molecular cancer · 2025Review
- Nanomedicines for the treatment of genitourinary neoplasms.Materials today. Bio · 2025Review
- Ophthalmic drug discovery and development using artificial intelligence and digital health technologies.NPJ digital medicine · 2025Review
- Programmed Cell Death in Cancer.MedComm · 2025Review
- Emerging Target Discovery Strategies Drive the Decoding of Therapeutic Power of Natural Products and Further Drug Development: A Case Study of Celastrol.Exploration (Beijing, China) · 2025Review
- Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches.Cancer biology & medicine · 2025Review
- Cancer chemoprevention: signaling pathways and strategic approaches.Signal transduction and targeted therapy · 2025Review
- Drug combination discovery assisted by AI and untargeted metabolomics: pamiparib and anlotinib synergistic potentiation for ovarian cancer treatment.Frontiers in pharmacology · 2025Article
Corrections and comments
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Authors and funding
20 authors.
Funding
Abstract
Due to low success rates and long cycles of traditional drug development, the clinical tendency is to apply omics techniques to reveal patient-level disease characteristics and individualized responses to treatment. However, the heterogeneous form of data and uneven distribution of targets make drug discovery and precision medicine a non-trivial task. This study takes pyroptosis therapy for triple-negative breast cancer (TNBC) as a paradigm and uses data mining of a large TNBC cohort and drug databases to establish a biofactor-regulated neural network for rapidly screening and optimizing compound pyroptosis drug pairs. Subsequently, biomimetic nanococrystals are prepared using the preferred combination of mitoxantrone and gambogic acid for rational drug delivery. The unique mechanism of obtained nanococrystals regulating pyroptosis genes through ribosomal stress and triggering pyroptosis cascade immune effects are revealed in TNBC models. In this work, a target omics-based intelligent compound drug discovery framework explores an innovative drug development paradigm, which repurposes existing drugs and enables precise treatment of refractory diseases.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.