Advancing Breast Cancer Research: Multi-Omics, AI, and Emerging Cellular Mechanisms
A special issue of Cells (ISSN 2073-4409).
Deadline for manuscript submissions: 30 April 2026 | Viewed by 110
Special Issue Editors
2. Department of Developmental & Molecular Biology, Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine, Bronx, NY, USA
Interests: oncology
Interests: human cancers; radiation therapy; cancer biology; breast cancer; lipid metabolism
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Breast cancer remains the leading cause of cancer death in women globally, rising 1% annually. Advances in multi-omics, single-cell, spatial technologies, and AI have explored unique subtypes and uncovered tumor environments. Despite new targeted therapies, challenges like resistance, immune escape, and TNBC treatment gaps drive ongoing research efforts. We welcome original research, reviews, and communications on emerging therapeutic strategies, AI-driven diagnostics, and molecular mechanisms underlying drug resistance, tumor heterogeneity, and immune evasion. Contributions addressing cancer stem cells, cell plasticity, and key signaling pathways are also encouraged to support the development of personalized cancer therapies. Topics of interest include (but are not limited to):
Multi-Omics Biomarkers: Integration of epigenomics, genomics, proteomics, and metabolomics to identify novel diagnostic, prognostic, and predictive biomarkers. Emerging therapeutic strategies: Advances in immunotherapy, targeted therapies, combinatorial therapies, and antibody–drug conjugates (ADCs). Non-invasive liquid biopsy biomarkers: CTC, ctDNA, exosomes, non-coding RNAs in early diagnosis, tumor progression, and treatment. Artificial Intelligence (AI) in Precision Medicine: AI in early detection and prognosis, resolving tumor heterogeneity, subtypes, drug resistance, and immune escape. Immune landscape signatures: Dissecting tumor microenvironment through single-cell and spatial omics to identify prognostic and predictive immune biomarkers and immune evasion, breast cancer subtypes. Non-coding RNAs as diagnostic, prognostic, and predictive biomarkers.
Dr. Rahul Sanawar
Dr. Naoshad Muhammad
Dr. Satheesh Kumar Sengodan
Guest Editors
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Keywords
- breast cancer
- cancer stem cells
- cell plasticity
- immune evasion
- drug resistance
- tumor microenvironment
- non-coding RNAs
- circulating tumor cells (CTC)
- circulating tumor DNA (ctDNA)
- exosomes
- signaling pathways (e.g., PI3K/AKT, MAPK)
- targeted therapy
- immunotherapy
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