ReviewJournal of the National Cancer Center2026
Cytoskeletal dynamics in breast cancer: mechanistic insights and therapeutic opportunities.
Review in Journal of the National Cancer Center, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Integrative RNA-Seq and TCGA-BRCA Analyses Highlight the Role of LINC01133 in Triple-Negative Breast Cancer.Biomedicines · 2026Article
- Gene signatures of palmitoylation and fatty acid metabolism predict prognosis and immunotherapy response in breast cancer patients by machine learning, single-cell analysis, and experimental validation.Frontiers in pharmacology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer (BC) progression, metastasis, and therapy resistance are intricately linked to the cytoskeletal dynamics. The cytoskeleton, a central hub of cellular architecture, is composed of three primary filament systems: microtubules (MTs), actin filaments (AFs), and intermediate filaments (IFs). These filaments are not passive scaffolds but active, integrated systems that govern the processes of cell division, invasion, and migration, thereby providing the direct mechanistic basis for tumor growth, metastasis, and therapy resistance. Therefore, this review examines the pivotal roles of MTs, AFs, and IFs in mediating drug resistance by adapting to the breast cancer (BC) microenvironment (BC-ME). This review summarizes recent insights into how key signaling pathways, such as PAKs (p21-activated kinases), FAK (Focal adhesion kinase), and the ARF (ADP-ribosylation factor) signaling, regulate actin dynamics, focal adhesion turnover, and cytoskeletal organization. Furthermore, the review highlights the control of microtubule (MT) assembly and stability by microtubule-associated proteins (MAPs), detailing the distinct contributions of tumor suppressors, such as ATIP3 and Tektins, and oncogenes, including MASTL and Tau. Aberrations in the pathways controlling cytoskeletal dynamics and MAP expression significantly contribute to metastatic potential and resistance to conventional therapies. Emerging therapeutic strategies targeting specific cytoskeletal regulators, including PAKs, FAK, and MASTL inhibitors, are discussed as promising approaches to mitigate resistance and metastasis. Furthermore, targeting ARF has been highlighted as a potential means to sensitize TNBC cells to EGFR inhibitors. Finally, a cytoskeleton dynamics-based 3P medicine approach for breast cancer was discussed. Future perspectives emphasize the development of specific inhibitors, the establishment of robust predictive biomarkers (e.g., ATIP3, TEKT4 variants, Tau levels), the exploitation of vulnerabilities created by MAP alterations, and the rational optimization of combination therapies to overcome resistance and improve BC treatment outcomes, especially in aggressive subtypes like TNBC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.