SynthesisCells, tissues, organs2021
Conservation of Epithelial-to-Mesenchymal Transition Process in Neural Crest Cells and Metastatic Cancer.
Synthesis in Cells, tissues, organs, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 11 citations in OpenAlex.
- The Redox-Adhesion-Exosome (RAX) Hub in Cancer: Lipid Peroxidation-Driven EMT Plasticity and Ferroptosis Defense with HNE/MDA Signaling and Lipidomic Perspectives.Antioxidants (Basel, Switzerland) · 2025Review
- Unraveling the Hippo pathway: YAP/TAZ as central players in cancer metastasis and drug resistance.EXCLI journal · 2025Review
- Targeting Hippo-YAP/TAZ signaling pathway: an updated review demonstrating the therapeutic potential of key plant derived anticancer compounds.Frontiers in pharmacology · 2025Review
- Craniofacial Development Is Fine-Tuned by Sox2.Genes · 2023Review
- Article
- TWIST1 interacts with β/δ-catenins during neural tube development and regulates fate transition in cranial neural crest cells.Development (Cambridge, England) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Epithelial to mesenchymal transition (EMT) is a highly conserved cellular process in several species, from worms to humans. EMT plays a fundamental role in early embryogenesis, wound healing, and cancer metastasis. For neural crest cell (NCC) development, EMT typically results in forming a migratory and potent cell population that generates a wide variety of cell and tissue, including cartilage, bone, connective tissue, endocrine cells, neurons, and glia amongst many others. The degree of conservation between the signaling pathways that regulate EMT during development and metastatic cancer (MC) has not been fully established, despite ample studies. This systematic review and meta-analysis dissects the major signaling pathways involved in EMT of NCC development and MC to unravel the similarities and differences. While the FGF, TGFβ/BMP, SHH, and NOTCH pathways have been rigorously investigated in both systems, the EGF, IGF, HIPPO, Factor Receptor Superfamily, and their intracellular signaling cascades need to be the focus of future NCC studies. In general, meta-analyses of the associated signaling pathways show a significant number of overlapping genes (particularly ligands, transcription regulators, and targeted cadherins) involved in each signaling pathway of both systems without stratification by body segments and cancer type. Lack of stratification makes it difficult to meaningfully evaluate the intracellular downstream effectors of each signaling pathway. Finally, pediatric neuroblastoma and melanoma are NCC-derived malignancies, which emphasize the importance of uncovering the EMT events that convert NCC into treatment-resistant malignant cells.
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.