ArticleScientific reports2015
A novel embryonic plasticity gene signature that predicts metastatic competence and clinical outcome.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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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.
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Who cites it
27 citing papers in PubMed, 45 citations in OpenAlex.
- MEF2D-expressing cancer precursors reprogram tissue-resident macrophages to support liver tumorigenesis.Nature cancer · 2025Article
- VEGF-C propagates 'onward' colorectal cancer metastasis from liver to lung.British journal of cancer · 2025Article
- Modeling epithelial-mesenchymal transition in patient-derived breast cancer organoids.Frontiers in oncology · 2024Article
- Stabilizing vimentin phosphorylation inhibits stem-like cell properties and metastasis of hybrid epithelial/mesenchymal carcinomas.Cell reports · 2023Article
- Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer.NPJ breast cancer · 2023Article
- Acetylated HOXB13 Regulated Super Enhancer Genes Define Therapeutic Vulnerabilities of Castration-Resistant Prostate Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022Article
- CCM signaling complex (CSC) couples both classic and non-classic Progesterone receptor signaling.Cell communication and signaling : CCS · 2022Article
- Cellular plasticity in bone metastasis.Bone · 2022Article
- Embryonic Programs in Cancer and Metastasis-Insights From the Mammary Gland.Frontiers in cell and developmental biology · 2022Review
- Transcription Control of Liver Development.Cells · 2021Review
- Lessons from the Embryo: an Unrejected Transplant and a Benign Tumor.Stem cell reviews and reports · 2021Review
- EMTome: a resource for pan-cancer analysis of epithelial-mesenchymal transition genes and signatures.British journal of cancer · 2021Article
- Osteoclasts in Tumor Biology: Metastasis and Epithelial-Mesenchymal-Myeloid Transition.Pathology oncology research : POR · 2021Review
- TRA-1-60-positive/CD45Heliyon · 2020Article
- The Complexities of Metastasis.Cancers · 2019Review
- Proliferation genes in lung development associated with the prognosis of lung adenocarcinoma but not squamous cell carcinoma.Cancer science · 2018Article
- Article
- Opposite feedback from mTORC1 to H-ras and K-ras4B downstream of SREBP1.Scientific reports · 2017Article
- EMT: Present and future in clinical oncology.Molecular oncology · 2017Review
- Transcription Factor Networks derived from Breast Cancer Stem Cells control the immune response in the Basal subtype.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Currently, very few prognosticators accurately predict metastasis in cancer patients. In order to complete the metastatic cascade and successfully colonize distant sites, carcinoma cells undergo dynamic epithelial-mesenchymal-transition (EMT) and its reversal, mesenchymal-epithelial-transition (MET). While EMT-centric signatures correlate with response to therapy, they are unable to predict metastatic outcome. One reason is due to the wide range of transient phenotypes required for a tumor cell to disseminate and recreate a similar histology at distant sites. Since such dynamic cellular processes are also seen during embryo development (epithelial-like epiblast cells undergo transient EMT to generate the mesoderm, which eventually redifferentiates into epithelial tissues by MET), we sought to utilize this unique and highly conserved property of cellular plasticity to predict metastasis. Here we present the identification of a novel prognostic gene expression signature derived from mouse embryonic day 6.5 that is representative of extensive cellular plasticity, and predicts metastatic competence in human breast tumor cells. This signature may thus complement conventional clinical parameters to offer accurate prediction for outcome among multiple classes of breast cancer patients.
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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.