ArticleBreast cancer research : BCR2020
Superior breast cancer metastasis risk stratification using an epithelial-mesenchymal-amoeboid transition gene signature.
Article in Breast cancer research : BCR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 22 citations in OpenAlex.
- Transcriptional Heterogeneity Underlying Cancer Cell Migration Converges on Shared Regulatory Programs.Genes · 2026Article
- Epithelial-mesenchymal transition in carcinoma: navigating phenotypic states to target resistance and metastasis.Cancer metastasis reviews · 2026Review
- Circulating tumor cell-derived lines exhibit an amoeboid mode of migration.Scientific reports · 2026Article
- Therapy as a State-Generator: Dynamic Phenotypic Landscapes and Adaptive Stress Circuits in Chemotherapy Resistance of Breast Cancer.Antioxidants (Basel, Switzerland) · 2026Review
- Unbiased characterization of COVID-19 endotypes leads to prognostication of high-risk individuals using routine blood tests.Communications medicine · 2026Article
- Biophysical modeling identifies an optimal hybrid amoeboid-mesenchymal mechanism for maximal T cell migration speeds.Cell reports · 2026Article
- Biophysical modeling identifies an optimal hybrid amoeboid-mesenchymal mechanism for maximal T cell migration speeds.bioRxiv : the preprint server for biology · 2025Article
- The first embryo, the origin of cancer and animal phylogeny. V. Cancer stem cells as the unifying biomechanical principle between embryology and oncology.Mechanobiology in medicine · 2025Review
- How important is EMT for cancer metastasis?PLoS biology · 2024Article
- The first embryo, the origin of cancer and animal phylogeny. II. The neoplastic process as an evolutionary engine.Journal of biosciences · 2024Article
- Tumour invasion and dissemination.Biochemical Society transactions · 2022Review
- A tEMTing target? Clinical and experimental evidence for epithelial-mesenchymal transition in the progression of cutaneous squamous cell carcinoma (a scoping systematic review).Discover oncology · 2022Article
- Distinct Gene Expression Profiles of Matched Primary and Metastatic Triple-Negative Breast Cancers.Cancers · 2022Article
- RhoA-ROCK competes with YAP to regulate amoeboid breast cancer cell migration in response to lymphatic-like flow.FASEB bioAdvances · 2022Article
- Cancer cell metabolic plasticity in migration and metastasis.Clinical & experimental metastasis · 2021Review
- Inference of phenotype-relevant transcriptional regulatory networks elucidates cancer type-specific regulatory mechanisms in a pan-cancer study.NPJ systems biology and applications · 2021Article
- Therapeutically Targeting Cancers That Overexpress FOXC1: A Transcriptional Driver of Cell Plasticity, Partial EMT, and Cancer Metastasis.Frontiers in oncology · 2021Review
- Sustained Inflammatory Signalling through Stat1/Stat2/IRF9 Is Associated with Amoeboid Phenotype of Melanoma Cells.Cancers · 2020Article
- Superior breast cancer metastasis risk stratification using an epithelial-mesenchymal-amoeboid transition gene signature.Breast cancer research : BCR · 2020Article
- Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform.PLoS biology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 4 countries.
Funding
Abstract
backgroundCancer cells are known to display varying degrees of metastatic propensity, but the molecular basis underlying such heterogeneity remains unclear. Our aims in this study were to (i) elucidate prognostic subtypes in primary tumors based on an epithelial-to-mesenchymal-to-amoeboid transition (EMAT) continuum that captures the heterogeneity of metastatic propensity and (ii) to more comprehensively define biologically informed subtypes predictive of breast cancer metastasis and survival in lymph node-negative (LNN) patients.
methodsWe constructed a novel metastasis biology-based gene signature (EMAT) derived exclusively from cancer cells induced to undergo either epithelial-to-mesenchymal transition (EMT) or mesenchymal-to-amoeboid transition (MAT) to gauge their metastatic potential. Genome-wide gene expression data obtained from 913 primary tumors of lymph node-negative breast cancer (LNNBC) patients were analyzed. EMAT gene signature-based prognostic stratification of patients was performed to identify biologically relevant subtypes associated with distinct metastatic propensity.
resultsDelineated EMAT subtypes display a biologic range from less stem-like to more stem-like cell states and from less invasive to more invasive modes of cancer progression. Consideration of EMAT subtypes in combination with standard clinical parameters significantly improved survival prediction. EMAT subtypes outperformed prognosis accuracy of receptor or PAM50-based BC intrinsic subtypes even after adjusting for treatment variables in 3 independent, LNNBC cohorts including a treatment-naïve patient cohort.
conclusionsEMAT classification is a biologically informed method that provides prognostic information beyond that which can be provided by traditional cancer staging or PAM50 molecular subtype status and may improve metastasis risk assessment in early stage, LNNBC patients, who may otherwise be perceived to be at low metastasis risk.
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.