ArticlePLoS computational biology2018
Integration of pan-cancer transcriptomics with RPPA proteomics reveals mechanisms of epithelial-mesenchymal transition.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Suppression of ARID1A associated with decreased CD8 T cells improves cell survival of ovarian clear cell carcinoma.Journal of gynecologic oncology · 2021Pooled it
- Decoding epithelial-mesenchymal transitions with multi-omics.Nature reviews. Genetics · 2026Review
- Selenite modulates phenotype-dependent epithelial-mesenchymal plasticity in pancreatic ductal adenocarcinoma: integrated in vitro analyses and patient-derived ex vivo tissue-slice cultures.Journal of experimental & clinical cancer research : CR · 2026Article
- Antibody reliability influences observed mRNA-protein correlations in tumour samples.Life science alliance · 2023Article
- The NALCN channel regulates metastasis and nonmalignant cell dissemination.Nature genetics · 2022Article
- Deep learning and multi-omics approach to predict drug responses in cancer.BMC bioinformatics · 2022Article
- Pan-sarcoma characterization of lncRNAs in the crosstalk of EMT and tumour immunity identifies distinct clinical outcomes and potential implications for immunotherapy.Cellular and molecular life sciences : CMLS · 2022Article
- Data-driven learning how oncogenic gene expression locally alters heterocellular networks.Nature communications · 2022Article
- PLUS: Predicting cancer metastasis potential based on positive and unlabeled learning.PLoS computational biology · 2022Article
- Pan-cancer quantitation of epithelial-mesenchymal transition dynamics using parallel reaction monitoring-based targeted proteomics approach.Journal of translational medicine · 2022Article
- Review
- Competing Endogenous RNA Networks in the Epithelial to Mesenchymal Transition in Diffuse-Type of Gastric Cancer.Cancers · 2020Review
- Article
- An Unsupervised Strategy for Identifying Epithelial-Mesenchymal Transition State Metrics in Breast Cancer and Melanoma.iScience · 2020Article
- Tumor cell sensitivity to vemurafenib can be predicted from protein expression in a BRAF-V600E basket trial setting.BMC cancer · 2019Article
- Cancer mutational burden is shaped by G4 DNA, replication stress and mitochondrial dysfunction.Progress in biophysics and molecular biology · 2019Article
- Metabolic Plasticity and Epithelial-Mesenchymal Transition.Journal of clinical medicine · 2019Review
- Multi-omics Integration Analysis Robustly Predicts High-Grade Patient Survival and Identifies CPT1B Effect on Fatty Acid Metabolism in Bladder Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019Article
- Identification via Numerical Computation of Transcriptional Determinants of a Cell Phenotype Decision Making.Frontiers in genetics · 2019Article
- Proteomic Technology "Lens" for Epithelial-Mesenchymal Transition Process Identification in Oncology.Analytical cellular pathology (Amsterdam) · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Integrating data from multiple regulatory layers across cancer types could elucidate additional mechanisms of oncogenesis. Using antibody-based protein profiling of 736 cancer cell lines, along with matching transcriptomic data, we show that pan-cancer bimodality in the amounts of mRNA, protein, and protein phosphorylation reveals mechanisms related to the epithelial-mesenchymal transition (EMT). Based on the bimodal expression of E-cadherin, we define an EMT signature consisting of 239 genes, many of which were not previously associated with EMT. By querying gene expression signatures collected from cancer cell lines after small-molecule perturbations, we identify enrichment for histone deacetylase (HDAC) inhibitors as inducers of EMT, and kinase inhibitors as mesenchymal-to-epithelial transition (MET) promoters. Causal modeling of protein-based signaling identifies putative drivers of EMT. In conclusion, integrative analysis of pan-cancer proteomic and transcriptomic data reveals key regulatory mechanisms of oncogenic transformation.
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.