ArticlePLoS computational biology2018
Model-driven discovery of long-chain fatty acid metabolic reprogramming in heterogeneous prostate cancer cells.
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 18 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
18 citing papers in PubMed, 36 citations in OpenAlex.
- Effects of Docosahexaenoic Acid on Prostate Cancer.Journal of xenobiotics · 2025Review
- Targeting Prostate Cancer Metabolism Through Transcriptional and Epigenetic Modulation: A Multi-Target Approach to Therapeutic Innovation.International journal of molecular sciences · 2025Review
- A Multi-Level Systems Biology Analysis of Aldrin's Metabolic Effects on Prostate Cancer Cells.Proteomes · 2023Article
- A Dual Role for FADD in Human Precursor T-Cell Neoplasms.International journal of molecular sciences · 2022Article
- Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer.Frontiers in oncology · 2022Review
- [EJNMMI research · 2021Article
- Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development.Biomedicines · 2021Article
- Cysteine and Folate Metabolism Are Targetable Vulnerabilities of Metastatic Colorectal Cancer.Cancers · 2021Article
- Genome-scale integration of transcriptome and metabolome unveils squalene synthase and dihydrofolate reductase as targets against AML cells resistant to chemotherapy.Computational and structural biotechnology journal · 2021Article
- Functional genetic variant of HSD17B12 in the fatty acid biosynthesis pathway predicts the outcome of colorectal cancer.Journal of cellular and molecular medicine · 2020Article
- Low Entropy Sub-Networks Prevent the Integration of Metabolomic and Transcriptomic Data.Entropy (Basel, Switzerland) · 2020Article
- Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis.Metabolites · 2020Review
- Towards the routine use of in silico screenings for drug discovery using metabolic modelling.Biochemical Society transactions · 2020Review
- Stoichiometric gene-to-reaction associations enhance model-driven analysis performance: Metabolic response to chronic exposure to Aldrin in prostate cancer.BMC genomics · 2019Article
- Current status and applications of genome-scale metabolic models.Genome biology · 2019Review
- Discovery of therapeutic agents for prostate cancer using genome-scale metabolic modeling and drug repositioning.EBioMedicine · 2019Article
- Drug Repositioning for Effective Prostate Cancer Treatment.Frontiers in physiology · 2018Review
- Development Of A Three-Gene Prognostic Signature For Hepatitis B Virus Associated Hepatocellular Carcinoma Based On Integrated Transcriptomic Analysis.Journal of Cancer · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epithelial-mesenchymal-transition promotes intra-tumoral heterogeneity, by enhancing tumor cell invasiveness and promoting drug resistance. We integrated transcriptomic data for two clonal subpopulations from a prostate cancer cell line (PC-3) into a genome-scale metabolic network model to explore their metabolic differences and potential vulnerabilities. In this dual cell model, PC-3/S cells express Epithelial-mesenchymal-transition markers and display high invasiveness and low metastatic potential, while PC-3/M cells present the opposite phenotype and higher proliferative rate. Model-driven analysis and experimental validations unveiled a marked metabolic reprogramming in long-chain fatty acids metabolism. While PC-3/M cells showed an enhanced entry of long-chain fatty acids into the mitochondria, PC-3/S cells used long-chain fatty acids as precursors of eicosanoid metabolism. We suggest that this metabolic reprogramming endows PC-3/M cells with augmented energy metabolism for fast proliferation and PC-3/S cells with increased eicosanoid production impacting angiogenesis, cell adhesion and invasion. PC-3/S metabolism also promotes the accumulation of docosahexaenoic acid, a long-chain fatty acid with antiproliferative effects. The potential therapeutic significance of our model was supported by a differential sensitivity of PC-3/M cells to etomoxir, an inhibitor of long-chain fatty acid transport to the mitochondria.
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.