Biology subjects

Jakobsen, S. T.

Publications and source records attributed to Jakobsen, S. T..

3 recordsLinked to original sources

bioRxiv2023

Propionate reinforces epithelial identity and reduces aggressiveness of non-small cell lung carcinoma via chromatin remodelling

Epithelial to mesenchymal transition (EMT) is a developmental cellular program driving metastasis and chemo-resistance in cancer, but its pharmacological treatment has been so far challenging. Targeting deregulated metabolic processes in cancer is emerging as a realistic therapeutic strategy. Here, we used an EMT-focussed integrative functional genomic approach and identified negative association of the short-chain fatty acids propionate and butanoate with EMT in non-small cell lung cancer (NSCLC) patients. Strikingly, in vitro treatment of lung cancer cell lines with propionate reinforced the epithelial transcriptional program promoting cell adhesion and reverting the aggressive and chemoresistant EMT phenotype. Propionate treatment reduced cells metastatic ability in nude mice and limited lymph nodal spread in a genetic NSCLC mouse model. Further analyses indicated chromatin remodeling via H3K27 acetylation (p300-mediated) as the mechanism shifting the EMT balance towards epithelial state upon propionate. Propionate administration could be tested in the clinic for reducing NSCLC aggressiveness. HighlightsAn EMT-centric investigation of metabolic processes in a comprehensive lung cancer transcriptome profiles identified negative associations between EMT and SCFAs (propionate and butyrate) Propionate enhances the epithelial features both at the molecular and cellular levels Pre-treatment of cells with propionate inhibits EMT associated processes including migration and sensitizes the cells to chemotherapeutic drug cisplatin Oral administration of propionate inhibits EMT-mediated lung colonization ability of NSCLC cells, and lymph node metastasis in a genetic mouse NSCLC model Molecular mechanistic investigation of propionate revealed chromatin remodelling through p300-mediated histone acetylation in E-cadherin gene regulation along with epithelial features reinforcement

cancer biology↗

bioRxiv2023

MYC enhancer invasion promotes prognostic cancer type-specific gene programs through an epigenetic switch

The transcription factor MYC is overexpressed in most cancers, where it drives multiple hallmarks of cancer progression. MYC is known to promote oncogenic transcription by binding to active promoters. In addition, MYC has also been shown to invade distal enhancers when expressed at oncogenic levels, but this enhancer binding has been proposed to have low gene-regulatory potential. Here, we demonstrate that MYC enhancer binding directly promotes cancer type-specific gene programs predictive of poor patient prognosis. MYC induces transcription of enhancer RNA through recruitment of RNAPII, rather than regulating RNAPII pause-release as is the case at promoters. This is mediated by MYC-induced H3K9 demethylation by KDM3A and acetylation by GCN5, leading to enhancer-specific BRD4 recruitment through its bromodomains, which facilitates RNAPII recruitment. Thus, we propose that MYC drives prognostic cancer type-specific gene programs by promoting RNAPII recruitment to enhancers through induction of an epigenetic switch.

genomics↗

bioRxiv2019

Gene network reconstruction using single cell transcriptomic data reveals key factors for embryonic stem cell differentiation

Accurate prediction of gene regulatory rules is important towards understanding of cellular processes. Existing computational algorithms devised for bulk transcriptomics typically require a large number of time points to infer gene regulatory networks (GRNs), are applicable for a small number of genes, and fail to detect potential causal relationships effectively. Here, we propose a novel approach TENET to reconstruct GRNs from single cell RNA sequencing (scRNAseq) datasets. Employing transfer entropy (TE) to measure the amount of causal relationships between genes, TENET predicts large-scale gene regulatory cascades/relationships from scRNAseq data. TENET showed better performance than other GRN reconstructors, in identifying key regulators from public datasets. Specifically from scRNAseq, TENET identified key transcriptional factors in embryonic stem cells (ESCs) and during direct cardiomyocytes reprogramming, where other predictors failed. We further demonstrate that known target genes have significantly higher TE values, and TENET predicted higher TE genes were more influenced by the perturbation of their regulator. Using TENET, we identified and validated that Nme2 is a culture condition specific stem cell factor. These results indicate that TENET is uniquely capable of identifying key regulators from scRNAseq data. Key PointsO_LITENET measures putative causal relationships between genes using transfer entropy. C_LIO_LITENET shows outstanding performance in identifying key regulators compared to existing methods. C_LIO_LITENET can reveal previously uncharacterized regulators. C_LI

bioinformatics↗