p53 modeling as a route to mesothelioma patients stratification and novel therapeutic identification

Background Malignant pleural mesothelioma (MPM) is an orphan disease that is difficult to treat using traditional chemotherapy, an approach which has been effective in other types of cancer. Most chemotherapeutics cause DNA damage leading to cell death. Recent discoveries have highlighted a potential role for the p53 tumor suppressor in this disease. Given the pivotal role of p53 in the DNA damage response, here we investigated the predictive power of the p53 interactome model for MPM patients’ stratification. Methods We used bioinformatics approaches including omics type analysis of data from MPM cells and from MPM patients in order to predict which pathways are crucial for patients’ survival. Analysis of the PKT206 model of the p53 network was validated by microarrays from the Mero-14 MPM cell line and RNA-seq data from 71 MPM patients, whilst statistical analysis was used to identify the deregulated pathways and predict therapeutic schemes by linking the affected pathway with the patients’ clinical state. Results In silico simulations demonstrated successful predictions ranging from 52 to 85% depending on the drug, algorithm or sample used for validation. Clinical outcomes of individual patients stratified in three groups and simulation comparisons identified 30 genes that correlated with survival. In patients carrying wild-type p53 either treated or not treated with chemotherapy, FEN1 and MMP2 exhibited the highest inverse correlation, whereas in untreated patients bearing mutated p53, SIAH1 negatively correlated with survival. Numerous repositioned and experimental drugs targeting FEN1 and MMP2 were identified and selected drugs tested. Epinephrine and myricetin, which target FEN1, have shown cytotoxic effect on Mero-14 cells whereas marimastat and batimastat, which target MMP2 demonstrated a modest but significant inhibitory effect on MPM cell migration. Finally, 8 genes displayed correlation with disease stage, which may have diagnostic implications. Conclusions Clinical decisions related to MPM personalized therapy based on individual patients’ genetic profile and previous chemotherapeutic treatment could be reached using computational tools and the predictions reported in this study upon further testing in animal models

Transcriptome-wide study of the role of arginine methylation on E2F1

The transcription factor E2F1 can have diverse phenotypic effects on the cell, from stimulating cell cycle progression and proliferation, to inducing apoptosis. These seemingly opposite effects are regulated by a multiplicity of post-translational modifications. Three sites of arginine methylation have been shown to cause a switch in E2F1 function, with PRMT5 mediated symmetric dimethylation at R111/113 associated with a proliferative outcome and asymmetric dimethylation at R109 by PRMT1 resulting in apoptosis. Importantly, these sites of arginine methylation by PRMT1 or PRMT5 were shown to be mutually exclusive, eliciting an either / or response. Furthermore, a reader for the R111/113Me2s mark was found to be the tudor-domain containing transcription co-activator and RNA binding protein p100-TSN. In this study we have used genome-wide sequencing techniques to explore the role of arginine methylation on E2F1 and identify how it is exerting these diverse effects. We found that, although there were few transcription level changes upon expression of an R111/113K mutant derivative compared to the wild-type expressing cells, these cells exhibited dramatic changes at the RNA isoform level across many E2F1 target genes, including increased levels of proapoptotic isoforms of p73 and BCL-X. Interestingly, the vast majority of these differentially spliced genes did not overlap with the genes showing transcription level changes, suggesting a new role for E2F1 to modulate target gene expression via RNA processing. Furthermore, we discovered that E2F1 can bind to nascent RNA via its interaction with p100-TSN and that this complex is spliceosome associated. Additionally, E2F1 can influence the RNA isoforms of p73 and BCL-X found interacting with p100-TSN. Thus, we present a model suggesting that E2F1 may be directly impacting on RNA processing by aiding assembly of splicing components as transcription occurs

Transcriptome-wide study of the role of arginine methylation on E2F1

The transcription factor E2F1 can have diverse phenotypic effects on the cell, from stimulating cell cycle progression and proliferation, to inducing apoptosis. These seemingly opposite effects are regulated by a multiplicity of post-translational modifications. Three sites of arginine methylation have been shown to cause a switch in E2F1 function, with PRMT5 mediated symmetric dimethylation at R111/113 associated with a proliferative outcome and asymmetric dimethylation at R109 by PRMT1 resulting in apoptosis. Importantly, these sites of arginine methylation by PRMT1 or PRMT5 were shown to be mutually exclusive, eliciting an either / or response. Furthermore, a reader for the R111/113Me2s mark was found to be the tudor-domain containing transcription co-activator and RNA binding protein p100-TSN. In this study we have used genome-wide sequencing techniques to explore the role of arginine methylation on E2F1 and identify how it is exerting these diverse effects. We found that, although there were few transcription level changes upon expression of an R111/113K mutant derivative compared to the wild-type expressing cells, these cells exhibited dramatic changes at the RNA isoform level across many E2F1 target genes, including increased levels of proapoptotic isoforms of p73 and BCL-X. Interestingly, the vast majority of these differentially spliced genes did not overlap with the genes showing transcription level changes, suggesting a new role for E2F1 to modulate target gene expression via RNA processing. Furthermore, we discovered that E2F1 can bind to nascent RNA via its interaction with p100-TSN and that this complex is spliceosome associated. Additionally, E2F1 can influence the RNA isoforms of p73 and BCL-X found interacting with p100-TSN. Thus, we present a model suggesting that E2F1 may be directly impacting on RNA processing by aiding assembly of splicing components as transcription occurs

Post‐translational control of transcription factors: methylation ranks highly

Methylation of lysine and arginine residues on histones has long been known to determine both chromatin structure and gene expression. In recent years, the methylation of non‐histone proteins has emerged as a prevalent modification which impacts on diverse processes such as cell cycle control, DNA repair, senescence, differentiation, apoptosis and tumourigenesis. Many of these non‐histone targets represent transcription factors, cell signalling molecules and tumour suppressor proteins. Evidence now suggests that the dysregulation of methyltransferases, demethylases and reader proteins is involved in the development of many diseases, including cancer, and several of these proteins represent potential therapeutic targets for small molecule compounds, fuelling a recent surge in chemical inhibitor design. Such molecules will greatly help us to understand the role of methylation in both health and disease

Post‐translational control of transcription factors: methylation ranks highly

Methylation of lysine and arginine residues on histones has long been known to determine both chromatin structure and gene expression. In recent years, the methylation of non‐histone proteins has emerged as a prevalent modification which impacts on diverse processes such as cell cycle control, DNA repair, senescence, differentiation, apoptosis and tumourigenesis. Many of these non‐histone targets represent transcription factors, cell signalling molecules and tumour suppressor proteins. Evidence now suggests that the dysregulation of methyltransferases, demethylases and reader proteins is involved in the development of many diseases, including cancer, and several of these proteins represent potential therapeutic targets for small molecule compounds, fuelling a recent surge in chemical inhibitor design. Such molecules will greatly help us to understand the role of methylation in both health and disease