Retinoic acid and androgen receptors combine to achieve tissue specific control of human prostatic transglutaminase expression: a novel regulatory network with broader significance

In the human prostate, expression of prostate-specific genes is known to be directly regulated by the androgen–induced stimulation of the androgen receptor (AR). However, less is known about the expression control of the prostate-restricted TGM4 (hTGP) gene. In the present study we demonstrate that the regulation of the hTGP gene depends mainly on retinoic acid (RA). We provide evidence that the retinoic acid receptor gamma (RAR-G) plays a major role in the regulation of the hTGP gene and that presence of the AR, but not its transcriptional transactivation activity, is critical for hTGP transcription. RA and androgen responsive elements (RARE and ARE) were mapped to the hTGP promoter by chromatin immunoprecipitation (ChIP), which also indicated that the active ARE and RARE sites were adjacent, suggesting that the antagonistic effect of androgen and RA is related to the relative position of binding sites. Publicly available AR and RAR ChIP-seq data was used to find gene potentially regulated by AR and RAR. Four of these genes (CDCA7L, CDK6, BTG1 and SAMD3) were tested for RAR and AR binding and two of them (CDCA7L and CDK6) proved to be antagonistically regulated by androgens and RA confirming that this regulation is not particular of hTGP

Prediction of clinical outcome in glioblastoma using a biologically relevant nine-microRNA signature

Background Glioblastoma is the most aggressive primary brain tumor, and is associated with a very poor prognosis. In this study we investigated the potential of microRNA expression profiles to predict survival in this challenging disease. Methods MicroRNA and mRNA expression data from glioblastoma (n = 475) and grade II and III glioma (n = 178) were accessed from The Cancer Genome Atlas. LASSO regression models were used to identify a prognostic microRNA signature. Functionally relevant targets of microRNAs were determined using microRNA target prediction, experimental validation and correlation of microRNA and mRNA expression data. Results A 9-microRNA prognostic signature was identified which stratified patients into risk groups strongly associated with survival (p = 2.26e−09), significant in all glioblastoma subtypes except the non-G-CIMP proneural group. The statistical significance of the microRNA signature was higher than MGMT methylation in temozolomide treated tumors. The 9-microRNA risk score was validated in an independent dataset (p = 4.50e−02) and also stratified patients into high- and low-risk groups in lower grade glioma (p = 5.20e−03). The majority of the 9 microRNAs have been previously linked to glioblastoma biology or treatment response. Integration of the expression patterns of predicted microRNA targets revealed a number of relevant microRNA/target pairs, which were validated in cell lines. Conclusions We have identified a novel, biologically relevant microRNA signature that stratifies high- and low-risk patients in glioblastoma. MicroRNA/mRNA interactions identified within the signature point to novel regulatory networks. This is the first study to formulate a survival risk score for glioblastoma which consists of microRNAs associated with glioblastoma biology and/or treatment response, indicating a functionally relevant signatur

Gene expression profiling of human prostate cancer stem cells reveals a pro-inflammatory phenotype and the importance of extracellular matrix interactions

An expression signature of human prostate cancer stem cells identifies 581 differentially expressed genes and suggests that the JAK-STAT pathway and focal adhesion signaling are important

CRISPR activation screen in mice identifies novel membrane proteins enhancing pulmonary metastatic colonisation

Abstract Melanoma represents ~5% of all cutaneous malignancies, yet accounts for the majority of skin cancer deaths due to its propensity to metastasise. To develop new therapies, novel target molecules must to be identified and the accessibility of cell surface proteins makes them attractive targets. Using CRISPR activation technology, we screened a library of guide RNAs targeting membrane protein-encoding genes to identify cell surface molecules whose upregulation enhances the metastatic pulmonary colonisation capabilities of tumour cells in vivo. We show that upregulated expression of the cell surface protein LRRN4CL led to increased pulmonary metastases in mice. Critically, LRRN4CL expression was elevated in melanoma patient samples, with high expression levels correlating with decreased survival. Collectively, our findings uncover an unappreciated role for LRRN4CL in the outcome of melanoma patients and identifies a potential therapeutic target and biomarker.info:eu-repo/semantics/publishe

Combinatorial CRISPR screen identifies fitness effects of gene paralogues.

Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. Our studies reveal the fitness effects of FAM50A/FAM50B in cancer cells

Chemically-induced Neurite-like Outgrowth Reveals Multicellular Network Function in Patient-derived Glioblastoma Cells

Tumor stem cells and malignant multicellular networks have been separately implicated in the therapeutic resistance of Glioblastoma Multiforme (GBM), the most aggressive type of brain cancer in adults. We show that small molecule inhibition of RHO-associated serine/threonine kinase (ROCKi) significantly promoted the outgrowth of neurite-like cell projections in cultures of heterogeneous patient-derived GBM stem-like cells. These projections formed de novo -induced cellular network (iNet) ‘webs’, which regressed after withdrawal of ROCKi. Connected cells within the iNet web exhibited long range calcium signal transmission, and significant lysosomal and mitochondrial trafficking. In contrast to their less-connected vehicle control counterparts, iNet cells remained viable and proliferative after high-dose radiation. These findings demonstrate a link between ROCKi-regulated cell projection dynamics and the formation of radiation-resistant multicellular networks. Our study identifies means to reversibly induce iNet webs ex vivo , and may thereby accelerate future studies into the biology of GBM cellular networks

A Case Matched Gender Comparison Transcriptomic Screen Identifies eIF4E and eIF5 as Potential Prognostic and Tractable Biomarkers in Male Breast Cancer

Purpose: Breast cancer (BC) affects both genders, but is understudied in men. Although still rare, male BC is being diagnosed more frequently. Treatments are wholly informed by clinical studies conducted in women, based on assumptions that underlying biology is similar. Experimental design: A transcriptomic investigation of male and female BC was performed, confirming transcriptomic data in silico. Biomarkers were immunohistochemically assessed in 697 MBCs (n=477, training; n=220, validation set) and quantified in pre- and post-treatment samples from a male BC patient receiving Everolimus and PI3K/mTOR inhibitor. Results: Gender-specific gene expression patterns were identified. eIF transcripts were up-regulated in MBC. eIF4E and eIF5 were negatively prognostic for overall survival alone (Log rank; p=0.013; HR=1.77, 1.12-2.8 and p=0.035; HR=1.68, 1.03-2.74, respectively), or when co-expressed (p=0.01; HR=2.66, 1.26-5.63), confirmed in the validation set. This remained upon multivariate Cox regression analysis (eIF4E p=0.016; HR 2.38 (1.18-4.8), eIF5 p=0.022; HR 2.55 (1.14-5.7); co-expression p=0.001; HR=7.04 (2.22-22.26)). Marked reduction in eIF4E and eIF5 expression was seen post BEZ235/Everolimus, with extended survival. Conclusions: Translational initiation pathway inhibition could be of clinical utility in male BC patients overexpressing eIF4E and eIF5. With mTOR inhibitors which target this pathway now in the clinic, these biomarkers may represent new targets for therapeutic intervention, although further independent validation is required

Phenotype-independent DNA methylation changes in prostate cancer

BACKGROUND: Human prostate cancers display numerous DNA methylation changes compared to normal tissue samples. However, definitive identification of features related to the cells' malignant status has been compromised by the predominance of cells with luminal features in prostate cancers. METHODS: We generated genome-wide DNA methylation profiles of cell subpopulations with basal or luminal features isolated from matched prostate cancer and normal tissue samples. RESULTS: Many frequent DNA methylation changes previously attributed to prostate cancers are here identified as differences between luminal and basal cells in both normal and cancer samples. We also identified changes unique to each of the two cancer subpopulations. Those specific to cancer luminal cells were associated with regulation of metabolic processes, cell proliferation and epithelial development. Within the prostate cancer TCGA dataset, these changes were able to distinguish not only cancers from normal samples, but also organ-confined cancers from those with extraprostatic extensions. Using changes present in both basal and luminal cancer cells, we derived a new 17-CpG prostate cancer signature with high predictive power in the TCGA dataset. CONCLUSIONS: This study demonstrates the importance of comparing phenotypically matched prostate cell populations from normal and cancer tissues to unmask biologically and clinically relevant DNA methylation changes