Biology subjects

McNamara, S.

Publications and source records attributed to McNamara, S..

2 recordsLinked to original sources

bioRxiv2021

Dual G9A and EZH2 inhibition stimulates an anti-tumour immune response in ovarian high-grade serous carcinoma

Ovarian high-grade serous carcinoma (HGSC) prognosis correlates directly with presence of intratumoral lymphocytes. However, cancer immunotherapy has yet to achieve meaningful survival benefit in patients with HGSC. Epigenetic silencing of immunostimulatory genes is implicated in immune evasion in HGSC and re-expression of these genes could promote tumour immune clearance. We discovered that simultaneous inhibition of the histone methyltransferases G9A and EZH2 activates the CXCL10-CXCR3 axis and increases homing of intratumoral effector lymphocytes and natural killer cells whilst suppressing tumour-promoting FoxP3+ CD4 T cells. The dual G9A/EZH2 inhibitor HKMTI-1-005 induced chromatin changes that resulted in the transcriptional activation of immunostimulatory gene networks, including the re-expression of elements of the ERV-K endogenous retroviral family. Importantly, treatment with HKMTI-1-005 improved the survival of mice bearing Trp53-/-null ID8 ovarian tumours and resulted in tumour burden reduction. These results indicate that inhibiting G9A and EZH2 in ovarian cancer alters the immune microenvironment and reduces tumour growth and therefore positions dual inhibition of G9A/EZH2 as a strategy for clinical development. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/443282v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@4c4323org.highwire.dtl.DTLVardef@cbd6fdorg.highwire.dtl.DTLVardef@8fb5e5org.highwire.dtl.DTLVardef@eef9c8_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2019

GEO2RNAseq: An easy-to-use R pipeline for complete pre-processing of RNA-seq data

In transcriptomics, the study of the total set of RNAs transcribed by the cell, RNA sequencing (RNA-seq) has become the standard tool for analysing gene expression. The primary goal is the detection of genes whose expression changes significantly between two or more conditions, either for a single species or for two or more interacting species at the same time (dual RNA-seq, triple RNA-seq and so forth). The analysis of RNA-seq can be simplified as many steps of the data pre-processing can be standardised in a pipeline.\n\nIn this publication we present the \"GEO2RNAseq\" pipeline for complete, quick and concurrent pre-processing of single, dual, and triple RNA-seq data. It covers all pre-processing steps starting from raw sequencing data to the analysis of differentially expressed genes, including various tables and figures to report intermediate and final results. Raw data may be provided in FASTQ format or can be downloaded automatically from the Gene Expression Omnibus repository. GEO2RNAseq strongly incorporates experimental as well as computational metadata. GEO2RNAseq is implemented in R, lightweight, easy to install via Conda and easy to use, but still very flexible through using modular programming and offering many extensions and alternative workflows.\n\nGEO2RNAseq is publicly available at https://anaconda.org/xentrics/r-geo2rnaseq and https://bitbucket.org/thomas_wolf/geo2rnaseq/overview, including source code, installation instruction, and comprehensive package documentation.

bioinformatics↗