Search bioRxiv⌕ Search

Biology subjects

Savage, K. I.

Publications and source records attributed to Savage, K. I..

3 recordsLinked to original sources

Chronic loss of STAG2 leads to altered chromatin structure contributing to de-regulated transcription in AML

The cohesin complex plays a major role in folding the human genome into 3D structural domains. Mutations in members of the cohesin complex are known early drivers of myelodysplastic syndromes (MDS) and acute myeloid leukaemia (AML), with STAG2 the most frequently mutated complex member. Here we use functional genomics to investigate the impact of chronic STAG2 loss on three-dimensional genome structure and transcriptional programming in a clinically relevant model of chronic STAG2 loss. The chronic loss of STAG2 led to loss of smaller loop domains and the maintenance/formation of large domains which in turn led to altered genome compartmentalisation. These changes in genome structure were linked with altered gene expression, including deregulation of the HOXA locus and the MAPK signalling pathway, which may contribute to disease development and response to therapy. AUTHOR SUMMARYAcute myeloid leukaemia (AML) and myelodysplastic syndromes (MDS) are clonal malignant diseases that affect the myeloid blood cell lineage. Around 40 different mutations have been identified as being associated with MDS and AML; several mutations effect genes in the cohesin complex particularly STAG2. STAG2 is an X-linked gene that is pivotal to the cohesin complex and the mutations result in a truncated gene and loss of function. We have introduced a clinically relevant truncating mutation into an isogeneic AML model. This has shown that changes in the sizes of loop and domains formed in the genome resulting in appropriate gene compartmentalisations. The associated changes in gene transcription has resulted in deregulation of HOX genes, essential for development and differentiation, and in the MAPK signalling pathway that could a therapeutic target.

cancer biology↗

Topoisomerase II inhibitors induce cGAS-STING dependent inflammation resulting in cytokine induction and immune checkpoint activation

Tumours with genomic instability demonstrate enhanced immunogenicity and potential for response to immune checkpoint blockade (ICB). We previously demonstrated activation of the cGAS-STING pathway following loss of DNA repair, resulting in cytokine induction, lymphocytic infiltration and immune checkpoint activation. Here we explore the role of chemotherapies in inducing this innate immune response, identifying topoisomerase II (topo-II) inhibitors, particularly doxorubicin and epirubicin, as potent inducers of a cGAS-STING dependent interferon response. Mechanistically, topo-II inhibition resulted in significant induction of cytoplasmic DNA and subsequent micronuclei formation, a requirement for efficient cGAS-STING activation and consequent cytokine and immune checkpoint gene induction. Importantly, increased cytokine and immune checkpoint gene expression, as well as increased immune cell infiltration, was also observed in patient derived breast tumour biopsies following topo-II inhibitor-based treatment. Taken together, this study indicates topo-II inhibitors such as doxorubicin, may be best placed to induce immunogenic inflammation, and thereby increase responses to ICB therapies.\n\nSignificanceThis work demonstrates how topo-II inhibitors induce STING-pathway activation, cytokine induction and immune checkpoint protein upregulation in cancer cells and provides a rationale for combining topo-II inhibitors with ICB therapy in early breast cancer.

cancer biology↗

ACE: A Workbench using Evolutionary Genetic Algorithms for analysing association in TCGA Data

Modern methods in generating molecular data have dramatically scaled in recent years, allowing researchers to efficiently acquire large volumes of information. However, this has increased the challenge of recognising interesting patterns within the data. Atlas Correlation Explorer (ACE) is a user-friendly workbench for seeking associations between attributes in the cancer genome atlas (TCGA) database. It allows any combination of clinical and genomic data streams to be selected for searching, and highlights significant correlations within the chosen data. It is based on an evolutionary algorithm which is capable of producing results for very large searches in a short time.

bioinformatics↗