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Brenton, J.

Publications and source records attributed to Brenton, J..

8 recordsLinked to original sources

Whole genome sequencing of endometrial cancer identifies novel subgroups, drivers, and actionable alterations

Endometrial cancer (EC) is the most common gynaecological malignancy in high income countries, and is increasing in incidence. While molecular stratification has improved its management, precision care is hampered by incomplete characterization of the EC genome. We address this by analysis of whole genome sequencing (WGS) of 665 ECs generated by the UK Genomics England 100,000 Genome Project (100kGP). 5% of cases were associated with germline pathogenic variants in cancer genes, including BRCA1 which we confirmed predisposes to EC. We identified 107 putative coding driver genes, 35% of which had no prior established role in EC. Novel structural variants included gains of MYCN and loss of its negative regulator NEDD4.1 which were significantly mutually exclusive in copy number (CN) high tumours. Immunogenomic analysis confirmed selection for driver alterations of low immunogenicity based on patient HLA haplotype, and pervasive immune escape through multiple mechanisms. Unsupervised clustering of mutational signatures and genomic alterations identified known and novel molecular subgroups, including a CN-high subset with mutational signatures of homologous recombination deficiency (HRD) and favourable outcome. Independent prognostic value of single nucleotide variant (SNV) burden, CN burden and multiple coding drivers, along with the identification of targetable molecular alterations in over one-third of cases, underscores the promise of WGS for precision medicine in EC.

genomics↗

Sensitizing Immune-Refractory Ovarian Tumors via p53 Mutation-Tailored Immunotherapy

High-grade serous ovarian cancer demonstrates limited responsiveness to immune checkpoint inhibitors, owing in part to immunosuppressive environments shaped by nearly universal p53 aberrations. Utilizing an immunocompetent mouse model and individual p53 mutations, we identified a dependence of the p53-R270H mutation (equivalent of human R273H) on regulatory T cells (Tregs) and the PD-1/PD-L1 axis. Analysis of patient datasets associated R273H with elevated levels of two p53 targets, PD-L1 and amphiregulin (AREG), a Tregs growth factor. In contrast to p53-R172H tumors, where there was limited activity, dual antibody therapy targeting AREG and PD-L1 selectively and effectively inhibited R270H tumors. This involved polarization toward M1 macrophages, infiltration of CD8+ T cells, diminished Ly6G+ neutrophils and downregulation of interleukin-4. In patient-derived R273C organoids, the combination treatment reduced the CD4/CD8 ratio. This study is the first to establish a mutation-tailored therapeutic approach that leverages the capacity of p53 to modulate immunosuppressive mechanisms.

cancer biology↗

Transcriptomic analysis of repeat expansion-ataxias uncovers distinct non-neuronal cell type-specific signatures of disease across the human brain

Hereditary ataxias are a heterogeneous group of neurogenetic conditions characterised by the clinical syndrome of progressive loss of coordination from neurodegeneration of the cerebellum. A commonality across the most prevalent ataxias is the underlying disease mechanism secondary to expansions of short tandem DNA repeats. There is currently an incomplete understanding of the pathogenic mechanisms of these repeat expansion disorders, a core feature of which revolves around RNA-dysregulation. In this study, we used both bulk and single nuclear RNA-sequencing to study post-mortem brain tissue of human donors with a range of repeat-expansion ataxias to reveal further mechanistic insights. We compared post-mortem paired cerebellar and frontal cortex tissue bulk RNA-sequencing data from 23 ataxia patients and 22 sex-, age-matched controls from two brain banks (spinocerebellar ataxia (SCA)1, SCA2, SCA6, SCA7, SCA17, Friedreichs ataxia (FRDA), and 7 cases with unknown molecular diagnoses). We analysed bulk RNA-sequencing data for transcript usage, differential and cell-type-specific expression to transcriptomically profile these diseases. We also generated single nuclear RNA-sequencing data of the cerebellum from donors with SCA1, SCA2, SCA6 and FRDA to decipher changes in cell type proportions in the disease state. Using this approach, we found that: (i) despite the commonalities in the genetics of ataxia, there were components of their transcriptional signatures which were distinct; (ii) there were extensive transcriptional changes evident not only in the cerebellum but also the frontal cortex in ataxia cases; (iii) activation of immune and inflammatory pathways, as well as involvement of non-neuronal cell types was a feature of all ataxias to a lesser or greater extent. This study provides a novel resource to understand the mechanisms of disease in ataxia. Furthermore, taken together, these results highlight immune pathways and the role of non-neuronal cell types as early and potentially important therapeutic targets. These findings provide a map of transcriptomic changes in ataxia to further understanding of the underlying pathogenesis.

neuroscience↗

Network nature of ligand-receptor interactions underlies disease comorbidity in the brain

Neurodegenerative disorders have overlapping symptoms and have high comorbidity rates, but this is not reflected in overlaps of risk genes. We have investigated whether ligand-receptor interactions (LRIs) are a mechanism by which distinct genes associated with disease risk can impact overlapping outcomes. We found that LRIs are likely disrupted in neurological disease and that the ligand-receptor networks associated with neurological diseases have substantial overlaps. Specifically, 96.8% of LRIs associated with disease risk are interconnected in a single LR network. These ligands and receptors are enriched for roles in inflammatory pathways and highlight the role of glia in cross-disease risk. Disruption to this LR network due to disease-associated processes (e.g. differential transcript use, protein misfolding) is likely to contribute to disease progression and risk of comorbidity. Our findings have implications for drug development, as they highlight the potential benefits and risks of pursuing cross-disease drug targets.

neuroscience↗

Pseudogenes limit the identification of novel common transcripts generated by their parent genes

The human genome contains numerous duplicated regions, such as parent-pseudogene pairs, causing sequencing reads to align equally well to either gene. The extent to which this ambiguity complicates transcriptomic analyses is currently unknown. This is concerning as many parent genes have been linked to disease, including GBA1, causally linked to both Parkinsons and Gaucher disease. We find that most of the short sequencing reads that map to GBA1, also map to its pseudogene, GBAP1. Using long-read RNA-sequencing in human brain, where all reads mapped uniquely, we demonstrate significant differences in expression compared to short-read data. We identify novel transcripts from both GBA1 and GBAP1, including protein-coding transcripts that are translated in vitro and detected in proteomic data, but that lack GCase activity. By combining long-read with single-nuclear RNA-sequencing to analyse brain-relevant cell types we demonstrate that transcript expression varies by brain region with cell-type-selectivity. Taken together, these results suggest a non-lysosomal function for both GBA1 and GBAP1 in brain. Finally, we demonstrate that inaccuracies in annotation are widespread among parent genes, with implications for many human diseases.

genetics↗

The genomic landscape of early stage ovarian high grade serous carcinoma

PurposeHigh grade serous carcinoma (HGSC) is the commonest type of ovarian cancer. Nearly all HGSC cases are diagnosed at late stage and it is not clear whether early stage HGSC has unique characteristics compared to late stage tumours. Experimental DesignWe analysed samples from 45 patients with FIGO stage I - IIA HGSC - 40 from the pathology archives of three large UK cancer centres and 5 from the BriTROC-1 study. We performed shallow whole genome sequencing (sWGS) and targeted next generation sequencing to investigate somatic mutations and copy number alterations. We compared results to 51 stage IIIC/IV HGSC patients from the BriTROC-1 study. ResultsThere was no difference in median age between the early stage (median 61.3 years, range 40-84) and late stage (median 62.3 years, range 34-76) patients at diagnosis. TP53 mutations were near-universal (92% early stage, 100% late stage samples) and there were no significant differences in the rates of other somatic mutations, including BRCA1 and BRCA2, or focal copy number alterations between early- and late-stage cohorts. There were also no unique amplifications or deletions in either cohort. However, median ploidy was greater in late stage (median 3.1) than early stage (median 2.0) samples. In addition, there were higher numbers of breakpoints per 10MB and per chromosome arm and higher absolute copy number in late stage than early stage cohorts; early stage samples had longer segment length. Overall copy number signature exposures were significantly different between early and late stage samples with greater signature 3 exposure in early stage and greater signature 4 in late stage. Both simplex plot and unsupervised hierarchical clustering suggested that a subset of late stage samples retain early stage appearances with high signature 3 and co-clustering with the early stage samples ConclusionsThese data suggest that there are no unique mutations or focal copy number alterations in early stage HGSC. However, whole genome duplication is significantly more common in late-stage disease, suggesting evolution during disease progression. However, a subset of late stage HGSC retains early-stage features, which are associated with improved overall survival.

cancer biology↗

Shared heritability and functional enrichment across six solid cancers

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg=0.57, p=4.6x10-8), breast and ovarian cancer (rg=0.24, p=7x10-5), breast and lung cancer (rg=0.18, p=1.5x10-6) and breast and colorectal cancer (rg=0.15, p=1.1x10-4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.

genomics↗

Genetic variability in response to Aβ deposition influences Alzheimer’s risk

Genetic analysis of late-onset Alzheimers disease risk has previously identified a network of largely microglial genes that form a transcriptional network. In transgenic mouse models of amyloid deposition we have previously shown that the expression of many of the mouse orthologs of these genes are co-ordinately up-regulated by amyloid deposition. Here we investigate whether systematic analysis of other members of this mouse amyloid-responsive network predicts other Alzheimers risk loci. This statistical comparison of the mouse amyloid-response network with Alzheimers disease genome-wide association studies identifies 5 other genetic risk loci for the disease (OAS1, CXCL10, LAPTM5, ITGAM and LILRB4). This work suggests that genetic variability in the microglial response to amyloid deposition is a major determinant for Alzheimers risk.\n\nOne Sentence SummaryIdentification of 5 new risk loci for Alzheimers by statistical comparison of mouse A{beta} microglial response with gene-based SNPs from human GWAS

neuroscience↗