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Elliott, D. J.

Publications and source records attributed to Elliott, D. J..

6 recordsLinked to original sources

Siglec-engaging immunosuppressive sialoglycans are upregulated in prostate cancer and are targetable to suppress bone metastasis

Prostate cancer is a leading cause of male cancer-related deaths over the age of 50. New treatment options for prostate cancer are urgently needed, especially for tumours that have spread to bone. Aberrant sialylation holds substantial potential for the discovery of new therapeutic targets but has remained relatively unexplored in the context of prostate cancer, primarily due to the lack of reliable reagents for detecting tumour sialoglycans in clinical tissue. Here, we address this knowledge gap using high-affinity Siglec-based sialoglycan-binding reagents (HYDRAs) to quantify tumour sialoglycans in tissues representing the full clinical heterogeneity of prostate tumours. Using HYDRA immunohistochemistry, we show that sialoglycans that can engage Siglec-3, -7, and -9 are upregulated in primary prostate cancer tissue and sialoglycan ligands for Siglec-7 correlate with prostate cancer bone metastasis and poorer patient prognosis. Analysis of prostate-derived tumours growing in bone reveals Siglec receptors are expressed by immune cells in the bone metastatic tumour microenvironment, suggesting that this axis may play a role in immune cell functions in bone metastatic prostate cancer. Indicating this is clinically actionable, an engineered bisialidase (E-612) can effectively strip Siglec ligands from prostate cancer cells and prolong survival times of mice with bone metastasis. Our findings identify a novel mechanism involving Siglec-engaging sialoglycans in driving the growth of prostate cancer bone metastasis and demonstrate how this axis can be targeted to impede lethal prostate cancer progression.

cancer biology↗

ST3Gal1 synthesis of Siglec ligands mediates anti-tumour immunity in prostate cancer

Immune checkpoint blockade trials have yet to produce a robust anti-cancer response in prostate cancer patients as a monotherapy due to the immunosuppressed prostate cancer tumour immune microenvironment. ST3Gal1 and other sialyltransferases are implicated in cancer and immune suppression by synthesizing sialoglycans, which act as ligands for Siglec receptors. These checkpoints are important for the immune response. However, its unclear how the synthesis of Siglec ligands is regulated, and little is known about the role of sialoglycan-Siglec-axis in prostate cancers evasion of anti-tumour immunity. We report that ST3Gal1 levels negatively correlate with androgen signalling in prostate tumours. Utilising syngeneic mouse models, we demonstrate that ST3Gal1 plays an important role in modulating tumour immune evasion. Using mouse models, patient samples and in vitro models we show that ST3Gal1 synthesises sialoglycans with the capacity to engage the Siglec-7 and Siglec-9 immunoreceptors preventing immune clearance of cancer cells. For the first time we provide evidence of the expression of Siglec-7/9 ligands and their respective immunoreceptors in prostate tumours. Importantly, we show that these interactions can be modulated by enzalutamide and may maintain immune suppression in enzalutamide treated tumours. We conclude that the activity of ST3Gal1 is critical to prostate cancer anti-tumour immunity and provide rationale for the use of glyco-immune checkpoint targeting therapies in advanced prostate cancer.

cancer biology↗

RBMX enables productive RNA processing of ultra-long exons important for genome stability

Previously we showed that the germline-specific RNA binding protein RBMXL2 is essential for male meiosis where it represses cryptic splicing patterns (1). Here we find that its ubiquitously expressed paralog RBMX helps underpin human genome stability by preventing non-productive splicing. In particular, RBMX blocks selection of aberrant splice and polyadenylation sites within some ultra-long exons that would interfere with genes needed for normal replication fork activity. Target exons include within the ETAA1 (Ewings Tumour Associated 1) gene, where RBMX collaborates with its interaction partner Tra2{beta} to enable full-length exon inclusion by blocking selection of an aberrant 3 splice site. Our data reveal a novel group of RNA processing targets potently repressed by RBMX, and help explain why RBMX is associated with gene expression networks in cancer, replication and sensitivity to genotoxic drugs.

molecular biology↗

Androgen-regulated transcription of ESRP2 drives alternative splicing patterns in prostate cancer

Prostate is the most frequent cancer in men. Prostate cancer progression is driven by androgen steroid hormones, and delayed by androgen deprivation therapy (ADT). Androgens control transcription by stimulating androgen receptor (AR) activity, yet also control pre-mRNA splicing through less clear mechanisms. Here we find androgens regulate splicing through AR-mediated transcriptional control of the epithelial-specific splicing regulator ESRP2. Both ESRP2 and its close paralog ESRP1 are highly expressed in primary prostate cancer. Androgen stimulation induces splicing switches in many endogenous ESRP2-controlled mRNA isoforms, including a key splicing switch in the metastatic regulator FLNB which is associated with disease relapse. ESRP2 expression in clinical prostate cancer is repressed by ADT, which may thus inadvertently dampen epithelial splice programmes. Supporting this, FLNB splicing was reciprocally switched by the AR antagonist bicalutamide (Casodex(R)). Our data reveal a new mechanism of splicing control in prostate cancer with important implications for metastatic disease progression.\n\nKey pointsO_LITranscriptional regulation of ESRP2 by the androgen receptor controls splice isoform patterns in prostate cancer cells.\nC_LIO_LISplicing switches regulated by the androgen-ESRP2 axis include a splice isoform in the FLNB gene that is a known metastatic driver.\nC_LIO_LIBoth ESRP1 and ESRP2 are highly expressed in prostate cancer tissue.\nC_LIO_LIEctopic expression of ESRP1 and 2 inhibits prostate cancer cell growth.\nC_LIO_LIBy repressing ESRP2 expression androgen deprivation therapy (ADT) may dampen epithelial splicing programmes to inadvertently prime disease progression towards metastasis.\nC_LI

molecular biology↗

Human iPSC-derived RPE and retinal organoids reveal impaired alternative splicing of genes involved in pre-mRNA splicing in PRPF31 autosomal dominant retinitis pigmentosa

Mutations in pre-mRNA processing factors (PRPFs) cause 40% of autosomal dominant retinitis pigmentosa (RP), but it is unclear why mutations in ubiquitously expressed PRPFs cause retinal disease. To understand the molecular basis of this phenotype, we have generated RP type 11 (PRPF31-mutated) patient-specific retinal organoids and retinal pigment epithelium (RPE) from induced pluripotent stem cells (iPSC). Impaired alternative splicing of genes encoding pre-mRNA splicing proteins occurred in patient-specific retinal cells and Prpf31+/- mouse retinae, but not fibroblasts and iPSCs, providing mechanistic insights into retinal-specific phenotypes of PRPFs. RPE was the most affected, characterised by loss of apical-basal polarity, reduced trans-epithelial resistance, phagocytic capacity, microvilli, and cilia length and incidence. Disrupted cilia morphology was observed in patient-derived-photoreceptors that displayed progressive features associated with degeneration and cell stress. In situ gene-editing of a pathogenic mutation rescued key structural and functional phenotypes in RPE and photoreceptors, providing proof-of-concept for future therapeutic strategies.\n\neTOCPRPF31 is a ubiquitously expressed pre-mRNA processing factor that when mutated causes autosomal dominant RP. Using a patient-specific iPSC approach, Buskin and Zhu et al. show that retinal-specific defects result from altered splicing of genes involved in the splicing process itself, leading to impaired splicing, loss of RPE polarity and diminished phagocytic ability as well as reduced cilia incidence and length in both photoreceptors and RPE.\n\nHighlightsO_LISuccessful generation of iPSC-derived RPE and photoreceptors from four RP type 11 patients\nC_LIO_LIRPE cells express the mutant PRPF31 protein and show the lowest expression of wildtype protein\nC_LIO_LIPRPF31 mutations result in altered splicing of genes involved in pre-mRNA splicing in RPE and retinal organoids\nC_LIO_LIPrpf31 haploinsufficiency results in altered splicing of genes involved in pre-mRNA splicing in mouse retina\nC_LIO_LIRPE cells display loss of polarity, reduced barrier function and phagocytosis\nC_LIO_LIPhotoreceptors display shorter and fewer cilia and degenerative features\nC_LIO_LIRPE cells display most abnormalities suggesting they might be the primary site of pathogenesis\nC_LIO_LIIn situ gene editing corrects the mutation and rescues key phenotypes\nC_LI

genetics↗

Fast and accurate differential splicing analysis across multiple conditions with replicates

Multiple approaches have been proposed to study differential splicing from RNA sequencing (RNA-seq) data1, including the analysis of transcript isoforms2,3, clusters of splice-junctions4,5, alternative splicing events6-8 and exonic regions9. However, many challenges remain unsolved, including the limitation in speed, the computing capacity and storage requirements, the constraints in the number of reads needed to achieve sufficient accuracy, and the lack of robust methods to account for variability between replicates and for analyses across multiple conditions. We present here a significant extension of SUPPA8 to enable streamlined analysis of differential splicing across multiple conditions, taking into account biological variability. We show that SUPPA differential splicing analysis achieves high accuracy using extensive experimental and simulated data compared to other methods; and shows higher accuracy at low sequencing depth, with short read lengths, and using replicas with unbalanced depth, which has important implications for the cost-effective use of RNA-seq data for splicing analysis. We also validate the analysis of multiple conditions with SUPPA by studying differential splicing during iPS-cell to neuron differentiation and during erythroblast differentiation, providing support for the applicability of SUPPA for the robust analysis of differential splicing beyond binary comparisons.

bioinformatics↗