Biology subjects

Beesley, J.

Publications and source records attributed to Beesley, J..

12 recordsLinked to original sources

bioRxiv2024

Pooled genetic screens identify breast cancer risk genes involved in evasion from T cell-mediated killing

Genome-wide association studies have identified more than 220 loci associated with breast cancer susceptibility. A major challenge is now to identify the effector genes with plausible functions in the context of breast cancer risk. We have previously performed pooled CRISPR screens to identify target genes at risk loci that drive cancer hallmarks including proliferation or modulating DNA damage response. We now extend these screens to identify genes involved in response to cytotoxic T lymphocyte (CTL) killing. We performed knockout and inhibition screens to identify genes that affect the response of the MCF7 human breast cancer cell line to CTL killing in an in vitro co-culture system. We identified 33 candidate risk genes associated with resistance or sensitisation to T cell-mediated killing. Using single gene perturbation, we showed that deletion of candidate risk genes IRF1, ATF7IP, CCDC170 and CASP8 induced resistance, while ablation of CFLAR, CREBBP, and PRMT7 sensitized cells to CTL killing. We used reporter assays to show that the risk-associated alleles at rs736801 and rs3769821 reduced transactivation of the IRF1 and CASP8 promoters, respectively. We showed that pharmacological inhibition of PRMT7 rendered breast cells sensitive to CTL killing and PRMT7 levels were negatively correlated with CD8+ infiltration and patient survival in luminal A breast cancer patient cohorts. Our results demonstrate that phenotypic pooled CRISPR screens are a useful approach for high throughput functional follow-up of GWAS findings, identifying genes which alter immune responses to breast cancer which offer opportunities to enhance immunotherapy.

genetics↗

bioRxiv2024

USP50 suppresses alternative RecQ helicase use and deleterious DNA2 activity during replication.

Mammalian DNA replication employs several RecQ DNA helicases to orchestrate the faithful duplication of genetic information. Helicase function is often coupled to the activity of specific nucleases, but how helicase and nuclease activities are co-directed is unclear. Here we identify the inactive ubiquitin-specific protease, USP50, as a ubiquitin-binding and chromatin-associated protein required for ongoing replication, fork restart, telomere maintenance and cellular survival during replicative stress. USP50 supports WRN:FEN1 at stalled replication forks, suppresses MUS81-dependent fork collapse and restricts double-strand DNA breaks at GC-rich sequences. Surprisingly we find that cells depleted for USP50 and recovering from a replication block exhibit increased DNA2 and RECQL4 foci and that the defects in ongoing replication, poor fork restart and increased fork collapse seen in these cells are mediated by DNA2, RECQL4 and RECQL5. These data define a novel ubiquitin-dependent pathway that promotes the balance of helicase: nuclease use at ongoing and stalled replication forks.

cancer biology↗

bioRxiv2023

The potential of Senicapoc, a KCNN4 inhibitor, for the prevention and treatment of breast cancer

BackgroundGenome-wide association studies have identified a breast cancer risk locus at 19q13.31. The candidate causal variants at this locus are located in the first exon of KCNN4. KCNN4, which regulates membrane potential and Ca2+ signaling, is a good candidate for drug repositioning because its inhibitor, Senicapoc, has been shown to be well tolerated in Phase-II and -III clinical trials for asthma and sickle cell anemia. MethodsWe evaluated public mRNA expression data to determine whether the allele at 19q13.31 associated with increased breast cancer risk was associated with KCNN4 expression. We also used immunohistochemistry to evaluate the relationship between KCNN4 protein expression and breast cancer survival. We then used Senicapoc in two murine mammary tumor models to determine if it would delay tumor development. We also treated mice bearing 4T1 mammary tumors with Senicapoc, by subcutaneous injection and by oral gavage. Finally we used gene editing to make deletions within Kcnn4 in 4T1 to determine whether Senicapoc had off-target effects on tumor growth. ResultsAnalysis of the Genotype-Tissue Expression Project showed that the allele at 19q13.31 associated with increased breast cancer risk is associated with increased KCNN4 expression, suggesting that inhibiting KCNN4 might reduce breast cancer risk. Using immunohistochemistry in a large breast cancer cohort, we found that membrane and cytoplasmic expression is a marker of poor prognosis in triple negative breast cancer. We then tested the efficacy of Senicapoc to prevent and treat breast cancer. This showed that it delays the development of mammary tumors in two murine models, and slows growth of a syngeneic (4T1) model of triple negative breast cancer. Senicapoc monotherapy showed similar efficacy to anthracycline/taxane-based chemotherapy in these studies, with a stronger effect when they were combined. ConclusionsThese results provide a rationale for clinical testing of Senicapoc for treating, and even preventing, breast cancer.

cancer biology↗

bioRxiv2022

Redefining normal breast cell populations using long noncoding RNAs

Single-cell RNAseq has allowed unprecedented insight into gene expression across different cell populations in normal tissue and disease states. However, almost all studies rely on annotated gene sets to capture gene expression levels and sequencing reads that do not align to known genes are discarded. Here, we discover thousands of long noncoding RNAs (lncRNAs) expressed in human mammary epithelial cells and analyze their expression in individual cells of the normal breast. We show that lncRNA expression alone can discriminate between luminal and basal cell types and define subpopulations of both compartments. Clustering cells based on lncRNA expression identified additional basal subpopulations, compared to clustering based on annotated gene expression, suggesting that lncRNAs can provide an additional layer of information to better distinguish breast cell subpopulations. In contrast, these breast-specific lncRNAs poorly distinguish brain cell populations, highlighting the need to annotate tissue-specific lncRNAs prior to expression analyses. We also identified a panel of 100 breast lncRNAs that could discern breast cancer subtypes better than protein-coding markers. Overall, our results suggest that lncRNAs are an unexplored resource for new biomarker and therapeutic target discovery in the normal breast and breast cancer subtypes.

cell biology↗

bioRxiv2022

RAD52 underlies the synthetic-lethal relationship between BRCA1/2 and 53BP1 deficiencies and DNA polymerase theta loss.

Introductory paragraphCells lacking several DNA repair proteins, including those promoting homologous recombination (HR), are sensitive to polymerase theta (Pol{theta}) repression1-4. Pol{theta} drives theta-mediated end joining (TMEJ) and suppresses HR but what mediates its synthetic lethal relationships is unclear. Here we examine murine Brca1C61G/C61G 53bp1-/-cells and find they are largely HR proficient by using RNF168 and RAD52. They exhibit no more TMEJ than 53bp1-/- cells yet are more sensitive to targeting of Pol{theta}. We find that RAD52 recruitment to damaged chromatin is increased following Pol{theta} depletion. RAD52 accumulation and cellular sensitivity to Pol{theta} repression can be curbed by the RAD51-binding regions of BARD1 and BRCA2, and sensitivity of BRCA1/2 depleted cells to Pol{theta} repression is suppressed by RAD52 inhibition. 53bp1-/- cells exhibit a smaller increase in RAD52 recruitment following Pol{theta} repression and also become resistant to Pol{theta} repression following RAD52 inhibition. Thus, RAD52 mediates sensitivity to targeting Pol{theta} in these contexts.

molecular biology↗

bioRxiv2021

CRISPR screens identify gene targets and drug repositioning opportunities at breast cancer risk loci

Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and are likely to modulate cancer risk by regulating gene expression. We recently developed a scoring system, INQUISIT, to predict candidate risk genes at BC-risk loci. Here, we used pooled CRISPR activation and suppression screens to validate INQUISIT predictions, and to define the cancer phenotypes they mediate. We measured proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on the DNA damage response. We performed 60 CRISPR screens and identified 21 high-confidence INQUISIT predictions that mediate a cancer phenotype. We validated the direct regulation of a subset of genes by BC-risk variants using HiCHIP and CRISPRqtl. Furthermore, we show the utility of expression profiling for drug repurposing against these targets. We provide a platform for identifying gene targets of risk variants, and lay a blueprint of interventions for BC risk reduction and treatment.

cancer biology↗

bioRxiv2021

Epigenome erosion drives neural crest-like phenotypic mimicry in triple-negative breast cancer and other SOX10+ malignancies

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSIntratumoural heterogeneity is a poor prognostic feature in triple-negative breast cancer (TNBC) and other high-grade malignancies. It is caused by genomic instability and phenotypic plasticity, but how these features co-evolve during tumour development remains unclear. SOX10 is a transcription factor, neural crest stem cell (NCSC) specifier and candidate mediator of cancer-associated phenotypic plasticity. MethodsUsing immunophenotyping, we investigated the expression of SOX10 in normal human breast tissue and breast cancer (n=21 cosmetic breast reduction and 1,860 tumour samples with clinical annotation). We then defined the context and evolution of its expression in TNBC compared to 21 other malignancies using systems-level transcriptomics. ResultsSOX10 was detected in nuclei of normal mammary luminal progenitor cells, the histogenic origin of most TNBCs. In breast cancer, nuclear SOX10 predicted poor outcome amongst cross-sectional (log-rank p=0.0015, hazard ratio 2.02, n=224) and metaplastic (log-rank p=0.04, n=66) TNBCs. Systems-level transcriptional network analysis identified a core module in SOX10s normal mammary epithelial transcription program that is rewired to NCSC genes in TNBC. Reprogramming was proportional to DNA damage and genome-wide promoter hypomethylation, particularly at CpG island shores. Using a novel network analysis pipeline, we found that NCSC-like transcriptional reprogramming is also strongly associated with promoter hypomethylation in other SOX10+ malignancies: glioma and melanoma. ConclusionsWe propose that cancer-associated genome hypomethylation simulates the open chromatin landscape of more primitive cell states, and that on this relatively unrestricted background, SOX10 recreates its ancestral gene regulatory circuits by default. These findings provide new insights about the basis of intratumoural heterogeneity and resurrection of developmental phenotypes in cancer; and highlight the potential for therapeutics that limit chromatin remodelling.

cancer biology↗

bioRxiv2019

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P<5.0x10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate <0.05). Five loci showed associations (P<0.05) in opposite directions between luminal- and non-luminal subtypes. In-silico analyses showed these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 37.6% for triple-negative and 54.2% for luminal A-like disease. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

genetics↗

bioRxiv2019

Chromatin interactome mapping at 139 independent breast cancer risk signals

Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression. We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals, and explore the functional mechanism underlying altered risk at the 12q24 risk region. Our results demonstrate the power of combining genetics, computational genomics and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.

molecular biology↗

bioRxiv2019

High-throughput allelic expression imbalance analyses identify candidate breast cancer risk genes

Fine-mapping of breast cancer GWAS regions has identified 195 high confidence signals containing more than 5,000 credible causal variants (CCVs). The CCVs are predominantly noncoding and enriched in regulatory elements and thus may confer the risk by altering gene expression in cis. We analyzed allelic expression imbalance (AEI) of genes surrounding known breast cancer signals, using normal breast and breast tumor transcriptome data and imputed genotypes. Fourteen genes, including NTN4, were identified whose expression was associated with CCV genotype. We showed that CCVs at this signal were located within an enhancer that physically interacts with the NTN4 promoter. Furthermore, knockdown of NTN4 in breast cells increased cell proliferation in vitro and tumor growth in vivo. Here, we present the most comprehensive AEI analysis of breast cancer CCVs resulting in identification of new candidate risk genes.

genetics↗

bioRxiv2019

Fine-mapping of 150 breast cancer risk regions identifies 178 high confidence target genes

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants (CCVs) in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium, and enriched genomic features to determine variants with high posterior probabilities (HPPs) of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of potentially causal variants, using gene expression (eQTL), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways, were over-represented among the 178 highest confidence target genes.

genetics↗

bioRxiv2017

Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways

The total number of acquired melanocytic nevi on the skin is strongly correlated with melanoma risk. Here we report a meta-analysis of 11 nevus GWAS from Australia, Netherlands, United Kingdom, and United States, comprising a total of 52,506 phenotyped individuals. We confirm known loci including MTAP, PLA2G6, and IRF4, and detect novel SNPs at a genome-wide level of significance in KITLG, DOCK8, and a broad region of 9q32. In a bivariate analysis combining the nevus results with those from a recent melanoma GWAS meta-analysis (12,874 cases, 23,203 controls), SNPs near GPRC5A, CYP1B1, PPARGC1B, HDAC4, FAM208B and SYNE2 reached global significance, and other loci, including MIR146A and OBFC1, reached a suggestive level of significance. Overall, we conclude that most nevus genes affect melanoma risk (KITLG an exception), while many melanoma risk loci do not alter nevus count. For example, variants in TERC and OBFC1 affect both traits, but other telomere length maintenance genes seem to affect melanoma risk only. Our findings implicate multiple pathways in nevogenesis via genes we can show to be expressed under control of the MITF melanocytic cell lineage regulator.

genetics↗