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Chenevix-Trench, G.

Publications and source records attributed to Chenevix-Trench, G..

11 recordsLinked to original sources

Cell-of-origin shapes tumor subtype in BRCA1-associated triple-negative breast cancer

Pathogenic germline BRCA1 variants greatly increase lifetime breast cancer risk, with no targeted prevention. Accrual of mutations following DNA repair errors in luminal progenitors is considered the chief mechanism of triple-negative breast cancer (TNBC) initiation, which cannot explain the organ specificity nor the phenotypic spectrum of the disease. Here we show that TNBC also originates in basal-myoepithelial cells, and that the cell of origin shapes TNBC subtype through aberrant epithelial differentiation, likely due to pleiotropic role of BRCA1 in regulating hormone signaling. Single-cell RNA sequencing of 67,001 cells from Wap-Cre Brca1/p53 mice and reanalysis of published Blg-Cre data show that aberrant basal-myoepithelial differentiation (Wap-Cre) generates the mesenchymal subtype (TNBC-M) and aberrant luminal differentiation (Blg-Cre) the basal-like subtype (TNBC-BL1). We also show that both subtypes occur at comparable frequency in BRCA1 carriers. Aberrant basal-myoepithelial differentiation precedes tumor formation, and only tumors derived from transplanted basal cells reproduce the basal-containing phenotype of spontaneous tumors. Comparison with a developmental atlas identifies de-differentiation of myoepithelial cells into basal cells lacking myoepithelial markers, a fetal state, whereas experimental metastases shift toward luminal states while retaining a TNBC-M-like transcriptional program. These findings support the inclusion of basal-myoepithelial and luminal cells in targeted prevention strategies for BRCA1 carriers, and adoption of TNBC subtyping for patient stratification and improving outcomes.

cancer biology↗

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↗

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↗

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↗

Rare copy number variants (CNVs) and breast cancer risk

BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

genetics↗

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↗

A short ERK5 isoform modulates nucleocytoplasmic shuttling of active ERK5 and associates with poor survival in breast cancer

BackgroundThe nucleocytoplasmic shuttling of ERK5 has gained recent attention as a regulator of its diverse roles in cancer progression but the exact mechanisms for this shuttling are still under investigation. MethodsUsing in vitro, in vivo and in silico studies, we investigated the roles of shorter ERK5 isoforms in regulating the nucleocytoplasmic shuttling of active phosphorylated-ERK5 (pERK5). Retrospective cohorts of primary and metastatic breast cancer cases were used to evaluate the association of the subcellular localization of pERK5 with clinicopathological features. ResultsExtranuclear localization of pERK5 was observed during cell migration in vitro and at the invasive fronts of metastatic tumors in vivo. The nuclear and extranuclear cell fractions contained different isoforms of pERK5, which are encoded by splice variants expressed in breast and other cancers in the TCGA data. One isoform, isoform-3, lacks the C-terminal transcriptional domain and the nuclear localization signal. The co-expression of isoform-3 and full-length ERK5 associated with high epithelial-to-mesenchymal transition (EMT) and poor patient survival. Experimentally, expressing isoform-3 with full-length ERK5 in breast cancer cells increased cell migration, drove EMT and led to tamoxifen resistance. In breast cancer patient samples, pERK5 showed variable subcellular localizations where its extranuclear localization associated with aggressive clinicopathological features, metastasis, and poor survival. ConclusionOur studies support a model of ERK5 nucleocytoplasmic shuttling driven by splice variants in an interplay between mesenchymal and epithelial states during metastasis. Using ERK5 as a biomarker and a therapeutic target should account for its splicing and context-dependent biological functions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/436061v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@1491ed5org.highwire.dtl.DTLVardef@1875fbeorg.highwire.dtl.DTLVardef@9edbbcorg.highwire.dtl.DTLVardef@16c34c8_HPS_FORMAT_FIGEXP M_FIG C_FIG ERK5 isoform-3 expression deploys active ERK5 (pERK5) outside the nucleus to facilitate EMT and cell migration. In cells dominantly expressing isoform-1, pERK5 shuttles to the nucleus to drive cell expansion.

cancer biology↗

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies new candidate susceptibility genes for breast and ovarian cancer

Familial, genome-wide association (GWAS), and sequencing studies and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWAS) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through novel application of a pleiotropy-guided conditional/conjunction false discovery rate approach for the first time in the setting of a TWAS. This identified 14 new candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 new candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were > 1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. Overlaying candidate causal risk variants identified by GWAS fine mapping onto expression prediction models for genes at known loci suggested that the association for 55% of these genes was driven by the underlying GWAS signal. SignificanceThe 22 new genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

genetics↗

Common breast cancer risk loci predispose to distinct tumor subtypes

BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER), but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate <5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at P<0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. ConclusionThis report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

genetics↗

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↗

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↗