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Civitarese, A.

Publications and source records attributed to Civitarese, A..

3 recordsLinked to original sources

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↗