Age-related loss of chromosome Y is associated with levels of sex hormone binding globulin and clonal hematopoiesis defined by TET2, TP53, and CBL mutations.

Mosaic loss of the Y-chromosome (LOY) in peripheral blood leukocytes is the most common somatic alteration in men and linked to wide range of malignant and nonmalignant conditions. LOY is associated with age, smoking, and constitutional genetics. Here, we aimed to assess the relationships between LOY, serum biomarkers, and clonal hematopoiesis (CH). LOY in U.K. Biobank was strongly associated with levels of sex hormone binding globulin (SHBG), a key regulator of testosterone bioavailability. Mendelian randomization suggested a causal effect of SHBG on LOY but there was no evidence for an effect of LOY on SHBG. In contrast, age-related CH defined by somatic driver mutations was not associated with SHBG but was associated with LOY at clonal fractions above 30%. TET2, TP53, and CBL mutations were enriched in LOY cases, but JAK2 V617F was depleted. Our findings thus identify independent relationships between LOY, sex hormone levels, and CH.

Integration of Genomic Risk Scores to Improve the Prediction of Childhood Asthma Diagnosis.

Genome-wide and epigenome-wide association studies have identified genetic variants and differentially methylated nucleotides associated with childhood asthma. Incorporation of such genomic data may improve performance of childhood asthma prediction models which use phenotypic and environmental data. Using genome-wide genotype and methylation data at birth from the Isle of Wight Birth Cohort (n = 1456), a polygenic risk score (PRS), and newborn (nMRS) and childhood (cMRS) methylation risk scores, were developed to predict childhood asthma diagnosis. Each risk score was integrated with two previously published childhood asthma prediction models (CAPE and CAPP) and were validated in the Manchester Asthma and Allergy Study. Individually, the genomic risk scores demonstrated modest-to-moderate discriminative performance (area under the receiver operating characteristic curve, AUC: PRS = 0.64, nMRS = 0.55, cMRS = 0.54), and their integration only marginally improved the performance of the CAPE (AUC: 0.75 vs. 0.71) and CAPP models (AUC: 0.84 vs. 0.82). The limited predictive performance of each genomic risk score individually and their inability to substantially improve upon the performance of the CAPE and CAPP models suggests that genetic and epigenetic predictors of the broad phenotype of asthma are unlikely to have clinical utility. Hence, further studies predicting specific asthma endotypes are warranted.

Predicting Pancreatic Cancer in the UK Biobank Cohort Using Polygenic Risk Scores and Diabetes Mellitus.

BACKGROUND & AIMS: Diabetes mellitus (DM) is known to be associated with pancreatic ductal adenocarcinoma (PDAC), particularly new-onset DM (NODM). Others have developed polygenic risk scores (PRS) associated with PDAC risk. We aimed to compare the performance of these PRS in an independent cohort to determine if they can discriminate between NODM and long-standing DM patients with PDAC. METHODS: Cases (1042) and matched cancer-free controls (10,420) were drawn from the UK Biobank. Five PRS models were calculated using single nucleotide polymorphisms (SNPs) from previous studies (Nakatochi, Galeotti, Molina, Jia, and Rashkin) and a combination of these. Regression models were used to assess the association between PDAC and PRS adjusted for ancestry, smoking, DM, waist circumference, and family history of digestive cancer. Receiver operator characteristic curves and area under the curve metrics (AUC) were used to assess the performance of each PRS for classifying PDAC risk. RESULTS: The combined PRS model achieved the highest AUC (0.605), and significantly improved a clinical risk model in this cohort (AUC = 0.83; P = .0002). Individuals within the fifth quintile have a 2.74-fold increased risk of developing PDAC vs those in the first quintile (P < .001), and have a 3.05-fold increased risk of developing PDAC if they have DM vs those without DM (P < .001). The positive predictive value was 11.9% in participants without DM, 23.9% with long-standing DM, and 86.7% with NODM. CONCLUSIONS: The PDAC-related common genetic variants are more strongly associated with DM. This PRS has the potential for targeting individuals with NODM for PDAC secondary screening measures.

Clonal myelopoiesis promotes adverse outcomes in chronic kidney disease.

We sought to determine the relationship between age-related clonal hematopoiesis (CH) and chronic kidney disease (CKD). CH, defined as mosaic chromosome abnormalities (mCA) and/or driver mutations was identified in 5449 (2.9%) eligible UK Biobank participants (n = 190,487 median age = 58 years). CH was negatively associated with glomerular filtration rate estimated from cystatin-C (eGFR.cys; ß = -0.75, P = 2.37 × 10-4), but not with eGFR estimated from creatinine, and was specifically associated with CKD defined by eGFR.cys < 60 (OR = 1.02, P = 8.44 × 10-8). In participants without prevalent myeloid neoplasms, eGFR.cys was associated with myeloid mCA (n = 148, ß = -3.36, P = 0.01) and somatic driver mutations (n = 3241, ß = -1.08, P = 6.25 × 10-5) associated with myeloid neoplasia (myeloid CH), specifically mutations in CBL, TET2, JAK2, PPM1D and GNB1 but not DNMT3A or ASXL1. In participants with no history of cardiovascular disease or myeloid neoplasms, myeloid CH increased the risk of adverse outcomes in CKD (HR = 1.6, P = 0.002) compared to those without myeloid CH. Mendelian randomisation analysis provided suggestive evidence for a causal relationship between CH and CKD (P = 0.03). We conclude that CH, and specifically myeloid CH, is associated with CKD defined by eGFR.cys. Myeloid CH promotes adverse outcomes in CKD, highlighting the importance of the interaction between intrinsic and extrinsic factors to define the health risk associated with CH.

Development of childhood asthma prediction models using machine learning approaches.

BACKGROUND: Respiratory symptoms are common in early life and often transient. It is difficult to identify in which children these will persist and result in asthma. Machine learning (ML) approaches have the potential for better predictive performance and generalisability over existing childhood asthma prediction models. This study applied ML approaches to predict school-age asthma (age 10) in early life (Childhood Asthma Prediction in Early life, CAPE model) and at preschool age (Childhood Asthma Prediction at Preschool age, CAPP model). METHODS: Clinical and environmental exposure data was collected from children enrolled in the Isle of Wight Birth Cohort (N = 1368, ∼15% asthma prevalence). Recursive Feature Elimination (RFE) identified an optimal subset of features predictive of school-age asthma for each model. Seven state-of-the-art ML classification algorithms were used to develop prognostic models. Training was performed by applying fivefold cross-validation, imputation, and resampling. Predictive performance was evaluated on the test set. Models were further externally validated in the Manchester Asthma and Allergy Study (MAAS) cohort. RESULTS: RFE identified eight and twelve predictors for the CAPE and CAPP models, respectively. Support Vector Machine (SVM) algorithms provided the best performance for both the CAPE (area under the receiver operating characteristic curve, AUC = 0.71) and CAPP (AUC = 0.82) models. Both models demonstrated good generalisability in MAAS (CAPE 8-year = 0.71, 11-year = 0.71, CAPP 8-year = 0.83, 11-year = 0.79) and excellent sensitivity to predict a subgroup of persistent wheezers. CONCLUSION: Using ML approaches improved upon the predictive performance of existing regression-based models, with good generalisability and ability to rule in asthma and predict persistent wheeze.

Genome-wide association study identifies novel susceptibility loci for KIT D816V positive mastocytosis.

Mastocytosis is a rare myeloid neoplasm characterized by uncontrolled expansion of mast cells, driven in >80% of affected individuals by acquisition of the KIT D816V mutation. To explore the hypothesis that inherited variation predisposes to mastocytosis, we performed a two-stage genome-wide association study, analyzing 1,035 individuals with KIT D816V positive disease and 17,960 healthy control individuals from five European populations. After quality control, we tested 592,007 SNPs at stage 1 and 75 SNPs at stage 2 for association by using logistic regression and performed a fixed effects meta-analysis to combine evidence across the two stages. From the meta-analysis, we identified three intergenic SNPs associated with mastocytosis that achieved genome-wide significance without heterogeneity between cohorts: rs4616402 (pmeta = 1.37 × 10-15, OR = 1.52), rs4662380 (pmeta = 2.11 × 10-12, OR = 1.46), and rs13077541 (pmeta = 2.10 × 10-9, OR = 1.33). Expression quantitative trait analyses demonstrated that rs4616402 is associated with the expression of CEBPA (peQTL = 2.3 × 10-14), a gene encoding a transcription factor known to play a critical role in myelopoiesis. The role of the other two SNPs is less clear: rs4662380 is associated with expression of the long non-coding RNA gene TEX41 (peQTL = 2.55 × 10-11), whereas rs13077541 is associated with the expression of TBL1XR1, which encodes transducin (ß)-like 1 X-linked receptor 1 (peQTL = 5.70 × 10-8). In individuals with available data and non-advanced disease, rs4616402 was associated with age at presentation (p = 0.009; beta = 4.41; n = 422). Additional focused analysis identified suggestive associations between mastocytosis and genetic variation at TERT, TPSAB1/TPSB2, and IL13. These findings demonstrate that multiple germline variants predispose to KIT D816V positive mastocytosis and provide novel avenues for functional investigation.

A CRISPR and high-content imaging assay compliant with ACMG/AMP guidelines for clinical variant interpretation in ciliopathies.

Ciliopathies are a broad range of inherited developmental and degenerative diseases associated with structural or functional defects in motile or primary non-motile cilia. There are around 200 known ciliopathy disease genes and whilst genetic testing can provide an accurate diagnosis, 24-60% of ciliopathy patients who undergo genetic testing do not receive a genetic diagnosis. This is partly because following current guidelines from the American College of Medical Genetics and the Association for Molecular Pathology, it is difficult to provide a confident clinical diagnosis of disease caused by missense or non-coding variants, which account for more than one-third of cases of disease. Mutations in PRPF31 are the second most common cause of the degenerative retinal ciliopathy autosomal dominant retinitis pigmentosa. Here, we present a high-throughput high-content imaging assay providing quantitative measure of effect of missense variants in PRPF31 which meets the recently published criteria for a baseline standard in vitro test for clinical variant interpretation. This assay utilizes a new PRPF31+/- human retinal cell line generated using CRISPR gene editing to provide a stable cell line with significantly fewer cilia in which novel missense variants are expressed and characterised. We show that high-content imaging of cells expressing missense variants in a ciliopathy gene on a null background can allow characterisation of variants according to the cilia phenotype. We hope that this will be a useful tool for clinical characterisation of PRPF31 variants of uncertain significance, and can be extended to variant classification in other ciliopathies.

Pathogenic Variants in CHEK2 Are Associated With an Adverse Prognosis in Symptomatic Early-Onset Breast Cancer.

PURPOSE: Checkpoint kinase 2 (CHEK2) is frequently included in multigene panels. We describe the associated outcomes among carriers of CHEK2 pathogenic variants in young patients with symptomatic breast cancer. PATIENTS AND METHODS: Participants (N = 2,344) in the Prospective Outcomes in Sporadic Versus Hereditary Breast Cancer study had a diagnosis of primary invasive breast cancer at age ≤ 40 years. Summary statistics were used to compare tumor characteristics among CHEK2+ carriers with those who were CHEK2-. Kaplan-Meier curves were used to demonstrate overall survival (OS) and distant disease-free survival. RESULTS: Overall, 53 of the 2,344 participants (2.3%) had a pathogenic CHEK2 variant. CHEK2+-associated tumors were significantly more likely to be grade 2, estrogen receptor and progesterone receptor-positive compared with CHEK2- tumors (grade 2, n = 28 of 52 [53.8%] v n = 803 of 2,229 [36.0%]; P = .029). CHEK2-associated tumors were significantly more likely to have nodal involvement (N1, n = 37 of 53 [69.8%] v 1,169 of 2,253 [51.9%]; P = .0098) and demonstrated a trend toward multifocality. A higher proportion of participants with CHEK2+ variants with invasive breast cancer were obese than were those with CHEK2- variant (28.3% v 18.8%; P = .039). Univariate and multivariable analyses revealed that OS and distant disease-free survival were significantly worse in CHEK2+ versus CHEK2- carriers (OS hazard ratio, 1.58; 95% CI, 1.01 to 2.48; P = .043). CONCLUSION: This work highlights the adverse prognosis associated with breast cancer in carriers of CHEK2 pathogenic variants. It also identifies a potential association among obesity, family history, and breast cancer risk in young CHEK2 gene carriers.

Clonal myelopoiesis in the UK Biobank cohort: ASXL1 mutations are strongly associated with smoking.

We sought to determine the significance of myeloid clonal hematopoiesis (CH) in the UK Biobank cohort (n = 502,524, median age = 58 years). Utilizing SNP array (n = 486,941) and whole exome sequencing data (n = 49,956), we identified 1166 participants with myeloid CH, defined by myeloid-associated mosaic chromosome abnormalities (mCA) and/or likely somatic driver mutations in DNMT3A, TET2, ASXL1, JAK2, SRSF2, or PPM1D. Myeloid CH increased by 1.1-fold per annum (myeloid mCA, P = 1.57 × 10-38; driver mutations, P = 5.89 × 10-47). Genome-wide association analysis identified two distinct signals within TERT that predisposed to myeloid CH, plus a weaker signal corresponding to the JAK2 46/1 haplotype. Specific subtypes of myeloid CH were associated with several blood features and clinical phenotypes, including TET2 mutations and chronic obstructive pulmonary disease. Smoking history was significantly associated with myeloid CH: 53% of myeloid CH cases were smokers compared to 44% of controls (P = 3.38 × 10-6), a difference principally due to current (OR = 1.10; P = 6.14 × 10-6) rather than past smoking (P = 0.08). Breakdown of CH by specific mutation type revealed that ASXL1 loss of function mutations were most strongly associated with current smoking status (OR = 1.07; P = 1.92 × 10-5), and the only abnormality associated with past smoking (OR = 1.04; P = 0.0026). We suggest that the inflammatory environment induced by smoking may promote the outgrowth of ASXL1-mutant clones.

Prediction of contralateral breast cancer: external validation of risk calculators in 20 international cohorts.

BACKGROUND: Three tools are currently available to predict the risk of contralateral breast cancer (CBC). We aimed to compare the performance of the Manchester formula, CBCrisk, and PredictCBC in patients with invasive breast cancer (BC). METHODS: We analyzed data of 132,756 patients (4682 CBC) from 20 international studies with a median follow-up of 8.8 years. Prediction performance included discrimination, quantified as a time-dependent Area-Under-the-Curve (AUC) at 5 and 10 years after diagnosis of primary BC, and calibration, quantified as the expected-observed (E/O) ratio at 5 and 10 years and the calibration slope. RESULTS: The AUC at 10 years was: 0.58 (95% confidence intervals [CI] 0.57-0.59) for CBCrisk; 0.60 (95% CI 0.59-0.61) for the Manchester formula; 0.63 (95% CI 0.59-0.66) and 0.59 (95% CI 0.56-0.62) for PredictCBC-1A (for settings where BRCA1/2 mutation status is available) and PredictCBC-1B (for the general population), respectively. The E/O at 10 years: 0.82 (95% CI 0.51-1.32) for CBCrisk; 1.53 (95% CI 0.63-3.73) for the Manchester formula; 1.28 (95% CI 0.63-2.58) for PredictCBC-1A and 1.35 (95% CI 0.65-2.77) for PredictCBC-1B. The calibration slope was 1.26 (95% CI 1.01-1.50) for CBCrisk; 0.90 (95% CI 0.79-1.02) for PredictCBC-1A; 0.81 (95% CI 0.63-0.99) for PredictCBC-1B, and 0.39 (95% CI 0.34-0.43) for the Manchester formula. CONCLUSIONS: Current CBC risk prediction tools provide only moderate discrimination and the Manchester formula was poorly calibrated. Better predictors and re-calibration are needed to improve CBC prediction and to identify low- and high-CBC risk patients for clinical decision-making.

Prediction and clinical utility of a contralateral breast cancer risk model.

BACKGROUND: Breast cancer survivors are at risk for contralateral breast cancer (CBC), with the consequent burden of further treatment and potentially less favorable prognosis. We aimed to develop and validate a CBC risk prediction model and evaluate its applicability for clinical decision-making. METHODS: We included data of 132,756 invasive non-metastatic breast cancer patients from 20 studies with 4682 CBC events and a median follow-up of 8.8 years. We developed a multivariable Fine and Gray prediction model (PredictCBC-1A) including patient, primary tumor, and treatment characteristics and BRCA1/2 germline mutation status, accounting for the competing risks of death and distant metastasis. We also developed a model without BRCA1/2 mutation status (PredictCBC-1B) since this information was available for only 6% of patients and is routinely unavailable in the general breast cancer population. Prediction performance was evaluated using calibration and discrimination, calculated by a time-dependent area under the curve (AUC) at 5 and 10 years after diagnosis of primary breast cancer, and an internal-external cross-validation procedure. Decision curve analysis was performed to evaluate the net benefit of the model to quantify clinical utility. RESULTS: In the multivariable model, BRCA1/2 germline mutation status, family history, and systemic adjuvant treatment showed the strongest associations with CBC risk. The AUC of PredictCBC-1A was 0.63 (95% prediction interval (PI) at 5 years, 0.52-0.74; at 10 years, 0.53-0.72). Calibration-in-the-large was -0.13 (95% PI: -1.62-1.37), and the calibration slope was 0.90 (95% PI: 0.73-1.08). The AUC of Predict-1B at 10 years was 0.59 (95% PI: 0.52-0.66); calibration was slightly lower. Decision curve analysis for preventive contralateral mastectomy showed potential clinical utility of PredictCBC-1A between thresholds of 4-10% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers. CONCLUSIONS: We developed a reasonably calibrated model to predict the risk of CBC in women of European-descent; however, prediction accuracy was moderate. Our model shows potential for improved risk counseling, but decision-making regarding contralateral preventive mastectomy, especially in the general breast cancer population where limited information of the mutation status in BRCA1/2 is available, remains challenging.

Recurrent activating STAT5B N642H mutation in myeloid neoplasms with eosinophilia.

Determining the underlying cause of persistent eosinophilia is important for effective clinical management but remains a diagnostic challenge in many cases. We identified STAT5B N642H, an established oncogenic mutation, in 27/1715 (1.6%) cases referred for investigation of eosinophilia. Of the 27 mutated cases, a working diagnosis of hypereosinophilic syndrome (HES; n = 7) or a myeloid neoplasm with eosinophilia (n = 20) had been made prior to the detection of STAT5B N642H. Myeloid panel analysis identified a median of 2 additional mutated genes (range 0-4) with 4 cases having STAT5B N642H as a sole abnormality. STAT5B N642H was absent in cultured T cells of 4/4 positive cases. Individuals with SF3B1 mutations (9/27; 33%) or STAT5B N642H as a sole abnormality had a markedly better overall survival compared to cases with other additional mutations (median 65 months vs. 14 months; hazard ratio = 8.1; P < 0.001). The overall survival of STAT5B-mutated HES cases was only 30 months, suggesting that these cases should be reclassified as chronic eosinophilic leukemia, not otherwise specified (CEL-NOS). The finding of STAT5B N642H as a recurrent mutation in myeloid neoplasia with eosinophilia provides a new diagnostic and prognostic marker as well as a potential target for therapy.

PRR14L mutations are associated with chromosome 22 acquired uniparental disomy, age-related clonal hematopoiesis and myeloid neoplasia.

Acquired uniparental disomy (aUPD, also known as copy-neutral loss of heterozygosity) is a common feature of cancer cells and characterized by extended tracts of somatically-acquired homozygosity without any concurrent loss or gain of genetic material. The presumed genetic targets of many regions of aUPD remain unknown. Here we describe the association of chromosome 22 aUPD with mutations that delete the C-terminus of PRR14L in patients with chronic myelomonocytic leukemia (CMML), related myeloid neoplasms and age-related clonal hematopoiesis (ARCH). Myeloid panel analysis identified a median of three additional mutated genes (range 1-6) in cases with a myeloid neoplasm (n = 8), but no additional mutations in cases with ARCH (n = 2) suggesting that mutated PRR14L alone may be sufficient to drive clonality. PRR14L has very limited homology to other proteins and its function is unknown. ShRNA knockdown of PRR14L in human CD34+ cells followed by in vitro growth and differentiation assays showed an increase in monocytes and decrease in neutrophils, consistent with a CMML-like phenotype. RNA-Seq and cellular localization studies suggest a role for PRR14L in cell division. PRR14L is thus a novel, biallelically mutated gene and potential founding abnormality in myeloid neoplasms.

Inherited mutations in 17 breast cancer susceptibility genes among a large triple-negative breast cancer cohort unselected for family history of breast cancer.

PURPOSE: Recent advances in DNA sequencing have led to the development of breast cancer susceptibility gene panels for germline genetic testing of patients. We assessed the frequency of mutations in 17 predisposition genes, including BRCA1 and BRCA2, in a large cohort of patients with triple-negative breast cancer (TNBC) unselected for family history of breast or ovarian cancer to determine the utility of germline genetic testing for those with TNBC. PATIENTS AND METHODS: Patients with TNBC (N = 1,824) unselected for family history of breast or ovarian cancer were recruited through 12 studies, and germline DNA was sequenced to identify mutations. RESULTS: Deleterious mutations were identified in 14.6% of all patients. Of these, 11.2% had mutations in the BRCA1 (8.5%) and BRCA2 (2.7%) genes. Deleterious mutations in 15 other predisposition genes were detected in 3.7% of patients, with the majority observed in genes involved in homologous recombination, including PALB2 (1.2%) and BARD1, RAD51D, RAD51C, and BRIP1 (0.3% to 0.5%). Patients with TNBC with mutations were diagnosed at an earlier age (P < .001) and had higher-grade tumors (P = .01) than those without mutations. CONCLUSION: Deleterious mutations in predisposition genes are present at high frequency in patients with TNBC unselected for family history of cancer. Mutation prevalence estimates suggest that patients with TNBC, regardless of age at diagnosis or family history of cancer, should be considered for germline genetic testing of BRCA1 and BRCA2. Although mutations in other predisposition genes are observed among patients with TNBC, better cancer risk estimates are needed before these mutations are used for clinical risk assessment in relatives.

Exome sequence read depth methods for identifying copy number changes.

Copy number variants (CNVs) play important roles in a number of human diseases and in pharmacogenetics. Powerful methods exist for CNV detection in whole genome sequencing (WGS) data, but such data are costly to obtain. Many disease causal CNVs span or are found in genome coding regions (exons), which makes CNV detection using whole exome sequencing (WES) data attractive. If reliably validated against WGS-based CNVs, exome-derived CNVs have potential applications in a clinical setting. Several algorithms have been developed to exploit exome data for CNV detection and comparisons made to find the most suitable methods for particular data samples. The results are not consistent across studies. Here, we review some of the exome CNV detection methods based on depth of coverage profiles and examine their performance to identify problems contributing to discrepancies in published results. We also present a streamlined strategy that uses a single metric, the likelihood ratio, to compare exome methods, and we demonstrated its utility using the VarScan 2 and eXome Hidden Markov Model (XHMM) programs using paired normal and tumour exome data from chronic lymphocytic leukaemia patients. We use array-based somatic CNV (SCNV) calls as a reference standard to compute prevalence-independent statistics, such as sensitivity, specificity and likelihood ratio, for validation of the exome-derived SCNVs. We also account for factors known to influence the performance of exome read depth methods, such as CNV size and frequency, while comparing our findings with published results.

Therapeutic targeting of integrin αvß6 in breast cancer.

BACKGROUND: Integrin αvß6 promotes migration, invasion, and survival of cancer cells; however, the relevance and role of αvß6 has yet to be elucidated in breast cancer. METHODS: Protein expression of integrin subunit beta6 (ß6) was measured in breast cancers by immunohistochemistry (n > 2000) and ITGB6 mRNA expression measured in the Molecular Taxonomy of Breast Cancer International Consortium dataset. Overall survival was assessed using Kaplan Meier curves, and bioinformatics statistical analyses were performed (Cox proportional hazards model, Wald test, and Chi-square test of association). Using antibody (264RAD) blockade and siRNA knockdown of ß6 in breast cell lines, the role of αvß6 in Human Epidermal Growth Factor Receptor 2 (HER2) biology (expression, proliferation, invasion, growth in vivo) was assessed by flow cytometry, MTT, Transwell invasion, proximity ligation assay, and xenografts (n ≥ 3), respectively. A student's t-test was used for two variables; three-plus variables used one-way analysis of variance with Bonferroni's Multiple Comparison Test. Xenograft growth was analyzed using linear mixed model analysis, followed by Wald testing and survival, analyzed using the Log-Rank test. All statistical tests were two sided. RESULTS: High expression of either the mRNA or protein for the integrin subunit ß6 was associated with very poor survival (HR = 1.60, 95% CI = 1.19 to 2.15, P = .002) and increased metastases to distant sites. Co-expression of ß6 and HER2 was associated with worse prognosis (HR = 1.97, 95% CI = 1.16 to 3.35, P = .01). Monotherapy with 264RAD or trastuzumab slowed growth of MCF-7/HER2-18 and BT-474 xenografts similarly (P < .001), but combining 264RAD with trastuzumab effectively stopped tumor growth, even in trastuzumab-resistant MCF-7/HER2-18 xenografts. CONCLUSIONS: Targeting αvß6 with 264RAD alone or in combination with trastuzumab may provide a novel therapy for treating high-risk and trastuzumab-resistant breast cancer patients.

Megalencephaly syndromes: exome pipeline strategies for detecting low-level mosaic mutations.

Two megalencephaly (MEG) syndromes, megalencephaly-capillary malformation (MCAP) and megalencephaly-polymicrogyriapolydactyly-hydrocephalus (MPPH), have recently been defined on the basis of physical and neuroimaging features. Subsequently, exome sequencing of ten MEG cases identified de-novo postzygotic mutations in PIK3CA which cause MCAP and de-novo mutations in AKT and PIK3R2 which cause MPPH. Here we present findings from exome sequencing three unrelated megalencephaly patients which identified a causal PIK3CA mutation in two cases and a causal PIK3R2 mutation in the third case. However, our patient with the PIK3R2 mutation which is considered to cause MPPH has a marked bifrontal band heterotopia which is a feature of MCAP. Furthermore, one of our patients with a PIK3CA mutation lacks syndactyly/polydactyly which is a characteristic of MCAP. These findings suggest that the overlap between MCAP and MPPH may be greater than the available studies suggest. In addition, the PIK3CA mutation in one of our patients could not be detected using standard exome analysis because the mutation was observed at a low frequency consistent with somatic mosaicism. We have therefore investigated several alternative methods of exome analysis and demonstrate that alteration of the initial allele frequency spectrum (AFS), used as a prior for variant calling in samtools, had the greatest power to detect variants with low mutant allele frequencies in our 3 MEG exomes and in simulated data. We therefore recommend non-default settings of the AFS in combination with stringent quality control when searching for causal mutation(s) that could have low levels of mutant reads due to post-zygotic mutation.

Genome-wide association study identifies 25 known breast cancer susceptibility loci as risk factors for triple-negative breast cancer.

Triple-negative (TN) breast cancer is an aggressive subtype of breast cancer associated with a unique set of epidemiologic and genetic risk factors. We conducted a two-stage genome-wide association study of TN breast cancer (stage 1: 1529 TN cases, 3399 controls; stage 2: 2148 cases, 1309 controls) to identify loci that influence TN breast cancer risk. Variants in the 19p13.1 and PTHLH loci showed genome-wide significant associations (P < 5 × 10(-) (8)) in stage 1 and 2 combined. Results also suggested a substantial enrichment of significantly associated variants among the single nucleotide polymorphisms (SNPs) analyzed in stage 2. Variants from 25 of 74 known breast cancer susceptibility loci were also associated with risk of TN breast cancer (P < 0.05). Associations with TN breast cancer were confirmed for 10 loci (LGR6, MDM4, CASP8, 2q35, 2p24.1, TERT-rs10069690, ESR1, TOX3, 19p13.1, RALY), and we identified associations with TN breast cancer for 15 additional breast cancer loci (P < 0.05: PEX14, 2q24.1, 2q31.1, ADAM29, EBF1, TCF7L2, 11q13.1, 11q24.3, 12p13.1, PTHLH, NTN4, 12q24, BRCA2, RAD51L1-rs2588809, MKL1). Further, two SNPs independent of previously reported signals in ESR1 [rs12525163 odds ratio (OR) = 1.15, P = 4.9 × 10(-) (4)] and 19p13.1 (rs1864112 OR = 0.84, P = 1.8 × 10(-) (9)) were associated with TN breast cancer. A polygenic risk score (PRS) for TN breast cancer based on known breast cancer risk variants showed a 4-fold difference in risk between the highest and lowest PRS quintiles (OR = 4.03, 95% confidence interval 3.46-4.70, P = 4.8 × 10(-) (69)). This translates to an absolute risk for TN breast cancer ranging from 0.8% to 3.4%, suggesting that genetic variation may be used for TN breast cancer risk prediction.