Citations

Abstract Background: High percent mammographic density (MD), which reflects the relative fibroglandular tissue content of the breast, is one of the strongest breast cancer risk factors; however, the pathologic mediators of this risk are unknown. We hypothesize that analysis of breast tissue sections using deep learning approaches may characterize histologic features that underpin risk associated with high MD. Methods: Non-targeted H&E stained breast tissue sections of diagnostic image-guided breast biopsies were evaluated among 588 women enrolled following an abnormal mammogram in the Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project (2007-2010). Overall volumetric percent MD for the biopsied breast and localized volumetric percent MD surrounding the biopsy site were determined for each participant. A deep convolutional neural network (CNN) model was trained to identify and quantitatively assess breast epithelial, stroma and fat tissue and their organizational and spatial arrangements. Least absolute shrinkage and selection operator (Lasso) regression was used to determine relationships between MD measures and pathological features. To ensure reliability of the model, a cross-validation strategy was employed to build and assess the performance of the fitted model. Finally, Spearman correlation coefficients were estimated to test the association between the predicted density values by each model (predicting overall or localized MD) and the actual MD measurements. We report the average and standard deviation (SD) of the correlation coefficients. Results: In an independent validation set, the CNN model was 95.5% accurate in classifying epithelial, stromal and fat tissue. The mean (SD) correlations between the predicted model and the actual measurements for overall and localized MD were 0.70 (0.06) and 0.65 (0.06) respectively. The amount of stroma identified (normalized to tissue area) had the highest selection probability (P-value) by the Lasso model and thus the strongest positive relationship with MD (P-value >0.9 for each MD measurement). In contrast, the amount of normalized epithelial tissue was not related to MD (P-value=0.01 for each MD measurement). No association was observed for the total normalized fat area with MD (P-value <0.31 for each MD measurement). In addition, the number of distributed epithelial regions was positively associated, whereas the distance between epithelial regions was inversely associated with overall MD (P-value <0.87 and 0.62, respectively). Conclusions: These results show that greater stromal tissue amount and spatial distribution patterns of epithelial regions, rather than total epithelial amounts, had the strongest relationships with elevated MD. Future work will determine the relationship of these MD features with biopsy diagnosis. Citation Format: Maeve Mullooly, Babak Ehteshami Bejnordi, Maya Palakal, Pamela M. Vacek, Donald L. Weaver, John A. Shepherd, Bo Fan, Amir Pasha Mahmoudzadeh, Jeff Wang, Jason M. Johnson, Sally D. Herschorn, Brian L. Sprague, Ruth M. Pfeiffer, Louise A. Brinton, Mark E. Sherman, Andrew Beck, Gretchen L. Gierach. Application of convolutional neural networks to breast biopsies to uncover tissue correlates of mammographic breast density [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4235. doi:10.1158/1538-7445.AM2017-4235

Abstract Objective: To elucidate the genetic architecture of gene expression in pancreatic tissues. Design: We performed expression quantitative trait locus (eQTL) and allele specific expression (ASE) analyses using RNA-sequence data and 1000 Genomes (1000G) imputed GWAS genotypes from 95 fresh frozen histologically normal pancreatic tissue samples. Data from 115 pancreatic tumor-derived tissue samples from The Cancer Genome Atlas (TCGA) was included for comparison. Results: We identified 38,615 cis-eQTLs (corresponding to 484 Genes) in histologically normal tissues and 39,713 cis-eQTL (corresponding to 237 Genes) in tumor tissues (FDR<0.1), with the strongest effects seen near transcriptional start sites (TSS). Approximately 23% and 42% of genes with significant cis-eQTLs (eGenes) appeared to be specific for tumor and normal derived tissues, respectively. Significant enrichment of cis-eQTL variants was noted in noncoding regulatory regions marked by modified histones, DNAse hypersensitivity and bound transcription factors, in particular for pancreatic tissues (1.53-3.12 fold, P≤0.0001), indicating tissue-specific functional relevance. A common pancreatic cancer risk locus on 9q34.2 in the ABO gene (rs687289) was associated with ABO expression in histologically normal (P=5.8x10-8) and tumor-derived (P=8.3x10-5) pancreatic tissues. The high linkage disequilibrium (LD) between this variant and the O blood group generating deletion variant in exon 6 of ABO suggested that nonsense-mediated decay (NMD) of the “O” mRNA could explain the eQTL. However, knock-down of crucial NMD regulators did not influence decay of the ABO “O” mRNA, indicating that a gene regulatory element influenced by pancreatic cancer risk alleles may underlie the eQTL. Conclusions: We have identified cis-eQTLs representing potential functional regulatory variants in the pancreas and generated a rich dataset for further studies on gene expression and regulation in pancreatic tissues. Citation Format: Laufey T. Amundadottir, Soren Lykke Andresen, Wenming Xiao, Jason Hoskins, Ashley Jermusyk, Lauren Rost, Irene Collins, Jinping Jia, Michael Mobaraki, Bin Zhu, Robert Kurtz, Hemang Parikh, Lei Song, Meredith Yeager, Torben Jensen, William Bamlet, Nilanjan Chatterjee, Brian Wolpin, Jill Smith, Sara Olson, Gloria Petersen, Jianxin Shi, Mingfeng Zhang. Analysis of cis-eQTLs in normal and tumor-derived pancreatic tissues reveals functional insights, including for the 9q34.1 ABO pancreatic cancer risk locus [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1442. doi:10.1158/1538-7445.AM2017-1442

AbstractRenal agenesis is a devastating birth defect, and although genes encoding retinoic acid signaling components have been shown to be important for renal...Renal agenesis (RA) is one of the more extreme examples of congenital anomalies of the kidney and urinary tract (CAKUT). Bilateral renal agenesis is almost invariably fatal at birth, and unilateral renal agenesis can lead to future health issues including end-stage renal disease. Genetic investigations have identified several gene variants that cause RA, including EYA1, LHX1, and WT1. However, whereas compound null mutations of genes encoding α and γ retinoic acid receptors (RARs) cause RA in mice, to date there have been no reports of variants in RAR genes causing RA in humans. In this study, we carried out whole exome sequence analysis of two families showing inheritance of an RA phenotype, and in both identified a single candidate gene, GREB1L. Analysis of a zebrafish greb1l loss-of-function mutant revealed defects in the pronephric kidney just prior to death, and F0 CRISPR/Cas9 mutagenesis of Greb1l in the mouse revealed kidney agenesis phenotypes, implicating Greb1l in this disorder. GREB1L resides in a chromatin complex with RAR members, and our data implicate GREB1L as a coactivator for RARs. This study is the first to associate a component of the RAR pathway with renal agenesis in humans.

In pigs, the deep location of the common carotid artery and overlying sternomastoideus muscle in the neck has led to the recommendation for a surgical cutdown for common carotid access, as opposed to minimally invasive techniques for vascular access. We sought to determine if direct percutaneous common carotid artery access in piglets is attainable. Seventeen piglets were anesthetized and intubated. Under two-dimensional and color flow Doppler ultrasound guidance, a 21 gauge needle was utilized to access the right common carotid artery. Following arterial puncture, the Seldinger technique was applied to place a 4 or 5 French introducer. Upon completion of cardiac catheterization with intracoronary stem cell infusion the introducer was removed and manual pressure was applied to prevent hematoma development. Successful access with an introducer was achieved in all 17 piglets. The average weight was 8.5 ± 1.7 kg. One piglet developed a hematoma with hemorrhaging from the catheterization site and was euthanized. This piglet was given bivalirudin for the procedure. After this incident, subsequent piglets were not given anticoagulation and no other complications occurred. Ultrasound guided percutaneous common carotid artery access in piglets is attainable in a safe, reliable, and reproducible manner when performed by microvascular experts.

Objective To elucidate the genetic architecture of gene expression in pancreatic tissues. Design We performed expression quantitative trait locus (eQTL) analysis in histologically normal pancreatic tissue samples (n=95) using RNA sequencing and the corresponding 1000 genomes imputed germline genotypes. Data from pancreatic tumour-derived tissue samples (n=115) from The Cancer Genome Atlas were included for comparison. Results We identified 38 615 cis -eQTLs (in 484 genes) in histologically normal tissues and 39 713 cis -eQTL (in 237 genes) in tumour-derived tissues (false discovery rate <0.1), with the strongest effects seen near transcriptional start sites. Approximately 23% and 42% of genes with significant cis -eQTLs appeared to be specific for tumour-derived and normal-derived tissues, respectively. Significant enrichment of cis -eQTL variants was noted in non-coding regulatory regions, in particular for pancreatic tissues (1.53-fold to 3.12-fold, p≤0.0001), indicating tissue-specific functional relevance. A common pancreatic cancer risk locus on 9q34.2 (rs687289) was associated with ABO expression in histologically normal (p=5.8×10 −8 ) and tumour-derived (p=8.3×10 −5 ) tissues. The high linkage disequilibrium between this variant and the O blood group generating deletion variant in ABO (exon 6) suggested that nonsense-mediated decay (NMD) of the ‘O’ mRNA might explain this finding. However, knockdown of crucial NMD regulators did not influence decay of the ABO ‘O’ mRNA, indicating that a gene regulatory element influenced by pancreatic cancer risk alleles may underlie the eQTL. Conclusions We have identified cis -eQTLs representing potential functional regulatory variants in the pancreas and generated a rich data set for further studies on gene expression and its regulation in pancreatic tissues.

Background. We test the hypotheses that use of the Chest Pain Choice (CPC) decision aid (DA) would be similarly effective in potentially vulnerable subgroups but increase knowledge more in patients with higher education and trust in physicians more in patients from racial minority groups. Methods. This was a secondary analysis of a multicenter randomized trial in adults with chest pain potentially due to acute coronary syndrome. The trial compared an intervention group engaged in shared decision making (SDM) using CPC to a control group receiving usual care (UC). We assessed for subgroup effects based on age, sex, race, income, insurance, education, literacy, and numeracy. We dichotomized each characteristic and tested for interactions using regression models with indicators for arm assignment and study site. Results. Of 898 patients (451 DA, 447 UC), over 50% were female, over one-third were black, nearly one-third had a high school education or less, and over 60% had “low” health literacy. The DA did not increase knowledge more in patients with higher education ( P for interaction = 0.06) but did increase knowledge more in the “typical” than in the “low” numeracy subgroup (10.6% v. 4.7%, absolute difference [AD] = 5.9%, P for interaction = 0.025). The DA did not significantly increase patient trust in physicians in racial minorities ( P for interaction = 0.06) but did increase trust more in patients with “low” literacy compared with those with “typical” literacy (3.7% v. –1.4%, AD = 5.1, P for interaction = 0.011). Conclusions. CPC benefited all sociodemographic groups to a similar extent, with greater knowledge transfer in patients with higher numeracy and greater physician trust in patients with “low” health literacy. Tailoring SDM interventions to patient characteristics may be necessary for optimal effectiveness.