Citations

Abstract Genomic analyses of cutaneous melanoma (CM) have yielded biological and therapeutic insights, but understanding of non-ultraviolet (UV)-derived CMs remains limited. Deeper analysis of acral lentiginous melanoma (ALM), a rare sun-shielded melanoma subtype associated with worse survival than CM, is needed to delineate non-UV oncogenic mechanisms. We thus performed comprehensive genomic and transcriptomic analysis of 34 ALM patients. Unlike CM, somatic alterations were dominated by structural variation and absence of UV-derived mutation signatures. Only 38% of patients demonstrated driver BRAF/NRAS/NF1 mutations. Contrasting with CM, we observed PAK1 copy gains in 15% of patients, and somatic TERT translocations, copy gains, and missense and promoter mutations, or germline events, in 41% of patients. We further show that in vitro TERT inhibition has cytotoxic effects on primary ALM cells. These findings provide insight into the role of TERT in ALM tumorigenesis, and reveal preliminary evidence that TERT inhibition represents a potential therapeutic strategy in ALM. Citation Format: Winnie S. Liang, William Hendricks, Jeffrey Kiefer, Jessica Schmidt, Shobana Sekar, John Carpten, David W. Craig, Jonathan Adkins, Lori Cuyugan, Zarko Manojlovic, Rebecca F. Halperin, Adrienne Helland, Sara Nasser, Christophe Legendre, Laurence H. Hurley, Karthigayini Sivaprakasam, Douglas B. Johnson, Holly Crandall, Klaus J. Busam, Victoria Zismann, Valerie De Luca, Jeeyun Lee, Aleksandar Sekulic, Charlotte E. Ariyan, Jeffrey Sosman, Jeffrey Trent. Integrated genomic analyses reveal frequent TERT aberrations in acral melanoma [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 3389. doi:10.1158/1538-7445.AM2017-3389

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

Abstract BACKGROUND: Incidence of glioma varies significantly by sex, and most glioma histologies occur with greater incidence in males. Previous analyses have examined the impact of estrogen exposure as a risk factor for these tumors, but have found results of varying significance and low effect size. There may be differences in effect of previously discovered risk alleles that contribute to sex differences. METHODS: Using data collected for three previous glioma GWAS in European-ancestry populations (MD Anderson Cancer Center, the San Francisco Adult Glioma Study, and the Glioma International Case Control Study) we assessed sex-specific effects for 14 previously identified and 13 newly identified glioma risk SNPs (27 total) overall and for glioblastoma (GBM) and non-GBM tumors separately. There were 3,892 male cases (59% GBM), 4,522 male controls, 2,500 female cases (52% GBM) and 4,940 female controls. Sex-specific odds ratios (ORM and ORF), 95% confidence intervals (95% CI) and p values (pM and pF) were generated using stratified logistic regression models. Data from each study were analyzed separately and combined using inverse variance weighted meta-analysis. Results were considered statistically significant at p<6.2x10-4. RESULTS: In GBM, rs11979158 (7p11.2, pM=1.01x10-10, ORM=1.43 [95% CI: 1.28-1.59]; pF=3.43x10-3, ORF=1.22 [95% CI: 1.07-1.39]) and rs2562152 (16p13.3, pM=5.59x10-4, ORM=1.23 [95% CI: 1.09-1.39]; pF=1.22x10-1, ORF=1.12 [95% CI: 0.97-1.29]) had significant effect in males only. In non-GBM gliomas, rs12076373 (1q44, pM=3.56x10-7, ORM=1.41, 95% CI: 1.23-1.61; pF=1.76x10-2, ORF=1.20, 95% CI: 1.03-1.38), rs11979158 (7p11.2, pM=1.77x10-5, ORM=1.32 [95% CI: 1.16-1.49]; pF=2.73x10-1, ORF=1.08 [95% CI: 0.94-1.24]), and rs3751667 (16p13.3, pM=9.44x10-7, ORM=1.30 [95% CI: 1.17-1.44]; pF=5.18x10-2, ORF=1.13 [95% CI: 1.00-1.28]) had significant effect in males only. Effect size for rs55705857 (8q24.21) varied significantly by sex, with ORM=2.63 (95% CI: 2.24-3.09, pM=4.42x10-32), as compared to ORF=3.95 (95% CI: 3.28-4.76, pF=1.82x10-47). A sensitivity analysis was performed due to allele frequency heterogeneity by study and results did not change. CONCLUSIONS: Sex differences and other demographic differences in cancer susceptibility can provide important clues to etiology, and these differences can be leveraged for discovery in genetic association studies. Significant differences in effect size may suggest variation in genetic effect of risk alleles or in unidentified risk factors that vary in prevalence or effect by sex. There may also be differences in the distribution of molecular subtypes within each histology by sex. Further investigation using an agnostic approach may further elucidate the relationship between effect of risk alleles and sex. Citation Format: Quinn T. Ostrom, Ben Kinnersley, Margaret Wrensch, Jeanette E. Eckel-Passow, Georgina Armstrong, Terri Rice, Yanwen Chen, John Wiencke, Lucie McCoy, Helen Hansen, Christopher Amos, Jonine L. Bernstein, Elizabeth B. Claus, Dora Il'yasova, Christoffer Johansen, Daniel Lachance, Rose Lai, Ching C. Lau, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, Richard S. Houlston, Robert B. Jenkins, Beatrice Melin, Melissa Bondy, Jill S. Barnholtz-Sloan. Estimating sex-specific effects of genetic loci associated with glioma risk [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 1315. doi:10.1158/1538-7445.AM2017-1315

Abstract BACKGROUND: Glioma accounts for ~27% of all primary brain tumors and is responsible for ~13,000 cancer-related deaths in the US each year. Glioma tumors can be broadly classified into glioblastoma (GBM) and lower-grade non-GBM. Typically gliomas have a poor prognosis irrespective of medical care, with the most common form, GBM, having a five-year survival rate of only 5%. While genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, individual studies have had limited power to identify risk loci. METHODS: We performed the largest glioma GWAS to date, comprising a meta-analysis of six existing GWAS (6,405 cases, 14,100 controls) as well as new GWAS from the Glioma International Case Control Consortium (GICC; 4,572 cases and 3,286 controls) and University of California, San Francisco (UCSF)-Mayo (1,519 cases, 804 controls), totaling 12,496 cases (6,191 classified as GBM, 5,819 as non-GBM) and 18,190 controls. RESULTS: We identified five new risk loci for GBM at 1p31.3 (rs12752552; near JAK1, P=2.04×10-9, odds ratio (OR)=1.22), 11q14.1 (rs11233250; P=9.95×10-10, OR=1.24), 16p13.3 (rs2562152; near MPG, P=1.93x10-8, OR=1.21), 16q12.1 (rs10852606; HEATR3, P=1.29×10-11, OR=1.18), 22q13.1 (rs2235573; P=1.76×10-10, OR=1.15) and eight for non-GBM at 1q32.1 (rs4252707; MDM4, P=3.34×10-9, OR=1.19), 1q44 (rs12076373; AKT3, P=2.63×10-10, OR=1.23), 2q33.3 (rs7572263; near IDH1, P=2.18×10-10, OR=1.20), 3p14.1 (rs11706832; LRIG1, P=7.66×10-9, OR=1.15), 10q24.33 (rs11598018; OBFC1, P=3.39×10-8, OR=1.14), 11q21 (rs7107785; P=3.87×10-10, OR=1.16), 14q12 (rs10131032; P=5.07x10-11, OR=1.33) and 16p13.3 (rs3751667; P=2.61×10-9, OR=1.18). Case-only analyses confirmed the specificity of 11q14.1, 16p13.3 and 22q13.1 associations for GBM and 1q44, 2q33.3, 3p14.1, 11q21 and 14q12 for non-GBM tumors. In the combined meta-analysis, among previously published glioma risk SNPs, those for all glioma at 17p13.1 (TP53), GBM at 5p15.33 (TERT), 7p11.2 (EGFR), 9p21.3 (CDKN2B-AS1) and 20q13.33 (RTEL1) and for non-GBM at 8q24.21 (CCDC26), 11q23.2, 11q23.3 (PHLDB1) and 15q24.2 (ETFA) showed even greater evidence for association. SNPs at 10q25.2 and 12q12.1 for non-GBM tumors retained genome-wide significance (i.e. P<5.0x10-8). Associations at the previously reported loci for GBM at 3q26.2 (near TERC) and 12q23.33 (POLR3B) did not retain statistical significance. CONCLUSIONS: Our findings substantiate genetic susceptibility to GBM and non-GBM glioma being highly distinct, consistent with their distinctive molecular profiles presumably resulting from different etiological pathways. Functional analyses should lead to further insights into the biological basis of the different glioma histologies. Such information can inform gene discovery initiatives and therefore have a measurable impact on the successful development of new therapeutic agents. Citation Format: Ben Kinnersley, Beatrice S. Melin, Jill S. Barnholtz-Sloan, Margaret R. Wrensch, Christoffer Johansen, Dora Il’yasova, Quinn Ostrom, and members of GICC, Karim Labreche, Jeanette E. Eckel-Passow, Paul A. Decker, Marianne Labussière, Ahmed Idbaih, Khe Hoang-Xuan, Anna-Luisa Di Stefano, Karima Mokhtari, Jean-Yves Delattre, Pilar Galan, Konstantinos Gousias, Johannes Schramm, Minouk J. Schoemaker, Sarah J. Fleming, Stefan Herms, Stefanie Heilmann, Marcus M. Nöthen, Heinz-Erich Wichmann, Stefan Schreiber, Anthony Swerdlow, Mark Lathrop, Matthias Simon, Marc Sanson, Preetha Rajaraman, Stephen Chanock, Martha Linet, Zhaoming Wang, Meredith Yeager, Rose K. Lai, Elizabeth B. Claus, Sara H. Olson, Robert B. Jenkins, Richard S. Houlston, Melissa L. Bondy. Genome-wide association study of glioma reveals specific differences in genetic susceptibility to glioblastoma and non-glioblastoma [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 1302. doi:10.1158/1538-7445.AM2017-1302

Dietitians have extensive training and are considered the experts in medical nutrition therapy (MNT). Although dietitian competencies for MNT are well established, competencies that account for the expanded roles of dietitians working in transplantation have not been developed. These expanded roles require a better understanding of transplant processes, regulations, and even the business side of transplant, novel concepts to most dietitians. Therefore, we proposed a standardized framework of transplant-specific competencies for dietitians practicing in transplantation. These competencies can help improve and standardize initial and ongoing training for transplant dietitians moving forward, ultimately leading to improved patient care for transplant candidates, recipients, and donors.

Abstract Objectives The purpose of this systematic review is to provide a comprehensive overview on the clinical course, perinatal outcome, and effectiveness of prenatal management options for pericardial teratoma. Methods A comprehensive search including Ovid MEDLINE, Ovid EMBASE, and Scopus was conducted from inception to September 2016. All studies that reported the prenatal course of pericardial teratoma in singleton or twin gestations were considered eligible. Standardized forms were used for data abstraction by two independent reviewers. Results Out of 217 screened abstracts, 59 studies reporting 67 fetuses with pericardial teratoma were included. Twenty‐three singleton fetuses and 3 fetuses in twin gestations underwent prenatal treatment, and 20 (76.9%) of them were hydropic at the time of intervention. Of those, 15/20 (75%) had a favorable outcome. In the non‐intervention group ( n = 41), 26 (63.4%) developed hydrops, and out of those, 8 (30.8%) had a favorable outcome. Conclusion Prenatal fluid drainage and other prenatal techniques have been utilized in the treatment of intrapericardial teratoma. While most fetuses tolerated pericardiocentesis, the neonatal benefit of this procedure is still uncertain, and outcomes of other interventions had variable success. Prenatal intervention for pericardial teratoma may be an option in specialized units but, given the maternal and fetal risks, needs careful consideration. © 2017 John Wiley & Sons, Ltd.

Abstract Background: Many cancers share specific genetic risk factors, including both rare high-penetrance mutations and common SNPs identified through genome-wide association studies (GWAS). However, little is known about the overall shared heritability across cancers. Quantifying the extent to which two distinct cancers share genetic origin will give insights to shared biological mechanisms underlying cancer and inform design for future genetic association studies. Methods: In this study, we estimated the pair-wise genetic correlation between six cancer types (breast, colorectal, lung, ovarian, pancreatic, and prostate) using cancer-specific GWAS summary statistics data based on 66,958 case and 70,665 control subjects of European ancestry. We also estimated genetic correlations between cancers and 14 noncancer diseases and traits. Results: After adjusting for 15 pair-wise genetic correlation tests between cancers, we found significant (P < 0.003) genetic correlations between pancreatic and colorectal cancer (rg = 0.55, P = 0.003), lung and colorectal cancer (rg = 0.31, P = 0.001). We also found suggestive genetic correlations between lung and breast cancer (rg = 0.27, P = 0.009), and colorectal and breast cancer (rg = 0.22, P = 0.01). In contrast, we found no evidence that prostate cancer shared an appreciable proportion of heritability with other cancers. After adjusting for 84 tests studying genetic correlations between cancer types and other traits (Bonferroni-corrected P value: 0.0006), only the genetic correlation between lung cancer and smoking remained significant (rg = 0.41, P = 1.03 × 10−6). We also observed nominally significant genetic correlations between body mass index and all cancers except ovarian cancer. Conclusions: Our results highlight novel genetic correlations and lend support to previous observational studies that have observed links between cancers and risk factors. Impact: This study demonstrates modest genetic correlations between cancers; in particular, breast, colorectal, and lung cancer share some degree of genetic basis. Cancer Epidemiol Biomarkers Prev; 26(9); 1427–35. ©2017 AACR.

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.