Citations

Abstract Introduction: Terminal duct lobular unit (TDLU) involution, an age-related physiological process, is characterized by the reduction of size and numbers. Reduced involution is associated with higher mammographic density, a strong breast cancer risk factor. Both factors predict risk of developing breast cancer among women with benign disease. Given that prior studies have been conducted mainly in White women, we compared the extent of TDLU involution among Western and Asian breast cancer cases to describe potential racial heterogeneity in breast cancer etiology. Method: We obtained three TDLU involution metrics (count/100 mm2, mean span, and mean acini count/TDLU; all inversely correlated with TDLU involution) measured in benign breast tissue sections from 379 Chinese (254 luminal A and 125 core basal phenotype [CBP] cases) and 476 Polish (407 luminal A and 69 CBP) breast cancer cases. Polytomous logistic regression was performed using tertiles of TDLU measures as ordinal dependent variable and race as an independent variable. Covariates included age, body mass index, and parity. Analyses were performed separately by age group (<50, ≥50) and subtype (luminal A and CBP). Results: Among luminal A cases, Chinese had significantly greater TDLU count compared with Polish in both age groups (ORtrend= 11.0; 95% CI=2.80-43.2; Ptrend=0.001 for age<50; ORtrend= 12.1; 95% CI=5.12-28.7; Ptrend=1E-08 for age≥50). In addition, Chinese were more likely to have greater mean span and acini count among younger cases (ORtrend=2.5; 95% CI=1.44-4.28; Ptrend=0.001 for mean span and ORtrend=7.4; 95% CI=4.13-13.4; Ptrend=3E-11 for acini count) but not among older cases. Among CBP cases, Chinese were more likely to have greater acini count compared to Polish only among younger women (ORtrend=2.6; 95% CI=1.12-6.95; Ptrend=0.03 for age<50). Conclusion: We found Chinese were more likely to have reduced TDLU involution compared to Polish cases after accounting for potential confounders, with greater differences for luminal A and younger women. Studies of TDLU involution in diverse populations are needed to confirm and understand whether population difference in TDLU involution metrics are related to age at breast cancer onset and risks for specific tumor subtypes. Citation Format: Hyuna Sung, Changyuan Guo, Jennifer Guida, Shan Zheng, Erni Li, Jing Li, Nan Hu, Joseph Deng, Montserrat Garcia-Closas, Jonine Figueroa, Mark Sherman, Gretchen Gierach, Ning Lu, Xiaohong R. Yang. Racial variation in terminal duct lobular unit (TDLU) involution in Chinese and Polish breast cancer patients [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 5290. doi:10.1158/1538-7445.AM2017-5290

Abstract By regulating gene expression networks that mediate neoplastic behavior, epigenetic protein complexes are the ultimate effectors of oncogenic pathways. This hierarchical position of epigenetic pathways within the mechanisms that regulate cancer makes them ideal candidates for therapeutic targets. The current work was designed to characterize the role of the K9H3 Histone Methyltransferase (HMT) pathway in mediating oncogenic signals downstream of Aurora Kinase A (AurkA), with the goal of designing efficient combinatorial therapies against PDAC. Affinity protein purification, combined with mass spectrometry, demonstrates that HP1γ isolated from mitotic cells interacts with AurkA and the HMTs, G9a and GLP. We also find that this complex is critical for mitotic progression and cell proliferation. Congruently, treatment of PDAC cells with individual drugs against AurkA or HP1-HMT inhibits cell growth by inducing senescence, a cytostatic response. However, the combination of these agents has a synergistic effect of reducing cell growth in both, monolayer and spheroid cultures to result in a cytotoxic effect. Confocal and electron microscopy, along with cell cycle analysis, demonstrate that the cytotoxic effect of this combination is due to induction of mitotic catastrophe, a distinct form of cell death that occurs during mitosis. Molecularly, the combination of AurkA and HP1-HMT inhibition bypasses G2/M arrest with downregulation of the Chk1-Cdc25c pathway. In vivo treatment of PDAC orthotopic xenografts with the HP1-HMT inhibitor alone demonstrated reduced PDAC growth, and increased efficacy in PDAC growth reduction was observed in combination with the AurkA inhibitor over either individual treatment. Thus, our data demonstrate a novel AurkA-HP1-HMT mitotic pathway that holds promise for potential pharmacological targeting in combinatorial therapy for this malignancy. Citation Format: Angela Mathison, Ann Salmonson, Mckenna Missfeldt, Thiago de Assuncao, Jennifer Bintz, Trace Christensen, Sarah Kossak, Asha Nair, Juan Iovanna, Robert Huebert, Gwen Lomberk. Pharmacological targeting of the Aurora A and Histone 3 lysine 9 methyltransferase pathways in pancreatic cancer induces mitotic catastrophe [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 4060. doi:10.1158/1538-7445.AM2017-4060

Abstract Background: Understanding heterogeneity within individual breast tumors is key to the ability to predict therapeutic outcome. Molecular heterogeneity is commonly evaluated based on genomic features, including mRNA abundance, gene copy number events, and somatic mutations. The expression profile and activation state of key proteins is widely recognized as another key element in defining tumor heterogeneity. We have taken advantage of NanoString 3D Biology™ technology (for research use only) and curated nCounter Vantage 3DTM Solid Tumor Assay to interrogate a survey panel of HER2-positive breast tumors with the ultimate goal of determining key relationships between multiple genomic and proteomic profiles in individual tumors. Methods: We analyzed samples from 24 HER2+ breast cancer patients using NanoString technology to quantify the expression profile for over 25 total and phospho signaling proteins, including PI3K/MAPK/EGFR/HER2, 770 mRNA corresponding to 13 canonical cancer pathways, and 104 somatic mutations and small INDELS that are commonly associated with cancer, including 8 known PIK3CA mutations. These analyses were carried out in a matched fresh frozen and FFPE samples on the nCounter paltform. Data were analyzed by nSolver to identify genotype specific expression profiles across the 24 samples. Results: In our proof-of-concept data set, we successfully demonstrate that NanoString’s 3D biology Technology shows concordance across both FFPE and fresh frozen sample types for DNA, RNA, and protein. NanoString analysis also showed high concordance to gold-standard techniques used to assess genotype and RNA expression profiles. The combination of digital DNA, RNA, and protein data from our HER2+ breast cancer samples yielded potentially actionable data based on mapping of mutational status as the driver of key differences in protein expression and mRNA abundance of the signaling targets profiled. This work sheds new light on HER2+ breast cancer biology and the interplay between genomic and proteomic profiles while setting the stage for future studies that further probe the differences observed in this sample set. Conclusions: Simultaneous analysis of mutational status (SNV) and expression at the level of both mRNA and protein promises to enable a more detailed view of the relationship between genotype and the biological and clinical behavior of key tumor types. The NanoString Vantage 3DTM Solid Tumor platform provides a rapid, reliable, and economic means of assessing these analytes simultaneously. The application of these analytes to models that make clinically actionable predictions will require additional analyses of large sample cohorts, but such analysis is quite feasible using a variety of sample types. Acknowledgements: Supported in part by grants from the Breast Cancer Research Foundation and the 26.2 with Donna Foundation. Citation Format: Sarayna Chumsri, Daniel J. Serie, Brian M. Necela, Jennifer M. Kachergus, Bianca C. Axenfeld, Gokhan Demirkan, Gavin Meredith, P. Martin Ross, Anisha Kharkia, Erin Piazza, Afshin Mashadi-Hossein, Sarah Warren, Sarah A. McLaughlin, Joseph Beechem, Gary Geiss, E. Aubrey Thompson. Simultaneous analysis of the mutational landscape and RNA and protein expression profile of HER2-positive breast cancer using 3D BiologyTM [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 3377. doi:10.1158/1538-7445.AM2017-3377

Abstract Background: Large-scale genome-wide association studies (GWAS) have identified ~35 loci associated with epithelial ovarian cancer risk. However, these genetic loci together explain only a small portion of the heritability of this malignancy. The large majority of the GWAS-identified variants are located in non-coding regions, thus possible causal genes in these loci remain largely unknown. We performed a transcriptome-wide association study (TWAS) to search for novel genetic loci for ovarian cancer risk and plausible causal genes at GWAS-identified loci. Method: Transcriptome data from normal ovarian tissue samples (n=68) and all tissue samples (n = 369), along with their high-density genotyping data, obtained from only European descendants included in the Genotype-Tissue Expression Project (GTEx), were used to build ovarian linear prediction models and cross-tissue models (to increase statistical power) using the elastic net method. Based on model performance, we evaluated 17,121 genes for their cis-predicted gene expressions in relation to ovarian cancer risk using summary statistics data generated in GWAS of ovarian cancer from 25,509 cases and 40,941 controls. MetaXcan was used to integrate gene expression prediction model with summary statistics. Results: We identified 35 genes with predicted expression levels associated with ovarian cancer risk at P value < 2.2 × 10-6, the Bonferroni corrected significance level for multiple comparisons. Of these, 12 genes at 4 genetic loci are located ≥500kb away from risk SNPs previously reported in GWAS, representing potential novel genetic loci for ovarian cancer risk. The remaining 23 genes at 12 loci are located within known ovarian cancer risk loci. Fifteen of these genes at the 12 loci have not been reported in previous studies. Analyses by ovarian cancer histological subtypes showed that the majority of these 35 genes are associated with serous invasive carcinoma. Several new associations were identified in histological subtype analyses. Conclusion: In this TWAS we identified multiple genes with predicted expressions related to ovarian cancer risk and provide substantial new information to enhance the understanding of ovarian cancer biology and genetics. Citation Format: Yingchang Lu, Joellen M. Schildkraut, Thomas A. Sellers, Lang Wu, Xingyi Guo, Bingshan Li, Y. Ann Chen, Jennifer B. Doherty, Simon Gayther, Ellen L. Goode, Hae Kyung Im, Siddhartha Kar, Kate Lawrenson, Ani W. Manichaikul, Jennifer B. Permuth, Brett M. Reid, Jamie K. Teer, Paul Pharoah, Wei Zheng, Jirong Long. Transcriptome-wide association study among 66,450 women to identify candidate susceptible genes for ovarian cancer 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 1308. doi:10.1158/1538-7445.AM2017-1308

Abstract Epithelial ovarian cancer (EOC) is a rare but deadly disease for which there is notably poorer survival in women of African Ancestry (AA) compared to women of European Ancestry (EA). Previous EA-based genome-wide association studies (GWAS) have identified 30 common, low penetrant EOC susceptibility alleles. Using the custom-designed 533,631 SNP Illumina OncoArray and imputation to ~12 million genetic variants in the 1000 Genomes Phase 3, we conducted a GWAS in 755 AA EOC cases, including 537 high-grade serous ovarian cancer (HGSOC) cases, and 1,235 AA controls from the Ovarian Cancer Association Consortium (OCAC). We identified novel susceptibility loci with suggestive evidence of association with EOC, based on a threshold of P<1x10-6, at three distinct loci including 10p15.1 (lead SNP rs4525119, intronic to AKR1C3, P=4.9 x 10-7, minor allele frequency [MAF]=0.33), 3p25.3 (lead SNP rs7643459, intronic to LOC101927394, P=8.4 x 10-7, MAF=0.36), and 4q13.3 (lead SNP rs4286604, 15 kb 3’ of UGT2A1, P=8.5x10-7, MAF=0.27). In analysis of HGSOC, we identified suggestive evidence of association at six distinct loci including 5q11.2 (lead SNP rs37792, 132 kb 5’ of FST, P=6.0x10-8, MAF=0.34), Xq27.2 (lead SNP rs57403204, 81 kb 3' of MAGEC1, P=1.7x10-7, MAF=0.06), 10p15.1 (lead SNP rs79079890, LOC105376360 intronic, P=3.0x10-7, MAF=0.03), 17p25.1 (lead SNP rs66459581, 5 kb 5’ of PRPSAP1, P=5.1x10-7, MAF=0.23), 15p12 (lead SNP rs116046250, GABRG3 intronic, P=8.7x10-7, MAF=0.05), and 4q21.21 (lead SNP rs192876988, 30 kb 3’ of GK2, P=9.2x10-7, MAF=0.05). These SNPs showed no evidence of association with risk in the OCAC EA GWAS including up to 23,543 EOC cases and 29,444 controls. Of the SNPs identified with suggestive evidence of association in our GWAS, two are located near genes known to regulate hormones and previously reported in relation to diseases of the ovary (AKR1C3 and FST), two have been linked to cancer (AKR1C3 and MAGEC1) and one represents testis-specific expression (GK2). Of the 30 SNPs identified previously in a EA EOC GWAS, we observed nominally significant associations (P<0.05) with consistent direction of effect for eight SNPs in AA women. Our investigation presents evidence of (1) variants for EOC shared among EA and AA women and (2) novel EOC risk loci of importance for AA women. Citation Format: Ani Manichaikul, Lauren C. Peres, Xin-Qun Wang, Kate Lawrenson, Sarah Abbott, Ann G. Schwartz, Anna H. Wu, Edward Peters, Patricia G. Moorman, Michele L. Cote, Melissa Bondy, Linda Kelemen, Ellen L. Goode, Jill Barnholtz-Sloan, Simon A. Gather, Andrew Berchuck, Jennifer A. Doherty, Paul Pharoah, Joellen Schildkraut. Identification of novel epithelial ovarian cancer loci in women of African ancestry from the Ovarian Cancer Association Consortium [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 1307. doi:10.1158/1538-7445.AM2017-1307

AbstractBackgroundThe CYP11A1 gene encodes the cytochrome P450 side‐chain cleavage enzyme, which is essential for steroid formation. Recessive variants in this gene can lead to impairment of sexual differentiation caused by a complete or partial loss of steroid hormone production. The phenotypic spectrum in affected 46XY males may vary from surgically repairable defects including cryptorchidism and hypospadias to complete feminization of external gonads, accompanied by symptoms of adrenal dysfunction.MethodsWhole‐exome sequencing (WES) of a 12‐year‐old male proband and his parents was performed after a protracted diagnostic odyssey failed to uncover the cause of his primary adrenal insufficiency. Of note, the proband had early symptomatology and corrective surgery for hypospadias, raising suspicion for a disorder of steroidogenesis.ResultsWES identified compound heterozygous variants in CYP11A1 including a novel canonical splice site variant (c.425+1G>A) and a previously reported p.E314K variant, which were consistent with a diagnosis of congenital adrenal insufficiency with partial 46XY sex reversal.ConclusionCongenital adrenal insufficiency with 46XY sex reversal is a rare disorder that is characterized by dysregulation of steroid hormone synthesis, leading to adrenal and gonadal dysfunction. In this report, we describe a patient with adrenal insufficiency, hypospadias, and skin hyperpigmentation who was found to have a novel c.425+1G>A variant in trans with the p.E314K variant in CYP11A1. We performed structural analyses to examine the effect of the p.E314K variant on protein function and show that it falls in the core of the protein may disrupt cholesterol binding in the active site.

Skull base osteomyelitis in the setting of granulomatosis with polyangiitis (GPA) is rare and entails significant diagnostic challenges. We present a case of a 65-year-old Caucasian man with a history of rheumatoid arthritis, off immunosuppression for 18 months, who presented with 2 years of chronic headaches, severe fatigue, saddle nose deformity and 20-kilogram unintentional weight loss. Maxillofacial CT revealed an extensive destructive sinonasal and erosive skull base process. Laboratory evaluation showed equivocal elevation of antiproteinase 3 antibodies with negative antineutrophil cytoplasmic antibody panel. Biopsy of the skull base/clivus revealed necrotising granulomatous inflammation with focal vasculitis consistent with GPA, and multiple bone cultures were positive for Pseudomonas aeruginosa. This patient was diagnosed concurrently with GPA and P. aeruginosa skull base osteomyelitis. He was started on a 6-week course of cefepime intravenously and oral prednisone, with the plan to initiate rituximab infusion 2 weeks after initiation of antibiotic therapy.