Citations

Abstract Background: Extranodal follicular dendritic cell sarcoma (FDCS) is an exceedingly rare tumor type that is limited to few cases in the literature. Given the rarity of this tumor, there is a lack of genetic understanding of this disease resulting in a non-individualized plan of care for patients with this disease. Herein, we are the first to describe extensively molecularly the DNA and RNA of this tumor. Methods: Under an IRB approved protocol, the patient's tumor and whole blood was freshly frozen for molecular analysis. We performed Next Generation Sequencing (NGS) genomic profiling including exome capture, mate pair and mRNA sequencing on this tumor. Exome and mRNA data were processed through Mayo's Bioinformatics Core standard pipelines, GENOME GPS 1.2.1 and MAPRSeq v1.2.1. Mutations and indels were prioritized depending on whether or not they belonged to known cancer associated genes. Copy number variations (CNVs) in Exome and Mate Pair data was found through PatternCNV v 1.0.1 and fusion transcripts were found using SNOWSHOES-FTD and Tophat-Fusion 2.0.6. Results: At the genomic level large scale genomic rearrangements were detected, including chr19 and chr20 trisomy, chr15q and chr17q segmental duplications result in two intra-chromosomal fusion genes, and translocations leading to four inter-chromosomal fusion genes between chr15 and chr17. Of particular interest is a stop codon gain in the CLTC1 (chr22) gene, which is involved in the mitotic spindle organization which has been associated with meningiomas and breast tumorigenesis. The new stop codon is before the site required for the recruitment of the proteins to the spindle. The large scale genomic rearrangement described above is consistent with this defective spindle assembly hypothesis. Another intriguing mutation detected in the VEGFR1 (chr13) gene leads to a 45% mis-spliced transcript. VEGFR1 is thought to modulate VEGFR2 which plays an essential role in angiogenesis, by acting as a decoy receptor. Therefore the loss of function of VEGFR1 might lead to hyper-activity of VEGFR2 pathway and a potential therapeutic strategy is to directly inhibit the VEGFR2 pathway. Furthermore missense mutations in the ATM (chr11) and TP53 (chr17) genes were found. PARP inhibitors have been used with success for cancer with defects in the ATM gene. Finally a novel fusion transcript of HDGRFP3 (chr15) and SHC4 (chr15) was identified. Such fusion results in an overexpressed SHC4 gene which has been associated with metastatic melanomas. Conclusions: In summary, genomic profiling of a rare thyroid FDCS identified drug targetable genes as well as changes related to tumor etiology. Future work is necessary to determine the functional significance of these molecular findings and whether they will predict benefit to targeted therapies. Citation Format: Jaime I. Davila, Jason Starr, Steven Attia, Chen Wang, Xue Wang, Brian Necela, Casler John, David Menke, Vivek Sarangi, Gavin Oliver, Richard Joseph, John Copland, Alexander Parker, E. Aubrey Thompson, Robert Smallridge, Yan W. Asmann. Extensive genomic profiling of a rare extranodal-follicular dendritic cell sarcoma: Implications for future individualized therapy. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1894. doi:10.1158/1538-7445.AM2014-1894

Abstract Introduction: Current models to predict breast cancer risk do not differentiate risk for estrogen receptor (ER) positive and negative breast cancer (BC), despite growing evidence that these tumors are biologically very different. We hypothesized that women with ER+ BC cancers have different clinical risk factors and histologic findings on prior benign breast biopsies than those with ER- BC. Methods: After IRB approval, we examined associations of age at benign biopsy and histologic features of the benign biopsy with ER status of incident BCs within the Mayo Benign Breast Disease Cohort. Benign biopsy slides were reviewed for extent of lobular involution and degree of epithelial proliferation by a single breast pathologist blinded to BC events. Invasive BCs occurring within 15 years after benign biopsy were classified as ER+ if ER staining was >1%. BC case-only associations with ER status were evaluated using multivariate logistic regression. Full-cohort hazard ratios (HR) and 95% confidence intervals (CI) for risk of ER-specific subtypes were estimated using Cox proportion hazards regression. Results: Among 13,410 women undergoing a benign breast biopsy from 1967-2001, 656 invasive BCs (459 ER+, 106 ER, 106 unknown) occurred within 15 years. Women who developed ER+ and ER- BCs were similar in age at the time of their prior benign breast biopsy (p=0.34). Although benign biopsies in women who later developed ER+ BC were more likely to show complete involution (23% vs 15% for ER- BC), this was not statistically significant (p=0.06). However, the degree of epithelial proliferation was significantly associated with ER status of later BCs (p=0.001), with ER+ BCs more likely than ER- BCs to have had a prior biopsy with atypical hyperplasia (16% vs 8%), and ER+ BCs less likely than ER- BCs to have had a prior biopsy with proliferative disease without atypia (33% vs 52%); this association remained after multivariate adjustment (p=0.003). We further pursued the association of epithelial proliferation with differential risk of ER+ and ER- BC in our overall cohort of 13,410 women (Table 1). Compared to women with non-proliferative disease, women with proliferative disease +/- atypia had ∼2-fold hazard ratios for ER- BC, whereas hazard ratios for ER+ BC were higher in women with atypical hyperplasia (∼4-fold) compared to proliferative disease. Hazard Ratio of ER+ and ER- BC within 15 years of BBD based upon degree of epithelial proliferation at benign biopsyCancer TypeGroupNN EventsHazard Ratio (95% CI)p-valueInvasive ER- ≤15 yearsNP8478421.00 (ref)<0.0001 PD4229542.63 (1.76, 3.93) AH70382.60 (1.22, 5.54) Invasive ER+ ≤15 yearsNP84782321.00 (ref)<0.0001 PD42291511.33 (1.09, 1.64) AH703744.41 (3.39, 5.73) NP=nonproliferative disease, PD=proliferative disease without atypia; AH=atypical hyperplasia Conclusion: ER+ and ER- breast cancers appear to have different features on prior benign breast biopsy, with atypical hyperplasia showing increased risk for both types of breast cancer, but a greater risk for ER+ tumors. Citation Format: Amy C Degnim, Derek C Radisky, Robert A Vierkant, Ryan D Frank, Marlene H Frost, Vernon S Pankratz, Celine M Vachon, Tanya L Hoskin, Julie M Cunningham, Chen Wang, Jean-Pierre Kocher, Teresa M Allers, Joanne L Johnson, Tina J Hieken, Karthik Ghosh, Lynn C Hartmann, Daniel W Visscher. Histologic features of benign breast biopsy tissue and association with ER positive and ER negative breast cancer in the Mayo BBD cohort study [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-10-06.

Abstract Objectives and Rationale: Structural variants (SV) including large copy number aberrations (CNV), translocations, inversions, and large insertions and deletions (INDEL) play a critical role in tumorigenesis and progression. In fact, we now know that tumors can be categorized according to the size of mutations harbored. In several cancers, including ovarian and breast cancer, the large structural mutations, rather than single site mutations, play a dominate role in tumor etiology. Therefore, it's critical to implement reliable algorithm for the detection of structural variants in DNA sequencing data. Mate-pair sequencing is a protocol specifically implemented for detection of the whole-genome level structural variants. It requires less sequencing depth therefor is cost effective, and enables the detection of CNVs, translocations, and inversions simultaneously. However, so far there has been no reliable bioinformatics pipeline for the analyses of the mate-pair sequencing data. Methods: Our novel algorithm, the SnowShoes-SV, is an exhaustive search algorithm designed specifically for mate-pair DNA sequencing data analyses. It calls the SVs based on disconcordant read pairs. The false SVs are filtered according to the following criteria: (i) the number of the supporting read pairs; (ii) the lack of reads from control data that implicate SV at the same region; (iii) the mappability and uniqueness of the region based on data from the ENCODE project; (iv) consistencies of the mapping orientations of the supporting read pairs; (v) the similar sizes between sequencing library and the two end read clusters. Results: Using a set of samples previously genotyped by aCGH, the SnowShoes-SV successfully detected all known CNVs and other SVs. It also identified copy number neutral translocations and inversions previously not identified by aCGH. In addition, the algorithm nominated novel SVs which are to be validated by PCR. Conclusions: SnowShoes-SV is a highly sensitive and specific algorithm for SV detection from the mate-pair DNA sequencing data. Citation Format: Yan W Asmann, Chen Wang, Brian M Necela, Xianfeng Chen, Jean-Pierre A Kocher, Matthew J Maurer, Thomas M Habermann, Susan L Slager, Andrew L Feldman, Anne J Novak, James R Cerhan, Edith A Perez, E Aubrey Thompson. An exhaustive algorithm for detecting copy number aberrations and large structural variants in whole-genome mate-pair sequencing data [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-07-03.

Abstract Motivation: RNA-seq has become the method of choice to quantify genes and exons, discover novel transcripts and detect fusion genes. However, reliable variant identification from RNA-seq data remains challenging because of the complexities of the transcriptome, the challenges of accurately mapping exon boundary spanning reads and the bias introduced during the sequencing library preparation. Method: We developed RVboost, a novel method specific for RNA variant prioritization. RVboost uses several attributes unique in the process of RNA library preparation, sequencing and RNA-seq data analyses. It uses a boosting method to train a model of ‘good quality’ variants using common variants from HapMap, and prioritizes and calls the RNA variants based on the trained model. We packaged RVboost in a comprehensive workflow, which integrates tools of variant calling, annotation and filtering. Results: RVboost consistently outperforms the variant quality score recalibration from the Genome Analysis Tool Kit and the RNA-seq variant-calling pipeline SNPiR in 12 RNA-seq samples using ground-truth variants from paired exome sequencing data. Several RNA-seq–specific attributes were identified as critical to differentiate true and false variants, including the distance of the variant positions to exon boundaries, and the percent of the reads supporting the variant in the first six base pairs. The latter identifies false variants introduced by the random hexamer priming during the library construction. Availability and implementation: The RVboost package is implemented to readily run in Mac or Linux environments. The software and user manual are available at http://bioinformaticstools.mayo.edu/research/rvboost/. Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract Motivation: Exome sequencing (exome-seq) data, which are typically used for calling exonic mutations, have also been utilized in detecting DNA copy number variations (CNVs). Despite the existence of several CNV detection tools, there is still a great need for a sensitive and an accurate CNV-calling algorithm with built-in QC steps, and does not require a paired reference for each sample. Results: We developed a novel method named PatternCNV, which (i) accounts for the read coverage variations between exons while leveraging the consistencies of this variability across different samples; (ii) reduces alignment BAM files to WIG format and therefore greatly accelerates computation; (iii) incorporates multiple QC measures designed to identify outlier samples and batch effects; and (iv) provides a variety of visualization options including chromosome, gene and exon-level views of CNVs, along with a tabular summarization of the exon-level CNVs. Compared with other CNV-calling algorithms using data from a lymphoma exome-seq study, PatternCNV has higher sensitivity and specificity. Availability and implementation: The software for PatternCNV is implemented using Perl and R, and can be used in Mac or Linux environments. Software and user manual are available at http://bioinformaticstools.mayo.edu/research/patterncnv/ , and R package at https://github.com/topsoil/patternCNV/ . Contact: Asmann.Yan@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract To reveal biologic mechanisms underlying clinical outcome of high-grade serous (HGS) epithelial ovarian carcinomas (EOC), we evaluated the association between tumor epigenetic changes and time to recurrence (TTR). We assessed methylation at approximately 450,000 genome-wide CpGs in tumors of 337 Mayo Clinic (Rochester, MN) patients. Semi-supervised clustering of discovery (n = 168) and validation (n = 169) sets was used to determine clinically relevant methylation classes. Clustering identified two methylation classes based on 60 informative CpGs, which differed in TTR in the validation set [R vs. L class, P = 2.9 × 10−3, HR = 0.52; 95% confidence interval (CI), 0.34–0.80]. Follow-up analyses considered genome-wide tumor mRNA expression (n = 104) and CD8 T-cell infiltration (n = 89) in patient subsets. Hypomethylation of CpGs located in 6p21.3 in the R class associated with cis upregulation of genes enriched in immune response processes (TAP1, PSMB8, PSMB9, HLA-DQB1, HLA-DQB2, HLA-DMA, and HLA-DOA), increased CD8 T-cell tumor infiltration (P = 7.6 × 10−5), and trans-regulation of genes in immune-related pathways (P = 1.6 × 10−32). This is the most comprehensive assessment of clinical outcomes with regard to epithelial ovarian carcinoma tumor methylation to date. Collectively, these results suggest that an epigenetically mediated immune response is a predictor of recurrence and, possibly, treatment response for HGS EOC. Cancer Res; 74(11); 3084–91. ©2014 AACR.

Abstract The presence of regulatory T cells (Treg) in solid tumors is known to play a role in patient survival in ovarian cancer and other malignancies. We assessed inherited genetic variations via 749 tag single-nucleotide polymorphisms (SNP) in 25 Treg-associated genes (CD28, CTLA4, FOXP3, IDO1, IL10, IL10RA, IL15, 1L17RA, IL23A, IL23R, IL2RA, IL6, IL6R, IL8, LGALS1, LGALS9, MAP3K8, STAT5A, STAT5B, TGFB1, TGFB2, TGFB3, TGFBR1, TGRBR2, and TGFBR3) in relation to ovarian cancer survival. We analyzed genotype and overall survival in 10,084 women with invasive epithelial ovarian cancer, including 5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous carcinoma cases of European descent across 28 studies from the Ovarian Cancer Association Consortium (OCAC). The strongest associations were found for endometrioid carcinoma and IL2RA SNPs rs11256497 [HR, 1.42; 95% confidence interval (CI), 1.22–1.64; P = 5.7 × 10−6], rs791587 (HR, 1.36; 95% CI, 1.17–1.57; P = 6.2 × 10−5), rs2476491 (HR, = 1.40; 95% CI, 1.19–1.64; P = 5.6 × 10−5), and rs10795763 (HR, 1.35; 95% CI, 1.17–1.57; P = 7.9 × 10−5), and for clear cell carcinoma and CTLA4 SNP rs231775 (HR, 0.67; 95% CI, 0.54–0.82; P = 9.3 × 10−5) after adjustment for age, study site, population stratification, stage, grade, and oral contraceptive use. The rs231775 allele associated with improved survival in our study also results in an amino acid change in CTLA4 and previously has been reported to be associated with autoimmune conditions. Thus, we found evidence that SNPs in genes related to Tregs seem to play a role in ovarian cancer survival, particularly in patients with clear cell and endometrioid epithelial ovarian cancer. Cancer Immunol Res; 2(4); 332–40. ©2014 AACR.