Wang, Chen

Abstract Background: Little transcriptomic research has compared epithelial ovarian cancer (EOC) histological subtypes. We set out to characterize the transcriptomes of high-grade serous carcinomas (HGSC) and endometrioid carcinomas (EC), which make up around 70% and 20% of EOC tumors, respectively, and have some histopathological similarities. Methods: Fresh frozen tumors from EOC patients seen at the Mayo Clinic (30 EC and 62 HGSC) were used. 1ug RNA riboZero was used for library preparation using the Illumina TruSeq kit and sequenced on a HiSeq 2000 machine. Reads were aligned using TopHat2 followed by quantification of abundances using RSEM and differential expression analysis with edgeR. We analyzed transcriptomes, conducted pathway analyses, and summarized key candidate gene sets. Expressed SNVs (eSNVs) from the RNA-seq data were determined using GATK and RVboost. Results: The analysis found 699 genes with FDR < 1×10-5 for differential expression between HGSC and EC, with most genes being up-regulated in EC. The top most associated genes were TPH1, MAP2K6, KLK2, ADAM23, TESC and TRAF3IP2 (p<10-22). Pathway analysis of the genes up-regulated in EC revealed enrichment of the “basal cell carcinoma signaling pathway” (p = 1.2×10-5). Within 1 Mb of the 25 known EOC risk loci, we observed higher expression in HGSC for RSPO1 and HPSE (p <5×10-7). For genes functionally related to EOC, we observed in HGSC up-regulation (*p < 10-5, ⁁p<0.003) for FOXM1⁁, CDKN2A⁁, CCNE1*, CCND2⁁, PIK3CA*, BRCA2⁁, BIRC5⁁, MMP9⁁, FANCD2⁁, and MAML2⁁. In contrast, we found up-regulation in EC for MDM2*, KLK4*, BCL2⁁, CCND1*, ANXA4*, CDH1⁁, MMP7⁁, and MAML3⁁. We also identified 204 eSNVs (44 non-synonymous) associated with EC v HGSC subtype (p<10-4); this included an exonic TRAF3IP2 eSNV (66% EC, 13% HGSC, p = 4×10-7, chr6:111877117). Discussion: Using one of the largest sets of identically processed fresh-frozen EOC tumors, some patterns emerged among the numerous EC v HGSC transcriptomic differences. TPH1, up-expressed in EC, is regulated by SOX4 which was also up-regulated in EC. Two sets of genes related to Kallikreins serine proteases were differentially expressed, including KLK2 which is known to regulate EGFR and pro-inflammatory cytokines and is regulated by MYC. Lastly, TRAF3IP2 encodes for a protein involved in regulating cytokines through members of the NFKB pathway. Conclusions: These findings suggest important biological insights into one of the rarer EOC histologies and may aid in the development of targeted treatment options. Research is on-going to incorporate additional features (e.g., DNA methylation, copy number) into a “systems biology” framework to better understand the molecular differences between EOC histologies. Citation Format: Brooke L. Fridley, Junqiang Dai, Rama Raghavan, Chen Wang, Pengcheng Lu, Stacey Winham, Madalene Earp, Kate Lawrenson, Simon A. Gayther, Kimberly R. Kalli, Ellen L. Goode. Transcriptome characterization of high grade serous and endometrioid epithelial ovarian cancer tumors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1833.

Abstract Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer death among women in the United States (5% of cancer deaths). The standard treatment for patients with advanced EOC is initial debulking surgery followed by carboplatin-paclitaxel combination chemotherapy. Unfortunately, even with modern chemotherapy, most patients relapse and die with the five-year overall survival around 45%. In addition, those patients that initially respond to taxane-platinum therapy eventually develop platinum-resistant tumors and relapse. Thus, finding novel therapeutics for treating EOC is essential. One approach that has been used widely in cancer drug discovery is Connectivity Mapping (CMAP) using gene expression data and drug phenotype data assessed on cancer cell lines (CCL) (i.e. “sensitive” or “resistant” based on dose-response drug data). However, recent publications have highlighted some issues with the use of these standard CCL sets that are often used in these drug screening studies. Therefore, instead of CMAP analysis based on gene expression signatures developed on drug response data collected on a small set of EOC cell lines, we took a novel CMAP approach based on information collected on EOC patients and clinical endpoints. That is, we determined the gene expression signature (e.g., set of genes) that were associated with time to recurrence in data collected on EOC patients within TCGA (n = 518) and a Mayo Clinic study (n = 474). The set of genes associated with time to recurrence (with and without adjustment for additional clinical covariates) was completed separately for TCGA and Mayo Clinic studies, restricting all analyses to EOC tumor of high-grade serous histology. Each of these 4 sets of genes, where genes with hazard ratios (HR) > 1 coded as “positively” associated and genes with HR < 1 coded as “negatively” associated with the phenotype, were inputted into CMAP software (Broad Institute) to determine a set of drugs for which our signature “matches” the “reference” signature. The drugs that overlapped between the CMAP analyses on the two studies were carried forward for validation studies involving drug screens on a set of 10 EOC cell lines. Of the 11 drugs carried forward, we a priori hypothesized that 5 of these drugs would kill EOC cells (mitoxantrone, podophyllotoxin, wortmannin, doxorubicin, and 17-AAG), for which all 5 showed an ability to kill EOC cells in vitro (cell lines were treated using serial dilutions of the drugs (20-0 μM) for 72 h followed by measuring cell viability using the CellTiter-Blue assay). Further research is on-going to understand the functional mechanism by which these candidate drugs might treat EOC and to apply this bioinformatics approach to other cancer drug screening studies. Note: This abstract was not presented at the meeting. Citation Format: Brooke L. Fridley, Rama Raghavan, Gottfried E. Konecny, Chen Wang, Ellen L. Goode, Harsh B. Pathak, Stephen Hyter. A bioinformatics approach to drug discovery: patient based connectivity mapping. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4853. doi:10.1158/1538-7445.AM2015-4853

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.