Wang, Chen

Abstract Background Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are often sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different library preparations. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92% of the uniquely called FFPE variants were of low allelic frequency range (<5%), and collectively shared a “C>T|G>A” mutational signature known to be representative of FFPE artifacts resulting fromcytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.

AbstractX chromosome inactivation (XCI) is a key epigenetic gene expression regulatory process, which may play a role in women’s cancer. In particular tissues, some genes are known to escape XCI, yet patterns of XCI in ovarian cancer (OC) and their clinical associations are largely unknown. To examine XCI in OC, we integrated germline genotype with tumor copy number, gene expression and DNA methylation information from 99 OC patients. Approximately 10% of genes showed different XCI status (either escaping or being subject to XCI) compared with the studies of other tissues. Many of these genes are known oncogenes or tumor suppressors (e.g. DDX3X, TRAPPC2 and TCEANC). We also observed strong association between cis promoter DNA methylation and allele-specific expression imbalance (P = 2.0 × 10−10). Cluster analyses of the integrated data identified two molecular subgroups of OC patients representing those with regulated (N = 47) and dysregulated (N = 52) XCI. This XCI cluster membership was associated with expression of X inactive specific transcript (P = 0.002), a known driver of XCI, as well as age, grade, stage, tumor histology and extent of rl disease following surgical debulking. Patients with dysregulated XCI (N = 52) had shorter time to recurrence (HR = 2.34, P = 0.001) and overall survival time (HR = 1.87, P = 0.02) than those with regulated XCI, although results were attenuated after covariate adjustment. Similar findings were observed when restricted to high-grade serous tumors. We found evidence of a unique OC XCI profile, suggesting that XCI may play an important role in OC biology. Additional studies to examine somatic changes with paired tumor-normal tissue are needed.

Perineuriomas are rare nerve sheath tumors, divided into intraneural and extraneural (soft tissue) types. Intraneural perineuriomas frequently contain TRAF7 mutations, and rarely, chr22q12 deletions. While chr22q losses can occur in soft tissue perineuriomas, comprehensive high-resolution molecular profiling has not been reported in these tumors and TRAF7 status is unknown. We used whole-exome sequencing and OncoScan single nucleotide polymorphism (SNP) array to evaluate 14 soft tissue perineuriomas. Thirteen cases showed 2 or more chromosomal abnormalities, composed primarily of large deletions. Recurrent chr22q deletions, containing the NF2 locus (n=6) and the previously unreported finding of chr17q deletions, with the NF1 locus (n=4) were frequent events and were mutually exclusive in all but1 case. In addition, 5 cases had varying chr2 deletions; and 4 cases had chr6 deletions. A chr10 deletion (previously reported in the sclerosing variant of soft tissue perineurioma) was observed in one case and another case had chr7 chromothripsis as the sole chromosomal abnormality. No TRAF7 mutations or alterations were identified in any case and no other evaluated gene (MAF<0.0001) had recurrent, deleterious mutations in >2 cases. The molecular genetic profiles showed no association with patient sex, age, tumoral histology or anatomic site. OncoScan SNP array analysis was performed on 10 cases and showed high concordance with the whole exome data, validating the large-scale deletions, duplications, and chr7 chromothripsis findings. In soft tissue perineuriomas, recurrent 22q12 deletions (with NF2) and 17q11 deletions (with NF1) appear to be mutually exclusive events, and alterations in NF1 or NF2 likely contribute to perineurioma pathogenesis, similar to other nerve sheath tumors. Moreover, the lack of TRAF7 mutations in soft tissue perineuriomas indicates divergent pathogenetic mechanisms from those of intraneural perineuriomas.

Abstract Introduction: Mitochondria are intracellular organelles that play an important role in energy metabolism, reactive oxygen species generation, and apoptosis. They possess their own haploid genome distinct from nuclear DNA, and mutations in mitochondrial DNA (mtDNA) have previously been linked to cancer risk, disease progression, and treatment response for multiple tumor types. However, the spectrum of mtDNA variation in epithelial ovarian carcinoma (EOC) and associations with clinical characteristics have not been fully explored. Methods: We extracted mtDNA from fresh frozen EOC tumors of women diagnosed with primary invasive epithelial ovarian, fallopian tube, or peritoneal carcinoma, and performed targeted sequencing using the Illumina MiSeq Reporter mtDNA workflow. Homoplasmic and heteroplasmic SNVs and indels were called using an in-house bioinformatics pipeline. We estimated mtDNA haplogroup using Haplogrep and compared to results from available germline mtDNA SNP genotyping. We derived regional weighted variant burden scores based on mtDNA functional domains, accounting for underlying haplogroup, heteroplasmic fraction, and predicted functional impact. To assess potential differences in variant burden by histotype, we compared burden scores using Kruskal-Wallis testing. Among high-grade serous tubo-ovarian cases, we explored associations with overall survival (OS) using Cox proportional hazards regression. After quality control filtering, 389 mitochondrial genomes were analyzed, including those from 320 tubo-ovarian high-grade serous tumors, 42 endometrioid tumors, and 18 clear cell tumors. Results: Accounting for predicted haplogroup, we identified a median count of two global private heteroplasmies per tumor (range: 0-9). Elevated mutation rates were identified in the regulatory control region as well as among the various mt-tRNAs (&gt;3 per 10kb per sample) relative to the remainder of the mtDNA. The majority of recurrent variants across tumors were also identified in the mtDNA control region. We did not observe an association with overall mtDNA variant burden and patient age at diagnosis. Regional mtDNA burden scores revealed a significant association with histotype (P&lt;0.001) for the oxidative phosphorylation complex IV genes, with higher burden in tubo-ovarian high-grade serous and clear-cell tumors relative to endometrioid tumors. For patients with tubo-ovarian high-grade serous tumors, increased variant burden in MT-CO1 (cytochrome C oxidase I) was associated with improved OS (HR = 0.32; 95% CI = [0.14,0.70], LRT P = 0.001) after adjustment for age, stage, and debulking status. Conclusions: We demonstrate a wide range of tumor mtDNA variant patterns in the largest known collection of EOC patients. This work provides the first extensive evaluation of mtDNA variation in these diseases and highlights the potential prognostic relevance of mitochondrial dysfunction. Citation Format: Nicholas B. Larson, Stacey J. Winham, Chen Wang, Jared M. Evans, Sebastian M. Armasu, Bryan M. McCauley, Sean J. Yoder, Lan Min Zhang, Catherine M. Phelan, Ellen L. Goode. Targeted deep sequencing of mitochondrial DNA in epithelial ovarian carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 420.

AbstractWe aimed to validate the prognostic association of p16 expression in ovarian high‐grade serous carcinomas (HGSC) and to explore it in other ovarian carcinoma histotypes. p16 protein expression was assessed by clinical‐grade immunohistochemistry in 6525 ovarian carcinomas including 4334 HGSC using tissue microarrays from 24 studies participating in the Ovarian Tumor Tissue Analysis consortium. p16 expression patterns were interpreted as abnormal (either overexpression referred to as block expression or absence) or normal (heterogeneous). CDKN2A (which encodes p16) mRNA expression was also analyzed in a subset (n = 2280) mostly representing HGSC (n = 2010). Association of p16 expression with overall survival (OS) was determined within histotypes as was CDKN2A expression for HGSC only. p16 block expression was most frequent in HGSC (56%) but neither protein nor mRNA expression was associated with OS. However, relative to heterogeneous expression, block expression was associated with shorter OS in endometriosis‐associated carcinomas, clear cell [hazard ratio (HR): 2.02, 95% confidence (CI) 1.47–2.77, p < 0.001] and endometrioid (HR: 1.88, 95% CI 1.30–2.75, p = 0.004), while absence was associated with shorter OS in low‐grade serous carcinomas (HR: 2.95, 95% CI 1.61–5.38, p = 0.001). Absence was most frequent in mucinous carcinoma (50%), and was not associated with OS in this histotype. The prognostic value of p16 expression is histotype‐specific and pattern dependent. We provide definitive evidence against an association of p16 expression with survival in ovarian HGSC as previously suggested. Block expression of p16 in clear cell and endometrioid carcinoma should be further validated as a prognostic marker, and absence in low‐grade serous carcinoma justifies CDK4 inhibition.

Abstract Background: Endometrioid carcinoma (EC) and clear cell carcinoma (CC) histotypes of epithelial ovarian cancer are understudied compared with the more common high-grade serous carcinomas (HGSC). We therefore sought to characterize EC and CC transcriptomes in relation to HGSC. Methods: Following bioinformatics processing and gene abundance normalization, differential expression analysis of RNA sequence data collected on fresh-frozen tumors was completed with nonparametric statistical analysis methods (55 ECs, 19 CCs, 112 HGSCs). Association of gene expression with progression-free survival (PFS) was completed with Cox proportional hazards models. Eight additional multi-histotype expression array datasets (N = 852 patients) were used for replication. Results: In the discovery set, tumors generally clustered together by histotype. Thirty-two protein-coding genes were differentially expressed across histotype (P &lt; 1 × 10−10) and showed similar associations in replication datasets, including MAP2K6, KIAA1324, CDH1, ENTPD5, LAMB1, and DRAM1. Nine genes associated with PFS (P &lt; 0.0001) showed similar associations in replication datasets. In particular, we observed shorter PFS time for CC and EC patients with high gene expression for CCNB2, CORO2A, CSNK1G1, FRMD8, LIN54, LINC00664, PDK1, and PEX6, whereas, the converse was observed for HGSC patients. Conclusions: The results suggest important histotype differences that may aid in the development of treatment options, particularly those for patients with EC or CC. Impact: We present replicated findings on transcriptomic differences and how they relate to clinical outcome for two of the rarer ovarian cancer histotypes of EC and CC, along with comparison with the common histotype of HGSC. Cancer Epidemiol Biomarkers Prev; 27(9); 1101–9. ©2018 AACR.