Larson, Melissa C.

95 Background: While PA is known to improve quality of life in lymphoma pts, its impact on OS is not known. We studied the effect of PA on OS in lymphoma pts enrolled at diagnosis in the Iowa/Mayo Molecular Epidemiology Resource. Methods: Godin Leisure Score Index (LSI; Range 0-50) was calculated based on level of PA pre-diagnosis (baseline) and 3 years post diagnosis (FU3), with pts grouped by tertile into high, moderate, or low PA. At FU3, pts also reported perceived change in PA since diagnosis. OS was measured as time from assessment (baseline or FU3) until death from any cause. Associations between LSI tertiles and OS were assessed using Cox models adjusted for lymphoma subtype, age and sex. Results: PA level was available for 3060 pts at baseline and 1371 pts at FU3. 95% had an ECOG performance status < 2, 37% had an aggressive subtype, 29% had BMI ≥ 30, and 54% were age > 60. Indolent lymphoma pts with higher PA at baseline had no difference in OS. Higher PA at FU3 had improved OS (moderate vs low HR 0.63, CI 0.42-0.93; high vs low HR 0.53, CI 0.33-0.86). Pts with BMI < 30 who had higher PA at baseline showed no difference in OS. Higher PA at FU3 had improved OS for pts with BMI < 30 (moderate vs low HR 0.68 CI, 0.48-0.98; high vs low HR = 0.41, CI 0.26-0.64). For pts > 60 years, high vs low baseline PA showed improved OS (HR 0.77, CI 0.63-0.93). Higher PA at FU3 (moderate vs low HR 0.68 CI 0.48-0.96, high vs low HR 0.53 CI 0.34-0.83) was associated with OS. At FU3, compared to no change, perceived reduction of PA was associated with worse OS for indolent lymphoma (HR 2.13, CI 1.56-2.91), BMI < 30 (HR 1.95, CI 1.45-2.62), BMI > 30 (HR 2.00, CI 1.21-3.30), age ≤ 60 (HR 3.06, CI 1.72-5.46), and age > 60 (HR 1.98, CI 1.52-2.58). Perceived increase in PA was not associated with OS. Higher PA in pts with aggressive lymphoma, BMI ≥30, and age < 60 was not significantly associated with OS but trended similarly. All results were similar when analyzing by continuous LSI score. Conclusions: Higher levels of PA, especially at FU3, were associated with superior OS. The effect was more pronounced in pts with indolent lymphoma, BMI < 30, or age > 60. Perceived reduction in PA was associated with worse outcomes. PA should be incorporated into lymphoma survivorship plans.

SummaryWe evaluated the association of Human Pegivirus (HPgV) viraemia with risk of developing lymphoma, overall and by major subtypes. Because this virus has also been associated with better prognosis in the setting of co‐infection with human immunodeficiency virus, we further assessed the association of HPgV with prognosis. We used risk factor data and banked plasma samples from 2094 lymphoma cases newly diagnosed between 2002 and 2009 and 1572 frequency‐matched controls. Plasma samples were tested for HPgV RNA by reverse transcription polymerase chain reaction (RT‐PCR), and those with RNA concentrations <5000 genome equivalents/ml were confirmed using nested RT‐PCR methods. To assess the role of HPgV in lymphoma prognosis, we used 2948 cases from a cohort study of newly diagnosed lymphoma patients (included all cases from the case‐control study). There was a positive association of HPgV viraemia with risk of lymphoma overall (Odds ratio = 2·14; 95% confidence interval [CI] 1·63–2·80; P < 0·0001), and for all major subtypes except Hodgkin lymphoma and chronic lymphocytic leukaemia/small lymphocytic lymphoma, and this was not confounded by other lymphoma risk factors. In contrast, there was no association of HPgV viraemia with event‐free survival (Hazard ratio [HR] = 1·00; 95% CI 0·85–1·18) or overall survival (HR = 0·97; 95% CI 0·79–1·20) for lymphoma overall, or any of the subtypes. These data support the hypothesis for a role of HPgV in the aetiology of multiple lymphoma subtypes.

High-grade serous ovarian cancer (HGSOC) is a complex disease in which initiation and progression have been associated with copy number alterations, epigenetic processes, and, to a lesser extent, germline variation. We hypothesized that, when summarized at the gene level, tumor methylation and germline genetic variation, alone or in combination, influence tumor gene expression in HGSOC. We used Elastic Net (ENET) penalized regression method to evaluate these associations and adjust for somatic copy number in 3 independent data sets comprising tumors from more than 470 patients. Penalized regression models of germline variation, with or without methylation, did not reveal a role in HGSOC gene expression. However, we observed significant association between regional methylation and expression of 5 genes ( WDPCP, KRT6C, BRCA2, EFCAB13, and ZNF283). CpGs retained in ENET model for BRCA2 and ZNF283 appeared enriched in several regulatory elements, suggesting that regularized regression may provide a novel utility for integrative genomic analysis.

ABSTRACTX‐chromosome inactivation (XCI) epigenetically silences transcription of an X chromosome in females; patterns of XCI are thought to be aberrant in women's cancers, but are understudied due to statistical challenges. We develop a two‐stage statistical framework to assess skewed XCI and evaluate gene‐level patterns of XCI for an individual sample by integration of RNA sequence, copy number alteration, and genotype data. Our method relies on allele‐specific expression (ASE) to directly measure XCI and does not rely on male samples or paired normal tissue for comparison. We model ASE using a two‐component mixture of beta distributions, allowing estimation for a given sample of the degree of skewness (based on a composite likelihood ratio test) and the posterior probability that a given gene escapes XCI (using a Bayesian beta‐binomial mixture model). To illustrate the utility of our approach, we applied these methods to data from tumors of ovarian cancer patients. Among 99 patients, 45 tumors were informative for analysis and showed evidence of XCI skewed toward a particular parental chromosome. For 397 X‐linked genes, we observed tumor XCI patterns largely consistent with previously identified consensus states based on multiple normal tissue types. However, 37 genes differed in XCI state between ovarian tumors and the consensus state; 17 genes aberrantly escaped XCI in ovarian tumors (including many oncogenes), whereas 20 genes were unexpectedly inactivated in ovarian tumors (including many tumor suppressor genes). These results provide evidence of the importance of XCI in ovarian cancer and demonstrate the utility of our two‐stage analysis.

AbstractThe prevalence of liver dysfunction and its association with outcomes in patients with previously untreated chronic lymphocytic leukemia (CLL) is unknown. Newly diagnosed (<12 months) previously untreated CLL patients seen at Mayo Clinic, Rochester, MN between 9/1993 and 4/2016 who had baseline assessment of at least one liver function test (LFT) were included in this analysis. The prevalence of liver dysfunction at baseline, proportion of patients who acquired LFT abnormalities, time to first therapy (TTFT) and overall survival (OS) were assessed. An abnormal LFT was present in 82/2336 (3.5%) patients at diagnosis and was associated with advanced Rai stage (Rai III–IV) (21% vs. 6%; P < .001), lower hemoglobin (13.1 g/dL vs. 13.9 g/dL; P < .001), and lower platelet count (187 × 109/L vs. 200 × 109/L; P = .03). Additionally, 236 patients with normal LFTs at diagnosis developed acquired liver dysfunction during follow‐up. Patients with abnormal LFTs at diagnosis had a shorter OS compared to those with normal LFTs (HR 1.80 95% CI 1.13‐2.87; P = .014, adjusted for age, sex, Rai stage, and treatment), although TTFT was not different. Of 52 patients who underwent a liver biopsy, CLL was present in liver tissue in 39/52 (73%) patients, with the portal tracts the most common region involved. Histopathology findings of liver involvement by CLL had limited correlation with choice of CLL therapy. In conclusion, approximately 1 of 25 newly diagnosed CLL patients has abnormal LFTs at diagnosis. Although the TTFT was not different among patients with abnormal LFTs, these patients have a shorter OS compared to those with normal LFTs.

Abstract High grade serous ovarian cancer (HGSOC) is a complex disease in which initiation and progression have been associated with gene mutation, DNA methylation changes, genetic variation, and epigenetic processes. Variation in several susceptibility regions and cancer-typical global methylation patterns have been observed in HGSOC; however, this knowledge has not been compelling in understanding HGSOC intiation or progression. As ingetration of genomic, epigenomic, and transcriptomic data has increased mechanistic understanding in other cancers, we hypothesized that tumor methylation alone or in combination with germline genetic variation influences tumor gene expression in HGSOC. We examined three nested models using an Elastnic Net (ENET) penalized regression method while adjusting for somatic copy number (CNV): a) germline genotype and tumor DNA methylation (full model), b) genotype only, and c) DNA methylation only. We included 339 cases from The Cancer Genome Atlas (TCGA), 54 cases from Mayo Clinic, and 78 cases from the Australian Ovarian Cancer Study (AOCS). Genotyping and copy number calls on germline DNA, expression, methylation and copy number on somatic samples were collected and analyzed on different platforms separately at each study site. We excluded genes with low overall expression and thus analyzed a total of 11,922 genes available in three datasets ( Ensembl IDs, 500kb window up- and downstream). In general, combining genomic data in HGSOC did not reveal a role for germline genetic variation in altering gene expression. However, in methylation only models 79 genes were associated with differential expression in the TCGA cases (permutation multiple testing adjusted p-val &lt;0.05), in the Mayo cases (unadjusted p-val &lt;0.05) and AOCS cases (unadjusted p-val &lt;0.05). A known tummor suppressor (FBXW7) was associated with differential expression in the three datasets at p-val &lt;0.01. This work demonstrates the feasibility, utility, and statistical power of ENET gene-level analyses incoporating maximal genomic information. Citation Format: Yanina Natanzon, Madalene Earp, Julie M. Cunningham, Kimberly R. Kalli, Stacey J. Winham, Sebastian M. Armasu, Melissa C. Larson, Chen Wang, David D. Bowtell, Dale W. Garsed, Ellen Goode. Omics data integration analysis in high grade serous ovarian cancer: results from three studies [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 3368. doi:10.1158/1538-7445.AM2017-3368

Abstract Introduction: In females, X-chromosome inactivation (XCI) epigenetically silences transcription of one copy of the X chromosome. Which chromosome is silenced is randomly selected, and is tissue- and cell-specific. While some genes are known to escape XCI under normal conditions, aberrant XCI patterns are thought to occur in female-specific cancers, although the role of XCI in ovarian tumorigenesis and progression is largely unknown. The process of XCI is complex, and integration of gene expression, DNA methylation, and copy number data can inform the XCI status of individual genes and chromosome-wide XCI patterns for individual patients. Methods: We evaluated gene- and chromosome-level patterns of XCI by integrating RNA sequence, copy number alteration, genotype, and DNA methylation data to study XCI escape patterns in tumor samples from 99 ovarian cancer patients. We measured allele-specific expression (ASE) for 397 X-linked genes to identify the active alleles for each tumor. Combining ASE data with knowledge of copy number status, we used a Bayesian beta-binomial mixture model to estimate which genes escaped XCI for each patient, and validated our findings using DNA methylation data. To assess global XCI patterns, we performed cluster analyses on the ASE and methylation data, after adjusting for loss of heterozygosity. We examined the relationship between the clusters and clinical factors, including overall survival and time to recurrence. Results: DNA promoter methylation demonstrated inverse regional correlations with ASE. Cluster analyses using ASE and methylation data demonstrated evidence of two tumor clusters, representing normal XCI and global XCI dysregulation. The dysregulated XCI cluster (N=52) was associated with lower X-inactive specific transcript expression as expected (p&lt;0.01). Patients with XCI dysregulated tumors were higher grade, stage, serous histology and were sub-optimally debulked (p&lt;0.05). These patients also had shorter overall survival time (HR=1.87, p=0.02) and time to recurrence (HR=2.34, p&lt;0.01), although associations were attenuated after covariate adjustment. In 45 tumor samples with sufficient data, we observed escape patterns largely consistent with previous reports of multiple tissue types. When comparing tumor to normal ovarian tissue, eight genes (CXorf23, CXorf36, BRWD3, ELF4, SLITRK4, GABRE, CLCN4, SH3BGRL) showed putative escape in the tumor and two genes (RBBP7, OFD1) showed discrepant tumor inactivation. Conclusions: We identified discrepant gene-level XCI tumor classifications compared to normal tissue and identified a group of patients with chromosome-wide XCI dysregulation associated with worse clinical prognosis. This provides evidence of the role of XCI in ovarian cancer and highlights the need to integrate multiple genomic data types to study XCI. Citation Format: Stacey J. Winham, Nicholas B. Larson, Sebastian M. Armasu, Zachary C. Fogarty, Melissa C. Larson, Kimberly R. Kalli, Kate Lawrenson, Simon Gayther, Brooke L. Fridley, Ellen L. Goode. Integrative analyses of gene expression, DNA methylation, genotype and copy number alterations characterize X-chromosome inactivation in ovarian cancer [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 2420. doi:10.1158/1538-7445.AM2017-2420