Cunningham, Julie M.

Abstract Background: Chronic inflammation is implicated in ovarian carcinogenesis, but how different inflammation-related exposures individually or jointly affect histotype-specific associations remains unclear. Materials and Methods: We pooled data from 16 case-control studies in the Ovarian Cancer Association Consortium to evaluate associations of eight inflammation-related factors (anti-inflammatory: aspirin use, tubal ligation (TL); pro-inflammatory: endometriosis, obesity, lifetime ovulatory cycles (LOC), smoking, pelvic inflammatory disease (PID), polycystic ovary syndrome (PCOS)) with epithelial ovarian cancer (OvC) by histologic subtype. We examined individual associations and clustering of risk factors across histotypes and computed population attributable risk (PAR) for each factor. We assessed additive and multiplicative interactions for exposure combinations. Results: Associations with OvC risk differed by histotype (e.g., high-grade serous: aspirin: OR=0.90; 95%CI 0.82, 0.99; TL: OR=0.80; 95%CI 0.73, 0.88; overall serous: endometriosis: OR=1.17; 95%CI 1.03, 1.31; high LOC: OR=1.42; 95%CI 1.28, 1.58; obesity (low-grade serous): OR=1.50; 95%CI 1.14, 1.98). Clustering analyses showed highly correlated risk profiles in endometrioid and clear cell (r=0.91). High-grade serous and mucinous profiles were moderately correlated with endometrioid and clear cell (r=0.60) tumors. The profile for low-grade serous (r=0.36) tumors was distinct from other histotypes. PAR estimates suggested modifying aspirin use, TL, and LOCs could substantially reduce burdens of endometrioid, clear cell and mucinous tumors. Out of 28 exposure combinations tested in overall OvC and 189 by histotype, we observed 12 interactions. Not using aspirin regularly showed positive additive interactions with obesity and high LOCs, particularly in endometrioid tumors (obesity relative excess risk due to interaction (RERI)=0.74, 95%CI 0.31, 1.18; Pint=0.001 for; LOCs RERI=0.80, 95%CI 0.03, 1.56; Pint=0.04). Not using aspirin regularly also showed a positive additive interaction with endometriosis in clear cell tumors (RERI=1.77, 95%CI 0.03, 3.52; Pint=0.05). Lack of TL showed positive interactions with obesity in endometrioid (RERI=0.86, 95%CI 0.17, 1.53; Pint=0.01) and mucinous (RERI=1.10, 95%CI 0.23, 1.97; Pint=0.01) tumors, while negative additive interactions were observed for smoking and endometriosis in endometrioid tumors (RERI=-1.12, 95%CI -2.19, -0.05; Pint=0.04). A multiplicative interaction was observed between obesity and endometriosis in mucinous tumors (Pint=0.01). Conclusion: The findings suggest ovarian tumorigenesis is strongly shaped by pro- and anti-inflammatory pathways that act largely independently. Further examining these pathways may clarify the origins of histotype heterogeneity and guide prevention strategies. Citation Format: Maxwell Akonde, Britton Trabert, SHELLEY TWOROGER, Allan Jensen, Kathryn L. Terry, Joshua Sampson, Hoda Anton-Culver, David Bowtell, Elisa V. Bandera, Angela Brooks-Wilson, Andrew Berchuck, Daniel William Cramer, Linda S. Cook, Julie M. Cunningham, Jennifer A. Doherty, Ellen L. Goode, Marc T. Goodman, Holly Ruth Harris, Susanne K. Kjaer, Nhu Le, Alice Wen-Ron Lee, Francesmary Modugno, Kirsten B. Moysich, Celeste Pearce, Malcolm C. Pike, Harvey A. Risch, Mary A. Rossing, Joellen M. Schildkrau, Daniel O. Stram, Rebecca Sutphen, David Van Den Berg, Penelope M. Webb, Anna Wu, Argyrios Ziogas, Nicolas A. Wentzensen. Inflammation-related exposures and histotype- specific ovarian cancer risk in the Ovarian Cancer Association Consortium (OCAC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6261.

Abstract Transcriptome profiling using RNA sequencing (RNA-seq) of bulk formalin-fixed paraffin-embedded (FFPE) tissue blocks is a standard method in biomedical research. However, when used on tissues with diverse cell type compositions, it yields averaged gene expression profiles, complicating biomarker identification due to variations in cell proportions. To address the need for optimized strategies for defining individual cell type compositions from bulk FFPE samples, we constructed single-cell RNA-seq reference data for breast tissue and tested cell type deconvolution methods. Initial simulation experiments showed similar performances across multiple commonly used deconvolution methods. However, the introduction of FFPE artifacts significantly impacted their performances, with a root mean squared error (RMSE) ranging between 0.04 and 0.17. Scaden, a deep learning-based method, consistently outperformed the others, demonstrating robustness against FFPE artifacts. Testing these methods on our 62-sample RNA-seq benign breast disease cohort in which cell type composition was estimated using digital pathology approaches, we found that pre-filtering of the reference data enhanced the accuracy of most methods, realizing up to a 32% reduction in RMSE. To support further research efforts in this domain, we introduce SCdeconR, an R package designed for streamlined cell type deconvolution assessments and downstream analyses.

Abstract Background: Women with an inherited pathogenic variant in BRCA1 or BRCA2 have a greatly increased risk of developing ovarian cancer, but the importance of behavioral factors is less clear. We used a case-only design to compare the magnitude of associations with established reproductive, hormonal, and lifestyle risk factors between BRCA mutation carriers and noncarriers. Methods: We pooled data from five studies from the Ovarian Cancer Association Consortium including 637 BRCA carriers and 4,289 noncarriers. Covariate-adjusted generalized linear mixed models were used to estimate interaction risk ratios (IRR) and 95% confidence intervals (CI), with BRCA (carrier vs. noncarrier) as the response variable. Results: IRRs were above 1.0 for known protective factors including ever being pregnant (IRR = 1.29, 95% CI; 1.00–1.67) and ever using the oral contraceptive pill (1.30, 95% CI; 1.07–1.60), suggesting the protective effects of these factors may be reduced in carriers compared with noncarriers. Conversely, the IRRs for risk factors including endometriosis and menopausal hormone therapy were below 1.0, suggesting weaker positive associations among BRCA carriers. In contrast, associations with lifestyle factors including smoking, physical inactivity, body mass index, and aspirin use did not appear to differ by BRCA status. Conclusions: Our results suggest that associations with hormonal and reproductive factors are generally weaker for those with a pathogenic BRCA variant than those without, while associations with modifiable lifestyle factors are similar for carriers and noncarriers. Impact: Advice to maintain a healthy weight, be physically active, and refrain from smoking will therefore benefit BRCA carriers as well as noncarriers.

ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an unprecedented impact on human health and highlights the need for genomic epidemiology studies to increase our understanding of virus evolution and spread and to inform policy decisions. We sequenced viral genomes from over 22,000 patient samples tested at Mayo Clinic Laboratories between 2020 and 2022 and used Bayesian phylodynamics to describe county and regional spread in Minnesota. The earliest calculated introduction into Minnesota was to Hennepin County from a domestic source around 22 January 2020; 6 weeks before the first confirmed case in the state. This led to the virus spreading to Northern Minnesota and, eventually, the rest of the state. International introductions were most abundant in Hennepin (home to the Minneapolis/St. Paul International Airport) totaling 45 (out of 107) over the 2-year period. Southern Minnesota counties were most common for domestic introductions, with 19 (out of 64), potentially driven by bordering states such as Iowa and Wisconsin as well as Illinois, which is nearby. Hennepin also was, by far, the most dominant source of in-state transmissions to other Minnesota locations ( n = 772) over the 2-year period. We also analyzed the diversity of the location source of SARS-CoV-2 viruses in each county and noted the timing of state-wide policies as well as trends in clinical cases. Neither the number of clinical cases nor the major policy decisions, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, appeared to have an impact on virus diversity across each individual county. IMPORTANCE We analyzed over 22,000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes of patient samples tested at Mayo Clinic Laboratories during a 2-year period in the COVID-19 pandemic, which included Alpha, Delta, and Omicron variants of concern to examine the roles and relationships of Minnesota virus transmission. We found that Hennepin County, the most populous county, drove the transmission of SARS-CoV-2 viruses in the state after including the formation of earlier clades including 20A, 20C, and 20G, as well as variants of concern Alpha and Delta. We also found that Hennepin County was the source for most of the county-to-county introductions after an initial predicted introduction with the virus in early 2020 from an international source, while other counties acted as transmission “sinks.” In addition, major policies, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, did not appear to have an impact on virus diversity across individual counties.

Abstract Purpose: Benign breast disease (BBD) is viewed as a non-obligate precursor stage in the development of breast cancer (BC). Transcriptome profiling using RNA sequencing (RNA-seq) of bulk formalin-fixed paraffin-embedded (FFPE) tissue blocks has been routinely used in BC research. However, RNA-seq of heterogeneous bulk samples represents an averaged expression profile across all cell mixtures. Downstream analyses, such as biomarker discovery, are likely confounded by differences in cell proportions. There is a lack of research in optimizing strategies for cell type deconvolution especially for FFPE samples. We evaluated and optimized strategies for cell type deconvolution using existing single cell RNA-seq (scRNA-seq) and single nucleus RNA-seq (snRNA-seq) breast tissue references, and applied these to a cohort of BBD FFPE samples to assess risk of subsequent BC. Methods: 7 scRNA-seq and 3 snRNA-seq public samples from women’s breast tissue were normalized using SCTransform, then integrated using Harmony to form a complete reference set. Bioinformatics evaluations examined the performance of existing statistical and deep learning-based deconvolution methods. Computational simulations were conducted to evaluate those methods on three scenarios: 1) baseline; 2) incomplete reference set; 3) FFPE artifacts. FFPE artifacts were simulated based on a generalized additive model using 7 in-house paired FFPE-fresh frozen samples. Finally, we applied the best performing method to our BBD cohort of 62 samples. Differential expression analysis adjusting for cell proportions was performed to identify transcriptomic aberrations in BBD cases. Results: snRNA-seq was more sensitive in capturing adipocytes, while scRNA-seq was more sensitive in detecting lymphocytes in breast tissue. The median number of detectable genes per cell was higher for scRNA-seq than snRNA-seq before integration (1264 vs 558). Marker gene-based regression methods (e.g. CIBERSORT) displayed higher variance and lower bias compared to methods directly using scRNA-seq data (e.g. SCDC). Incomplete reference data led to increased bias and little effect on variance. FFPE artifacts had a higher impact on performance compared to incomplete reference data. Overall, Scaden, a deep learning-based method, was the top performing method across all simulation scenarios and was especially robust to FFPE artifacts. 59 differential expressed genes (DEGs) were identified with fold change > 1.5 and p value < 0.01. DEGs involved in BC, e.g. S100A8, WNT4 and HIST1H3H, would be left out if cell proportions were not properly adjusted. Conclusions: We constructed the first complete single cell reference data for women’s breast tissue and benchmarked existing cell type deconvolution methods. Compared to analyses not adjusting for cell proportions, we observed substantial differences in perturbed genes and pathways associated with BC risk for BBD patients. Citation Format: Yuanhang Liu, Chen Wang, Stacey J. Winham, Aditya Bhagwate, Robert A. Vierkant, Julie M. Cunningham, Bryan M. McCauley, William A. Jons, Derek C. Radisky, Amy C. Degnim. Deconvolution of cell type composition in FFPE tissue: Application to benign breast disease. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4291.

Abstract Background: Better understanding of prognostic factors in tubo-ovarian high-grade serous carcinoma (HGSC) is critical, as diagnosis confers an aggressive disease course. Variation in tumor DNA methylation shows promise predicting outcome, yet prior studies were largely platform-specific and unable to evaluate multiple molecular features. Methods: We analyzed genome-wide DNA methylation in 1,040 frozen HGSC, including 325 previously reported upon, seeking a multi-platform quantitative methylation signature that we evaluated in relation to clinical features, tumor characteristics, time to recurrence/death, extent of CD8+ tumor-infiltrating lymphocytes (TIL), gene expression molecular subtypes, and gene expression of the ATP-binding cassette transporter TAP1. Results: Methylation signature was associated with shorter time to recurrence, independent of clinical factors (N = 715 new set, hazard ratio (HR), 1.65; 95% confidence interval (CI), 1.10–2.46; P = 0.015; N = 325 published set HR, 2.87; 95% CI, 2.17–3.81; P = 2.2 × 10−13) and remained prognostic after adjustment for gene expression molecular subtype and TAP1 expression (N = 599; HR, 2.22; 95% CI, 1.66–2.95; P = 4.1 × 10−8). Methylation signature was inversely related to CD8+ TIL levels (P = 2.4 × 10−7) and TAP1 expression (P = 0.0011) and was associated with gene expression molecular subtype (P = 5.9 × 10−4) in covariate-adjusted analysis. Conclusions: Multi-center analysis identified a novel quantitative tumor methylation signature of HGSC applicable to numerous commercially available platforms indicative of shorter time to recurrence/death, adjusting for other factors. Along with immune cell composition analysis, these results suggest a role for DNA methylation in the immunosuppressive microenvironment. Impact: This work aids in identification of targetable epigenome processes and stratification of patients for whom tailored treatment may be most beneficial.

AbstractBackgroundCyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo‐ovarian high‐grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large‐scale, histotype‐specific validation has been performed. The hypothesis was that high‐level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC.MethodsWithin the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated.ResultsHigh‐level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high‐level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08‐1.47, p = .034, and HR, 1.18; 95% CI, 1.05‐1.32, p = .015, respectively). This was also true for cases with combined high‐level amplification/overexpression (HR, 1.26; 95% CI, 1.09‐1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1‐SD increase; 95% CI, 0.94‐1.06; p = .58). CCNE1 high‐level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss.ConclusionThis study provides large‐scale validation that CCNE1 high‐level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.

Abstract Purpose: To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes. Experimental Design: We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival. Results: We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy. Conclusions: Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838

Abstract Purpose: To identify molecular predictors of grade 3/4 neutropenic or leukopenic events (NLE) after chemotherapy using a genome-wide association study (GWAS). Experimental Design: A GWAS was performed on patients in the phase III chemotherapy study SUCCESS-A (n = 3,322). Genotyping was done using the Illumina HumanOmniExpress-12v1 array. Findings were functionally validated with cell culture models and the genotypes and gene expression of possible causative genes were correlated with clinical treatment response and prognostic outcomes. Results: One locus on chromosome 16 (rs4784750; NLRC5; P = 1.56E-8) and another locus on chromosome 13 (rs16972207; TNFSF13B; P = 3.42E-8) were identified at a genome-wide significance level. Functional validation revealed that expression of these two genes is altered by genotype-dependent and chemotherapy-dependent activity of two transcription factors. Genotypes also showed an association with disease-free survival in patients with an NLE. Conclusions: Two loci in NLRC5 and TNFSF13B are associated with NLEs. The involvement of the MHC I regulator NLRC5 implies the possible involvement of immuno-oncological pathways.