Papers by Francesmary Modugno
JNCI: Journal of the National Cancer Institute
Background The role of ovulation in epithelial ovarian cancer (EOC) is supported by the consisten... more Background The role of ovulation in epithelial ovarian cancer (EOC) is supported by the consistent protective effects of parity and oral contraceptive use. Whether these factors protect through anovulation alone remains unclear. We explored the association between lifetime ovulatory years (LOY) and EOC. Methods LOY was calculated using 12 algorithms. Odds ratios (ORs) and 95% confidence intervals (CIs) estimated the association between LOY or LOY components and EOC among 26 204 control participants and 21 267 case patients from 25 studies. To assess whether LOY components act through ovulation suppression alone, we compared beta coefficients obtained from regression models with expected estimates assuming 1 year of ovulation suppression has the same effect regardless of source. Results LOY was associated with increased EOC risk (OR per year increase = 1.014, 95% CI = 1.009 to 1.020 to OR per year increase = 1.044, 95% CI = 1.041 to 1.048). Individual LOY components, except age at me...
Gynecologic Oncology, 2022
OBJECTIVE Evaluate the association between metformin and survival in women with Type 2 diabetes (... more OBJECTIVE Evaluate the association between metformin and survival in women with Type 2 diabetes (T2DM) and breast, endometrial and ovarian cancer- 3 hormonally mediated cancers. METHODS We evaluated outcomes in a cohort of 6225 women with T2DM with a new diagnosis of ovarian, breast or endometrial cancer from 2010 to 2019. We classified glycemic medications at time of first cancer diagnosis into 3 tiers in accordance with ADA guidelines. Approaches compared: (i) metformin (tier 1) vs. no glycemic medication, (ii) metformin vs tier 2 medications (sulfonylureas, thiazolidinediones, SGLT2-inhibitors, DPP4-inhibitors, alpha glucosidase-inhibitors, GLP-1 agonists), (iii) metformin vs tier 3 medications (insulins, amylinomimetics), and (iv) tier 2 vs tier 3 medications. Analyses included Cox proportional-hazards models, Kaplan-Meier curves, and conditional logistic regression in a risk set-sampled nested case-control matched on T2DM duration- all modeling survival. Models were adjusted for demographics, cancer type, A1C, T2DM duration, and number of office visits and hospitalizations. RESULTS Metformin was the most used medication (n = 3232) and consistently demonstrated survival benefit compared with tier 2 and 3 medications, across all methods. Tier 3-users demonstrated highest risk of death when compared to metformin rather than tier 2 [adjHR = 1.83 (95% CI: 1.58, 2.13) vs. adjHR = 1.32 (95% CI: 1.11, 1.57)], despite similar baseline profiles between tier 1 and 2 users. CONCLUSIONS Metformin users experienced increased survival even after accounting for surrogates of diabetes progression. Benefit extended beyond that seen in tier 2-users. Our findings, consistent with prior studies, indicate metformin use improves survival in women with T2DM and hormonally mediated women's cancers.
Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve ris... more Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally-efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestry; 7,669 women of East Asian ancestry; 1,072 women of African ancestry, and in 18,915 BRCA1 ...
Gynecologic Oncology, 2020
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service... more This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
American journal of epidemiology, Jan 3, 2016
Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer ha... more Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models pe...
Nature Communications, 2013
Song et al. w HNF1B is overexpressed in clear cell epithelial ovarian cancer, and we observed epi... more Song et al. w HNF1B is overexpressed in clear cell epithelial ovarian cancer, and we observed epigenetic silencing in serous epithelial ovarian cancer, leading us to hypothesize that variation in this gene differentially associates with epithelial ovarian cancer risk according to histological subtype. Here we comprehensively map variation in HNF1B with respect to epithelial ovarian cancer risk and analyse DNA methylation and expression profiles across histological subtypes. Different single-nucleotide polymorphisms associate with invasive serous (rs7405776 odds ratio (OR) ¼ 1.13, P ¼ 3.1 Â 10 À 10) and clear cell (rs11651755 OR ¼ 0.77, P ¼ 1.6 Â 10 À 8) epithelial ovarian cancer. Risk alleles for the serous subtype associate with higher HNF1B-promoter methylation in these tumours. Unmethylated, expressed HNF1B, primarily present in clear cell tumours, coincides with a CpG island methylator phenotype affecting numerous other promoters throughout the genome. Different variants in HNF1B associate with risk of serous and clear cell epithelial ovarian cancer; DNA methylation and expression patterns are also notably distinct between these subtypes. These findings underscore distinct mechanisms driving different epithelial ovarian cancer histological subtypes.
Gynecologic Oncology
OBJECTIVE To assess the relationship between lifetime ovulatory years (LOY) and Epithelial ovaria... more OBJECTIVE To assess the relationship between lifetime ovulatory years (LOY) and Epithelial ovarian cancer (EOC) risk and survival. METHODS A systematic review was performed in accordance with PRISMA guidelines. Relevant studies were identified from PubMed, MEDLINE, and Embase through December 31, 2021 combining the following search: [("ovulation" or "ovulation cycles" or "ovulatory age" or "ovulatory cycles") and ("ovarian cancer" or "ovarian neoplasms") and ("humans" and "female")]. Reference lists of identified articles were searched for additional studies. Studies were excluded from consideration if they were not a published, peer-review article; not in English; lacked data on effect sizes; had data included in another publication; or were a review article, cross-sectional study, or case report. Two independent investigators screened abstracts and full texts for eligibility, extracted study-level data, and assigned study quality. Disagreements between abstractors were discussed and resolved by consensus. RESULTS Thirty-one reports were included in the qualitative review of LOY and EOC risk, inclusive of 24 studies with sufficient data to be included in the meta-analysis. Women with the highest level of LOY had 2.26 times higher odds of EOC than women with the lowest level of LOY (95% CI 1.94-2.83). LOY was associated with risk of serous (pooled OR 2.31, 95% CI 1.60-3.33) and endometrioid tumors (pooled OR 3.05, 95% CI 2.08-4.45) but not mucinous disease (pooled OR 1.52, 95% CI 0.87-2.64). There were only four studies examining the LOY-survival association, which precluded a quantitative assessment; however, three of the published studies reported worse outcome with greater LOY. CONCLUSION LOY is a risk factor for specific EOC histotypes and may also influences EOC survival. Standard definitions of LOY, participant-level data, and larger sample size will enable more precise quantitation of the LOY-EOC association, which can inform EOC risk assessment models.
Cancer Causes & Control
Objective: To examine the association between (GWG) and epithelial ovarian cancer (EOC). Methods:... more Objective: To examine the association between (GWG) and epithelial ovarian cancer (EOC). Methods: We compared GWG between 670 incident EOC cases to 1551 community controls from a population-based, case-control study conducted in Pennsylvania, Ohio, and New York from 2003-2008. Multivariable unconditional logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) associated with GWG adjusting for potential Terms of use and reuse: academic research for non-commercial purposes, see here for full terms. https://www.springer.com/aamterms-v1
Cancer Epidemiology, Biomarkers & Prevention
Objective: In clinical settings, transvaginal ultrasound has been used to evaluate abnormal vagin... more Objective: In clinical settings, transvaginal ultrasound has been used to evaluate abnormal vaginal bleeding. Because the endometrium responds to estrogens, endometrial thickness may constitute a biomarker of estrogen status in postmenopausal women. This study aimed to validate the transvaginal ultrasonographic measurement of endometrial thickness as an estrogen biomarker in asymptomatic, postmenopausal women by demonstrating an association between endometrial thickness and risk factors known to be associated with estrogen exposure. Method: Endometrial thickness was measured in 1,271 women ages 55 to 74 years who underwent transvaginal ultrasound screening as part of the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. A questionnaire, completed before screening, provided risk factor information, including reproductive and hormone use histories. Results: Endometrial thickness measurements ranged from 1 to 32 mm (median 3.0 mm). The frequencies of thicker endometrium (≥...
Cancers
Objective: Studies on low-grade serous ovarian cancer (LGSC) are limited by a low number of cases... more Objective: Studies on low-grade serous ovarian cancer (LGSC) are limited by a low number of cases. The aim of this study was to define the prognostic significance of age, stage, and CA-125 levels on survival in a multi-institutional cohort of women with pathologically confirmed LGSC. Methods: Women with LGSC were identified from the collaborative Ovarian Cancer Association Consortium (OCAC). Cases of newly diagnosed primary LGSC were included if peri-operative CA-125 levels were available. Age at diagnosis, FIGO stage, pre- and post-treatment CA-125 levels, residual disease, adjuvant chemotherapy, disease recurrence, and vital status were collected by the participating institutions. Progression-free (PFS) and overall survival (OS) were calculated. Multivariable (MVA) Cox proportional hazard models were used and hazard ratios (HR) calculated. Results: A total of 176 women with LGSC were included in this study; 82% had stage III/IV disease. The median PFS was 2.3 years and the median ...
Skip to main content Research Showcase. Research Showcase. My Account; FAQ; About; Home. &amp... more Skip to main content Research Showcase. Research Showcase. My Account; FAQ; About; Home. &amp;lt; Previous; Next &amp;gt;; Home &amp;gt; School of Computer Science &amp;gt; Institute for Software Research &amp;gt; 742. Institute for Software Research. Authors. Francesmary Modugno Brad Myers, Carnegie Mellon UniversityFollow. Title. Graphical Representation and Feedback in a PBD System. Date of Original Version. 1993. Type. Book Chapter. Download this Article Link to Full Text. Tell a Colleague Print COinS. ...
Gene list for clustering premenopausal (preM) estrogen receptor-positive (ER+) tumors. Table S1. ... more Gene list for clustering premenopausal (preM) estrogen receptor-positive (ER+) tumors. Table S1. Gene list selected by sparse k-means algorithm in The Cancer Genome Atlas (TCGA) data. Table S2. Genes selected based on TCGA data that are also in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data for validation. Table S3. Fixed number of genes (n = 21), gene list being selected from sparse k-means in TCGA. Table S4. Gene list selected by semi-supervised algorithm in METABRIC. Table S5. Fixed number of genes (n = 21), gene list being selected by semi-supervised algorithm in TCGA. Table S6. Genes (n = 28) in the LumA cluster that are significantly different between clusters 1 and 3. (XLSX 37 kb)
Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with s... more Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. Cancer Epidemiol Biomarkers Prev; 24(10); 1-11. Ó2015 AACR.
of fertility drugs and risk of ovarian cancer: results from a US-based case-control study
ARID1A (BAF250a) is a component of the SWI/SNF chromatin modifying complex, plays an important tu... more ARID1A (BAF250a) is a component of the SWI/SNF chromatin modifying complex, plays an important tumor suppressor role, and is considered prognostic in several malignancies. However, in ovarian carcinomas there are contradictory reports on its relationship to outcome, immune response, and correlation with clinicopathological features. We assembled a series of 1623 endometriosis-associated ovarian carcinomas, including 1078 endometrioid (ENOC) and 545 clear cell (CCOC) ovarian carcinomas through combining resources of the Ovarian Tumor Tissue Analysis (OTTA) Consortium, the Canadian Ovarian Unified Experimental Resource (COEUR), local, and collaborative networks. Validated immunohistochemical surrogate assays for ARID1A mutations were applied to all samples. We investigated associations between ARID1A loss/mutation, clinical features, outcome, CD8+ tumor-infiltrating lymphocytes (CD8+ TIL), and DNA mismatch repair deficiency (MMRd). ARID1A loss was observed in 42% of CCOC and 25% of EN...
Cancer Research, 2018
DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape h... more DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 × 10−7. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not prev...
Breast Cancer Research and Treatment, 2018
and approved this study. Availability of data and material All data generated during this study a... more and approved this study. Availability of data and material All data generated during this study are included in this published article and its supplementary information files. The NHS/NHSII microarray data is publicly available at GSE115577. TCGA RNASeq data is available at https://cancergenome.nih.gov/. PBCS data are available from GSE49175 and GSE50939.
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Papers by Francesmary Modugno