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1. A framework for assessing interactions for risk stratification models: the example of ovarian cancer

Author

Phung, Minh Tung, Lee, Alice W, McLean, Karen, Anton-Culver, Hoda, Bandera, Elisa V, Carney, Michael E, Chang-Claude, Jenny, Cramer, Daniel W, Doherty, Jennifer Anne, Fortner, Renee T, Goodman, Marc T, Harris, Holly R, Jensen, Allan, Modugno, Francesmary, Moysich, Kirsten B, Pharoah, Paul DP, Qin, Bo, Terry, Kathryn L, Titus, Linda J, Webb, Penelope M, Wu, Anna H, Zeinomar, Nur, Ziogas, Argyrios, Berchuck, Andrew, Cho, Kathleen R, Hanley, Gillian E, Meza, Rafael, Mukherjee, Bhramar, Pike, Malcolm C, Pearce, Celeste Leigh, and Trabert, Britton

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Rare Diseases, Women's Health, Ovarian Cancer, Cancer, Prevention, Aetiology, 2.1 Biological and endogenous factors, 2.5 Research design and methodologies (aetiology), Good Health and Well Being, Humans, Female, Ovarian Neoplasms, Risk Factors, Risk Assessment, Case-Control Studies, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

Generally, risk stratification models for cancer use effect estimates from risk/protective factor analyses that have not assessed potential interactions between these exposures. We have developed a 4-criterion framework for assessing interactions that includes statistical, qualitative, biological, and practical approaches. We present the application of this framework in an ovarian cancer setting because this is an important step in developing more accurate risk stratification models. Using data from 9 case-control studies in the Ovarian Cancer Association Consortium, we conducted a comprehensive analysis of interactions among 15 unequivocal risk and protective factors for ovarian cancer (including 14 non-genetic factors and a 36-variant polygenic score) with age and menopausal status. Pairwise interactions between the risk/protective factors were also assessed. We found that menopausal status modifies the association among endometriosis, first-degree family history of ovarian cancer, breastfeeding, and depot-medroxyprogesterone acetate use and disease risk, highlighting the importance of understanding multiplicative interactions when developing risk prediction models.

Published
2023

2. High pre-diagnosis inflammation-related risk score associated with decreased ovarian cancer survival

Author

Brieger, Katharine K, Phung, Minh Tung, Mukherjee, Bhramar, Bakulski, Kelly M, Anton-Culver, Hoda, Bandera, Elisa V, Bowtell, David DL, Cramer, Daniel W, DeFazio, Anna, Doherty, Jennifer A, Fereday, Sian, Fortner, Renée Turzanski, Gentry-Maharaj, Aleksandra, Goode, Ellen L, Goodman, Marc T, Harris, Holly R, Matsuo, Keitaro, Menon, Usha, Modugno, Francesmary, Moysich, Kirsten B, Qin, Bo, Ramus, Susan J, Risch, Harvey A, Rossing, Mary Anne, Schildkraut, Joellen M, Trabert, Britton, Vierkant, Robert A, Winham, Stacey J, Wentzensen, Nicolas, Wu, Anna H, Ziogas, Argyrios, Khoja, Lilah, Cho, Kathleen R, McLean, Karen, Richardson, Jean, Grout, Bronwyn, Chase, Anne, Deurloo, Cindy McKinnon, Odunsi, Kunle, Nelson, Brad H, Brenton, James D, Terry, Kathryn L, Pharoah, Paul DP, Berchuck, Andrew, Hanley, Gillian E, Webb, Penelope M, Pike, Malcolm C, and Pearce, Celeste Leigh

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Tobacco Smoke and Health, Prevention, Ovarian Cancer, Tobacco, Cancer, Rare Diseases, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Aged, Carcinoma, Ovarian Epithelial, Female, Health Behavior, Humans, Inflammation, Middle Aged, Ovarian Neoplasms, Proportional Hazards Models, Risk Assessment, Ovarian Cancer Association Consortium, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundThere is suggestive evidence that inflammation is related to ovarian cancer survival. However, more research is needed to identify inflammation-related factors that are associated with ovarian cancer survival and to determine their combined effects.MethodsThis analysis used pooled data on 8,147 women with invasive epithelial ovarian cancer from the Ovarian Cancer Association Consortium. The prediagnosis inflammation-related exposures of interest included alcohol use; aspirin use; other nonsteroidal anti-inflammatory drug use; body mass index; environmental tobacco smoke exposure; history of pelvic inflammatory disease, polycystic ovarian syndrome, and endometriosis; menopausal hormone therapy use; physical inactivity; smoking status; and talc use. Using Cox proportional hazards models, the relationship between each exposure and survival was assessed in 50% of the data. A weighted inflammation-related risk score (IRRS) was developed, and its association with survival was assessed using Cox proportional hazards models in the remaining 50% of the data.ResultsThere was a statistically significant trend of increasing risk of death per quartile of the IRRS [HR = 1.09; 95% confidence interval (CI), 1.03-1.14]. Women in the upper quartile of the IRRS had a 31% higher death rate compared with the lowest quartile (95% CI, 1.11-1.54).ConclusionsA higher prediagnosis IRRS was associated with an increased mortality risk after an ovarian cancer diagnosis. Further investigation is warranted to evaluate whether postdiagnosis exposures are also associated with survival.ImpactGiven that pre- and postdiagnosis exposures are often correlated and many are modifiable, our study results can ultimately motivate the development of behavioral recommendations to enhance survival among patients with ovarian cancer.

Published
2022

3. Menopausal hormone therapy prior to the diagnosis of ovarian cancer is associated with improved survival

Author

Brieger, Katharine K, Peterson, Siri, Lee, Alice W, Mukherjee, Bhramar, Bakulski, Kelly M, Alimujiang, Aliya, Anton-Culver, Hoda, Anglesio, Michael S, Bandera, Elisa V, Berchuck, Andrew, Bowtell, David DL, Chenevix-Trench, Georgia, Cho, Kathleen R, Cramer, Daniel W, DeFazio, Anna, Doherty, Jennifer A, Fortner, Renée T, Garsed, Dale W, Gayther, Simon A, Gentry-Maharaj, Aleksandra, Goode, Ellen L, Goodman, Marc T, Harris, Holly R, Høgdall, Estrid, Huntsman, David G, Shen, Hui, Jensen, Allan, Johnatty, Sharon E, Jordan, Susan J, Kjaer, Susanne K, Kupryjanczyk, Jolanta, Lambrechts, Diether, McLean, Karen, Menon, Usha, Modugno, Francesmary, Moysich, Kirsten, Ness, Roberta, Ramus, Susan J, Richardson, Jean, Risch, Harvey, Rossing, Mary Anne, Trabert, Britton, Wentzensen, Nicolas, Ziogas, Argyrios, Terry, Kathryn L, Wu, Anna H, Hanley, Gillian E, Pharoah, Paul, Webb, Penelope M, Pike, Malcolm C, Pearce, Celeste Leigh, and Consortium, for the Ovarian Cancer Association

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Estrogen, Rare Diseases, Cancer, Ovarian Cancer, Aging, Aged, Estrogen Replacement Therapy, Female, Hormone Replacement Therapy, Humans, Middle Aged, Neoplasm Staging, Neoplasm, Residual, Ovarian Neoplasms, Postmenopause, Progestins, Progression-Free Survival, Proportional Hazards Models, Survival Rate, Ovarian Cancer Association Consortium, Paediatrics and Reproductive Medicine, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis, Reproductive medicine
Abstract

PurposePrior studies of menopausal hormone therapy (MHT) and ovarian cancer survival have been limited by lack of hormone regimen detail and insufficient sample sizes. To address these limitations, a comprehensive analysis of 6419 post-menopausal women with pathologically confirmed ovarian carcinoma was conducted to examine the association between MHT use prior to diagnosis and survival.MethodsData from 15 studies in the Ovarian Cancer Association Consortium were included. MHT use was examined by type (estrogen-only (ET) or estrogen+progestin (EPT)), duration, and recency of use relative to diagnosis. Cox proportional hazards models were used to estimate the association between hormone therapy use and survival. Logistic regression and mediation analysis was used to explore the relationship between MHT use and residual disease following debulking surgery.ResultsUse of ET or EPT for at least five years prior to diagnosis was associated with better ovarian cancer survival (hazard ratio, 0.80; 95% CI, 0.74 to 0.87). Among women with advanced stage, high-grade serous carcinoma, those who used MHT were less likely to have any macroscopic residual disease at the time of primary debulking surgery (p for trend

Published
2020

4. Preclinical Models of Ovarian Cancer

Author

Karnezis, Anthony N and Cho, Kathleen R

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer, Ovarian Cancer, Prevention, Rare Diseases, Animals, Carcinoma, Chemoprevention, Chickens, Disease Models, Animal, Female, Humans, Mice, Ovarian Neoplasms, Ovariectomy, Prophylactic Surgical Procedures, Salpingectomy, ovarian cancer, ovary, fallopian tube, mouse model, laying hen, prevention, Paediatrics and Reproductive Medicine, Obstetrics & Reproductive Medicine, Reproductive medicine
Abstract

Preclinical models are relatively underutilized and underfunded resources for modeling the pathogenesis and prevention of ovarian cancers. Several reviews have detailed the numerous published models of ovarian cancer. In this review, we will provide an overview of experimental model systems, their strengths and limitations, and use selected models to illustrate how they can be used to address specific issues about ovarian cancer pathogenesis. We will then highlight some of the preclinical prevention studies performed to date and discuss experiments needed to address important unanswered questions about ovarian cancer prevention strategies.

Published
2017

5. Impact of oviductal versus ovarian epithelial cell of origin on ovarian endometrioid carcinoma phenotype in the mouse

Author

Wu, Rong, Zhai, Yali, Kuick, Rork, Karnezis, Anthony N, Garcia, Paloma, Naseem, Anum, Hu, Tom C, Fearon, Eric R, and Cho, Kathleen R

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Rare Diseases, Genetics, Cancer, Ovarian Cancer, Aetiology, 2.1 Biological and endogenous factors, Adenomatous Polyposis Coli Protein, Animals, Animals, Genetically Modified, Carcinoma, Endometrioid, Carcinoma, Ovarian Epithelial, Cell Differentiation, Disease Models, Animal, Epithelial Cells, Epithelium, Fallopian Tubes, Female, Glycoproteins, Humans, Integrases, Male, Mice, Neoplasms, Glandular and Epithelial, Ovarian Neoplasms, Ovary, PTEN Phosphohydrolase, Phenotype, Promoter Regions, Genetic, Tamoxifen, mouse ovarian cancer model, cell of origin, Fallopian tube, oviduct, endometrioid carcinoma, Clinical Sciences, Pathology, Clinical sciences, Oncology and carcinogenesis
Abstract

Endometrioid carcinoma (EC) is a relatively indolent ovarian carcinoma subtype that is nonetheless deadly if detected late. Existing genetically engineered mouse models (GEMMs) of the disease, based on transformation of the ovarian surface epithelium (OSE), take advantage of known ovarian EC driver gene lesions, but do not fully recapitulate the disease features seen in patients. An EC model in which the Apc and Pten tumour suppressor genes are conditionally deleted in murine OSE yields tumours that are biologically more aggressive and significantly less differentiated than human ECs. Importantly, OSE is not currently thought to be the tissue of origin of most ovarian cancers, including ECs, suggesting that tumour initiation in Müllerian epithelium may produce tumours that more closely resemble their human tumour counterparts. We have developed Ovgp1-iCreERT2 mice in which the Ovgp1 promoter controls expression of tamoxifen (TAM)-regulated Cre recombinase in oviductal epithelium - the murine equivalent of human Fallopian tube epithelium. Ovgp1-iCreERT2 ;Apcfl/fl ;Ptenfl/fl mice treated with TAM or injected with adenovirus expressing Cre into the ovarian bursa uniformly develop oviductal or ovarian ECs, respectively. On the basis of their morphology and global gene expression profiles, the oviduct-derived tumours more closely resemble human ovarian ECs than do OSE-derived tumours. Furthermore, mice with oviductal tumours survive much longer than their counterparts with ovarian tumours. The slow progression and late metastasis of oviductal tumours resembles the relatively indolent behaviour characteristic of so-called Type I ovarian carcinomas in humans, for which EC is a prototype. Our studies demonstrate the utility of Ovgp1-iCreERT2 mice for manipulating genes of interest specifically in the oviductal epithelium, and establish that the cell of origin is an important consideration in mouse ovarian cancer GEMMs. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Published
2016

6. High-grade serous carcinomas arise in the mouse oviduct via defects linked to the human disease

Author

Zhai, Yali, Wu, Rong, Kuick, Rork, Sessine, Michael S., Schulman, Stephanie, Green, Megan, Fearon, Eric R., and Cho, Kathleen R.

Subjects
Genes, BRCA1, Mice, Transgenic, Oviducts, Carcinoma, Ovarian Epithelial, Article, Mice, Carcinosarcoma, Genes, Neurofibromatosis 1, Biomarkers, Tumor, Animals, Fallopian Tube Neoplasms, Humans, Genetic Predisposition to Disease, Genes, Retinoblastoma, Promoter Regions, Genetic, Fallopian Tubes, Glycoproteins, Ovarian Neoplasms, Metaplasia, Hyperplasia, Integrases, PTEN Phosphohydrolase, Genes, p53, United Kingdom, Phenotype, Mutation, Female, Neoplasm Grading, Neoplasms, Cystic, Mucinous, and Serous, Carcinoma in Situ
Abstract

Recent studies suggest that the most common and lethal type of “ovarian” cancer, high-grade serous carcinoma (HGSC), usually arises from epithelium on the fallopian tube fimbriae, and not from the ovarian surface epithelium (OSE). We have developed Ovgp1-iCreERT2 mice in which the Ovgp1 promoter controls expression of tamoxifen (TAM)-regulated Cre recombinase in oviductal epithelium – the murine equivalent of human fallopian tube epithelium (FTE). We employed Ovgp1-iCreERT2 mice to show that FTE-specific inactivation of several different combinations of tumour suppressor genes recurrently mutated in human HGSCs – namely Brca1, Trp53, Rb1, and Nf1 – results in serous tubal intraepithelial carcinomas (STICs) that progress to HGSC or carcinosarcoma, and to widely metastatic disease in a subset of mice. The cancer phenotype is highly penetrant and more rapid in mice carrying engineered alleles of all four tumour suppressor genes. Brca1, Trp53 and Pten inactivation in the oviduct also results in STICs and HGSCs, and is associated with diffuse epithelial hyperplasia and mucinous metaplasia not observed in mice with intact Pten. Oviductal tumours arise earlier in these mice, compared to those with Brca1, Trp53, Rb1 and Nf1 inactivation. Tumour initiation and/or progression in mice lacking conditional Pten alleles likely requires acquisition of additional defects, a notion supported by our identification of loss of the wild-type Rb1 allele in the tumours of mice carrying only one floxed Rb1 allele. Collectively, the models closely recapitulate the heterogeneity and histological, genetic, and biological features of human HGSC. These models should prove useful for studying the pathobiology and genetics of HGSC in vivo, and for testing new approaches for prevention, early detection, and treatment.

Published
2017

7. Type I to Type II Ovarian Carcinoma Progression: Mutant Trp53 or Pik3ca Confers a More Aggressive Tumor Phenotype in a Mouse Model of Ovarian Cancer

Author

Wu, Rong, Baker, Suzanne J., Hu, Tom C., Norman, Kyle M., Fearon, Eric R., and Cho, Kathleen R.

Subjects
endocrine system diseases, Class I Phosphatidylinositol 3-Kinases, Adenomatous Polyposis Coli Protein, Mutation, Missense, Endometrium, Mice, Phosphatidylinositol 3-Kinases, Animals, Humans, Neoplasm Invasiveness, Neoplasm Metastasis, neoplasms, Ovarian Neoplasms, Hyperplasia, PTEN Phosphohydrolase, Regular Article, Epithelial Cells, Survival Analysis, female genital diseases and pregnancy complications, Disease Models, Animal, Cell Transformation, Neoplastic, Phenotype, Disease Progression, Female, Mutant Proteins, Tumor Suppressor Protein p53, Signal Transduction
Abstract

A dualistic pathway model of ovarian carcinoma (OvCA) pathogenesis has been proposed: type I OvCAs are low grade, genetically stable, and relatively more indolent than type II OvCAs, most of which are high-grade serous carcinomas. Endometrioid OvCA (EOC) is a prototypical type I tumor, often harboring mutations that affect the Wnt and phosphatidylinositol 3-kinase/AKT/mammalian target of rapamycin signaling pathways. Molecular and histopathologic analyses indicate type I and II OvCAs share overlapping features, and a subset of EOCs may undergo type I→type II progression accompanied by acquisition of somatic TP53 or PIK3CA mutations. We used a murine model of EOC initiated by conditional inactivation of the Apc and Pten tumor suppressor genes to investigate mutant Trp53 or Pik3ca alleles as key drivers of type I→type II OvCA progression. In the mouse EOC model, the presence of somatic Trp53 or Pik3ca mutations resulted in shortened survival and more widespread metastasis. Activation of mutant Pik3ca alone had no demonstrable effect on the ovarian surface epithelium but resulted in papillary hyperplasia when coupled with Pten inactivation. Our findings indicate that the adverse prognosis associated with TP53 and PIK3CA mutations in human cancers can be functionally replicated in mouse models of type I→type II OvCA progression. Moreover, the models should represent a robust platform for assessment of the contributions of Trp53 or Pik3ca defects in the response of EOCs to conventional and targeted drugs.

Published
2013

8. Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data

Author

Gruber Stephen B, Giordano Thomas J, Cho Kathleen R, Macdonald James, Ghosh Debashis, Kuick Rork, Chen Wei, Shedden Kerby, Fearon Eric R, Taylor Jeremy MG, and Hanash Samir

Subjects
Transcription, Genetic, Gene Expression, lcsh:Computer applications to medicine. Medical informatics, Models, Biological, Sensitivity and Specificity, Random Allocation, Humans, Computer Simulation, False Positive Reactions, lcsh:QH301-705.5, Oligonucleotide Array Sequence Analysis, Analysis of Variance, Models, Statistical, Models, Genetic, Gene Expression Profiling, Computational Biology, Reproducibility of Results, Sequence Analysis, DNA, lcsh:Biology (General), Research Design, Data Interpretation, Statistical, Calibration, lcsh:R858-859.7, RNA, DNA Probes, Oligonucleotide Probes, Algorithms, Software, Research Article
Abstract

Background A critical step in processing oligonucleotide microarray data is combining the information in multiple probes to produce a single number that best captures the expression level of a RNA transcript. Several systematic studies comparing multiple methods for array processing have used tightly controlled calibration data sets as the basis for comparison. Here we compare performances for seven processing methods using two data sets originally collected for disease profiling studies. An emphasis is placed on understanding sensitivity for detecting differentially expressed genes in terms of two key statistical determinants: test statistic variability for non-differentially expressed genes, and test statistic size for truly differentially expressed genes. Results In the two data sets considered here, up to seven-fold variation across the processing methods was found in the number of genes detected at a given false discovery rate (FDR). The best performing methods called up to 90% of the same genes differentially expressed, had less variable test statistics under randomization, and had a greater number of large test statistics in the experimental data. Poor performance of one method was directly tied to a tendency to produce highly variable test statistic values under randomization. Based on an overall measure of performance, two of the seven methods (Dchip and a trimmed mean approach) are superior in the two data sets considered here. Two other methods (MAS5 and GCRMA-EB) are inferior, while results for the other three methods are mixed. Conclusions Choice of processing method has a major impact on differential expression analysis of microarray data. Previously reported performance analyses using tightly controlled calibration data sets are not highly consistent with results reported here using data from human tissue samples. Performance of array processing methods in disease profiling and other realistic biological studies should be given greater consideration when comparing Affymetrix processing methods.

Published
2004

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