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Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
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Research Articles

Reproductive and Hormonal Factors and Risk of Ovarian Cancer by Tumor Dominance: Results from the Ovarian Cancer Cohort Consortium (OC3)

Tianyi Huang, Mary K. Townsend, Nicolas Wentzensen, Britton Trabert, Emily White, Alan A. Arslan, Elisabete Weiderpass, Julie E. Buring, Tess V. Clendenen, Graham G. Giles, I-Min Lee, Roger L. Milne, N. Charlotte Onland-Moret, Ulrike Peters, Dale P. Sandler, Leo J. Schouten, Piet A. van den Brandt, Alicja Wolk, Anne Zeleniuch-Jacquotte and Shelley S. Tworoger
Tianyi Huang
1Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
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  • For correspondence: tih541@mail.harvard.edu
Mary K. Townsend
2Division of Population Science, Moffitt Cancer Center and Research Institute, Tampa, Florida.
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Nicolas Wentzensen
3Division of Cancer Epidemiology and Genetics, NCI, NIH, Washington, D.C.
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Britton Trabert
3Division of Cancer Epidemiology and Genetics, NCI, NIH, Washington, D.C.
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Emily White
4Fred Hutchinson Cancer Research Center, Seattle, Washington.
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Alan A. Arslan
5Department of Population Health, New York University School of Medicine, New York, New York.
6Department of Environmental Medicine, New York University School of Medicine, New York, New York.
7Department of Obstetrics and Gynecology, New York University School of Medicine, New York, New York.
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Elisabete Weiderpass
8International Agency for Research on Cancer, World Health Organization, Lyon, France.
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Julie E. Buring
9Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
10Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
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Tess V. Clendenen
5Department of Population Health, New York University School of Medicine, New York, New York.
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Graham G. Giles
11Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
12Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia.
13Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
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I-Min Lee
9Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
10Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
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Roger L. Milne
11Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
12Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia.
13Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
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N. Charlotte Onland-Moret
14Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
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Ulrike Peters
4Fred Hutchinson Cancer Research Center, Seattle, Washington.
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Dale P. Sandler
15National Institute of Environmental Health Science, Bethesda, Maryland.
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Leo J. Schouten
16GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands.
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Piet A. van den Brandt
16GROW-School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands.
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Alicja Wolk
17Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
18Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
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Anne Zeleniuch-Jacquotte
5Department of Population Health, New York University School of Medicine, New York, New York.
6Department of Environmental Medicine, New York University School of Medicine, New York, New York.
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Shelley S. Tworoger
1Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
2Division of Population Science, Moffitt Cancer Center and Research Institute, Tampa, Florida.
9Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
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DOI: 10.1158/1055-9965.EPI-19-0734 Published January 2020
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Abstract

Background: Laterality of epithelial ovarian tumors may reflect the underlying carcinogenic pathways and origins of tumor cells.

Methods: We pooled data from 9 prospective studies participating in the Ovarian Cancer Cohort Consortium. Information on measures of tumor size or tumor dominance was extracted from surgical pathology reports or obtained through cancer registries. We defined dominant tumors as those restricted to one ovary or where the dimension of one ovary was at least twice as large as the other, and nondominant tumors as those with similar dimensions across the two ovaries or peritoneal tumors. Competing risks Cox models were used to examine whether associations with reproductive and hormonal risk factors differed by ovarian tumor dominance.

Results: Of 1,058 ovarian cancer cases with tumor dominance information, 401 were left-dominant, 363 were right-dominant, and 294 were nondominant. Parity was more strongly inversely associated with risk of dominant than nondominant ovarian cancer (Pheterogeneity = 0.004). Ever use of oral contraceptives (OC) was associated with lower risk of dominant tumors, but was not associated with nondominant tumors (Pheterogeneity = 0.01). Higher body mass index was associated with higher risk of left-dominant tumors, but not significantly associated with risk of right-dominant or nondominant tumors (Pheterogeneity = 0.08).

Conclusions: These data suggest that reproductive and hormonal risk factors appear to have a stronger impact on dominant tumors, which may have an ovarian or endometriosis origin.

Impact: Examining the associations of ovarian cancer risk factors by tumor dominance may help elucidate the mechanisms through which these factors influence ovarian cancer risk.

This article is featured in Highlights of This Issue, p. 1

Introduction

Ovarian cancer, the most deadly gynecologic malignancy in the U. S. women, is a highly heterogeneous disease. For example, each histotype of ovarian cancer likely originates through a different etiologic pathway, displaying a high level of heterogeneity in clinical behavior and disease progression; importantly, each histotype displays a distinct risk factor profile (1–3). Furthermore, recent evidence suggests that different types of ovarian tumors may have distinct cellular origins, potentially representing two major carcinogenic pathways (4–6). Type I ovarian tumors are more likely to arise from the ovarian surface epithelium, be histologically classified as low-grade serous, endometrioid, mucinous, or clear cell subtypes, and harbor mutations in the genes of KRAS, BRAF, β-catenin, and pTEN (4–6). In contrast, type II tumors are more likely to be high-grade serous carcinomas with a distal fallopian tube origin and p53 mutations (4–6). Prior work suggests that tumors originating from the ovarian surface (i.e., those with type I tumor characteristics) tend to present with a dominant tumor mass with tumor growth primarily confined to one ovary, whereas tumors of fallopian tube origin (i.e., those with type II tumor characteristics) tend to be nondominant resulting in bilateral tumors with a similar extent of growth or peritoneal tumors (7–11). In addition to ovarian and fallopian tube origin, emerging evidence suggests that endometrioid and clear cell ovarian cancers, which are more likely to have dominant tumor masses, may directly arise from endometriotic tissues (12). Thus, tumor dominance can be considered as an indicator for ovarian or endometriosis versus fallopian tube cancer cell of origin. While a growing body of evidence documented substantial heterogeneity in risk factor profiles by ovarian tumor characteristics including histologic subtype and aggressiveness (2, 13), less is known for tumor dominance that may be an indicator of tumor developmental features such as cell of origin or tumor spread. As such, elucidating the associations with ovarian cancer risk factors by tumor dominance may provide further insights into the mechanisms through which these factors influence ovarian cancer development (14, 15). We conducted the current analysis in the Ovarian Cancer Cohort Consortium (OC3), a large-scale collaborative effort to understand etiologic heterogeneity in ovarian cancer, to examine whether the associations of ovarian cancer risk with reproductive, hormonal, anthropometric, and lifestyle factors differed by ovarian tumor dominance.

Materials and Methods

Study populations

Nine prospective cohort studies (out of a total of 23 contributing studies) in the OC3 with available data on tumor dominance were included in this analysis (Table 1; ref. 2). All OC3-participating studies had a prospective design with regular follow-up of ovarian cancer diagnoses and death, and collected key ovarian cancer risk factors [e.g., age, oral contraceptive (OC) use, parity] at baseline. Individual studies were approved by the respective institutional review board following the institution's requirement. The OC3 study protocol was approved by the institutional review boards of the Brigham and Women's Hospital (Boston, MA) and Harvard T.H. Chan School of Public Health (Boston, MA), and those of participating registries as required. The approaches for data pooling, harmonization, and analysis, developed by OC3 Data Coordinating Center, were approved by the institutional review board of the Brigham and Women's Hospital (Boston, MA).

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Table 1.

Characteristics of included cohorts participating in the Ovarian Cancer Cohort Consortium.

Exposure assessment

Exposure information at baseline was obtained and harmonized centrally for either the full cohort (8 studies) or a case-cohort sample with weights for subcohort members (1 study). We examined multiple putative and known ovarian cancer risk factors, including parity (nulliparous, 1 child, 2 children, 3 children, ≥4 children; per 1 child), age at first birth (<20, 20–<25, 25–<30, 30+ years; per 1 year), age at last birth (<25, 25–<30, 30–<35, 35+ years; per 1 year), years since last birth (per 1 year), duration of OC use (ever, never; never, ≤1, >1–≤5, >5–≤10, >10 years; per 5 years of use), duration of breastfeeding (per 1 year among parous women), age at menarche (≤11, 12, 13, 14, ≥15 years; per 1 year), age at natural menopause (among postmenopausal women: ≤45, >45–≤50, >50–≤55, >55 years; per 5 years), duration of postmenopausal hormone therapy (HT) use (among postmenopausal women: ever, never; never, ≤5, >5 years; per 1 year), tubal ligation (yes, no), hysterectomy (yes, no), endometriosis (yes, no), first degree family history of breast cancer (yes, no), first degree family history of ovarian cancer (yes, no), body mass index (BMI) at baseline (<20, 20–<25, 25–<30, 30–<35, ≥35 kg/m2; per 5 kg/m2), BMI at age 18–20 years (<18, 18–<20, 20–<22, ≥22 kg/m2; per 5 kg/m2), height (<1.60, 1.60–< .65, 1.65–<1.70, ≥1.70 m; per 0.05 m), and smoking at baseline (never, ever; never, <10, 10–<20, 20–<35, ≥35 pack-years; per 20 pack-years).

Ovarian cancer ascertainment and tumor dominance definition

Incident cases of epithelial ovarian cancer or peritoneal cancer were identified by self-report or through linkage with cancer registry. Diagnoses were confirmed, and tumor characteristics, including histology, stage, grade, and tumor size, were obtained, by review of medical or surgical pathology report or linkage with cancer registry data. Specifically, of the nine cohorts included in this study, the Melbourne Collaborative Cohort Study, the Nurses' Health Study (NHS), NHSII, the Sister Study, and the Women's Health Study obtained ovarian cancer characteristics and tumor dominance data primarily from pathology report abstraction, supplementing with cancer registry, whereas the Netherlands Cohort Study (NCS) on Diet and Cancer and the VITamins And Lifestyle Cohort (VITAL) obtained information from cancer registry data with pathology report summaries (NCS) or full-report abstraction (VITAL) to obtain additional information on tumor dominance. Data from the New York University Women's Health Study and the Swedish Mammography Cohort Study were solely based on cancer registry. For cases with a surgical pathology report available, we abstracted dimensions, area, or volume recorded for ovarian tumors identified on each side of the peritoneal cavity (left and right). For cases classified through cancer registry, we collected information regarding the extent of tumor growth on each ovary, further extracting data on tumor size on the left and right when available. We considered an ovarian cancer case as having dominant tumor mass if any of the following was met: (i) the growth of tumor was limited to one ovary, (ii) a tumor mass was found on one ovary, with only tumor foci on the other ovary, or (iii) the tumor dimensions, area, or volume on one side was at least twice that of the other side. A case was considered nondominant if any of the following was met: (i) the tumor was classified as primary peritoneal cancer, (ii) only tumor foci were found on both ovaries, (iii) no ovaries could be identified on either side of the peritoneal cavity, or (iv) the tumor dimensions, area, or volume on one side was within two times that of the other side. Cases without appropriate information to classify tumor dominance were censored at time of diagnosis.

Statistical analysis

Women with a history of cancer (other than nonmelanoma skin cancer), with bilateral oophorectomy prior to study entry, or missing age at baseline were excluded. We calculated HRs and 95% confidence intervals (95% CI) using competing risks Cox proportional hazards regression to evaluate associations between exposures and ovarian cancer by tumor dominance (right dominant, left dominant, nondominant; ref. 16). Person-time was counted from study entry until date of (i) invasive ovarian cancer diagnosis, (ii) death, or (iii) end of follow-up, whichever occurred first. Given the relatively small number of available cases in individual cohorts, we pooled data and stratified on year of birth and cohort to account for potential differences in baseline hazards by these factors. Heterogeneity in the associations by tumor dominance was tested using a likelihood ratio test comparing the model allowing the association for the risk factor of interest to vary by dominance versus the one not allowing the association to vary (17). All models were adjusted for age at entry, number of children, and duration of OC use. Additional adjustment for HT use was conducted for hysterectomy analyses. For missing covariates, we included a missing indicator in the model. Primary analyses included all available invasive cases evaluating dominant versus nondominant tumors, and secondary, hypothesis-generating analyses were conducted to assess potential differences between left- and right-dominant tumors. We also performed sensitivity analyses restricted to serous tumors. To address the concern that tumor dominance may reflect tumor stage or that nondominant tumors are advanced-stage tumors that progress from early-stage, dominant tumors, we further examined the associations by tumor dominance for stage I/II and stage III ovarian cancer separately. All analyses were performed using SAS 9.4 (SAS Institute, Cary, NC), with a P < 0.05 considered statistically significant.

Results

Compared with women who did not develop ovarian cancer during follow-up, those later diagnosed with ovarian cancer were older and more likely to be postmenopausal, but were less likely to have ever used OC, be parous, or have tubal ligation at baseline (Table 2). Compared with patients with ovarian cancer with nondominant tumors, those with a dominant tumor mass were less likely to be parous and, among those who were parous, had fewer children. In addition, women with a dominant tumor mass were less likely to have ever smoked, have ever used OC, or have tubal ligation, hysterectomy, and unilateral oophorectomy than those with nondominant tumors. Furthermore, compared with women with right-dominant tumors, women with left-dominant tumors were less likely to be parous or have used OC.

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Table 2.

Reproductive and hormonal risk factors at baseline by ovarian cancer status and tumor dominance in OC3a.

Of 1,058 incident ovarian cancer cases identified during follow-up with tumor dominance information, 764 (72.2%) were classified as dominant tumors, with 401 (37.9%) having a dominant tumor mass on the left and 363 (34.3%) on the right (Table 3). There were higher proportions of serous, stage III, or poorly differentiated tumors among nondominant cases, whereas nonserous, stage I/II, and well or moderately differentiated tumors were more common in dominant cases. When comparing tumor characteristics by laterality of tumor dominance, there were more serous tumors in right-dominant tumors and more clear cell subtype in left-dominant tumors; other tumor characteristics were similar.

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Table 3.

Ovarian tumor dominance by tumor characteristics in OC3.

When evaluating reproductive factors with ovarian cancer risk by tumor dominance, parity, tubal ligation, and endometriosis appeared more strongly associated with risk of dominant versus nondominant ovarian cancer (Table 4). The HR (95% CI) for each additional child was 0.85 (0.81–0.89) for dominant tumors compared with 0.97 (0.90–1.04) for nondominant tumors (Pheterogeneity = 0.004). The association with parity was more inverse for left-dominant tumors (HR: 0.81; 95% CI, 0.76–0.87) than for right-dominant tumors (HR: 0.90; 95% CI, 0.84–0.96; Supplementary Table S1). Although the difference was not statistically significant (Pheterogeneity = 0.07), tubal ligation was associated with a suggestively lower risk of dominant tumors (HR: 0.74; 95%: 0.56–0.99) but a nonsignificant higher risk of nondominant tumors (HR: 1.13; 95% CI, 0.80–1.60); the inverse association with tubal ligation was similar for left- and right-dominant tumors. Similarly, despite a lack of statistically significant heterogeneity, there was a suggestion of a stronger positive association of endometriosis with dominant tumors (HR: 1.70; 95% CI, 1.00–3.00) than nondominant tumors (HR: 1.12; 95% CI, 0.40–3.15).

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Table 4.

Associations of reproductive factors with ovarian cancer risk by tumor dominance.

When examining the associations with exogenous hormonal factors, the association with OC use differed significantly by tumor dominance (Table 5). Ever OC use was associated with significantly lower risk of dominant ovarian tumors (HR: 0.70; 95% CI, 0.59–0.83), while no association was observed for nondominant tumors (HR: 1.05; 95% CI, 0.80–1.39; Pheterogeneity = 0.01). Furthermore, the reduced ovarian cancer risk among ever versus never OC users was significantly lower for left-dominant tumors (HR: 0.59; 95% CI, 0.47–0.76) and suggestively lower for right-dominant tumors (HR: 0.83; 95% CI, 0.65–1.06; Supplementary Table S2). In addition, while no heterogeneity was observed when comparing all dominant versus nondominant tumors (Pheterogeneity = 0.76), current BMI was associated with a significantly increased risk of left-dominant ovarian cancer (HR for every 5-unit increase in BMI: 1.14, 95% CI, 1.04–1.26), with no association for right-dominant or nondominant tumors (Pheterogeneity = 0.08). However, we did not observe clear differences by tumor dominance in the associations with postmenopausal HT, family history, anthropometric factors, or smoking. Postmenopausal HT, family history of ovarian cancer, and height were positively associated with ovarian cancer risk regardless of tumor dominance (Pheterogeneity > 0.30).

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Table 5.

Associations of exogenous hormonal factors, family history, anthropometric factors, and smoking with ovarian cancer risk by tumor dominance.

In sensitivity analyses, we examined associations with risk of serous ovarian cancer by tumor dominance. Among the reproductive factors, the association between parity and serous ovarian cancer by tumor dominance was similar to the primary analysis (Supplementary Table S3). The HR for each additional child was statistically significant for dominant tumors (HR: 0.92; 95% CI, 0.86–0.98), but not for nondominant tumors (HR: 0.99; 95% CI, 0.92–1.07; Pheterogeneity = 0.15). In analyses of hormonal factors, family history, anthropometric factors, and smoking, associations were largely similar to those in the primary analysis (Supplementary Table S4). Finally, when examining the associations by stage I/II and stage III separately, we observed similar differences by tumor dominance for parity, tubal ligation, and OC use (Supplementary Table S5), although the differences were less statistically significant due to reduced sample size within each stratum.

Discussion

In this pooled analysis of nine prospective cohort studies, we observed that several reproductive and hormonal factors, including parity, OC use, tubal ligation, and endometriosis, were differentially associated with ovarian cancer risk by tumor dominance, with suggestively stronger relationships with dominant versus nondominant ovarian tumors. However, the associations with other reproductive factors, hormonal factors, anthropometric measures, family history, and smoking did not vary substantially between dominant and nondominant tumors. Intriguingly, OC use and current BMI showed a different association with left-dominant and right-dominant ovarian tumors.

Our results were consistent with a prior study in NHS, NHSII, and New England Case–Control Study, which reported stronger associations of parity, tubal ligation, and endometriosis with dominant tumors than with nondominant tumors (14). Taken together, these findings suggest that parity, tubal ligation, and endometriosis are more likely to influence ovarian tumors originating from ovarian surface epithelial cells. Indeed, higher parity leads to a lower number of ovulatory cycles, which reduces the possibility of neoplastic progression on the ovarian surface epithelium resulting from ovulation-induced wounds (18, 19). On the other hand, the elevated progesterone levels during pregnancy may confer potential protection against ovarian carcinogenesis by suppressing proliferation and inducing apoptosis of ovarian epithelial cells (20). Interestingly, we also observed that OC use was more strongly inversely associated with dominant versus nondominant ovarian cancer risk, which was not noted in the prior study (14). The differential impact of OC use on ovarian cancer tumor dominance may be explained by similar mechanisms as proposed for parity, although the reasons for the stronger inverse association for left- versus right-dominant tumors require further study.

It is hypothesized that the mechanism through which endometriosis increases ovarian cancer risk is possibly due to the reflux and implantation of endometrial fragments onto the ovarian surface during menstruation, which leads to inflammation and malignant transformation (21, 22). Similarly, tubal ligation may be protective for ovarian cancer by blocking the retrograde passage of endometrial tissues through the fallopian tubes and preventing subsequent potential carcinogenesis on the ovarian surface (23, 24). These mechanisms point to the suggestively stronger associations of endometriosis and tubal ligation with dominant ovarian tumors, which may have an ovarian surface epithelium origin. However, although endometriosis and ovarian endometrioma have been suggested to have left lateral predisposition (25, 26), the observed association between endometriosis and risk of dominant ovarian cancer was suggestively stronger for right- (HR: 1.97) versus left-dominant tumors (HR: 1.55). Nevertheless, it should be noted that the analyses of endometriosis and tubal ligation were based on a smaller number of cases, and the observed differences, which did not reach statistical significance, could be due to chance. It is unclear why the associations with current BMI also differed by laterality of dominant ovarian tumors, with a positive association only observed for left-dominant cancers. A recent study suggests that adiposity during early life was more strongly associated with ovarian cancer risk, particularly nonserous ovarian cancer, compared with adiposity during adulthood (27). More research is needed to confirm whether the association between early-life adiposity and ovarian cancer risk is also primarily driven by left-dominant tumors. Furthermore, there is some evidence suggesting that BMI has a stronger positive association with distal colon cancer than proximal colon cancer (28), suggesting that the hormonal impact of adiposity may have different impact across tissue types/locations. Future investigation should replicate these analyses in independent datasets and evaluate potential underlying mechanisms.

Of note, tumor dominance was highly correlated with other tumor characteristics, with nondominant tumors more likely to be serous, high grade, and poorly differentiated. Despite this, we observed that the majority of both dominant and nondominant cases had a serous subtype (n = 357 dominant serous tumors vs. 235 nondominant serous tumors); similarly, there was a distribution of dominant and nondominant tumors within both low-stage and high-stage tumors. We conducted sensitivity analyses restricted to serous tumors or stratified by tumor stage. Interestingly, we observed similar differences in risk factor associations by tumor dominance in serous tumors, as well as in both low-stage tumors and in high-stage tumors, suggesting that tumor dominance provides additional insight that prediagnosis risk factors can influence tumor developmental pathways. Here, our results suggest that reproductive factors may be particularly relevant to tumor spread within the peritoneal cavity and may be more important for tumors likely to be of ovarian or endometriosis origin, beyond serous histotype and tumor stage (12). However, even with the large sample size through consortia efforts, we cannot exclude that the differential associations by tumor dominance in nonserous ovarian cancer may be partly due to the stronger associations of certain risk factors with nonserous subtypes. For example, we and others have previously shown that endometriosis was more strongly associated with risk of endometrioid and clear cell ovarian cancer (2, 22). Given that about 95% of endometrioid and clear cell tumors were classified as dominant, it is possible that the positive association between endometriosis and dominant ovarian cancer may be largely explained by histotype. Future studies are needed to elucidate whether the observed differences by tumor dominance are independent of histotype and other tumor characteristics.

This study is strengthened by the relatively large sample size including data from 10 prospective studies, each with abstracted data on tumor size and laterality using a standardized abstraction procedure. Furthermore, the use of harmonized exposure data reduced the potential for misclassification. However, this study was still limited by a relatively low number of cases, in part because tumor data were not available on a large proportion of cases, usually because a pathology report was not available or size information about the tumor was not listed in the report. This also precluded an analysis examining associations by tumor dominance within histotypes other than serous, the most common subtype. As discussed above, given that we previously showed associations of reproductive factors, in particular, varied by histotypes (2), we cannot fully clarify whether the observed differences in the associations were due to dominance or histotype.

In summary, we found that reproductive and hormonal factors were more strongly associated with dominant tumors, suggesting that progesterone exposure may be particularly relevant for tumors of ovarian origin. Furthermore, the intriguing, albeit suggestive, differences in association between dominant tumors on the left versus right side for OC use and BMI, should be explored in future studies. Additional research should also examine other ways to leverage pathology report data and assess key metrics of tumor heterogeneity to better elucidate etiologic mechanisms underlying ovarian cancer development.

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Disclaimer

The authors assume full responsibility for analyses and interpretation of these data. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/World Health Organization.

Authors' Contributions

Conception and design: T. Huang, N. Wentzensen, E. Weiderpass, G.G. Giles, P.A. van den Brandt, A. Wolk, S.S. Tworoger

Development of methodology: A.A. Arslan, S.S. Tworoger

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): N. Wentzensen, B. Trabert, E. White, A.A. Arslan, J.E. Buring, T.V. Clendenen, G.G. Giles, I.-M. Lee, R.L. Milne, U. Peters, D.P. Sandler, L.J. Schouten, P.A. van den Brandt, A. Wolk, A. Zeleniuch-Jacquotte, S.S. Tworoger

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): T. Huang, M.K. Townsend, N. Wentzensen, B. Trabert, E. White, R.L. Milne, A. Wolk, S.S. Tworoger

Writing, review, and/or revision of the manuscript: T. Huang, M.K. Townsend, N. Wentzensen, B. Trabert, E. White, A.A. Arslan, E. Weiderpass, J.E. Buring, T.V. Clendenen, G.G. Giles, I.-M. Lee, R.L. Milne, N.C. Onland-Moret, U. Peters, D.P. Sandler, L.J. Schouten, P.A. van den Brandt, A. Wolk, A. Zeleniuch-Jacquotte, S.S. Tworoger

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): M.K. Townsend, T.V. Clendenen, L.J. Schouten, S.S. Tworoger

Study supervision: I.-M. Lee, S.S. Tworoger

Acknowledgments

The authors acknowledge the Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital (Boston, MA), as the home of the Nurses' Health Study. The Nurses' Health Study would like to thank the following state cancer registries for their assistance: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. This work was supported by Department of Defense Ovarian Cancer Research Program grant W81XWH-12-1-0561 (to S.S. Tworoger). Additional research funding and support included NCI Intramural Research Program; VicHealth and Cancer Council Victoria, and Australian National Health and Medical Research Council grants 209057, 396414, and 1074383 (Melbourne Collaborative Cohort Study); UM1 CA186107, P01 CA87969 (Nurses' Health Study); UM1 CA176726 (Nurses' Health Study II); UM1 CA182934, P30 CA016087 and P30 ES000260 (NYU Women's Health Study); NIEHS Intramural Research Program (Sisters Study, Project Z01-ES044005 to D.P. Sandler); Swedish Cancer Foundation (Swedish Mammography Cohort); K05CA154337 from the NCI and Office of Dietary Supplements (VITamins And Lifestyle Cohort); and CA047988, HL043851, HL080467, HL099355, and CA182913 (Women's Health Study).

The costs of publication of this article were defrayed, in part, by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Footnotes

  • Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).

  • Cancer Epidemiol Biomarkers Prev 2020;29:200–7

  • Received June 24, 2019.
  • Revision received September 13, 2019.
  • Accepted November 4, 2019.
  • Published first November 12, 2019.
  • ©2019 American Association for Cancer Research.

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Cancer Epidemiology Biomarkers & Prevention: 29 (1)
January 2020
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Reproductive and Hormonal Factors and Risk of Ovarian Cancer by Tumor Dominance: Results from the Ovarian Cancer Cohort Consortium (OC3)
Tianyi Huang, Mary K. Townsend, Nicolas Wentzensen, Britton Trabert, Emily White, Alan A. Arslan, Elisabete Weiderpass, Julie E. Buring, Tess V. Clendenen, Graham G. Giles, I-Min Lee, Roger L. Milne, N. Charlotte Onland-Moret, Ulrike Peters, Dale P. Sandler, Leo J. Schouten, Piet A. van den Brandt, Alicja Wolk, Anne Zeleniuch-Jacquotte and Shelley S. Tworoger
Cancer Epidemiol Biomarkers Prev January 1 2020 (29) (1) 200-207; DOI: 10.1158/1055-9965.EPI-19-0734

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Reproductive and Hormonal Factors and Risk of Ovarian Cancer by Tumor Dominance: Results from the Ovarian Cancer Cohort Consortium (OC3)
Tianyi Huang, Mary K. Townsend, Nicolas Wentzensen, Britton Trabert, Emily White, Alan A. Arslan, Elisabete Weiderpass, Julie E. Buring, Tess V. Clendenen, Graham G. Giles, I-Min Lee, Roger L. Milne, N. Charlotte Onland-Moret, Ulrike Peters, Dale P. Sandler, Leo J. Schouten, Piet A. van den Brandt, Alicja Wolk, Anne Zeleniuch-Jacquotte and Shelley S. Tworoger
Cancer Epidemiol Biomarkers Prev January 1 2020 (29) (1) 200-207; DOI: 10.1158/1055-9965.EPI-19-0734
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