Hormone Concentrations during Pregnancy and Maternal Risk of Epithelial Ovarian …806991/... · 2015. 4. 22. · 17-hydroxyprogesterone, and progesterone), growth factors (insulin-like

UMEÅ UNIVERSITY MEDICAL DISSERTATIONS

New Series No. 1715 * ISSN 0346-6612 * ISBN 978-91-7601-273-4

Hormone Concentrations during Pregnancy and Maternal Risk of

Epithelial Ovarian Cancer

Helena Schock

Faculty of Medicine Umeå University, 2015

Copyright© Helena Schock 2015 Responsible publisher under Swedish law: the Dean of the Medical Faculty This work is protected by the Swedish Copyright Legislation (Act 1960:729) ISBN: 978-91-7601-273-4 ISSN: 0346-6612 Electronic version available at http://umu.diva-portal.org/ Printed by: Print & Media Umeå, Sweden 2015

Promise me you'll always remember: You're braver than you believe, and stronger than you seem, and smarter than you think.

A. A. Milne

i

Abstract

Background: The aim of this thesis was to study the relationship of pre-diagnostic

circulating concentrations of sex steroid hormones (androgens, estradiol,

17-hydroxyprogesterone, and progesterone), growth factors (insulin-like growth factor-I

(IGF-I), placental growth hormone (GH)), sex hormone binding globulin (SHBG), and

anti-Müllerian hormone (AMH) with risk of epithelial ovarian cancer (EOC) overall, and

by tumor invasiveness and histology. A longitudinal study was used to assess patterns of

hormonal changes during a single pregnancy, and in two consecutive pregnancies.

Materials & Methods: A case-control study was nested within the Finnish Maternity

Cohort and the Northern Sweden Maternity Cohort. A total of 1 052 EOC cases were

identified through linkages with the cancer registries in both countries. For each case,

2-3 controls were selected. Cases and controls were matched on cohort, age and date at

blood draw, as well as for parity at blood draw and at diagnosis (n=2 695). Odds ratios

(OR) and corresponding 95% confidence intervals [CI] were estimated using conditional

logistic regression. The longitudinal study was based on 71 pregnant Finnish women,

who donated blood samples in each trimester of pregnancy.

Results: Higher androgen concentrations were associated with an increased risk of

overall EOC (e.g., testosterone ORT3 vs. T1: 1.56 [1.30-1.87], ptrend<0.0001), while the risk

of endometrioid tumors increased with higher estradiol concentrations (ORT3 vs. T1: 2.76

[1.04-7.33], ptrend=0.03). Higher IGF-I was associated with a non-significant decrease in

risk for invasive (ORT3 vs. T1: 0.79 [0.62-1.02], ptrend=0.07) and endometrioid tumors

(ORT3 vs. T1: 0.55 [0.28-1.07], ptrend=0.07). The inverse association between IGF-I levels

and risk of invasive EOC was stronger in analyses limited to women aged <55 years at

diagnosis (ORT3 vs. T1: 0.74 [0.57-0.96], ptrend=0.03). No associations were observed

between pre-diagnostic progesterone, SHBG, placental GH, and AMH with EOC risk

overall, or by tumor invasiveness and histology.

The longitudinal study showed that hormone concentrations were more strongly

correlated between consecutive trimesters of a pregnancy than between the 1st and 3rd

trimesters. Further, 3rd trimester hormone concentrations can be estimated from 1st or

2nd trimester measurements.

Conclusion: Higher pre-diagnostic androgens, estradiol, and IGF-I are associated with

EOC risk, and associations differ by tumor invasiveness and histology.

Keywords:

epithelial ovarian cancer; sex steroid hormones; IGF-I; placental GH; AMH;

pregnancy; prospective study.

ii

Table of Contents

Abstract ................................................................................... i

Table of Contents ....................................................................ii

Abbreviations ......................................................................... iv

List of Tables and Figures....................................................... vi

Original Papers ..................................................................... vii

1. Introduction ........................................................................ 1

1.1 Ovarian Cancer ................................................................................................ 1

1.2 Pregnancy and Ovarian Cancer ..................................................................... 5

1.3 Hormones in Pregnancy and Ovarian Cancer............................................... 6

1.3.1 Progesterone ............................................................................................ 8

1.3.2 17-OHP ..................................................................................................... 9

1.3.3 Androgens ................................................................................................ 9

1.3.4 Estradiol ................................................................................................. 10

1.3.5 IGF-I and placental GH.......................................................................... 11

1.3.6 anti-Müllerian Hormone ...................................................................... 12

1.4 Hormone Measurements throughout Pregnancy ....................................... 13

2. Aims .................................................................................. 15

3. Materials and Methods ...................................................... 16

3.1 Nested Case-Control Study .......................................................................... 16

3.1.1 Cohort Descriptions ............................................................................... 16

3.1.2 Selection of Study Subjects ................................................................... 16

3.1.3 Tumor Data ............................................................................................ 17

3.1.4 Covariate Data ....................................................................................... 18

3.1.5 Participants by Study ............................................................................ 19

3.1.6 Laboratory Analyses .............................................................................. 20

3.1.7 Statistical Methods ................................................................................ 21

3.2 Longitudinal Study ....................................................................................... 23

3.2.1 Selection of Study Subjects ................................................................... 23

iii

3.2.2 Laboratory Analyses ............................................................................. 23

3.2.3 Statistical Methods ............................................................................... 24

4. Results .............................................................................. 26

4.1 Case-Control Study ....................................................................................... 26

4.1.1 Descriptive Statistics ............................................................................. 26

4.1.2 Associations between Hormones and EOC .......................................... 31

4.1.3 Mutual Adjustment ............................................................................... 35

4.1.4 Stratified Analyses ................................................................................. 38

4.1.5 Analyses by Tumor Stage ...................................................................... 42

4.1.6 Sensitivity Analyses ............................................................................... 42

4.2 Longitudinal Study....................................................................................... 43

4.2.1 One Pregnancy....................................................................................... 44

4.2.2 Two Consecutive Pregnancies .............................................................. 47

4.2.3 Sensitivity Analyses .............................................................................. 48

5. Discussion ......................................................................... 49

5.1 Methodological Considerations: Case-Control Study ................................. 49

5.2 Methodological Considerations: Longitudinal Study ................................ 52

5.3 General Discussion: Case-Control Study .................................................... 53

5.4 General Discussion: Longitudinal Study .................................................... 62

6. Conclusions ....................................................................... 64

7. Outlook and Future Directions .......................................... 65

Acknowledgments ................................................................. 66

References ............................................................................ 68

iv

Abbreviations

17-OHP 17-hydroxyprogesterone

AMH anti-Müllerian hormone (also known as MIS)

AMHRII AMH receptor type II

AR androgen receptor

CI confidence interval

D4 androstenedione

E2 estradiol

EOC epithelial ovarian cancer

ER estrogen receptor

FMC Finnish Maternity Cohort

GA gestational age

GH growth hormone

GHRH growth hormone-releasing hormone

HRT hormone replacement therapy

ICC intraclass correlation coefficient

IGF-I insulin-like growth factor-I

IGF-IR insulin-like growth factor-I receptor

LMP last menstrual period

MIS Müllerian inhibiting substance (also known as AMH)

NOS not otherwise specified

NSMC Northern Sweden Maternity Cohort

OC oral contraceptive

OR odds ratio

v

OSE ovarian surface epithelium

P progesterone

PCOS polycystic ovary syndrome

PR progesterone receptor

SHBG sex hormone binding globulin

T testosterone

vi

List of Tables and Figures

List of Tables

Table 1. Epithelial ovarian carcinomas – the main histologic subtypes.............. 2

Table 2. Distribution of characteristics of EOC cases by tumor histology ........ 27

Table 3. Spearman partial correlation coefficients ............................................. 30

Table 4. ORs by tumor invasiveness and histology across tertiles .................... 32

Table 5. Effect of mutual adjustment .................................................................. 36

Table 6. Longitudinal Study - Baseline characteristics ...................................... 43

Table 7. Spearman correlation coefficients between successive trimesters ...... 44

Table 8. Median hormone concentrations by parity .......................................... 45

Table 9. Percentage changes in 3rd trimester hormone concentrations ............ 46

Table 10. Median hormone concentrations by number of children .................. 47

Table 11. Characteristics of prospective studies on endogenous androgens ..... 54

Table 12. Characteristics of prospective studies on endogenous IGF-I ............ 58

List of Figures

Figure 1. Age-standardized incidence rates of ovarian cancer ............................. 1

Figure 2. Classification of epithelial ovarian tumors ........................................... 2

Figure 3. Circulating hormone concentrations (ng/mL) during pregnancy ...... 6

Figure 4. Main hormone production sites during pregnancy ............................. 7

Figure 5. Number of study participants per studied hormone .......................... 19

Figure 6. ORs for doubling of circulating hormone concentrations by age ..... 39

Figure 7. ORs of EOC for circulating androgen concentrations ........................ 55

Figure 8. ORs of EOC for circulating IGF-I in women age <55 years at dx ...... 59

vii

Original Papers

This thesis is based upon the following papers, which are referred to in the text

by their Roman numerals:

I. Schock H, Lundin E, Vääräsmäki M, Grankvist K, Fry A, Dorgan JF,

Pukkala E, Lehtinen M, Surcel HM, Lukanova A. Anti-Müllerian hormone

and risk of invasive serous ovarian cancer. Cancer Causes Control 2014;

25(5):583-9.

II. Schock H, Surcel HM, Zeleniuch-Jacquotte A, Grankvist K, Lakso HÅ,

Fortner RT, Kaaks R, Pukkala E, Lehtinen M, Toniolo P, Lundin E. Early

pregnancy sex steroids and maternal risk of epithelial ovarian cancer.

Endocr Relat Cancer 2014; 21(6):831-44

III. Schock H, Fortner RT, Surcel HM, Grankvist K, Pukkala E, Lehtinen M,

Lundin E. Early pregnancy IGF-I and placental GH and risk of epithelial

ovarian cancer: A nested case-control study.

Int J Cancer 2015; doi: 10.1002/ijc.29387

IV. Schock H, Zeleniuch-Jacquotte A, Lundin E, Grankvist K, Lakso HÅ,

Idahl A, Surcel HM, Fortner RT. Longitudinal assessment of pregnancy

hormones.

Manuscript submitted

All previously published papers were reproduced with kind permission from

BioScientifica (Endocrine-Related Cancer), John Wiley and Sons (International

Journal of Cancer), and Springer (Cancer Causes and Control).

1

1. Introduction

1.1 Ovarian Cancer

Ovarian cancer is the 7th most common cancer in females worldwide.1 The

age-standardized incidence rate in 2012 was 9.1 per 100 000 woman-years in

high-income countries (e.g., Northern Europe and North America) compared to

4.9 per 100 000 woman-years in low-income countries (e.g., Africa and large

parts of Asia; Figure 1). The observed variation between regions may reflect a

different prevalence of risk factors, use of screening, diagnostic methods, as well

as differences in lifespan, or simply varying data quality.

Figure 1. Age-standardized incidence rates of ovarian cancer worldwide

Figure obtained from Ferlay et al. 1

Despite being a rare disease, ovarian cancer is the most lethal gynecologic

cancer, causing approximately 150 000 deaths per year worldwide.1 To date,

there are no reliable effective screening procedures. Therefore, the majority of

ovarian cancer cases are diagnosed at an advanced stage, with peritoneal

metastases and/or metastases in distant organs, resulting in overall relative

5- and 10-year survival rates of only about 44% and 36%, respectively.2

The most common type of ovarian cancer, comprising more than 95% of

cases, is epithelial ovarian cancer (EOC); less common non-epithelial types

include germ cell tumors (~3%) and sex cord stromal tumors (~2%).3

2

Table 1. Epithelial ovarian carcinomas – the main histologic subtypes

Serous Mucinous Endometrioid Clear Cell

Mean age at diagnosis

~ 60 years 54 years 55-58 years 50-53 years

Distribution ~75% ~3% ~10% ~10%

Morphological resemblance to

Fallopian tube epithelium

Endocervical epithelium

Endometrial gland epithelium

Clear and hobnail-like

cells

Usual stage at diagnosis

Localized / advanced *

Localized Localized Localized

Response to chemotherapy

Intermediate / high *

Low High Low

Prognosis Favorable / poor * Favorable Favorable Intermediate

* serous tumors are further divided into low- and high-grade serous carcinomas

Accumulating evidence indicates that EOC histologic subgroups represent

clinically, morphologically, and molecularly distinct diseases, with the main

subtypes being serous, endometrioid, clear cell, and mucinous (Table 1).4-8 The

remaining invasive ovarian tumors are classified as not otherwise specified

(NOS) or “other” (Figure 2).9 While clear cell tumors account for about 10% of

invasive epithelial ovarian cancers in Western countries, the frequency in

Japanese women is substantially higher (~25%).4,10

Figure 2. Classification of epithelial ovarian tumors by histology and invasiveness

invasive mucinous

borderline mucinous

borderline serous

invasive serous

endometrioid

clear cell

other

borderline tumors

invasive tumors

3

Ovarian tumors of low malignant potential constitute a subgroup of

epithelial ovarian cancers also known as borderline tumors (Figure 2).

Approximately 10-20% of epithelial ovarian malignancies are borderline

tumors, which are distinguished from ovarian carcinomas by the absence of

destructive stromal invasion and high-grade atypia.11,12 Similar epidemiologic

risk factors have been reported for invasive cancers and borderline tumors, with

the latter occurring at a younger age, presenting at an earlier stage, and with a

more favorable prognosis.12-14 Borderline tumors are mostly of serous (43-53%)

or mucinous hystology (43-52%).12,13,15

The pathogenic mechanisms involved in the development of ovarian

cancer are poorly understood. The traditional view is that the ovarian surface

epithelium (OSE) repeatedly invaginates throughout a woman’s reproductive

life to form clefts and inclusion cysts (e.g., after ovulation). The epithelium

lining these cortical inclusion cysts may undergo Müllerian metaplasia induced

by the hormone-rich stromal milieu, giving rise to ovarian tumors via a series of

step-wise mutations.5 More recently, it has been proposed that a proportion of

EOCs may arise via different pathways depending on their histology: Serous

tumors may develop from implantation of tubal epithelial cells onto the ovarian

surface, or from serous tubal intraepithelial carcinomas that metastasize to the

ovary.5,16 Endometrioid and clear cell tumors may arise from endometriosis, and

mucinous tumors are hypothesized to develop in a step-wise manner from

pre-existing mucinous cystadenomas or borderline tumors.17,18

There are several epidemiologic factors associated with risk of EOC. Risk

has been shown to decrease with increasing parity, as well as with use of oral

contraceptives (OC),19-27 and to some extent also with older age at last birth,

lactation, hysterectomy, or tubal ligation.19,20,22,23,28-30 Well-established risk

factors for EOC include: age, nulliparity, prolonged use of hormone replacement

therapy (HRT), as well as family history of ovarian cancer, 20,23,31-36 and to some

extent also infertility (in involuntarily nulliparous women), endometriosis, talc

use, or smoking.19,20,37-41 Other factors, such as age at menarche and menopause,

yielded inconclusive results, with studies reporting a weak decrease in risk with

increasing age at menarche/menopause19,23 or showing no association.19,22 A

4

recent meta-analysis of 27 epidemiologic studies supported the inverse

association of older age at menarche and risk of ovarian cancer.42 Associations

between epidemiologic factors and disease risk have been reported to vary by

menopausal status at diagnosis,43 to differ in mucinous tumors as compared to

non-mucinous tumors (e.g., association of smoking with increased risk of

mucinous tumors only),44,45 and to vary by histologic subgroups46,47 or to be

similar among them.23,48

All of the major etiological hypotheses for carcinogenesis of EOC are

partially supported by epidemiologic observations, but none of them can explain

EOC carcinogenesis on its own: The ‘Incessant Ovulation Hypothesis’ postulates

that the repetitive wounding and healing of the OSE and the adjacent tubal

epithelium, induced by monthly ovulation, increases cell proliferation and thus

the likelihood of genomic instability which could lead to oncogenesis.49 This

hypothesis is in line with the observed risk reduction with parity, lactation, and

OC use. The ‘Gonadotropin Hypothesis’ implicates direct and indirect

stimulation of the OSE by gonadotropins, leading to the development and

progression of ovarian tumors.50 Support comes from the observed protective

effects of parity and OC use, but this hypothesis does not explain the increased

risk with HRT use, even though HRT reduces gonadotropin concentrations.51

Another hypothesis postulates that ovulation entails inflammation of the OSE,

promoting mutagenic factors such as oxidative stress, DNA damage and repair,

as well as elevated concentrations of cytokines and prostaglandins.52 In fact,

factors associated with inflammation (e.g., endometriosis, ovulation, talc use)

increase risk of EOC. On the other hand, no clear association was observed for

anti-inflammatory drugs with reduced risk.53 The ‘Incessant Menstruation

Hypothesis’ suggests that repeated exposure to retrograde menstruation

exposes the ovary and fallopian tube to reactive oxygen species and oxidative

iron from the blood.54 This hypothesis is supported by the reduced risk

associated with hysterectomy and tubal ligation. The ‘Wash-out Hypothesis’ is

based on the observed protective effect of pregnancy, implicating that cells that

have undergone malignant transformation are removed from the ovaries during

each pregnancy.21,55 Endogenous hormones are hypothesized to be involved in

the pathogenesis of EOC.56 Hormonal factors, such as steroid hormones or the

5

growth hormone (GH) / insulin-like growth factor-I (IGF-I) axis, may be

involved in the etiology of EOC, as they play a central role in regulating cell

proliferation, differentiation, and apoptosis.56-58 This work explores the

endogenous hormones hypothesis in detail.

1.2 Pregnancy and Ovarian Cancer

The overall protective effect of parity seems to pertain to all epithelial

ovarian tumors, with differing magnitude, irrespective of invasiveness,21,59-62

histological subtype,25,63,64 or other histo-pathological classifications.65,66

However, there are also studies indicating that pregnancy may not be related to

mucinous tumors or may even increase risk.61,67-69

Observations of low disease rates among groups with high parity, such as

Mormons and Seventh-Day Adventists,70,71 and high disease rates among

nulliparous women, such as nuns,72 provided some of the first evidence for a

possible protective effect of parity on risk of EOC. Since then, epidemiological

studies have consistently showed the protective effect of pregnancy irrespective

of maternal race/ethnicity.73

In comparison to nulliparous women, parous women have a 30 to 50%

lower risk of developing ovarian cancer.19,25,62 While the first childbirth is

considered to confer the greatest risk reduction (~40%),74 each subsequent birth

further decreases risk by 8-14%.19,21,25,75

Results from observational studies on the effect of incomplete

pregnancies on risk of EOC are inconclusive; some studies have reported a

decrease in risk,19,23 while others showed no association.20,76 Yet another study

observed an increased risk of EOC for women with multiple miscarriages.77 One

reason for the inconsistent findings might be that incomplete pregnancies

included voluntary abortions, miscarriages, and other terminations with

differing duration of pregnancy. These subtypes of incomplete pregnancy may

have a different association with risk due to associated medical conditions or

hormonal changes (e.g., underlying infertility, progesterone insufficiency).

Another reason could be under- or misreporting of incomplete pregnancies.78

Furthermore, women with voluntary abortions tend to have completed fewer

6

pregnancies over their reproductive lifespan and failure to study the effect of

incomplete pregnancies across strata of women with the same number of

full-term pregnancies could mask a possible association with risk of EOC. A

large pooled analysis indicated similar rates of protection per month of

gestation in full-term and incomplete pregnancies.19 The lesser protection

conferred by incomplete pregnancy was attributed to its shorter duration.19

1.3 Hormones in Pregnancy and Ovarian Cancer

The biological mechanisms underlying the protective effect of pregnancy

on EOC risk are largely unknown. The ovulation interruption related to

pregnancy is associated with greater decrease in risk as compared to 12 months

of anovulation induced by oral contraceptive use, delayed menarche, or early

menopause.19,56,74 Thus, it was proposed that hormonal changes associated with

pregnancy (other than gonadotropins) mediate the protective effect of

pregnancy on ovarian cancer risk.

Figure 3. Circulating hormone concentrations (ng/mL) during pregnancy. Adapted from references 79-82

17-OHP AMH D4

E2 IGF-I Placental GH

P T

Pre-conception concentrations are midcycle values obtained from ref 83

0

100

200

300

400

0

2

4

6

8

pre-conception 1st trimester 2nd trimester 3rd trimester

IGF

-I, placen

tal GH

, P 17

-OH

P, A

MH

, D4

, E2,

T

Luteal-placental shift

7

There are substantial alterations in the secretion, metabolism, and

concentrations of circulating hormones in maternal serum during gestation

(Figure 3). The main source of estradiol and progesterone production during

pregnancy is the placenta. The liver continuous the production of IGF-I and the

ovaries remain the main source of the anti-Müllerian hormone (AMH) and

androgens. A simplified illustration of the main hormone production sites

during pregnancy is presented in Figure 4.

During the very first weeks of pregnancy, the corpus luteum secretes

progesterone, 17-hydroxyprogesterone (17-OHP), and estradiol in increasing

quantities. The major site of synthesis for progesterone and estradiol shifts to

the placental trophoblasts as the corpus luteum declines (after approximately

the seventh week of gestation), and concentrations of these hormones further

increase as pregnancy progresses, whereas the concentration of 17-OHP

decreases.82 Early pregnancy androgen concentrations are similar to those in

non-pregnant women, and increase more modestly with progressing gestation.

Early pregnancy IGF-I concentrations are lower than those of non-pregnant

premenopausal women, but rise with progressing pregnancy, following the

Figure 4. Main hormone production sites during pregnancy

Mother Placenta Fetus

Cholesterol Cholesterol

Progesterone

3β-HSD

Adrenal glands Adrenal glands

3β-HSDAromatase

Estradiol

Placental GHIGF-I

AMHandrostenedione

testosterone

Liver

DHEA-SDHEADHEA-S

Ovary

Pituitary GH

Figure composed of information obtained from references 84-86

8

increasing concentrations of placental GH. AMH levels in early pregnancy are

similar to pre-pregnancy concentrations and decline across gestation.

1.3.1 Progesterone

In premenopausal, non-pregnant women, progesterone is mainly

synthesized by the corpus luteum in the luteal phase, with relatively low

concentrations in the follicular phase of the menstrual cycle. The site of

production in early pregnancy is the corpus luteum; this changes to the placenta

after the luteal-placental shift (between weeks 7-10 of pregnancy).87

Progesterone concentrations rise from <50 ng/mL in the first trimester to ~200

ng/mL in the third trimester (Figure 3).87

Progesterone is the most likely candidate to mediate a ‘washout effect’ of

pregnancy, i.e., to eliminate cells from the ovary that have undergone malignant

transformation.21 Progesterone has been shown to increase apoptosis, to induce

cellular senescence of ovarian cancer cells through FOXO1,88 and to inhibit the

growth of normal ovarian surface epithelial cells,89,90 as well as of benign and

malignant ovarian tumor cells.91-95

Exposure to high levels of progesterone as observed during pregnancy

(~3-15 - times higher with progressing pregnancy as compared to non-pregnant

women),96 combined with the strong pro-apoptotic effect of progesterone on the

ovarian surface epithelium, is one possible explanation for the observation that

the protection associated with pregnancy is stronger than the protection accrued

through simple ovulation suppression (e.g., by OC use). This hypothesis is also

supported by the beneficial effect of twin pregnancies, where progesterone

concentrations at gestation week 26 are 1.8-times higher as compared to a

singleton pregnancy.97 Several studies, but not all,98-100 have indicated that

women who had a twin pregnancy tend to have lower risk of ovarian cancer,

irrespective of tumor invasiveness, as compared to women who had only

singleton pregnancies.69,101,102

9

1.3.2 17-OHP

In premenopausal, non-pregnant women 17-OHP, the precursor hormone

for ovarian and adrenal synthesis of androgens, is secreted by the corpus

luteum, and concentrations peak during the luteal phase (~2.9 ng/mL), while

throughout the remaining menstrual cycle lower levels are observed (<2.25

ng/mL).83 In pregnant women, 17-OHP concentrations peak during weeks 5-6 of

gestation and gradually decrease and plateau after the luteal-placental shift

(Figure 3), as the placenta lacks P450C17 to convert progesterone to 17-OHP.82

Little is known about the biologic activity of 17-OHP, but it has been

shown that elevated 17-OHP levels are associated with 17-hydroxylase excess as

well as 21-hydroxylase deficiency both resulting in hyper-androgenism.103,104

To our knowledge, no prior epidemiologic data exist on the association of

17-OHP with EOC risk.

1.3.3 Androgens

During pregnancy, as in non-pregnant women, androgens are produced

by the ovaries and the adrenal cortex; the adrenal glands and liver of the fetus

are additional minor sources of androgens (Figure 4).105 Circulating testosterone

concentrations increase gradually (~2-fold) between preconception and the

third trimester, while concentrations of androstenedione remain stable across

gestation (Figure 3).82,96,106 Given that androgens are relatively stable in early

pregnancy, the androgens quantified in this study (testosterone and

androstenedione) are likely representative of circulating premenopausal

androgen concentrations.

Support for the involvement of androgens in the pathogenesis of EOC is

derived from results of in vitro studies demonstrating increased cell

proliferation of normal ovarian surface epithelial cells after androgen

administration.107,108 Epidemiological studies show a protective effect of OC use,

which reduces ovarian androgen synthesis and circulating androgen levels.58,107-

109 Women diagnosed with polycystic ovary syndrome (PCOS), a

hyper-androgenic disorder, might be at increased risk, however, available data

are sparse and inconclusive.110-112

10

To date, studies directly relating pre-diagnostic endogenous androgen

concentrations to risk of EOC are inconclusive and only few considered EOC

subtypes. Two studies reported that women with higher androstenedione

concentrations were at increased risk of developing EOC,113,114 whereas two

other studies observed no association between serum concentrations of

androgens with EOC risk.115,116 The most recent study observed no association

with risk overall, but a decreased risk of serous EOC with higher levels of

androstenedione.117

1.3.4 Estradiol

Estradiol is synthesized by aromatization of androgens that are derived

from the ovary and the maternal and fetal adrenal, and synthesized de novo in

placental syncytiotrophoblasts (Figure 4).105,118 In premenopausal, non-pregnant

women estradiol is secreted by the granulosa cells of the ovary, whereas during

pregnancy it is synthesized mainly in the placenta. Estradiol concentrations rise

from ~1 ng/mL at week 5 of gestation to ~15 ng/mL at week 40.82,106

In vitro and animal studies have shown the potential of estrogens to

stimulate cell proliferation and inhibit apoptosis of OSE and ovarian cancer

cells.119-123 To date, only one epidemiologic study (n=31 cases) reported a

non-significant association of endogenous estradiol and EOC risk.113 However,

prior studies reported increased risk of endometrial cancer with higher

endogenous estradiol concentrations in postmenopausal women.124,125 As

endometrioid ovarian tumors are histologically similar to endometrial tissue,

increased estradiol levels may also be associated with an increased risk of

endometrioid EOC.

It has also been observed that women with endometriosis, which is

associated with molecular aberrations that favor higher local production of

estradiol,126 are at an increased risk of developing endometrioid EOC.37,38

Furthermore, recent large-scale epidemiologic studies observed that women

using estrogen-progestin HRT regimens for more than 5 years or those using

estrogen-only regimens are at increased risk of developing EOC.34-36

11

1.3.5 IGF-I and placental GH

During pregnancy, IGF-I is involved in the regulation of fetal and

placental growth and development. Maternal concentrations of circulating IGF-I

are regulated by liver synthesis dependent on pituitary GH, which, by

mid-pregnancy, is replaced by placental GH (Figure 4).

Placental GH

Placental GH is a biologically active variant of the pituitary GH, with

similar somatogenic bioactivity, i.e., growth-related effects. In contrast to the

pulsatile secretion of pituitary GH, placental GH is secreted in a continuous

manner, providing an estimate of exposure through a single measurement.127,128

In sera of pregnant women, placental GH has been detected as early as weeks

5-8 of gestation. During pregnancy, it increases gradually (Figure 3), reaches

peak levels at 36-37 weeks, and is undetectable at delivery after placental

expulsion.79,129 Cross-sectional studies of normal pregnancies, as well as

pregnancies complicated by conditions such as pre-eclampsia or gestational

diabetes, have shown that placental GH correlates with IGF-I, regardless of

complications, confirming its role in the control of IGF-I synthesis during

pregnancy.130-132

IGF-I

Early pregnancy circulating IGF-I concentrations are slightly lower than

concentrations in non-pregnant women.79,130-132 However, pre-pregnancy IGF-I

concentrations are correlated with those measured at pregnancy week 8

(r=0.57) or week 16 (r=0.39).80 The observed decrease in IGF-I is a consequence

of the pregnancy-associated increase in circulating estradiol, which results in

hepatic resistance to pituitary GH.133 Maternal IGF-I levels increase by >40%

after 24-27 weeks of pregnancy and decrease rapidly postpartum to return to

pre-pregnancy values (Figure 3).80,87,134,135

IGF-I signaling may promote tumor development, including gynecologic

cancers,136 by exerting its well-established mitotic, anti-apoptotic, and

pro-angiogenic effects.137 IGF-I and its binding proteins are involved in the

12

regulation of ovarian follicle development, steroidogenesis, and cellular mitosis

and apoptosis in ovarian tissue.138,139 Experimental studies have shown the

presence of IGF-I protein, receptor, and mRNA in ovarian cancer cells and

tissues and have confirmed the association with progression of ovarian

cancer.136,140 It has also been reported that IGF-I levels are significantly higher

in cyst fluid from invasive malignant epithelial ovarian neoplasms compared to

cyst fluid from benign neoplasms, and that higher serum concentrations are

associated with a more favorable outcome.141,142

Prior prospective studies investigating the association between IGF-I and

ovarian cancer either did not see an overall association143-145 or observed a

modest inverse association.146

1.3.6 anti-Müllerian Hormone

The anti-Müllerian hormone (AMH), also known as the Müllerian

inhibiting substance (MIS), is responsible for the regression of the Müllerian

ducts during fetal life in males.147 Absence of AMH production in female fetuses

results in the development of the uterus, the fallopian tubes, and the upper

vagina from the Müllerian ducts.

During the reproductive life of women, AMH is secreted by the granulosa

cells of the growing follicles (i.e., primary, secondary, pre-antral, and small

antral follicles).148,149 AMH is a marker of the ovarian reserve; its concentrations

are very low at birth, increase significantly at puberty, remain stable thereafter

until age ~25 years, and then slowly decline to be undetectable at the onset of

menopause, when the ovarian follicle pool is exhausted.148,150 In early

pregnancy, AMH concentrations are similar to those in non-pregnant women,

with AMH levels decreasing ~50% by the third trimester of pregnancy

(Figure 3), and returning to pre-pregnancy concentrations shortly after

delivery.81,151,152 Possible reasons for the decline across gestation are

hypothesized to be the reduced follicular maturation, pregnancy-associated

haemodilution, and increased plasma-protein binding.153

The clinical use of AMH is well established. Serum AMH is utilized for the

diagnosis and follow-up of patients with granulosa cell tumors, it can be

13

predictive of ovarian response after in vitro fertilization treatments, and it is

under discussion to become a diagnostic criterion for patients with PCOS.153-155

AMH is a member of the transforming growth factor superfamily and

binding to its specific type II receptor (AMHRII) activates down-stream

pathways notable for differentiation and growth inhibition.156 AMH has been

shown to inhibit the growth and migration of EOC and to induce G1 arrest of

ovarian cancer stem/progenitor cells.147,156,157 Based on these properties and

with the advantage of limited toxicity (high expression of functioning AMHRII

in EOCs, but not in most healthy tissues), AMH was proposed as a candidate for

adjuvant treatment of patients with ovarian cancer.147

To our knowledge, no prior epidemiologic data are available on the

associations of AMH with EOC risk.

1.4 Hormone Measurements throughout Pregnancy

The in utero conditions of pregnancy may impact subsequent disease risk

in the mother and the offspring.158 Parity is associated with maternal

cardiovascular disease,159 and is an established protective factor in breast,160

endometrial,161 and ovarian cancers.66 Early pregnancy hormones have been

investigated in the context of breast cancer in the mother,162 and are

investigated in relation to risk of ovarian cancer as part of this thesis. In the

offspring, the intrauterine environment might influence the risk of breast and

testicular cancer, the development of autistic disorders, and several other

adverse health outcomes.163-165

Depending on the outcome of interest, hormone concentrations measured

at different periods during pregnancy may be of relevance. For instance,

hormones measured in early pregnancy, during which the fetal organogenesis

takes place, may be particularly important when cancer in the offspring is of

interest, whereas hormone concentrations during late pregnancy may be

relevant in relation to maternal risk of breast and ovarian cancers given

evidence that complete pregnancies are most strongly associated with these

malignancies.77,166

14

Established biorepositories in Northern Europe (e.g., Finland, Iceland,

Sweden) store sera collected during early pregnancy (mostly in weeks 8 to 14)

for screening on systemic infections such as HIV, hepatitis, or rubella.

Worldwide, several pregnancy and birth cohorts have been established over the

last three decades to study associations between early-life exposures

(e.g., genetic, environmental, or lifestyle factors) with health and disease

outcomes in the mother and/or the offspring. Many of the existing cohorts

include specimens drawn once during the first half of pregnancy,167-171 with few

collections obtaining a blood sample later in pregnancy.172,173 Furthermore, the

majority of cohorts with 2 or more specimens sampled in the same woman

during various periods of pregnancy have a limited number of participants

(<15 000 women).172,174-176 Few studies obtained blood in consecutive trimesters

from sizeable cohorts of pregnant women.177-179 A sufficiently large study base is

necessary as for some diseases (e.g., maternal cancer or chronic adult diseases

in the offspring) cohort members must be followed as long as decades to

accumulate a reasonable number of cases before an investigation can start.

It is not established whether the hormonal measurement from a single

blood specimen collected during one pregnancy is representative of the

exposure throughout gestation, or exposure in a subsequent pregnancy. Some

insights come from what is known about the regulation of hormonal synthesis

during pregnancy82,87 and initial epidemiological data.106,180 However,

characterizing the extent to which a single measurement in early pregnancy is

representative of concentrations in the third trimester of the same pregnancy, as

well as in a subsequent pregnancy, could help optimize the use of existing

maternity cohorts, in which only one single blood specimen is available.

15

2. Aims

Given essentially no data on endogenous hormones in pregnancy and

subsequent risk of ovarian cancer in the mother, we investigated the aims as

summarized below:

1) Examine the associations of circulating first trimester hormone

concentrations with risk of maternal epithelial ovarian cancer overall and in

subgroups defined by histological subtypes. Hormones of interest, and the

direction of association hypothesized, are:

a) Testosterone and androstenedione are expected to be positively

associated with risk.

b) Progesterone is expected to be inversely associated with risk.

c) 17-OHP is expected to be positively associated with risk.

d) Estradiol is expected to be positively associated with risk.

e) SHBG is expected to be inversely associated with risk.

f) IGF-I and placental GH are expected to be positively associated with.

2) Evaluate the associations of circulating first trimester AMH concentrations

with risk of maternal invasive serous ovarian cancer. Higher AMH levels are

expected to be inversely associated with risk.

3) Examine how well first and second trimester hormone concentrations are

representative of the concentrations in the third trimester during the same

or subsequent pregnancies.

16

3. Materials and Methods

3.1 Nested Case-Control Study

3.1.1 Cohort Descriptions

The Northern Sweden Maternity Cohort (NSMC) and the Finnish

Maternity Cohort (FMC) are two long-standing maternity cohorts that preserve

serum samples drawn from women during early pregnancy. Blood samples are

drawn and tested for systemic infections before being centrally stored at -20°C

(NSMC) or -25°C (FMC).

The NSMC at Umeå University, with more than 120 000 samples from

91 000 women (as of 2013), was established in 1975 and includes pregnancies

from the four northernmost counties of Sweden (Västerbotten, Norrbotten,

Jämtland, Västernorrland).167,181 The FMC, a nationwide initiative at the

National Institute of Health and Welfare in Oulu, was established in 1983 and

contains close to 2 million serum samples from more than 850 000 pregnant

women (as of 2011).167,182

3.1.2 Selection of Study Subjects

Study subjects were selected among members from the two cohorts with:

i) no history of twin or multiple pregnancies; ii) a blood sample obtained during

the first trimester of a pregnancy leading to childbirth; and iii) no history of

invasive cancer (except for non-melanoma skin cancer) or borderline ovarian

tumors before blood draw. Furthermore, due to changes in sample handling that

may affect hormone measurements, samples in the NSMC drawn after

December 31st, 1987 were excluded.183

Identification of Cases

Cases diagnosed with invasive or borderline EOC after blood donation

were identified through linkages with the Finnish Cancer Registry (founded in

1952) and the Swedish Cancer Registry (founded in 1958). Reporting of newly

diagnosed cases is mandatory in both nationwide cancer registries, leading to

very high (>95%) completeness of coverage for solid tumors.184,185 We identified

1 105 incident EOC cases among FMC participants diagnosed between July 1984

17

and December 2009 and 146 incident EOC cases among NSMC members

diagnosed between February 1979 and March 2011. The serum sample from the

last singleton pregnancy (or the most recent available for 69 cases) resulting in

delivery of a neonate before diagnosis was selected for the study.

Selection of Controls

Up to 12 potentially eligible controls per case were identified through

linkages with the national population registries. Controls were matched on

study cohort, age at sampling (±6 months), date of sampling (±3 months),

parity at sampling (1, 2, >2), and parity at diagnosis (1, 2, >2); eligible controls

were alive at the time of the diagnosis of the index case. In a second step, three

controls were selected at random for cases with information on gestational age

(n=906; 72%) at blood collection and two controls were randomly selected for

those cases without this information (n=345; 28%). This approach was chosen

to improve the statistical power in analyses on women with information on

gestational age.

Cases with insufficient serum volume for laboratory measurements

(FMC: n=157 and NSMC: n=31) and cases for whom no eligible controls could

be identified (FMC: n=5 and NSMC: n=6) were excluded. Therefore, a total of

1 052 EOC cases (FMC: n=943 and NSMC: n=109) and 2 695 controls (FMC:

n=2 384 and NSMC: n=311) were included in the final study population.

3.1.3 Tumor Data

Morphology codes were provided by the Finnish and Swedish cancer

registries and classified into the EOC histological subgroups serous (n=477,

45%), mucinous (n=356, 34%), endometrioid (n=102, 10%), clear cell (n=26,

3%), and NOS (n=66, 6%), using the World Health Organization guidelines.186

Data on histology were not available for 25 cases (2%), and, thus, these cases

were included only in overall analyses and analyses of tumor invasiveness, as

were tumors diagnosed as NOS. Data on stage at diagnosis were not available

for cases from the NSMC, but were available for 87% of cases from the FMC. For

cases from the FMC, stage I (n=482, 58%) was classified as localized, whereas

18

stages II (n=6), III (n=306), and IV (n=30) were classified as advanced EOC

(n=342, 42%).

3.1.4 Covariate Data

Characteristics related to pregnancy (e.g., pregnancy length, smoking

during pregnancy) and to the newborn (i.e., gender, and birth weight and

length) were obtained through linkages from the country-specific birth

registries. The completeness of the Swedish Birth Registry is limited,187 thus, a

full copy of the maternity and delivery records was requested for members from

the NSMC and information from the medical records was abstracted by trained

personnel. To ensure quality control, dates of sampling and last menstrual

period were computerized in duplicate.

Gestational age (GA) was calculated as difference in days between dates at

blood donation and last menstrual period (LMP) for participants from the

NSMC. As information on date of LMP was not available for the FMC,

gestational age was calculated using the following formula:

280 - (date of expected delivery - date at blood draw)

For 2 200 members of the FMC (n=629 case-control sets; 60%),

information on malignant cancers diagnosed among first-degree relatives was

obtained through linkages with the Finnish population and cancer registries.

Missing values of the continuous covariates maternal age at first birth

(2%), birth weight (22%), and birth length (22%) were assigned the individual

cohort (NSMC or FMC) case-control-specific median value for the respective

variable. Missing values for the categorical covariates smoking during index

pregnancy (24%), family history of breast and/or ovarian cancer (40%), and

child’s sex (0.1%) were assigned to a ‘missing’ category.

19

3.1.5 Participants by Study

Depending on the studied hormone, numbers of participants differed due

to study design and sample availability.

Androgens and IGF-I were measured in all participants (n=3 746) with

sufficient blood volume, whereas progesterone, 17-OHP, estradiol, SHBG, and

placental GH were measured only in women for whom information on

gestational day at blood draw was available (n=2 920).

AMH was measured in 107 Finnish cases that were diagnosed with

invasive serous ovarian cancer before December 2007 and a random set of their

matched controls (n=208); this study was limited to women with data on

gestational age at blood collection. Figure 5 shows the exact numbers of cases

and controls for the different sub-populations.

Figure 5. Number of study participants per studied hormone

All women 1 052 EOC cases 2 695 controls

With GA 765 EOC cases 2 155 controls

AMH 107 invasive serous

cases 208 controls

testosterone androstenedione IGF-I

17-OHP SHBG progesterone placental GH estradiol

AMH

20

3.1.6 Laboratory Analyses

The hormone analyses were performed on serum samples obtained from

the NSMC and the FMC. All hormonal measurements were performed at the

Clinical Chemistry Laboratory of the Umeå University Hospital, Umeå, Sweden.

Samples from case subjects and their matched control subjects were always

analyzed within the same batch, assay kit, and on the same day. The technicians

performing the assays were blinded to the case, control, or quality control status

of the specimens. In addition to routine laboratory quality controls, two pools of

serum from each of the cohorts were created at the beginning of the study and 3

aliquots, undistinguishable from the test samples, were inserted in each

laboratory run.

Concentrations of testosterone (ng/mL), androstenedione (ng/mL),

17-OHP (ng/mL), progesterone (ng/mL), and estradiol (ng/mL) were quantified

by high-performance liquid chromatography tandem mass spectrometry on an

Applied Biosystems API4000 triple stage quadrupole mass spectrometer.

SHBG (nmol/L) was quantified with solid-phase competitive

chemiluminescence assays on Immulite 2000 Siemens analyzer.

Concentrations of IGF-I (ng/mL) were measured on the Immulite 2000

Siemens analyzer, a solid-phase enzyme-labeled chemiluminescent

immunometric assay, using reagents from Siemens Medical Solutions

Diagnostics (Siemens, Los Angeles, CA, USA).

Placental GH (ng/mL) was quantified by an in-house method as no

commercial methods were available at the beginning of the project. A mouse

antihuman monoclonal antibody (Abnova, Taipei City, Taiwan) was used

against full-length placental growth hormone as capture antibody and a rabbit

polyclonal antibody (Abnova) as detection antibody. Detection was done by

electrochemoluminescence on a MSD Sector Imager 2400-instrument (Meso

Scale Discovery, Gaithersburg, MD, USA).

AMH (ng/mL) was quantified by a second generation specific ELISA

(Diagnostic Systems Laboratories, Webster, USA). One case and three controls

had AMH concentrations below the detection limit of the assay and they were

21

assigned the value of 0.08 ng/mL, which is the midpoint between 0 and the

assay detection limit of 0.16 ng/mL.

Inter- and intra-assay coefficients of variation (CV) based on the blinded

pooled quality controls were <15% for samples from the FMC and the NSMC for

all sex steroids, SHBG, IGF-I, placental GH, and AMH.

3.1.7 Statistical Methods

All statistical analyses were conducted using the Statistical Analyses

System (SAS) software, versions 9.2 and 9.3 (SAS Institute, Inc., Cary, North

Carolina). All statistical tests were two-sided and considered significant at

p<0.05.

All hormone values were log2-transformed to better normalize their

distributions and to allow estimation of the effect of a doubling of the hormone

concentrations on EOC risk. Concentrations of 17-OHP, progesterone, SHBG,

estradiol, and placental GH were correlated with gestational age (r=-0.26, 0.49,

0.57, 0.69, and 0.75, respectively; p<0.0001). Analyses including these

hormones were limited to women with information on GA (n=765 case-control

sets; 73%) and GA was included as a covariate in the statistical models.

Spearman correlation coefficients, adjusted for study cohort and gestational age,

where necessary, were used to assess correlations between individual hormone

concentrations and with covariates separately in cases and controls.

We used conditional logistic regression, appropriate for the individually

matched study design, to assess differences between cases and controls and to

calculate odds ratios (OR) and corresponding 95% confidence intervals [CI]. For

each of the hormones, ORs were calculated for tertiles of hormone

concentrations using the cohort-specific distribution in controls. Likelihood

ratio tests were used to assess linear trends across categories based on the

median hormone values for the tertiles. In addition, ORs were calculated for a

one-unit change of log2-transformed hormones (ORlog2).

The effect of potential confounders (maternal age at first birth, smoking

during index pregnancy, family history of breast and/or ovarian cancers, child’s

sex, birth length and weight) was evaluated. Apart from family history of

22

ovarian and/or breast cancer (no, yes, unknown) in the analyses of AMH,

adjustment for potential confounders had a negligible effect (<10%) on risk

estimates and were not retained in the final models. We repeated the analyses

for each of the hormones mutually adjusting for the other hormones.

Analyses were performed by histology, ages at sampling and diagnosis

(histology-specific; below/above median), time between blood donation and

diagnosis (i.e., ‘lag-time’; below/above median), stage (localized vs. advanced

disease), and number of children at diagnosis / selection as a control (1 vs. >1).

To assess risk of EOC occurring before and after menopause, analyses were

stratified by age at diagnosis <46 (premenopausal), 46-55, and ≥55 years

(postmenopausal).

Tests of heterogeneity between the ORs in different subgroups were based

on chi-square statistics, calculated as the deviations of logistic regression

coefficients observed in each of the subgroups, relative to the overall regression

coefficient.188

We conducted sensitivity analyses excluding women diagnosed <2 years

(n=85 case-control sets; 8%) or <3 years (n=130 case-control sets; 12%) after

blood donation to assess whether the study results were influenced by the

presence of undiagnosed, but hormonally active tumors. Further sensitivity

analyses were limited to women who provided a blood sample during a full-term

pregnancy (n=724 case-control sets; 69%) or to women who donated blood

during the last pregnancy before diagnosis or selection as a control (n=983

case-control sets; 93%). Finally, we repeated the analyses excluding statistical

outliers, i.e. women with hormone concentrations exceeding 3 times the

interquartile range (2 for analyses on androgens, progesterone, and placental

GH; 4 for analyses on 17-OHP; 8 for analyses on SHBG).

23

3.2 Longitudinal Study

3.2.1 Selection of Study Subjects

The longitudinal study was designed to establish how well first and

second trimester hormone concentrations represent hormone concentrations in

the third trimester of the same or subsequent pregnancies. The study is based

on serial samples available from the Finnish Maternity Cohort.

Study subjects were women participating in a population-based screening

trial for congenital infections conducted between January 1, 1988 and June 30,

1989 in the 76 maternity centers in the metropolitan Helsinki area. All pregnant

women aged 15-45 years (n=18 616) were invited to donate a blood sample

during the 1st, 2nd, and 3rd trimesters of pregnancy.179

Among the 16 793 participants who donated serum samples at three time

points during pregnancy (90% of women invited), we first selected women with

a singleton, healthy offspring at term resulting from a natural pregnancy. In a

second step, we randomly selected 25 women giving birth to their first child

(primiparous) and 25 women giving birth to their second child (biparous), aged

20-34 years at blood collection, and whose blood samples were obtained at

weeks 10-12 (1st trimester, T1), weeks 20-22 (2nd trimester, T2), and weeks 35-37

(3rd trimester, T3) of one pregnancy. Additionally, 21 women with two

consecutive singleton pregnancies during the study period were included. These

women donated samples for both pregnancies in gestational weeks 8-14, 18-24,

and 33-38. All blood samples were processed using a standardized protocol and

stored at -20ºC.179

Characteristics related to pregnancy (e.g., smoking during pregnancy,

pregnancy length, parity) and to the newborn (e.g., gender, birth weight and

length) were obtained through linkages from the Finnish Birth Registry.

3.2.2 Laboratory Analyses

All hormonal measurements were performed at the Clinical Chemistry

Laboratory of the Umeå University Hospital, Umeå, Sweden. Samples from a

single pregnancy were always analyzed within the same batch, assay kit, and on

the same day. Laboratory personnel were blinded to the study and quality

24

control status of the samples. In addition to routine laboratory quality controls,

a pool of serum was created at the beginning of the study and 2 aliquots,

undistinguishable from the test samples, were inserted in each laboratory run.

All reported intra- and inter-assay CVs are based on the blinded pooled quality

controls.

Serum concentrations of estradiol (ng/mL), progesterone (ng/mL), and

testosterone (ng/mL) were quantified by high-performance liquid

chromatography tandem mass spectrometry (HPLC-MS) on an Applied

Biosystems API4000 triple stage quadrupole mass spectrometer.

Inter- and intra-assay CVs were <18% for estradiol and progesterone,

whereas the inter-assay CV for testosterone was 44%. After removing a single

batch for testosterone, the inter-assay CV decreased to 12%.

3.2.3 Statistical Methods

Women with one pregnancy were analyzed separately from those with

two pregnancies.

Spearman's rank correlation coefficients were used to assess the

correlations between the investigated hormones at the same point in time

(e.g., correlation between estradiol and testosterone in the 1st trimester), as well

as between-trimester correlations for each hormone (e.g., correlation between

1st and 2nd trimester estradiol), and to measure the correlation of hormone

concentrations between two consecutive pregnancies in the same woman

(e.g., correlation between 1st trimester estradiol in pregnancy 1 and

pregnancy 2).

We calculated median percentage changes from the 1st to 3rd trimester to

assess the changes in maternal hormone concentrations throughout pregnancy

and tested the differences in hormone concentrations between the trimesters

with the Kruskal Wallis test (pKW).189 The Mann-Whitney-U test (pMW) was used

to assess whether hormone concentrations in the three trimesters were

significantly different by parity (primi- (n=25) vs. biparous (n=25)), smoking

status at first blood draw (current (n=8) vs. no (n=39)), and fetal gender (male

(n=23) vs. female (n=27)).

25

The percentage change in the 3rd trimester hormone concentrations were

estimated per 1% increase in hormone levels measured in the 1st and/or 2nd

trimester, adjusted for gestational age.190 Maternal and newborn characteristics

were added to these models, one at a time, to assess their individual

contribution to 3rd trimester hormone concentrations, and as a full adjustment

set.

We used the Wilcoxon signed rank sum (pWS) test to compare differences

in hormone concentrations by trimesters of the two consecutive pregnancies.189

For the study population of women with one pregnancy, we conducted

sensitivity analyses limited to women who were pregnant for the first

(primigravid; n=19) or second time (bigravid; n=19) to assess whether observed

differences between primi- and biparous women were due to gravidity or parity.

All statistical tests were two-sided and considered significant at p<0.05.

Statistical analyses were performed with the Statistical Analyses System (SAS)

software, version 9.3 (SAS Institute, Inc., Cary, North Carolina).

26

4. Results

4.1 Case-Control Study

4.1.1 Descriptive Statistics

Key characteristics of the study population, with cases presented by

tumor histology, are displayed in Table 2. The majority of the 1 052 cases were

diagnosed with invasive EOC (n=642, 61%). Of these, 283 (44%) were serous,

150 (23%) mucinous, 102 (16%) endometrioid, 26 (4%) clear cell, and 81 (13%)

with NOS or unknown histology. Among the borderline tumors (n=410, 39%),

194 (47%) were serous, 206 (50%) mucinous, and 10 (2%) NOS or unknown

histology. The distribution by histological subtype and invasiveness was

consistent between the two cohorts. Invasive tumors were predominantly

diagnosed as advanced disease (69%), whereas almost all borderline tumors

were diagnosed as localized disease (97%). Median age at EOC diagnosis was

43.9 years and, on average, 12.2 years elapsed between blood donation and

diagnosis among all cases.

Cases with mucinous tumors (borderline and invasive) had the shortest

lag-time between blood collection and cancer diagnosis (10 years) and the

youngest median age at diagnosis (40.1 and 40.9 years, respectively), whereas

cases diagnosed with endometrioid or clear cell tumors had the longest lag-time

(16.3 and 17.0 years, respectively) and were the oldest at diagnosis (48.1 years).

Cases with borderline tumors were younger at first birth, cases with

borderline and invasive mucinous and invasive serous tumors were more likely

to smoke, and cases with invasive serous tumors were more likely to have a

family history of breast and/or ovarian cancer relative to their matched controls.

AMH was analyzed in 107 cases diagnosed with invasive serous ovarian

cancer and 208 controls. Case and control characteristics were similar to those

observed in the overall study population.

27

Se

rou

s M

uci

nou

s E

nd

omet

rioi

d (1

02

case

s)

Cle

ar c

ell

(26

case

s)

Con

trol

wom

en

(n=

2,69

5)

In

vasi

ve

(28

3 ca

ses)

B

ord

erli

ne

(194

cas

es)

Inva

sive

(1

50 c

ases

) B

ord

erli

ne

(20

6 ca

ses)

Stud

y co

hort

FMC

26

3 (2

8%)

174

(19%

) 14

3 (1

5%)

189

(20%

) 92

(10%

) 23

(2%

) 2,

384

(88%

)

NSM

C 20

(18%

) 20

(18%

) 7

(6%

) 17

(16%

) 10

(9%

) 3

(3%

) 31

1 (1

2%)

Age

at b

lood

don

atio

n (y

ears

) 32

.5 (1

6.4-

45.2

) 31

.1 (1

7.5-

44.0

) 31

.7 (1

9.4 -

45.7

) 30

.3 (1

7.3-

44.1

) 32

.3 (2

1.1-

41.0

) 31

.4 (2

2.2-

40.5

) 31

.5 (1

5.7-

45.5

)

Pari

ty a

t ind

ex p

regn

ancy

1 ch

ild

84 (3

0%)

41 (2

1%)

40 (2

7%)

62 (3

0%)

20 (2

0%)

11 (4

2%)

767

(28%

)

2 ch

ildre

n 97

(34%

) 82

(42%

) 64

(43%

) 79

(38%

) 47

(46%

) 11

(42%

) 1,

058

(39%

)

>2

child

ren

102

(36%

) 71

(37%

) 46

(30%

) 65

(32%

) 35

(34%

) 4

(15%

) 87

0 (3

2%)

Ges

tatio

nal a

ge (d

ay)

74 (3

9-13

6)

74 (3

8-14

1)

73 (4

4-14

2)

75 (4

2-13

4)

76 (4

1-12

5)

79 (4

3-11

7)

73 (3

8-14

8)

Age

at 1

st b

irth

(yea

rs) b

26.9

(14.

8-41

.6)

25.8

(16.

1-39

.5) a

27

.2 (1

5.8-

46.2

) 23

.9 (1

5.5-

42.5

) a

26.5

(16.

9-38

.4)

28.6

(20.

4-41

.1)

26.7

(14.

6-45

.9)

Full-

term

pre

gnan

cy le

ngth

b 19

1 (9

6%)

139

(97%

) 10

8 (9

4%)

147

(94%

) 57

(97%

) 16

(94%

) 2,

066

(96%

)

Chi

ld w

eigh

t (kg

) b 3.

6 (0

.8-4

.9)

3.7

(1.6

-4.9

) 3.

5 (1

.5-4

.5)

3.6

(0.5

-5.1

) 3.

6 (1

.8-5

.1)

3.4

(2.1

-4.3

) 3.

6 (0

.6-5

.9)

Chi

ld le

ngth

(cm

) b 51

(31-

56)

50 (4

2-57

) 51

(42-

56)

50 (2

9-56

) 50

(39-

55)

50 (4

3-53

) 50

(25-

56)

Chi

ld g

ende

r

Mal

e 13

9 (4

9%)

108

(56%

) 77

(52%

) 10

5 (5

1%)

51 (5

0%)

9 (3

5%)

1,41

6 (5

3%)

Fem

ale

144

(51%

) 86

(44%

) 72

(48%

) 10

1 (4

9%)

51 (5

0%)

17 (6

5%)

1,27

7 (4

7%)

Smok

ing

duri

ng p

regn

ancy

b 35

(18%

) a

22 (1

6%)

35 (3

1%) a

62

(40%

) a

6 (1

0%)

2 (1

2%)

330

(16%

)

Fam

ily h

isto

ry o

f bre

ast

and/

or o

vari

an c

ance

r c

21 (1

2%) a

7

(6%

) 3

(3%

) 10

(8%

) 5

(8%

) 2

(22%

) 81

(5%

)

Tab

le 2

. Dis

trib

utio

n of

cha

ract

eris

tics

of E

OC

cas

es b

y tu

mor

his

tolo

gy, m

edia

n (m

in, m

ax) o

r n

(%)

28

Se

rou

s M

uci

nou

s E

nd

omet

rioi

d (1

02

case

s)

Cle

ar c

ell

(26

case

s)

Con

trol

wom

en

(n=

2,69

5)

In

vasi

ve

(28

3 ca

ses)

B

ord

erli

ne

(194

cas

es)

Inva

sive

(1

50 c

ases

) B

ord

erli

ne

(20

6 ca

ses)

Tu

mor

Ch

arac

teri

stic

s

Age

at d

iagn

osis

(yea

rs)

45.9

(25.

9-68

.0)

42.5

(23.

9-62

.9)

40.9

(25.

4-57

.8)

40.1

(19.

0-66

.0)

48.1

(27.

2-60

.8)

48.1

(32.

8-60

.2)

Lag

tim

e (y

ears

) 13

.5 (0

.2-3

0.7)

11

.4 (0

.1-2

8.7)

10

.2 (0

.2-2

7.6)

10

.2 (0

.1-2

8.7)

16

.3 (0

.6-2

9.7)

17

.0 (0

.4-3

0.8)

Dis

ease

spr

ead

d

Loca

lized

(sta

ge I)

38

(16%

) 15

8 (9

6%)

78 (7

1%)

171

(98%

) 18

(22%

) 6

(43%

)

Adv

ance

d (s

tage

II-I

V)

196

(84%

) 6

(4%

) 32

(29%

) 3

(2%

) 63

(78%

) 8

(57%

)

Unk

now

n 49

(17%

) 30

(15%

) 40

(27%

) 32

(16%

) 21

(21%

) 12

(46%

)

Hor

mon

es e

Test

oste

rone

(ng/

mL)

0.

8 (0

.7-0

.8)

0.8

(0.7

-0.9

) a

0.9

(0.8

-1.0

) a

0.9

(0.8

-1.0

) a

0.9

(0.8

-1.0

) 0.

9 (0

.7-1

.1)

0.8

(0.7

-0.8

)

And

rost

ened

ione

(ng/

mL)

1.

8 (1

.7-1

.9)

1.8

(1.7

-2.0

) 2.

2 (1

.9-2

.4) a

2.

1 (1

.9-2

.2) a

2.

0 (1

.8-2

.2)

2.1

(1.6

-2.7

) 1.

7 (1

.7-1

.8)

17-O

HP

(ng/

mL)

2.

3 (2

.1-2

.5)

2.2

(2.0

-2.4

) a

2.3

(2.0

-2.6

) 2.

3 (2

.1-2

.5)

2.1

(1.9

-2.4

) 2.

1 (1

.6-2

.7)

2.1

(2.1

-2.2

)

Prog

este

rone

(ng/

mL)

24

.9 (2

3.5-

26.3

) 22

.2 (2

0.8-

23.6

) 24

.0 (2

2.1-

26.0

) 22

.5 (2

1.1-

23.9

) 23

.7 (2

1.6-

25.9

) 22

.5 (1

8.3-

27.7

) 22

.8 (2

2.4-

23.3

)

Est

radi

ol (n

g/m

L)

1.9

(1.7

-2.0

) 1.

8 (1

.7-2

.0)

2.3

(2.0

-2.6

) 2.

0 (1

.8-2

.2)

2.5

(2.2

-2.9

) a

1.8

(1.3

-2.4

) 1.

9 (1

.8-1

.9)

SHB

G (n

mol

/L)

171

(159

-184

) 15

3 (1

40-1

67)

145

(130

-163

) 16

8 (1

54-1

84)

173

(152

-197

) 16

7 (1

33-2

09)

163

(158

-167

)

IGF-

I (ug

/L)

92.1

(85.

5-99

.2)

98.2

(91.

4-10

5.5)

10

4.6

(94.

6-11

5.7)

92

.4 (8

5.5-

99.8

) 98

.8 (8

8.8-

110.

0)

80.9

(67.

4-96

.9)

97.3

(94.

9-99

.7)

Plac

enta

l GH

(ng/

mL)

22

.3 (1

9.9-

24.9

) 18

.8 (1

6.8-

21.0

) 19

.1 (1

6.3-

22.3

) 19

.3 (1

7.2-

21.6

) 22

.1 (1

8.6-

26.4

) 16

.5 (1

1.2-

24.2

) 21

.5 (2

0.7-

22.3

)

AM

H (n

g/m

L) f

2.2

(1.9

-2.6

) -

- -

- -

2.1

(1.9

-2.4

)

T

able

2. c

onti

nued

a in

dica

tes

that

cas

es a

nd c

ontr

ols

are

sign

ifica

ntly

diff

eren

t (p<

0·05

) in

the

resp

ecti

ve s

ubgr

oup

b dat

a fr

om th

e Fi

nnis

h B

irth

Reg

istr

y on

ly a

vaila

ble

sinc

e 19

87

c dat

a on

fam

ily h

isto

ry o

f bre

ast a

nd/o

r ov

aria

n ca

ncer

is a

vaila

ble

for

629

case

s an

d 1,

571

cont

rols

from

the

Finn

ish

Mat

erni

ty C

ohor

t d t

umor

spr

ead

not a

vaila

ble

for

case

s fr

om th

e N

orth

ern

Swed

en M

ater

nity

Coh

ort

e geo

met

ric

mea

ns a

nd 1

0th-9

0th p

erce

ntile

of h

orm

one

conc

entr

atio

ns (a

djus

ted

for

stud

y co

hort

and

, exc

ept f

or a

ndro

gens

, and

IG

F-I,

for

gest

atio

nal a

ge)

f 107

inva

sive

ser

ous

case

s; 2

08 m

atch

ed c

ontr

ols

29

Case subjects from both cohorts had significantly higher geometric means

of testosterone (FMC: 0.9 vs. 0.8 ng/mL; p<0.0001 and NSMC: 0.8 vs. 0.7

ng/mL; p=0.004) and androstenedione (FMC: 1.9 vs. 1.7 ng/mL; p<0.0001 and

NSMC: 2.0 vs. 1.7 ng/mL; p=0.007) relative to controls. In the FMC, 17-OHP

was also higher in cases compared to controls (2.4 vs. 2.2 ng/mL; p=0.006).

Concentrations of placental GH and IGF-I were lower in members from the

NSMC compared to those from the FMC. Geometric means of placental GH

were similar in cases and controls for both cohorts (FMC: 43 vs. 44 ng/mL;

p=0.28 and NSMC: 10 vs. 10 ng/mL; p=0.98). In the FMC population,

geometric means of IGF-I were significantly lower in case than control subjects

(113 vs. 117 ng/mL; p=0.01), whereas in the NSMC geometric means were

similar in case and control subjects (84 vs. 80 ng/mL; p=0.46). Geometric

means of AMH in case and control samples were similar (2.2 vs. 2.1 ng/mL,

p=0.76).

Spearman partial correlation coefficients between early pregnancy

hormone concentrations were similar for cases and controls and are presented

in Table 3. In brief the coefficients for controls: androgens were strongly

correlated with each other (r=0.86). 17-OHP, estradiol, and AMH were

positively correlated with testosterone (r=0.48, r=0.43, and r=0.30) and with

androstenedione (r=0.53, r=0.36, and r=0.42). Positive correlations were also

observed for progesterone with 17-OHP (r=0.46) and with estradiol (r=0.39).

Placental GH was correlated with IGF-I (r=0.12) and progesterone (r=0.38).

The observed inverse correlation of age at sampling with AMH was

substantially more pronounced in cases than in controls (r=-0.50 vs. r=-0.27).

30

T

esto

ster

one

An

dro

sten

edio

ne

17-O

HP

P

roge

ster

one

Est

rad

iol

SHB

G

IGF

-I

pla

cen

tal G

H

AM

H

Tes

tost

eron

e

0.8

7*

0.5

0*

0.1

5*

0.4

5*

0.2

8*

0.0

4 0

.05

0.4

7*

An

dro

sten

edio

ne

0.86

*

0.5

5*

0.1

6*

0.3

6*

0.1

7*

0.0

8+

0

.02

0.5

4*

17-O

HP

0.

48*

0.53

*

0.4

7*

0.1

6*

0.0

8+

0

.08

+

0.0

04

0.0

2

Pro

gest

eron

e 0.

14*

0.16

* 0.

46*

0

.38

* 0

.29*

-0

.07

0.3

7*

-0.2

1+

Est

rad

iol

0.43

* 0.

36*

0.20

* 0.

39*

0

.58

* -0

.04

0.3

0*

0.1

1

SHB

G

0.24

* 0.

13*

0.11

* 0.

35*

0.54

*

-0.0

3 0

.38

* 0

.08

IGF

-I

0.04

+ 0.

08*

0.06

# -0

.01

-0.1

0*

-0.0

5+

0

.11#

0

.18

pla

cen

tal G

H

0.04

0.

003

-0.0

2 0.

38*

0.29

* 0.

36*

0.12

*

-0.0

9

AM

H

0.30

* 0.

42*

0.05

-0

.06

0.02

0.

03

0.12

0.

04

T

able

3. S

pear

man

par

tial

cor

rela

tion

coe

ffic

ient

s in

cas

es a

nd c

ontr

ols

*<0.

0001

, #<

0.01

, +<

0.05

31

4.1.2 Associations between Hormones and EOC

Associations between early pregnancy hormones and EOC differed by

tumor histology and, for the serous subtype, also by tumor invasiveness

(Table 4). No association was observed between the evaluated hormones and

risk of invasive serous or clear cell tumors in our study population. High AMH,

placental GH, progesterone, and SHBG were not associated with risk of EOC

overall or with the histological subgroups.

Testosterone concentrations were positively associated with increased

risk of borderline serous tumors (ORT3 vs. T1: 1.87 [1.18-2.96]; ptrend=0.008) and

an almost 2-fold increased risk of invasive mucinous (ORT3 vs. T1: 1.79

[1.10-2.90]; ptrend=0.02) and borderline mucinous tumors (ORT3 vs. T1: 1.97

[1.30-2.99]; ptrend=0.001). High androstenedione concentrations were

associated with increased risk of invasive mucinous (ORT3 vs. T1: 1.78 [1.09-2.92];

ptrend=0.01) and borderline mucinous tumors (ORT3 vs. T1: 2.00 [1.32-3.02];

ptrend=0.001), while 17-OHP was associated with increased risk of borderline

serous tumors (ORT3 vs. T1: 1.85 [1.14-2.99]; ptrend=0.02). A significantly increased

risk of endometrioid and borderline mucinous tumors was observed with high

estradiol concentrations (endometrioid: ORT3 vs. T1: 2.76 [1.04-7.33]; ptrend=0.03;

borderline mucinous: ORT3 vs. T1: 1.80 [1.00-3.22]; ptrend=0.04).

IGF-I was suggestively inversely associated with overall EOC (ORT3 vs. T1:

0.83 [0.69-1.01]; ptrend=0.08), invasive tumors (ORT3 vs. T1: 0.79 [0.62-1.02];

ptrend=0.07), and endometrioid tumors (ORT3 vs. T1: 0.55 [0.28-1.07]; ptrend=0.07).

32

Table 4. ORs [95%-CI] by tumor invasiveness and histology across tertiles a

Ca / Co T1 T2 T3 ptrend phet b

Testosterone

All women 1 047 / 2 673 1.0 1.27 [1.06-1.53] 1.56 [1.30-1.87] <0.0001

Invasive 640 / 1 609 1.0 1.18 [0.93-1.49] 1.37 [1.08-1.72] 0.008 0.08

Borderline 407 / 1 064 1.0 1.45 [1.07-1.96] 1.94 [1.43-2.63] <0.0001

Serous 475 / 1 212 1.0 1.28 [0.98-1.68] 1.26 [0.95-1.66] 0.11

Invasive serous 282 / 713 1.0 1.11 [0.78-1.57] 0.99 [0.70-1.41] 0.97 0.03

Borderline serous 193 / 499 1.0 1.62 [1.06-2.48] 1.87 [1.18-2.96] 0.008

Mucinous 354 / 925 1.0 1.29 [0.93-1.79] 1.89 [1.38-2.59] <0.0001

Invasive mucinous 150 / 388 1.0 1.21 [0.74-1.98] 1.79 [1.10-2.90] 0.02 0.76

Borderline mucinous 204 / 537 1.0 1.36 [0.88-2.10] 1.97 [1.30-2.99] 0.001

Endometrioid 101 / 235 1.0 1.41 [0.74-2.68] 1.83 [0.97-3.45] 0.06

Clear cell 26 / 65 1.0 0.52 [0.16-1.66] 0.62 [0.21-1.84] 0.36

Androstenedione

All women 1 049 / 2 677 1.0 1.03 [0.85-1.24] 1.50 [1.24-1.80] <0.0001

Invasive 640 / 1 609 1.0 0.91 [0.71-1.16] 1.36 [1.08-1.72] 0.004 0.21

Borderline 409 / 1 068 1.0 1.25 [0.91-1.70] 1.74 [1.29-2.35] 0.0003

Serous 475 / 1 213 1.0 1.12 [0.84-1.48] 1.30 [0.98-1.71] 0.07

Invasive serous 282 / 714 1.0 0.98 [0.69-1.41] 1.25 [0.88-1.77] 0.19 0.72


Mucinous 356 / 928 1.0 1.07 [0.77-1.50] 1.91 [1.39-2.62] <0.0001



Endometrioid 101 / 235 1.0 0.71 [0.37-1.38] 0.98 [0.54-1.79] 0.85

Clear cell 26 / 65 1.0 0.90 [0.27-3.06] 1.00 [0.33-3.07] 0.99

17-OHP

All women 762 / 2 138 1.0 1.05 [0.85-1.30] 1.26 [1.01-1.56] 0.04

Invasive 451 / 1 251 1.0 0.90 [0.68-1.18] 1.10 [0.83-1.46] 0.48 0.14

Borderline 311 / 887 1.0 1.35 [0.96-1.88] 1.53 [1.09-2.15] 0.02

Serous 345 / 973 1.0 1.17 [0.86-1.60] 1.37 [1.00-1.88] 0.05

Invasive serous 198 / 555 1.0 0.96 [0.63-1.44] 1.09 [0.72-1.67] 0.69 0.11


Mucinous 270 / 766 1.0 0.98 [0.68-1.40] 1.21 [0.84-1.73] 0.27



Endometrioid 60 / 159 1.0 1.12 [0.53-2.37] 0.84 [0.38-1.85] 0.69

Clear cell 17 / 46 1.0 0.61 [0.15-2.52] 0.52 [0.10-2.76] 0.42

33

Table 4. continued


Progesterone

All women 761 / 2 136 1.0 0.88 [0.71-1.08] 0.96 [0.76-1.21] 0.67

Invasive 451 / 1 252 1.0 0.90 [0.68-1.19] 0.99 [0.73-1.35] 0.95 0.71

Borderline 310 / 884 1.0 0.85 [0.62-1.18] 0.91 [0.63-1.31] 0.56

Serous 344 / 970 1.0 0.93 [0.68-1.27] 1.04 [0.73-1.47] 0.89

Invasive serous 198 / 555 1.0 0.98 [0.64-1.48] 1.03 [0.65-1.63] 0.93 0.96


Mucinous 270 / 767 1.0 0.85 [0.60-1.22] 0.92 [0.62-1.36] 0.67



Endometrioid 60 / 159 1.0 0.61 [0.28-1.32] 0.81 [0.34-1.95] 0.59

Clear cell 17 / 46 1.0 0.24 [0.04-1.53] 0.47 [0.10-2.23] 0.43

Estradiol

All women 761 / 2 136 1.0 1.01 [0.81-1.26] 1.24 [0.94-1.62] 0.11

Invasive 451 / 1 252 1.0 1.00 [0.75-1.33] 1.26 [0.88-1.79] 0.20 0.88

Borderline 310 / 884 1.0 1.03 [0.73-1.46] 1.20 [0.79-1.84] 0.36

Serous 344 / 970 1.0 0.80 [0.58-1.11] 0.93 [0.61-1.14] 0.68

Invasive serous 198 / 555 1.0 0.79 [0.51-1.21] 0.98 [0.57-1.69] 0.89 0.78


Mucinous 270 / 767 1.0 1.26 [0.86-1.84] 1.69 [1.08-2.63] 0.02



Endometrioid 60 / 159 1.0 1.41 [0.59-3.41] 2.76 [1.04-7.33] 0.03

Clear cell 17 / 46 1.0 1.93 [0.46-8.08] 1.58 [0.26-9.64] 0.53

SHBG

All women 735 / 2 088 1.0 1.01 [0.81-1.26] 1.14 [0.89-1.46] 0.40

Invasive 429 / 1 209 1.0 1.00 [0.75-1.34] 1.11 [0.80-1.53] 0.64 0.79

Borderline 306 / 879 1.0 1.03 [0.73-1.45] 1.19 [0.80-1.77] 0.45

Serous 328 / 941 1.0 1.10 [0.79-1.51] 1.04 [0.71-1.52] 0.77

Invasive serous 185 / 528 1.0 1.25 [0.81-1.92] 1.02 [0.63-1.67] 0.83 0.90


Mucinous 268 / 762 1.0 0.98 [0.67-1.42] 1.37 [0.90-2.10] 0.21



Endometrioid 55 / 150 1.0 0.88 [0.37-2.10] 1.29 [0.51-3.26] 0.63

Clear cell 15 / 43 1.0 0.91 [0.20-4.24] 1.25 [0.24-6.53] 0.86

34

Table 4. continued


IGF-I

All women 1 045 / 2 658 1.0 0.92 [0.77-1.10] 0.83 [0.69-1.01] 0.08

Invasive 635 / 1 591 1.0 0.89 [0.71-1.13] 0.79 [0.62-1.02] 0.07 0.54

Borderline 410 / 1 067 1.0 0.96 [0.72-1.28] 0.90 [0.66-1.22] 0.55

Serous 473 / 1 204 1.0 0.87 [0.66-1.14] 0.93 [0.70-1.23] 0.62

Invasive serous 279 / 703 1.0 0.97 [0.69-1.38] 1.01 [0.70-1.45] 0.97 0.46


Mucinous 355 / 923 1.0 1.08 [0.80-1.46] 0.85 [0.61-1.18] 0.37



Endometrioid 102 / 238 1.0 0.71 [0.38-1.34] 0.55 [0.28-1.07] 0.07

Clear cell 26 / 64 1.0 0.57 [0.20-1.60] 0.34 [0.09-1.29] 0.10

Placental GH

All women 730 / 2 061 1.0 0.86 [0.68-1.09] 0.94 [0.70-1.26] 0.62

Invasive 423 / 1 186 1.0 0.85 [0.63-1.15] 1.00 [0.69-1.46] 0.91 0.56

Borderline 307 / 875 1.0 0.87 [0.61-1.25] 0.84 [0.53-1.33] 0.62

Serous 325 / 928 1.0 0.88 [0.62-1.24] 0.97 [0.62-1.49] 0.83

Invasive serous 181 / 517 1.0 0.96 [0.61-1.53] 0.90 [0.51-1.60] 0.73 0.69


Mucinous 266 / 754 1.0 0.98 [0.67-1.45] 0.98 [0.60-1.61] 0.96



Endometrioid 57 / 151 1.0 1.06 [0.49-2.30] 1.00 [0.36-2.81] 0.98

Clear cell 15 / 42 1.0 0.20 [0.03-1.18] 0.17 [0.01-2.24] 0.08

AMH c

Invasive serous 107 / 208 1.0 0.99 [0.52-1.87] 0.93 [0.49-1.77] 0.83 a adjusted for gestational age (except for testosterone, androstenedione, and IGF-I) b heterogeneity tested between invasive and borderline tumors c adjusted for gestational age and family history

35

4.1.3 Mutual Adjustment

The effect of mutual adjustment for the evaluated hormones was assessed

(Table 5). After adjustment for androstenedione, the effect of a doubling of

testosterone concentrations on invasive and borderline mucinous tumors was

strongly attenuated and no longer statistically significant (invasive: crude

ORlog2: 1.33 [1.01-1.74], adjusted ORlog2: 0.77 [0.43-1.36]; borderline: crude

ORlog2: 1.50 [1.18-1.90], adjusted ORlog2: 1.12 [0.73-1.71]). On the other hand, the

association between testosterone and endometrioid tumors was strengthened

after adjustment for androstenedione (crude ORlog2: 1.39 [0.96-1.99], adjusted

ORlog2: 3.45 [1.62-7.35]). A doubling of androstenedione was associated with a

significantly increased risk of invasive serous tumors (crude ORlog2: 1.18

[0.95-1.46], adjusted ORlog2: 1.67 [1.09-2.55]) and a decreased risk of

endometrioid tumors (crude ORlog2: 1.02 [0.71-1.48], adjusted ORlog2: 0.33

[0.15-0.73]), after adjusting for testosterone.

After adjustment for testosterone or androstenedione, a doubling of

17-OHP was no longer significantly associated with the risk of borderline serous

tumors (crude ORlog2: 1.46 [1.08-1.97], adjusted for T ORlog2: 1.20 [0.87-1.67],

adjusted for D4 ORlog2: 1.27 [0.89-1.81]).

Adjusting for any of the remaining hormones did not change the direction

or the significance of the observed associations (data not shown).

36

A

dju

sted

for

C

a /

Co

Cru

de

T

D4

17-O

HP

E

2

Tes

tost

eron

e

All

wom

en

1 04

7 /

2 67

3 1.

32 [1

.19-

1.47

]

1.11

(0

.91-

1.36

) 1.

36 [1

.17-

1.57

] 1.

39 [1

.21-

1.60

]

Inva

sive

64

0 /

1 60

9 1.

24 [1

.08-

1.42

]

0.9

7 (0

.74

-1.2

7)

1.21

[1.0

0-1.

47]

1.25

[1.0

5-1.

50]

Bor

derl

ine

407

/ 1

064

1.47

[1.2

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1.83

) 1.

61 [1

.27-

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] 1.

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.31-

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]

Sero

us

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/ 1

212

1.16

[0.9

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(0.7

2-1.

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[0.8

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1.26

[1.0

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Inva

sive

ser

ous

282

/ 71

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]

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6 (0

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[0.7

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Bor

derl

ine

sero

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193

/ 49

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(1.

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.13-

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] 1.

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Muc

inou

s 35

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(0

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dro

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Bor

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409

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Sero

us

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Inva

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282

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Bor

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Inva

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T

able

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and

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7-O

HP,

and

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radi

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b

37

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dju

sted

for

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All

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38

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Inva

sive

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Inva

sive

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Bor

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Muc

inou

s 27

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End

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rad

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All

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sive

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Bor

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Sero

us

344

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0 0.

98 [0

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Inva

sive

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198

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322

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6 /

445

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End

omet

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d 60

/ 1

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[1.2

2-3.

05]

T

able

5. c

onti

nued

a all

mod

els

incl

udin

g no

n-an

drog

ens

are

adju

sted

for

GA

. Eff

ect e

stim

ates

in w

omen

wit

h da

ta o

n al

l hor

mon

es a

re s

imila

r to

the

ones

pre

sent

ed h

ere.

b O

Rs

in b

old

blue

indi

cate

a c

hang

e in

ris

k es

tim

ates

by

≥ 1

0%

38

4.1.4 Stratified Analyses

Sex steroids and growth factors

Due to the low proportion of cases diagnosed at age 55 years or older

(n=102 cases; 10%), heterogeneity by age at diagnosis (<46, 45-55, ≥55 years)

was assessed in all cases, invasive and borderline tumors, as well as serous,

mucinous, and endometrioid tumors (Figure 6). Heterogeneity was observed

overall for a doubling of IGF-I concentrations (ORlog2 <46 years: 0.75

[0.64-0.89], 46-55 years: 0.98 [0.78-1.23], ≥55 years: 1.41 [0.95-2.08];

phet=0.008). A similar pattern was observed for IGF-I in borderline and

mucinous tumors (Figure 6 G). Although heterogeneity was not observed for the

remaining hormones, associations with androgens in women diagnosed

<55 years were stronger than in older women overall and by tumor invasiveness

(Figure 6 A, B).

There was no evidence of heterogeneity (phet>0.05) by years between

blood donation and diagnosis (histology-specific; below/above median),

number of children, or study cohort.

AMH

Heterogeneous associations were observed for AMH with risk of invasive

serous ovarian cancer by median age at sampling (age=32.7 years; phet=0.002)

and age at diagnosis (age=42.9 years; phet=0.04). In women younger than the

median age at sampling, a doubling of AMH was associated with increased risk

of ovarian cancer (ORlog2: 1.64 [1.06-2.54]), whereas the opposite was observed

in older women (ORlog2: 0.69 [0.49-0.96]). When stratifying the analyses by age

at sampling in three groups (<30, 30-35, ≥35 years), a non-significant positive

association between AMH and risk was observed in women <30 years of age at

sampling (n=29 case-control sets; ORlog2: 1.42 [0.82-2.46]) and 30-35 years

(n=42 case-control sets; ORlog2: 1.36 [0.88-2.12]), whereas a significant inverse

association was observed in women older than age 35 years at sampling (n=36

case-control sets; ORlog2: 0.67 [0.45-0.97]). Analyses by median age at diagnosis

yielded lower risk estimates and the heterogeneity of the associations was less

39

pronounced. There was no heterogeneity by time between blood draw and

diagnosis or stage.

Figure 6. ORs [95%-CI] for doubling of circulating hormone concentrations by age at diagnosis a

A) Testosterone

B) Androstenedione

0

1

2

3

4

5

6

All Women Invasive Borderline Serous Mucinous Endometrioid

0

1

2

3

4

5

6


□<46 years □ 46-55 years □ ≥ 55 years

40

Figure 6. continued

C) 17-OHP

D) Progesterone

E) Estradiol

0

1

2

3

4

5

6


0

1

2

3

4

5

6


0

1

2

3

4

5

6



n=7 cases

n=7 cases

n=7 cases

41

Figure 6. continued

F) SHBG

G) IGF-I

H) Placental GH

a adjusted for gestational age (except for testosterone, androstenedione, and IGF-I)

0

1

2

3

4

5

6


0

1

2

3

4

5

6


0

1

2

3

4

5

6


pHet=0.02


pHet=0.008 pHet=0.02

n=5 cases

n=5 cases

42

4.1.5 Analyses by Tumor Stage

Heterogeneity by tumor stage at diagnosis was observed in invasive

serous tumors for a doubling of circulating IGF-I (ORlog2 localized: 0.42

[0.22-0.81], ORlog2 advanced: 0.99 [0.74-1.33]; phet=0.02), testosterone (ORlog2

localized: 1.91 [1.02-3.57], ORlog2 advanced: 0.88 [0.68-1.14]; phet=0.03) and

SHBG concentrations (ORlog2 localized: 2.38 [1.00-5.65], ORlog2 advanced: 0.88

[0.61-1.27]; phet=0.04), but not for any other hormones or EOC subtypes.

4.1.6 Sensitivity Analyses

Limiting the analyses of androgens to women with information on

gestational age at blood draw did not change risk estimates with the exception

of a strengthening of the association between androstenedione and borderline

serous tumors (ORlog2: 1.50 [1.10-2.05]; p=0.01).

Limiting the study population to women aged <55 years at diagnosis

strengthened the observed inverse associations for IGF-I with invasive

(ORlog2: 0.81 [0.68-0.96]) and invasive mucinous tumors (ORlog2: 0.70

[0.49-1.00]). Limiting the whole study population to women with lag-time

>2 years (n=960 cases; 85 cases diagnosed at age <55 years excluded)

attenuated the observed associations for IGF-I, but less so in women aged

<55 years at diagnosis (e.g., invasive tumors lag-time >2 years ORlog2: 0.88

[0.74-1.04]; lag-time >2 years and age at diagnosis <55 years ORlog2: 0.84

[0.70-1.01]).

No material change in risk estimates was observed when limiting the

study population to women i) with lag-time >2 or >3 years, ii) who provided a

blood sample during a full-term pregnancy, iii) who donated blood during the

last pregnancy before diagnosis or selection as a control, or iv) without hormone

levels exceeding 3 times the interquartile range. Analyses limited to members of

the FMC yielded similar results and analyses restricted to the NSMC (n=109

cases) were in the same direction but non-significant due to the small sample

size.

43

4.2 Longitudinal Study

Maternal and child characteristics were similar between primiparous

women, biparous women, and women participating with two consecutive

pregnancies (Table 6). Mean age of women with one pregnancy during the study

period was 27.2 years (range: 20.5-33.5 years) at first blood draw and in women

with two consecutive pregnancies 27.6 years (range: 17.8-42.7 years) at first

blood draw for the first birth. The median gestational ages at blood draw were

similar between women participating with one pregnancy (T1: 75, T2: 145, and

T3: 250 days) or two pregnancies (T1:75, T2: 148, and T3: 251 days). The majority

of study participants did not smoke during pregnancy (n=52; 73%) and a

somewhat higher percentage of pregnancies ended in the delivery of a boy

(n=51; 55%) than a girl (n=41; 45%).

Table 6. Baseline characteristics; median (range), or n (%)

One pregnancy during study period

Two consecutive pregnancies during study period

Characteristics Primiparous (n=25)

Biparous (n=25)

Pregnancy 1 (n=21)

Pregnancy 2 (n=21)

Maternal age, years 27.2 (20.6-33.5) 27.5 (20.5-33.1) 26.5 (17.8-42.7) 27.7 (18.6-44.0)

Pregnancy length, days 282 (255-296) 283 (266-292) 279 (258-294) 278 (262-291)

Parity (including the current pregnancy)

1 25 (100%) 13 (62%)

2 25 (100%) 6 (29%) 13 (62%)

3 2 (9%) 6 (29%)

4 2 (9%)

Child weight, kg 3.3 (2.4-4.7) 3.8 (2.8-4.6) 3.5 (2.8-4.5) 3.8 (2.9-4.3)

Child length, cm 49 (45-55) 51 (47-54) 50 (47-53) 50 (49-53)

Child sex

Boy 10 (40%) 13 (52%) 14 (67%) 14 (67%)

Girl 15 (60%) 12 (48%) 7 (33%) 7 (33%)

Maternal smoking

No 19 (76%) 20 (91%) 13 (62%) 13 (65%)

Yes 6 (24%) 2 (9%) 8 (38%) 7 (35%)

44

4.2.1 One Pregnancy

Hormones of placental origin (estradiol and progesterone) were strongly

correlated with each other (r=0.83). Testosterone was positively correlated with

estradiol (r=0.29) and progesterone (r=0.34). Gestational age was strongly

correlated with progesterone and estradiol (r>0.84).

The correlation coefficients for individual hormones between the

trimesters of a single pregnancy are presented in Table 7. In brief, hormone

concentrations were more strongly correlated between subsequent trimesters of

a pregnancy than between the 1st and 3rd trimester (e.g., estradiol, 1st vs. 2nd and

2nd vs. 3rd trimester r=0.51 and r=0.60, p<0.01; 1st vs. 3rd trimester r=0.32,

p<0.05). Except for progesterone, hormones between the trimesters of a single

pregnancy were somewhat more strongly correlated in primiparous relative to

biparous women.

Table 7. Spearman correlation coefficients adjusted for gestational age between successive trimesters of one pregnancy

Overall (n=50) Primiparous (n=25) Biparous (n=25)

Trimester 1st 2nd 1st 2nd 1st 2nd

Estradiol

2nd 0.51# 0.52+ 0.52+

3rd 0.32+ 0.597* 0.38 0.63# 0.12 0.52+

Progesterone

2nd 0.63* 0.31 0.72#

3rd 0.39# 0.643* 0.32 0.57+ 0.32 0.67#

Testosterone

2nd 0.67* 0.79* 0.51+

3rd 0.51# 0.765* 0.61# 0.85* 0.24 0.55#

significant p-values are indicated as *<0.0001, #<0.01, +<0.05

We examined median hormone concentrations across trimesters and the

median %-change from 1st to 3rd trimester overall and by parity (Table 8). From

the first (T1) to the third (T3) trimester, median levels significantly increased

(pKW<0.0001) 4-fold for progesterone (T1: 25.6 ng/mL; T3:130 ng/mL) and

9-fold for estradiol (T1: 2.2 ng/mL; T3: 20.4 ng/mL), whereas concentrations of

testosterone increased by ~60% (T1: 1.0 ng/mL; T3:1.3 ng/mL; pKW=0.12).

45

Progesterone and testosterone concentrations were lower in biparous

women as compared to primiparous women throughout gestation

(e.g., progesterone T3 primi=138 ng/mL, T3 bi=107 ng/mL; pMW=0.007;

testosterone T3 primi=2.6 ng/mL, T3 bi=0.7 ng/mL; pMW=0.0008).

Table 8. Median hormone concentrations (10th-90th percentiles) by parity

All women (n=50)

Primiparous (n=25)

Biparous (n=25) pMW a

Estradiol (ng/mL)

1st trimester 2.18 (1.16-3.59) 2.11 (1.19-4.00) 2.42 (1.12-3.12) 0.92

2nd trimester 9.71 (5.33-15.1) 10.3 (5.20-14.8) 9.45 (5.46-15.3) 0.64

3rd trimester 20.4 (12.8-32.9) 22.3 (13.6-35.6) 19.5 (12.8-31.5) 0.71

Median %-change b 876% 858% 889%

Progesterone (ng/mL)

1st trimester 25.6 (16.6-40.7) 27.3 (20.0-42.2) 23.0 (13.5-37.8) 0.03

2nd trimester 48.1 (31.6-78.5) 53.8 (37.8-85.2) 42.1 (28.7-71.3) 0.03

3rd trimester 130 (72.6-200) 138 (105-215) 107 (60.2-163) 0.007

Median %-change b 411% 422% 396%

Testosterone (ng/mL)

1st trimester 0.96 (0.42-1.98) 1.34 (0.78-2.15) 0.66 (0.36-1.11) <0.0001

2nd trimester 1.19 (0.55-3.35) 1.98 (1.05-3.96) 0.73 (0.44-1.43) <0.0001

3rd trimester 1.32 (0.50-4.07) 2.56 (0.54-6.06) 0.71 (0.50-2.41) 0.0008

Median %-change b 61% 74% 38% a p-value obtained from the Mann-Whitney-U test comparing primi- and biparous women b median %-change between the 1st and 3rd trimester

Testosterone concentrations were higher throughout gestation in women

who reported smoking in early pregnancy relative to non-smoking women

(e.g., T1 smoker=1.7 ng/mL, T1 non-smoker=0.9 ng/mL; pMW=0.03). Third trimester

concentrations of estradiol were higher in women reporting smoking in early

pregnancy as compared to non-smoking women (T3 smoker=25.7 ng/mL,

T3 non-smoker=18.6 ng/mL; pMW=0.01).

We further examined the effect of a 1% increase in 1st and/or 2nd trimester

hormone concentrations on the estimates of 3rd trimester hormone

concentrations. Hormone concentrations measured in the 1st trimester

accounted for 13% (progesterone), 16% (estradiol), and 31% (testosterone) of

the variation in the 3rd trimester (basic model, Table 9A). Addition of maternal

or newborn characteristics impacted all hormone concentrations (Table 9A).

46

Women who were pregnant with their second child had significantly lower

progesterone concentrations (24%) than primiparous women. Higher

concentrations of estradiol (42%) and testosterone (85%) were observed in

women who smoked at study enrollment compared to non-smoking women.

Second trimester hormone concentrations explained between 42%

(estradiol) and 63% (testosterone) of the variation in the 3rd trimester on their

own with similar changes in concentrations after addition of maternal or child

characteristics as observed for the 1st trimester concentrations (Table 9B).

Table 9. Percentage changes [95%-CI] in 3rd trimester hormone concentrations associated with 1st or 2nd hormone concentrations and covariates

Estradiol Progesterone Testosterone

A)

1st trimester hormone only 26 [7; 50] b 34 [10; 63] b 71 [36; 115] a

Adjusted R² - basic model 16% 13% 31%

1st trimester hormone +

+ Age at blood draw -2 [-5; 1] 0 [-3; 3] -2 [-8; 5]

+ Smoking 42 [11; 82] b 14 [-13; 45] 85 [2; 236] b

+ Parity -5 [-28; 16] -24 [-50; -3] b -57 [-158; 4] c

+ Child sex 27 [4; 54] b 16 [-4; 40] 11 [-39; 71]

+ Birth length (per 5 cm) -13 [-40; 9] -5 [-29; 17] 12 [-41; 76]

+ Birth weight (per 100 g) -1 [-2; 1] -1 [-2; 1] 0 [-4; 5]

Adjusted R² - full model 46% 20% 39%

B)

2nd trimester hormone only 57 [35; 83] a 57 [36; 82] a 103 [72; 140] a


2nd trimester hormone only

+ Age at blood draw -1 [-3; 2] 0 [-2; 2] 1 [-4; 6]

+ Smoking 27 [2; 57] b 20 [0; 44] b 59 [1; 151] b

+ Parity -2 [-21; 16] -17 [-36; 0] b -8 [-63; 40]

+ Child sex 8 [-9; 27] 4 [-12; 22] -10 [-52; 27]

+ Birth length (per 5 cm) -10 [-31; 9] -11 [-31; 6] 11 [-26; 57]

+ Birth weight (per 100 g) -1 [-3; 1] -1 [-2; 0] 0 [-3; 3]


C)

1st & 2nd trimester hormones



a<0.0001; b<0.05; c<0.10

all models include 1st or 2nd trimester hormone concentration and the respective gestational age

47

Models based on both the 1st and 2nd trimester hormone concentrations

accounted for 45% (estradiol and progesterone) to 61% (testosterone) of the

variation observed in the 3rd trimester (Table 9C); results were similar after

addition of all available maternal and newborn characteristics.

4.2.2 Two Consecutive Pregnancies

Next, we compared hormone concentrations by trimester in women

providing samples from two consecutive pregnancies. In terms of 1st trimester

hormone concentrations, progesterone was most strongly correlated between

two pregnancies (r=0.47; p<0.05), whereas for the 3rd trimester concentrations,

between pregnancy correlations were strongest for estradiol and testosterone

(rE2=0.68 and rT=0.69; p<0.01).

Median changes in hormone concentrations between the two pregnancies

were low and showed no significant differences with the exception of

testosterone in the 3rd trimester (T3 p1=1.04 ng/mL, T3 p2=0.89 ng/mL;

pWS=0.02). When comparing hormone concentrations by parity (Table 10),

primiparous women had higher 3rd trimester testosterone levels than biparous

women (T3 primi: 1.04 ng/mL, T3 bi: 0.98 ng/mL; pWS=0.007). However, no

further decrease in 3rd trimester testosterone levels was evident when

comparing biparous women to women with >2 children (T3 bi: 0.98 ng/mL,

T3 >2 ch: 0.87 ng/mL; pws>0.30).

Table 10. Median hormone concentrations (10th-90th percentiles) by number of children in 21 consecutive pregnancies

Child 1 (n=13) Child 2 (n=19) Child >2 (n=10)

Estradiol (ng/mL)

1st trimester 2.63 (1.25-4.04) 2.23 (1.13-3.75) 1.70 (0.98-2.89)

2nd trimester 9.00 (7.46-13.5) 8.11 (5.76-13.2) 6.97 (4.67-14.1)

3rd trimester 21.5 (16.6-34.7) 22.9 (13.3-31.0) 20.0 (16.2-32.0)

Progesterone (ng/mL)

1st trimester 33.5 (22.0-47.6) 34.6 (23.3-64.3) 27.2 (20.6-35.7)

2nd trimester 67.0 (39.3-90.6) 57.0 (41.1-82.2) 53.7 (37.9-75.8)

3rd trimester 183 (135-207) 149 (101-249) 165 (145-214)

Testosterone (ng/mL)

1st trimester 0.84 (0.57-1.49) 0.80 (0.46-1.43) 0.72 (0.40-1.27)

2nd trimester 1.10 (0.70-1.30) 1.02 (0.57-1.73) 1.01 (0.57-1.31)

3rd trimester 1.04 (0.74-2.81) 0.98 (0.59-2.16) 0.87 (0.46-1.77)

48

4.2.3 Sensitivity Analyses

The results presented for testosterone are based on all available

measurements. Excluding the testosterone measurements from the batch that

resulted in higher inter-assay CVs for this hormone (n=80 samples) did not

change the direction or significance of the associations with the exception of

attenuated results for 3rd trimester levels by parity (T3 original primi: 2.56 ng/mL vs.

T3 original bi: 0.71 ng/mL, pMW<0.01; T3 limited primi: 2.16 ng/mL vs. T3 limited bi: 0.69

ng/mL, pMW=0.13) and 1st trimester concentrations by smoking (T1 original smoker:

1.69 ng/mL vs. T1 original non-smoker: 0.89 ng/mL, pMW=0.03; T1 limited smoker: 1.04

ng/mL vs. T1 limited non-smoker: 0.74 ng/mL, pMW=0.08).

Results were similar after limiting the study population to primi- and

bi-gravid women.

49

5. Discussion

5.1 Methodological Considerations: Case-Control Study

Strengths

One strength of the nested case-control study is the well-defined source

population from two unique Maternity Cohorts in Finland and Northern

Sweden. It is the largest prospective study on the associations of pre-diagnostic

sex steroids and IGF-I with risk of EOC to date and the first with detailed

analyses by tumor histology. It is also the first prospective study on the

associations of placental GH and AMH with EOC risk.

The study population consisted of young women (median age at blood

draw=31.5 years; median age at diagnosis=43.9 years), which allowed us to

assess invasive and borderline tumors separately. Prior prospective studies

could not address risk by tumor invasiveness because study participants were

substantially older at recruitment (mean/median age at blood draw >50 years;

Tables 11 and 12) and borderline tumors are diagnosed at a younger age (~33%

<40 years, ~33% between 40 and 54 years);12,13 therefore, numbers would likely

have been too small to derive meaningful conclusions.

As the women in the current study were pregnant, we were able to

measure the continuously secreted placental GH, an analogue to the pulsatile

pituitary GH. Furthermore, it was methodologically easier to measure

progesterone and estradiol levels, as pregnancy concentrations of these

hormones do not cycle as observed in non-pregnant premenopausal women.

Case and control subjects were tightly matched for age and date at

sampling, as well as parity at the index pregnancy and parity at

diagnosis/selection as a control, thus controlling for several sources of potential

confounding factors (e.g., hormone concentrations differing by parity or

maternal age).

50

Missing / incomplete data

The lack of information on grade and the incomplete data on stage

(available for 824 (78%) cases) is a limitation of this study. Especially as

low- and high-grade serous cancers can be distinguished histologically and are

considered to be different tumor types.4 However, analyses by stage (as a proxy

for grade) for invasive serous tumors showed the expected heterogeneity.

Another limitation is the lack of data on OC use before pregnancy.

Previous studies investigating the effect of past OC use on levels of IGF-I were

inconclusive,191,192 however, it is known that oral estrogens can suppress hepatic

IGF-I production.193 Significantly lower AMH levels were observed in current

users as compared to never users, however, AMH levels were similar in previous

and never users.194 As the effect of OC use is reversible after cessation, previous

OC use is unlikely to substantially influence concentrations of sex steroid

hormones, IGF-I, or AMH during pregnancy.195,196

Samples

Although study samples had been in long-term storage (median=21 years)

at relatively high temperatures (-25/-20 °C), hormone concentrations were

uncorrelated with time in storage (r<0.15), as has been reported previously.197

Moreover, case and control samples were stored under the same conditions and

matched on date of blood draw. Furthermore, we used cohort-specific tertile

cutoff points to estimate risk.

Another limitation is that only one blood measurement was available.

Several longitudinal studies in premenopausal, non-pregnant women report

very high intraclass correlation coefficients (ICC) for AMH concentrations

measured during the same menstrual cycle phase: during three consecutive

cycles (ICC=0.89), one year apart (ICC=0.88), and also 4 years apart

(ICC=0.66), suggesting that AMH concentrations are well correlated over time

in the same woman.198-200 Another study in premenopausal women evaluated

the reproducibility of steroid hormones and IGF-I over a 2-3 year period and

concluded that a single measurement obtained during either the follicular or

luteal phase sufficiently characterizes the levels of IGF-I (ICCF=0.69;

51

ICCL=0.83), SHBG (ICCF=ICCL=0.83), and androgens (ICCF>0.57;

ICCL=0.56).201 On the other hand, relatively low ICCs were reported for

estradiol (ICCF=0.38; ICCL=0.45) and progesterone (ICCL=0.29).201 This is in

line with what is observed during pregnancy; while concentrations of androgens

can relatively reliably be characterized using a single measurement, this has

proved to be more difficult for levels of estradiol and progesterone.

Furthermore, the lack of association between pre-diagnostic circulating

hormones and EOC may reflect the possibility that intra-ovarian, rather than

circulating, hormone concentrations are more important in the etiology of this

disease.

Statistical analyses

It is important to take into account that several of the studied hormones

vary with gestational age. Exact matching for GA is not feasible and would have

resulted in substantial constraints for control selection. Instead, we included GA

as continuous term in the statistical models. Another approach is to model the

hormone levels as a function of GA using local linear regression, a

nonparametric smoothing technique that employs weighted regression and uses

varying subsets of the data to estimate the curve at each point,202 and to

calculate residuals, i.e. the difference between the woman’s measured level and

the estimated mean hormone value for the day of gestation on which the blood

sample was collected. For ease of interpretability, the presented results in this

thesis are based on analyses including GA as continuous term in the models.

However, we repeated the analyses using the ‘residual’ approach, which led to

very similar results.

Multiple statistical tests were carried out to analyze associations of

endogenous hormones with risk of EOC and thus some of our findings could be

due to chance.

Despite the large number of cases included in this study, numbers were

small for the clear cell subtype (n=26 cases) and for some groups in subgroup

analyses (e.g., by stage).

52

5.2 Methodological Considerations: Longitudinal Study

The longitudinal study has a number of strengths: 1) we specified 2-week

ranges in each trimester for sample collection to account for the changing

hormone concentrations during pregnancy; 2) with the equal number of primi-

and biparous women, we were able to investigate hormone variations by parity;

and 3) we focused on normal uncomplicated pregnancies with a healthy

singleton offspring, as pregnancy-related complications (e.g., pre-eclampsia)

can cause changes in the hormonal milieu.

The low number of women in some of the subgroup analyses is one

limitation but it is owed to the exploratory nature of our study.

The inter-assay CV for testosterone was relatively high (44%), however,

results did not change when excluding the measurements from the batch (n=80

samples) causing the high inter-assay CV.

Another limitation is that we could assess smoking status during the first

trimester only. However, more than 60% of women who smoke in the first

trimester are reported to continue throughout pregnancy.203,204 The observed

changes in estradiol and testosterone levels are therefore likely to represent

concentrations in current smokers.

53

5.3 General Discussion: Case-Control Study

The nested case-control study is the first study on hormone

concentrations measured during pregnancy and subsequent risk of maternal

EOC. The protective effect of parity on EOC risk has consistently been shown in

epidemiologic studies, but the underlying mechanisms are largely unknown.

The nested case-control study allowed us to explore associations of

pregnancy-related hormones (progesterone, estradiol, placental GH) with risk

of EOC. In addition, we assessed the relationship between hormones that are

not substantially affected by early pregnancy (androgens, AMH, IGF-I) and

consider them as a proxy for the associations in non-pregnant premenopausal

women. Furthermore, associations were assessed by tumor invasiveness and

histology providing further evidence for the heterogeneity of EOC.

We observed heterogeneity in the associations between endogenous

hormones measured in early pregnancy with respect to EOC subtypes: i) higher

androgen concentrations were associated with an increased risk of borderline

serous, as well as invasive and borderline mucinous tumors, ii) higher estradiol

was positively associated with the risk of endometrioid tumors, iii) higher IGF-I

was inversely associated with the risk of invasive tumors, especially in women

diagnosed at age <55 years, and iv) a heterogeneous association was observed

for AMH and invasive serous cancer by age at blood draw. None of the studied

hormones were associated with the risk of clear cell tumors. Progesterone,

SHBG, and placental GH were not associated with the risk of EOC, regardless of

tumor histology and invasiveness.

Five prior prospective studies explored the associations of circulating

androstenedione and testosterone with risk of EOC (Table 11). Rinaldi et al.115 is

based on a subset of the study population included in the more recent

publication by Ose et al.117

54

Table 11. Characteristics of prior prospective studies on endogenous androgens and risk of EOC

Study Helzlsouer 113 Lukanova 114 Rinaldi 115 Tworoger 116 Ose 117

Cancer type EOC + non-

epithelial tumors

Invasive EOC EOC EOC /

peritoneal cancer

Invasive EOC, fallopian, and

peritoneal cancer

Cases (n) 31 (26 EOC) 132 192 224 565

Age (yrs) at blood draw Mean: 53 Range: 30-70 - Mean: 56

(range: 34-72) Median: 57

(range: 34-81)

Premenopausal at blood draw (n) 13 (42%) 44 (33%) 56 (29%) 62 (28%) 112 (20%)

Results from the three largest studies did not show any association with

risk,115,116 or presented an inverse association of androstenedione for invasive

serous tumors (Figure 7).117 We observed an increased risk with both studied

androgens for borderline serous tumors and mucinous tumors. Our study

differs from the previous investigations on the association between androgens

and EOC in two important ways. First, we had the statistical power to study the

risk associations with respect to both tumor invasiveness and histology. Most of

the previous reports included mainly invasive serous tumors, with negligible

numbers of borderline and mucinous tumors. In the current study, we were able

to investigate associations with the rarer histological subtypes, which are usually

observed at a younger age.205 Second, blood samples used in our study were

collected exclusively from pregnant women (by definition premenopausal);

androgen concentrations are higher in premenopausal women when compared

to postmenopausal women. In previous prospective studies, only 20%117 to

42%113 of cases were premenopausal (Table 11).

It has been proposed that EOC originates via two main pathways of

carcinogenesis and can be divided into two subtypes (type I and type II

tumors).206,207 Type I tumors include low-grade serous and endometrioid

carcinoma, clear cell, mucinous, and malignant Brenner tumors that develop

slowly and are often diagnosed at an early stage. These tumors are typically

confined to one ovary and progress from benign, with increasing degrees of

atypia, to non-invasive and then invasive tumors. Thus, borderline ovarian

tumors may be the precursors of type I tumors. Type II tumors include

high-grade serous and endometrioid carcinoma, undifferentiated, malignant

55

mixed mesodermal, and transitional cell tumors that are highly aggressive and

usually present at an advanced stage. It has been suggested that type II tumors

mainly originate from epithelium outside the ovary and invade the ovary

secondarily.206,207

Figure 7. ORs [95% CIs] of overall EOC for top tertile/quartile of circulating androgen concentrations

A) Testosterone in women premenopausal at blood collection

B) Androstenedione in women premenopausal at blood collection

While we were unable to define EOC cases into type I / II due to missing

data on grade in our study, we observed significant positive associations

between androgen concentrations and borderline / invasive mucinous, as well

as borderline serous subtypes, suggesting that androgens may be involved in the

development of the slowly growing tumors in the ovaries, whereas they do not

appear to influence the risk of the most aggressive cancers, which are probably

of extra-ovarian origin. This hypothesis is also supported by the observation

that risk increased for a doubling of testosterone concentrations in invasive

Lukanova, 2003 (44 cases)

Rinaldi, 2007 (56 cases)

Tworoger, 2008 (62 cases)

Ose, 2014 (112 cases)

Present study (640 cases)

1.54 [0.56-4.24]

1.27 [0.60-2.69]

0.50 [0.20-1.40]

1.16 [0.57-2.38]

1.37 [1.08-1.72]

0.5 1.0 1.5 2.0 3.0 4.0

Helzlsouer, 1995 (31 cases)


Rinaldi, 2007 (56 cases)


Ose, 2014 (112 cases)

Present study (640 cases)

7.60 [1.20-48.70]

2.19 [0.80-6.01]

1.11 [0.55-2.24]

0.90 [0.30-2.90]

0.80 [0.38-1.70]

1.36 [1.08-1.72]

0.5 1.0 1.5 2.0 3.0 4.0 6.0 7.0 8.0

56

serous tumors diagnosed as localized (proxy for type I ORlog2: 1.91 [1.02-3.57]),

but not those diagnosed as advanced disease (proxy for type II ORlog2: 0.88

[0.68-1.14]; phet=0.03).

Associations of circulating 17-OHP concentrations with EOC risk have not

been evaluated previously. We observed a positive association between 17-OHP

concentrations and risk of borderline serous tumors. However, adjustment for

androgens resulted in substantial attenuation of the results (Table 5), suggesting

that higher circulating androgens are major determinants of borderline serous

tumors, whereas circulating 17-OHP contributes to tumor development mainly

as a precursor hormone for the synthesis of androgens.

Results from experimental studies, and a number of indirect

observations, indicate that elevated progesterone concentrations may be

inversely associated with the risk of EOC. Progesterone has been shown to have

a potent apoptotic effect on the surface epithelium and to induce cellular

senescence of ovarian cancer cells through FOXO1.88,90 Results from

epidemiological studies consistently show an inverse association between

increasing parity, and the use of OCs with EOC.25,65 Owing to its potent

apoptotic effect and elevated production during pregnancy, progesterone is the

most plausible candidate to mediate a ‘washout effect’, i.e., elimination from the

ovary of cells that have undergone malignant transformation, a hypothesis

proposed to explain the greater protective effect of pregnancies completed at an

older age.21 In addition, results from observational studies have indicated that

incomplete pregnancies confer less protection than a pregnancy conducted to

term or are not associated with EOC risk.19,20,23

However, we observed no association between early pregnancy

progesterone and risk of EOC. One explanation for the lack of association could

be that 1st trimester progesterone concentrations do not reflect exposure in the

3rd trimester. It is plausible that only very high progesterone concentrations, as

observed during the third trimester, are etiologically important, whereas the

57

substantially lower hormone concentrations during the first trimester are not.

Results obtained using cell culture models indicate that growth inhibition and

apoptosis occur only at very high concentrations (≥10-6M).108 In addition,

during multiple pregnancies, progesterone concentrations are higher compared

with singleton pregnancies, and women with a history of multiple births are at a

reduced risk of non-mucinous EOC.69,97

Our finding of a positive association between estrogen concentrations

with the risk of endometrioid tumors is novel. Elevated estrogen concentrations

are consistently associated with an increased risk of endometrial cancer in

postmenopausal women.124,125 Furthermore, endometrial cancer and

endometrioid EOC share similar risk factor profiles, as well as several common

genes and pathways that are involved in their molecular pathogenesis.208 It has

also been reported that patients with endometriosis, which is associated with

molecular aberrations that favor increased local production of estradiol,126 are at

an increased risk of developing endometrioid EOC.37,38 Although clear cell

tumors may originate in part from endometriosis, we did not find any

association between estradiol and clear cell tumors. This finding might be due to

the small number of cases in our study (n=26), but it is consistent with the

hypothesis that clear cell tumors may arise from endometriosis through

mechanisms independent of hormonal signaling.6

However, the direct association between estradiol and endometrioid EOC

should be interpreted cautiously and needs to be replicated in other studies in

premenopausal women.

Associations between GH and risk of EOC have not previously been

investigated directly, but only through investigations exploring the effect of

IGF-I on risk of EOC. We did not observe an association between placental GH

and EOC in our data. However, there is evidence from in vitro and animal

studies relating pituitary GH to other epithelial cancers, including breast,

prostate, and colon cancers.209 Evidence for the involvement of GH in human

58

carcinogenesis comes from patients suffering from acromegaly, i.e. GH

hyper-secretion, as they have an increased risk of developing colorectal cancer,

and potentially breast and prostate cancers.210 Conversely, in patients with

Laron syndrome, i.e. primary GH insensitivity, a reduced risk was observed.211

The release of pituitary GH is stimulated by the growth

hormone-releasing hormone (GHRH). Its antagonists have been shown to

reduce growth of human ovarian cancer cell lines in xenografted nude mice, but

it is not yet clear whether this effect is due to the inhibition of GH release, and

thus hepatic IGF-I synthesis, suppression of autocrine and/or paracrine IGF-I

production, or both.212,213

To date, four prospective studies evaluated the association of circulating

IGF-I with risk of EOC in pre- and postmenopausal women (Table 12). The

study by Peeters et al.144 is based on a subset of the study population included in

the more recent publication by Ose et al.145

Table 12. Characteristics of prior prospective studies on endogenous IGF-I and risk of EOC

Lukanova 143 Peeters 144 Tworoger 146 Ose 145

Cancer type Invasive EOC EOC EOC / peritoneal cancer

Invasive EOC, fallopian, and

primary peritoneal cancer

Age (yrs) at blood draw Range: 30-70 Median: 57 Mean: 56

(range: 34-73) Median: 57

(range: 34-80)

Cases (n) 132 214 222 565

Premenopausal at blood draw (n) 44 (33%) 56 (26%) 62 (28%) 112 (20%)

<55 years at diagnosis (n) 41 (31%) 66 (31%) 59 (27%) 105 (19%)

Study results were inconclusive and reported either no association143-145

or an inverse association with ovarian cancer risk.146 Two of these investigations

observed an increased risk in women diagnosed before age 55 years,143,144

whereas the remaining reported a non-significant decrease in risk for women

diagnosed before age 55 years (Figure 8).145,146 However, the proportion of

women <55 years in these studies was low (<35%; Table 12), whereas 90% of the

59

cases in our analysis fall within this age group. The observed significant inverse

associations between IGF-I and EOC risk overall, as well as in invasive tumors,

were stronger when limited to women younger than age 55 years at diagnosis in

our investigation, consistent with two prior studies.145,146

A plausible explanation for the observed inverse, protective association is

difficult to formulate, as experimental data consistently suggest that IGF-I may

increase risk of ovarian cancer by stimulating cell growth and that it is involved

in disease progression.214,215 Despite a large body of research suggesting positive

associations between IGF-I and risk of epithelial cancers (breast, colon, and

prostate cancer),137 we observed an inverse association with risk of epithelial

ovarian cancer in our study.

Figure 8. ORs [95% CIs] of EOC for top tertile/quartile of circulating IGF-I in women age <55 years at diagnosis

Associations of circulating AMH with risk of EOC have not been

evaluated previously. We focused on invasive serous tumors, as, first, it is the

most common EOC histologic subtype. Second, it is hypothesized that serous

tumors originate from the fimbriae of the Fallopian tube.16 Given that the

Fallopian tubes develop from the Müllerian ducts147 and AMH causes regression

of Müllerian ducts in the male fetus, we hypothesized to see an inverse

association between AMH and risk of invasive serous tumors.

However, we did not observe any association between pre-diagnostic

circulating AMH and risk of invasive serous ovarian cancer. The observed

increased risk in women younger than the median age at sampling, and the


Peeters, 2007 (66 cases)


Ose, 2014 (105 cases)

Schock, 2014 (561 cases)

4.73 [1.31-17.1]

1.00 [0.70-1.60]

0.70 [0.25-1.97]

0.66 [0.33-1.32]

0.74 [0.57-0.96]

0.5 1.0 2.0 3.0 4.0 5.0

60

opposite in older women in our study, was unexpected. These results may be

due to chance, or might reflect a different follicle recruitment rate pattern in

case and control subjects. A higher follicle recruitment rate before age

30-35 years would most likely result in higher circulating AMH at younger age,

but would cause a faster and earlier depletion of the primordial follicles,

resulting in a lower rate of follicle recruitment and lower AMH concentrations

at older reproductive age. Our data show a stronger inverse correlation of AMH

with age in cases (r=-0.50 [-0.62, -0.33]) relative to controls (r=-0.27

[-0.39, -0.14]), indicating a more rapid depletion of the pool of primordial

follicles with older age in cases. This observation is consistent with the

follicle-depletion hypothesis, which stipulates that slower follicle depletion may

decrease risk of developing EOC.216 High initial follicle recruitment rate and

early depletion of the primordial follicles have been observed in AMH null or

heterozygous mice that have preserved fertility.217,218 The growth inhibitory

effect of AMH on EOC risk could be more pronounced in older women, who

have accumulated greater genetic damage over time, than in younger women.

This may contribute to the inverse association of AMH with risk of invasive

ovarian cancer after age 35 years. The association of AMH with risk did not vary

by lag time.

As presented in this study, hormones are likely to play a role in the origin

and progression of EOC. They are primarily mediated through interaction with

their respective nuclear receptors, which are differently expressed in normal

ovarian tissue,219 fallopian tube epithelium,220 and in EOC depending on

histology.220-227

The androgen receptor (AR) is expressed in normal ovarian tissue (42%)

and fallopian tubes (69%).219,220 Positive staining (>10%) is observed in 18-44%

of EOC, with highest expression in serous tumors.220,221 Strong staining (>50%)

of the progesterone receptor (PR) is observed in 14% of EOC,227 with the highest

expression observed in endometrioid tumors.226,227 Estrogen action is mediated

by two estrogen receptor (ER) subtypes, ER-α and ER-β, with supposedly

different roles in the ovaries.228 Several studies report similar expression of

61

ER-α in normal and malignant ovarian tissue, but observe lower ER-β

expression and higher ER-α/ER-β ratio in malignant as compared to normal

ovarian tissue.229,230 No differences in expression of ER-α and ER-β mRNA were

observed in normal and malignant epithelial ovarian cell cultures.231,232

However, the ratio of ER-α/ER-β was increased in cell cultures derived from

EOC.231 One study (n=149 EOC) reported positive (≥10%) nuclear staining in

31% (ER-α) and 16% (ER-β) of patients diagnosed with serous EOC.233 The

IGF-I receptor (IGF-IR) is expressed in 50%-57% of serous tumors, but no

expression was detected in normal ovarian tissue.225,234 Two studies evaluated

the expression of AMHRII.223,224 While one study reported high expression of

AMHRII in mucinous (100%), serous (76%), endometrioid (55%), and clear cell

(40%) tumors,223 the other study observed positive staining in 25% of serous

EOC, with no or weak staining in the other histological subgroups.224 The wide

range of receptor expression within the same tissue may result from various

factors, e.g. type of the analyzed sample, differing immunohistochemical

platforms, sample size, and the lack of a standardized scoring system.

Given that EOC is a hormone-responsive cancer, endocrine therapy is an

attractive anticancer treatment, which can be easily administered. Studies on

cell lines and in mouse models were promising.88,235-238 In humans, high AR

expression was associated with prolonged disease specific survival in patients

with serous EOC.220 On the other hand, ER and PR expression were associated

with improved survival in patients diagnosed with endometrioid EOC.227

However, the limited number of small-scale clinical trials conducted so far

testing endocrine therapy in EOC have shown only modest response rates

overall with few patients that responded well.17,63

62

5.4 General Discussion: Longitudinal Study

The longitudinal study demonstrates patterns of change in hormone

concentrations throughout pregnancy. The substantial increase in maternal

serum concentrations of estradiol and progesterone throughout pregnancy is

well established82,106 and was also evident in our study. The gradual, more

modest increase in testosterone concentration across gestation has been

reported in prior longitudinal studies.106,239

Estradiol concentrations were correlated in successive pregnancies in our

investigation, with stronger correlation coefficients in the 3rd (r=0.68) as

compared to the 1st (r=0.47) trimester. A previous study based on 34 women

with uncomplicated first and second full-term pregnancies reported a strong

correlation (r=0.78) between early estradiol levels in the consecutive

pregnancies.180

We observed a non-significant suggestion of lower estradiol

concentrations throughout pregnancy in biparous women. This is consistent

with previous studies reporting lower first and second trimester estradiol levels

in multiparous as compared to primiparous women.240-245 The decreased

concentrations of estradiol in multiparous women are hypothesized to be a

result of increased pregnancy-induced 16α-hydroxylase activity in the maternal

liver during prior pregnancies leading to increased metabolism of estradiol, and

thus lower circulating estradiol in subsequent pregnancies.246 We observed

significantly lower progesterone and testosterone concentrations in biparous as

compared to primiparous women; this was also reported in prior studies on

early pregnancy hormones.241-244

Women who smoked during pregnancy had higher 3rd trimester estradiol

concentrations than non-smoking women. However, prior studies investigating

the relationship of estradiol and smoking in pregnant women, conducted in

1st or 2nd trimester samples, reported no association of estradiol concentrations

with smoking.241,242,244 Estradiol concentrations were also similar in

premenopausal smoking and non-smoking women, with blood samples

obtained during the early follicular phase or assessed longitudinally during two

63

cycles.247-249 In concordance with our results, higher testosterone levels in

smoking women were also observed in one large-scale study (1 343 pregnant

women),242 whereas a smaller study (420 pregnant women) did not observe

such an association.244 Studies in non-pregnant, premenopausal women are

inconclusive. While one large study reported no differences in testosterone

levels of smoking and non-smoking women,247 another study based on

10 women in both groups observed higher concentrations of testosterone among

smoking women as compared to non-smoking women.248

We observed no differences in hormone concentrations between women

pregnant with a boy or a girl. Prior studies are inconsistent, with some reporting

an increase in early pregnancy estradiol and testosterone concentrations in

women pregnant with a girl,242,243 and others observing no differences by fetal

sex.241,250 A decrease in pregnancy progesterone levels in women carrying a

female fetus was observed in one study that collected blood at gestational weeks

16 and 27,241 but not in studies conducted in gestational weeks 6-20.242,243,251

In conclusion, hormone concentrations measured in the 1st, 2nd, or

3rd trimester are correlated, as are hormone concentrations between

pregnancies. Furthermore, to some extent, it is possible to estimate selected

3rd trimester hormone concentrations based on one hormone measurement

drawn in early gestation and pregnancy characteristics. However, it is likely that

additional important factors are lacking to determine 3rd trimester

concentrations based on 1st and/or 2nd trimester levels.

64

6. Conclusions

Based on the results from the nested case-control study on endogenous

hormones and risk of EOC, we conclude that:

Early pregnancy androgen concentrations may be associated with

borderline serous, as well as borderline and invasive mucinous tumors.

Early pregnancy 17-OHP may be associated with borderline serous

tumors.

Early pregnancy estradiol concentrations may be associated with

endometrioid tumors.

Early pregnancy IGF-I concentrations may be inversely associated with

invasive EOC, especially in women aged <55 years at diagnosis.

Early pregnancy AMH concentrations may not be associated with

invasive serous EOC overall, but results by age at blood draw were

heterogeneous.

The study results do not support a role for early pregnancy placental

GH, progesterone, or SHBG in ovarian carcinogenesis.

Based on the results from the longitudinal study on circulating

concentrations of steroids throughout pregnancy, we conclude that:

Correlations between early pregnancy sex steroids are stronger between

consecutive trimesters of a pregnancy than between the 1st and

3rd trimester.

1st trimester measurement of testosterone represents the exposure

throughout pregnancy, whereas measurements of estradiol and

progesterone are representative for the first half only.

65

7. Outlook and Future Directions

Our results support the hypothesis of an involvement of hormones in the

etiology of EOC. To confirm our findings, studies in premenopausal,

non-pregnant women are necessary. Furthermore, this study supports EOC

heterogeneity. Future investigations by histologic EOC subgroups in consortia

are required for risk factor identification, risk prediction, and early detection.

To obtain knowledge on origin of EOC, underlying mechanisms of the

hormonal interplay in the female reproductive system have to be elucidated. It

is also necessary to explore pre-diagnostic hormone concentrations in relation

to the receptor status of the tumor, which may allow more refined investigations

of EOC etiology. To date this has been minimally explored in EOC, whereas in

breast cancer this approach has led to new insights and to development of

tailored treatment depending on the tumor receptor status.252

Data to predict risk of ovarian cancer in the general population are

sparse. So far, existing risk prediction models only include reproductive and

lifestyle factors and do not distinguish between the histological subgroups.253,254

Consideration of EOC heterogeneity and addition of endogenous hormone

concentrations to these models could improve the identification of women at

risk of developing EOC. Additional work investigating etiologic pathways by

histology is crucial.

66

Acknowledgments

There are many people involved in the process to complete a thesis. I wish to

express my sincere gratitude to those who have helped and supported me on

this journey. In particular I wish to express my deep and sincere gratitude to:

The women in the Northern Sweden Maternity Cohort and the Finnish

Maternity Cohort, without whose benevolence this work would have been

impossible.

Eva Lundin, my main supervisor, for your scientific guidance, endless support,

and encouragement. A big thank you for your hospitality and always warm

welcome!

Renée T Fortner, my assistant supervisor, for your enthusiasm, scientific

expertise, and constructive criticism. Thank you for all the inspiring

discussions!

My assistant supervisors Annika Idahl and Anne Zeleniuch-Jacquotte, for all

your support, scientific guidance, and constructive suggestions. It was great

having you on board!

Annie Lukanova, my initial supervisor, for your enthusiasm, scientific expertise,

and support. Thank you for introducing me to the world of research and giving

me the opportunity to grow!

Rudolf Kaaks, head of the department of Cancer Epidemiology, for giving me

the time and space to work on these exciting projects!

Kjell Grankvist, Hans-Åke Lakso, and all lab technicians for the high quality of

the laboratory work and support!

Robert Johansson, Lena Selbrand, Ritu Andersson, Heljä-Marja Surcel, Eero

Pukkala, and Matti Lehtinen for providing the Swedish and Finnish registry

data and constructive comments.

Terry Persson, Carina Ahlgren, Heike Weiss, and Petra Rössler for taking care

of travel arrangements, paperwork, and all .

67

Jasmine, Lisanne, Myrto, Kaja, Katja, Jennifer, and many other friends and

fellow doctoral students. I enjoyed sharing this experience with all of you!

Meinen Eltern, Katharina und Erwin, für Eure Liebe und Euer Vertrauen in

mich! Ihr seid immer für mich da und unterstützt mich bei all meinen Vorhaben

– dafür danke ich Euch von Herzen.

Meiner Schwester Olga für ihre Liebe und Geduld. Ich freue mich darauf

meinen Pflichten als Tante nachzukommen

All my colleagues at the department of Medical Biosciences in Umeå and at the

department of Cancer Epidemiology in Heidelberg for generating an inspiring

forum for scientific discussions.

All of you not mentioned, but nevertheless not forgotten, who have supported

and encouraged me during this work – my deepest thanks!

- THANK YOU -

This work was supported by grants from the National Cancer Institute at the

National Institute of Health, US and Lion’s Cancer Research Foundation at

Umeå University, Sweden.

68

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