We found an increasing risk of ovarian cancer with a doubling in the levels of IL-4, IL-6, IL-12p40, IL-12p70, and IL-13 and observed a trend across quartiles of IL-2, IL-4, IL-6, IL-12p40 and IL-13. These trends were statistically significant or of borderline significance after adjustment for parity, oral contraceptive use, and BMI.
Factors that inhibit ovulation, such as parity and oral contraceptive use, have consistently been shown to be inversely associated with ovarian cancer risk. The physiological process of ovulation has many characteristics of an inflammatory reaction, including the generation of an abundance of inflammatory cytokines to facilitate growth, development, and remodeling of the follicle and repair of the ovulatory wound (22
). The repeated wounding and healing process is thought to contribute to DNA and cellular damage at the ovarian surface epithelium (OSE) and/or in ovarian inclusion cysts (OIC), the putative site of origin for several ovarian tumor types (24
). The fallopian tube fimbria, which has recently been identified as another site of origin for ovarian tumors, is exposed to inflammatory cytokines due to retrograde transport of menstrual fluid and infections from the lower genital tract (23
). Local inflammatory conditions such as endometriosis, exposure to irritants such as talc, and low grade systemic inflammation due to factors such as obesity are also associated with increased ovarian cancer risk. Both ovulation-specific and ovulation-independent low-grade inflammatory processes are associated with increased ovarian cancer risk, which may be one reason why we did not observe evidence of effect modification by menopausal status. Inflammation mediators can act as tumor promoters by providing a proliferative, anti-apoptotic, and angiogenic environment for transformed cells in the fallopian tubes and ovaries (30
). The involvement of the global immune network in the regulation of physiologically normal ovarian processes (32
), suggests that these organs may be particularly exposed to systemic as well as local inflammation.
IL-2, IL-4, and IL-6 are archetypical cytokines expressed in Th1, Th2, and Th17 inflammatory responses, respectively (21
). These cytokines’ pivotal role in inflammation as well as their association with normal (41
) and malignant (44
) ovarian processes offer biologic plausibility to our findings. We observed that IL-2, IL-4, and IL-6 were associated with significantly increased risk. For IL-2 and IL-6, this association was particularly apparent when their modulators (sIL-2Ra and sIL-6R, respectively) were expressed at low levels, suggesting that an imbalance in cytokines and their modulators, which can act as antagonists of cytokine signaling, may be associated with increased risk. The T-helper (Th) immune cell paradigm suggests that Th1 cell populations secrete cytokines which can inhibit the Th2 cell type (and vice versa) to regulate cell-mediated as well as antibody-mediated immunity (53
). Furthermore, depending on their relative concentrations, Th1 and Th2 cytokines can also promote or inhibit Th17 cells, which are associated with immune-mediated tissue damage (53
). Although this classification system is thought to be an oversimplification of cytokine production and function, improved cytokine classification systems have not yet been developed. Our hypothesis was that having high Th1- or Th17-related cytokines and low Th2-related cytokines would be associated with increased risk of ovarian cancer due to the pro-inflammatory nature of Th1 and Th17 versus Th2 subtypes. However, we found that for the pairs IL-2 (Th1) and IL-4 (Th2), IL-6 (Th17) and IL-4 (Th2), and IL-2 (Th1) and IL-6 (Th17), having high levels of both markers was associated with a significant increase in risk, and having high levels of only one was not. This finding suggests that a persistent inflammatory state, involving elevations in all Th-cell type cytokine responses, may be associated with increased risk, though we had somewhat limited power to detect associations within subgroups.
Our study has several important strengths. A major strength of our study is its prospective design, which ensured that samples were collected before diagnosis, which is required to infer the proper temporal sequence from cytokine elevations to cancer, and also minimizes selection bias. An additional strength was that we evaluated the temporal reliability of all biomarkers in preliminary studies. Measurement error adjusted estimates for the cytokines that were associated with ovarian cancer risk did not differ appreciably from unadjusted estimates (absolute increase of ≤0.01 in the adjusted vs. unadjusted ORs) (data not shown). These results were not surprising since these markers had intra-class correlation coefficient (ICC, fraction of total variation due to between-subject variability) above 0.5, with most ranging from 0.7–0.9, indicating that a single measurement of these markers is representative of an individual’s average marker level and can therefore be used to rank individuals (7
A limitation of our study is that we did not have information on several factors that influence cytokine levels, such as the presence of autoimmune or infectious diseases. However, women were generally healthy at blood donation, and the proportion of women with serious infections and undiagnosed chronic diseases is likely to be very low. The main limitation of our study was its relatively small sample size resulting in sufficient power to detect moderate to strong ORs only, especially within subgroups. Another limitation is that multiple comparisons may have led to some spurious associations. However, associations were apparent for IL-4, IL-6, and IL-13 when modeled as continuous as well as categorical variables and after controlling for confounders, although less so for IL-2 and IL-12p40. Replication of our results in independent prospective studies, though, is needed, in particular for IL-4 and IL-13 for which there was some evidence of interaction by cohort and also for IL-12p70 which was associated with risk when modeled as a continuous variable, but did not show a trend across ordered categories. Finally, ovarian cancer is a heterogeneous disease, with multiple histological subtypes and diverse etiological pathways. Overall case-control comparisons may have prevented us from observing a cytokine effect that is limited to a specific subtype. However, our study is limited to ovarian cancers that originate from epithelial cells and each of the epithelial histological subtypes is associated with risk factors consistent with the inflammation hypothesis. When we restricted the analyses to the most common serous histological subtype, we found that odds ratios were not substantially different from overall analyses.
In summary, we found a positive association between IL-2, IL-4, IL-6, IL-12, and IL-13 and ovarian cancer risk. These findings provide support for the role of inflammation in the etiology of ovarian cancer.