Globally, ovarian cancer is the seventh most common cancer in women and the eighth most common cause of cancer death, with five-year survival rates below 45%. Although agestandardised rates are stable or falling in most high-income countries, they are rising in many low and middle income countries. Furthermore, with increasing life-expectancy, the number of cases diagnosed each year is increasing. To control ovarian cancer we need to understand the causes. This will allow better prediction of those at greatest risk for whom screening might be appropriate, while identification of potentially modifable causes provides an opportunity for intervention to reduce rates. In this paper we will summarise the current state of knowledge regarding the known and possible causes of epithelial ovarian cancer and discuss some of the main theories of ovarian carcinogenesis. We will also briefly review the relationship between lifestyle and survival after a diagnosis of ovarian cancer.[Words=148] KEY WORDSOvarian neoplasms; epidemiology; incidence; risk factors; survival M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 3 INTRODUCTIONGlobally, 240,000 women are diagnosed with ovarian cancer every year and, with five-year survival below 45%, it is responsible for 150,00 deaths making it the 7 th most common cancer and 8 th most common cause of cancer death among women [1]. Figure 1A shows that agestandardised incidence rates are highest in northern and central/eastern Europe, intermediate in north America, Australia and western Europe and lowest in Asia and Africa. Rates have been decreasing in most high incidence countries but increasing in many low incidence countries ( Figure 1B) thus the differences today are less marked than 30 years ago [2]. Rates also vary by ethnicity within countries such that in the United States, rates in non-Hispanic white women are approximately 30% higher than African-American and Asian women and 12% higher than Hispanic women [3].

ObjectiveTo estimate the numbers and proportions of cancers occurring in Australia in 2010 attributable to modifiable causal factors.MethodsWe estimated the population attributable fraction (PAF) of cancers associated with exposure to 13 causal factors using standard formulae incorporating exposure prevalence and relative risk data. We also calculated the potential impact of changing exposure to some factors.ResultsA total of 32% of all cancers diagnosed in Australia in 2010 (excluding keratinocyte cancers) were attributable to the 13 factors assessed (men 33%; women 31%). Leading factors were tobacco smoke (PAF all cancers: 13.4%), solar radiation (6.2%), inadequate diet (6.1%) and overweight/obesity (3.4%). Factors conferring highest PAFs differed by sex: highest PAFs for men were tobacco smoke (15.8%), solar radiation (7.1%) and alcohol (3.0%); while highest PAFs for women were tobacco smoke (10.1%), solar radiation (5.0%) and overweight/obesity (4.5%). Sites with the highest counts of potentially preventable cancers were lung (8,569), colorectal (7,404), melanoma of the skin (7,220) and breast (3,233).ConclusionsAt least one in three cancers in Australia is attributable to exposure to known modifiable factors.ImplicationsUp to 37,000 cancers could be prevented in Australia each year if the population avoided exposure to 13 common factors known or strongly suspected to cause cancer.

Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carcinoma (RCC). We conducted a meta-analysis of two new scans of 5,198 cases and 7,331 controls together with four existing scans, totalling 10,784 cases and 20,406 controls of European ancestry. Twenty-four loci were tested in an additional 3,182 cases and 6,301 controls. We confirm the six known RCC risk loci and identify seven new loci at 1p32.3 (rs4381241, P=3.1 × 10−10), 3p22.1 (rs67311347, P=2.5 × 10−8), 3q26.2 (rs10936602, P=8.8 × 10−9), 8p21.3 (rs2241261, P=5.8 × 10−9), 10q24.33-q25.1 (rs11813268, P=3.9 × 10−8), 11q22.3 (rs74911261, P=2.1 × 10−10) and 14q24.2 (rs4903064, P=2.2 × 10−24). Expression quantitative trait analyses suggest plausible candidate genes at these regions that may contribute to RCC susceptibility.