The gynaecological diseases endometriosis and endometrial cancer have serious consequences on quality of life for affected women and impose significant costs to the healthcare system in Australia, together accounting for >28,000 hospital bed days in 2009-10. A convincing link between these diseases has been difficult to establish epidemiologically, although both are hormonally regulated diseases of abnormal endometrium growth and share a number of risk factors and pathological features. Utilising previously generated GWAS data (1,2) we recently applied a cross-disease approach to explore the genetic relationship between endometriosis and endometrial cancer. Genetic prediction analyses revealed significant shared genetic architecture underlying the two diseases, with P-values plateauing at 7.8x10-10 for SNPs with P<0.3 in the endometrial cancer dataset predicting case status in the endometriosis dataset. We then performed a cross-disease meta-analysis of our GWAS datasets, incorporating data from 925 additional endometrial cancer samples from Oxford, UK, revealing two loci exceeding a genome-wide level of significance (Chr11 P=2.6x10-8, OR=1.16; Chr17 P=3.6x10-8, OR=1.15) and another two loci just under this significance threshold (Chr17 P=1.8x10-7, OR=1.16; Chr6 P=3.4x10-7, OR=1.19). Two of these regions harbour genes previously linked to other hormonal (breast and ovarian) cancers, suggesting the presence of multiple disease susceptibility variants at these loci. All four regions are currently undergoing bioinformatic analyses to investigate potential functional SNPs/sequences, and regional imputation of the published GWAS datasets to the latest 1000 Genomes release has suggested additional SNPs for follow-up in the future. SNPs at three of the four regions are currently being analysed in an independent endometrial cancer dataset, with results ready in June, 2012. Our current results indicate a number of loci that may contribute to the risk of both endometriosis and endometrial cancer, and provide further evidence of the value of a cross-disease approach to finding new genes contributing to complex disease susceptibility.