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Ovarian cancer (OC) is the eighth most common type of cancer for women worldwide. The current diagnostic and prognostic routine available for OC management either lack specificity or are very costly. Gene expression profiling has shown to be a very effective tool in exploring new molecular markers for patients with OC, although association of such markers with patient survival and clinical outcome is still elusive. Here, we performed gene expression profiling of different subtypes of OC to evaluate its association with patient overall survival (OS) and aggressive forms of the disease. By global mRNA microarray profiling in a total of 196 epithelial OC patients (161 serous, 15 endometrioid, 11 mucinous, and 9 clear cell carcinomas), we found four candidates-HSPA1A, CD99, RAB3A and POM121L9P, which associated with OS and poor clinicopathological features. The overexpression of all combined was correlated with shorter OS and progression-free survival (PFS). Furthermore, the combination of at least two markers were further associated with advanced grade, chemotherapy resistance, and progressive disease. These results indicate that a panel comprised of a few predictors that associates with a more aggressive form of OC may be clinically relevant, presenting a better performance than one marker alone.

Ovarian cancer (OC), the eighth-leading cause of cancer-related death among females worldwide, is mainly represented by epithelial OC (EOC) that can be further subdivided into four subtypes: Serous (75%), endometrioid (10%), clear cell (10%), and mucinous (3%). Major reasons for high mortality are the poor biological understanding of the OC mechanisms and a lack of reliable markers defining each EOC subtype. MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression primarily by targeting messenger RNA (mRNA) transcripts. Their aberrant expression patterns have been associated with cancer development, including OC. However, the role of miRNAs in tumorigenesis is still to be determined, mainly due to the lack of consensus regarding optimal methodologies for identification and validation of miRNAs and their targets. Several tools for computational target prediction exist, but false interpretations remain a problem. The experimental validation of every potential miRNA-mRNA pair is not feasible, as it is laborious and expensive. In this study, we analyzed the correlation between global miRNA and mRNA expression patterns derived from microarray profiling of 197 EOC patients to identify the signatures of miRNA-mRNA interactions associated with overall survival (OS). The aim was to investigate whether these miRNA-mRNA signatures might have a prognostic value for OS in different subtypes of EOC. The content of our cohort (162 serous carcinomas, 15 endometrioid carcinomas, 11 mucinous carcinomas, and 9 clear cell carcinomas) reflects a real-world scenario of EOC. Several interaction pairs between 6 miRNAs (hsamiR- 126-3p, hsa-miR-223-3p, hsa-miR-23a-5p, hsa-miR-27a-5p, hsa-miR-486-5p, and hsamiR- 506-3p) and 8 mRNAs (ATF3, CH25H, EMP1, HBB, HBEGF, NAMPT, POSTN, and PROCR) were identified and the findings appear to be well supported by the literature. This indicates that our study has a potential to reveal miRNA-mRNA signatures relevant for EOC. Th

The usage of next generation sequencing in combination with targeted gene panels has enforced a better understanding of tumor compositions. The identification of key genomic bi-omarkers underlying a disease are crucial for diagnosis, prognosis, treatment and therapeutic re-sponses. The Oncomine™ Comprehensive Assay v3 (OCAv3) covers 161 cancer‐associated genes and is routinely employed to support clinical decision making for a therapeutic course. An improved version, Oncomine™ Comprehensive Assay Plus (OCA‐Plus), has been recently developed, covering 501 genes (144 overlapping with OCAv3) in addition to microsatellite instability (MSI) and tumor mutational burden (TMB) assays in one workflow. The validation of MSI and TMB was not addressed in the present study. However, the implementation of new assays must be validated and confirmed across multiple samples before it can be introduced into a clinical setting. Here, we report the comparison of DNA sequencing results from 50 ovarian cancer formalin‐fixed, paraffin‐embed-ded samples subjected to OCAv3 and OCA‐Plus. A validation assessment of gene mutations identified using OCA‐Plus was performed on the 144 overlapping genes and 313,769 intersecting nucle-otide positions of the OCAv3 and the OCA‐Plus. Our results showed a 91% concordance within variants classified as likely‐pathogenic or pathogenic. Moreover, results showed that a region of PTEN is poorly covered by the OCA‐Plus assay, hence, we implemented rescue filters for those variants. In conclusion, the OCA‐Plus can reflect the mutational profile of genomic variants com-pared with OCAv3 of 144 overlapping genes, without compromising performance.

Ovarian clear cell carcinoma (OCCC) is characterized by dismal prognosis, partially due to its low sensitivity to standard chemotherapy regimen. It is also well-known for presenting unique molecular features in comparison to other epithelial ovarian cancer subtypes. Here, we aim to identify potential subgroups of patients in order to (1) determine their molecular features and (2) characterize their mutational signature. Furthermore, we sought to perform the investigation based on a potentially clinically relevant setting. To that end, we assessed the mutational profile and genomic instability of 55 patients extracted from the Gynecologic Cancer Database (DGCD) by using a panel comprised of 409 cancer-associated genes and a microsatellite assay, respectively; both are currently used in our routine environment. In accordance with previous findings, ARID1A and PIK3CA were the most prevalent mutations, present in 49.1% and 41.8%, respectively. From those, the co-occurrence of ARID1A and PIK3CA mutations was observed in 36.1% of subjects, indicating that this association might be a common feature of OCCC. The microsatellite instability frequency was low across samples. An unbiased assessment of signatures identified the presence of three subgroups, where “PIK3CA” and “Double hit” (with ARID1A and PIK3CA double mutation) subgroups exhibited unique signatures, whilst “ARID1A” and “Undetermined” (no mutations on ARID1A nor PIK3CA) subgroups showed similar profiles. Those differences were further indicated by COSMIC signatures. Taken together, the current findings suggest that OCCC presents distinct mutational landscapes within its group, which may indicate different therapeutic approaches according to its subgroup. Although encouraging, it is noteworthy that the current results are limited by sample size, and further investigation on a larger group would be crucial to better elucidate them.

Data analysis has become a crucial aspect in clinical oncology to interpret output from next-generation sequencing-based testing. NGS being able to resolve billions of sequencing reactions in a few days has consequently increased the demand for tools to handle and analyze such large data sets. Many tools have been developed since the advent of NGS, featuring their own peculiarities. Increased awareness when interpreting alterations in the genome is therefore of utmost importance, as the same data using different tools can provide diverse outcomes. Hence, it is crucial to evaluate and validate bioinformatic pipelines in clinical settings. Moreover, personalized medicine implies treatment targeting efficacy of biological drugs for specific genomic alterations. Here, we focused on different sequencing technologies, features underlying the genome complexity, and bioinformatic tools that can impact the final annotation. Additionally, we discuss the clinical demand and design for implementing NGS.

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were >1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

Background Ovarian cancer is the fifth most common cancer in women worldwide. Moreover, there are no reliable minimal invasive tests to secure the diagnosis of malignant pelvic masses. Cell-free, circulating microRNAs have the potential as diagnostic biomarkers in cancer. Here, we performed and validated a miRNA panel with the potential to distinguish OC from benign pelvic masses. Methods The profile of plasma microRNA was determined with a panel of 46 candidates in a discovery group and a validation group, each consisting of 190 pre-surgery plasma samples from age-matched patients with malignant (n = 95) and benign pelvic mass (n = 95), by real time RT-qPCR. Results Four up-regulated (miR-200c-3p, miR-221-3p, miR-21-5p, and miR-484) and two down-regulated (miR-195-5p and miR-451a) microRNAs were discovered. From those, miR-200c-3p and miR-221-3p were further confirmed in a validation cohort. A combination of these 2 microRNAs together with CA-125 yielded an overall diagnostic accuracy of AUC = 0.96. Conclusions We showed consistent plasma microRNA profiles that provide independent diagnostic information of late stage OC.

Background/Aim: New markers for ovarian cancer are needed. This study aimed to examine the expression of tumour cell p53 and endothelial cell CD31 proteins and correlate them to clinicopathological factors. Patients and Methods: Expression of proteins was immunohistochemically assessed using tissue sections from 585-599 ovarian cancer patients from the Danish MALOVA study. Results: High CD31 expression was found in poorly differentiated tumours (p=0.0006), and high p53 expression was found in poorly differentiated cancers (p<0.0001), high clinical stage (p<0.0001), non-radical surgery (p<0.0001) and high serum CA-125 values (p<0.0001). CD31 expression showed no prognostic survival value, but high hazard ratios were found for patients with high p53 expression (HR=2.313, p<0.0001). An interaction was found between p53 and stage of cancer, suggesting a prognostic impact of p53 in low-stage, but not in advanced-stage cancer. Conclusion: More than 5% of p53 tissue expression may predict shorter survival of ovarian cancer patients and may be useful for predicting the risk of disease progression in low-stage patients following primary surgery. CD31 has no strong prognostic value.

Ovarian cancer is a silent killer and, due to late diagnosis and frequent chemo resistance in patients, the primary cause of fatality amongst the various types of gynecological cancer. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, thereby saving lives. Biomarkers could also improve treatment, by predicting which patients will benefit from specific treatment strategies. DNA methylation is an epigenetic mechanism, and 'methylation imbalance' is characteristic of cancer. Previous research suggests that changes in DNA methylation can be used diagnostically, and that they may predict resistance to treatment. This paper gives an up-to-date overview of research investigating the potential of DNA methylation-based markers for diagnostics, prognostics, screening and prediction of drug resistance for ovarian cancer patients. DNA methylation cancer-biomarkers may be useful for cancer treatment, particularly since they are chemically stable and since cancer-associated changes in methylation typically precedes tumor growth. DNA methylation markers could improve diagnosis and treatment and might even be used for screening in the future. Furthermore, DNA methylation biomarkers could facilitate the development of precision medicine. However, at this point no biomarkers for ovarian cancer have a sufficient combination of sensitivity and specificity in a clinical setting. A reason for this is that most studies have focused on a single or a few methylation sites. More large screenings and genome-wide studies must be performed to increase the chance of identifying a DNA methylation marker which can identify ovarian cancer.

Annexin A2 is a 36-kDa protein interfering with multiple cellular processes especially in cancer progression. The present review aimed to show the relations between Annexin A2 and cancer. A systematic search for studies investigating cancer and Annexin A2 expression was conducted using PubMed. Acute lymphoblastic leukaemia, acute promyelocytic leukaemia, clear cell renal cell carcinoma, breast, cervical, colorectal, endometrial, gastric cancer, glioblastoma, hepatocellular carcinoma, lung, multiple myeloma, oesophageal squamous cell carcinoma, ovarian cancer, pancreatic duct adenocarcinoma, prostate cancer and urothelial carcinoma were evaluated. Annexin A2 expression correlates with resistance to treatment, binding to the bone marrow, histological grade and type, TNM-stage and shortened overall survival. The regulation of Annexin A2 is of interest due to its potential as target for a more individualized cancer management.

BACKGROUND: Genome-wide association studies (GWAS) have identified 18 loci associated with serous ovarian cancer (SOC) susceptibility but the biological mechanisms driving these findings remain poorly characterised. Germline cancer risk loci may be enriched for target genes of transcription factors (TFs) critical to somatic tumorigenesis.METHODS: All 615 TF-target sets from the Molecular Signatures Database were evaluated using gene set enrichment analysis (GSEA) and three GWAS for SOC risk: discovery (2196 cases/4396 controls), replication (7035 cases/21 693 controls; independent from discovery), and combined (9627 cases/30 845 controls; including additional individuals).RESULTS: The PAX8-target gene set was ranked 1/615 in the discovery (PGSEA<0.001; FDR=0.21), 7/615 in the replication (PGSEA=0.004; FDR=0.37), and 1/615 in the combined (PGSEA<0.001; FDR=0.21) studies. Adding other genes reported to interact with PAX8 in the literature to the PAX8-target set and applying an alternative to GSEA, interval enrichment, further confirmed this association (P=0.006). Fifteen of the 157 genes from this expanded PAX8 pathway were near eight loci associated with SOC risk at P<10(-5) (including six with P<5 × 10(-8)). The pathway was also associated with differential gene expression after shRNA-mediated silencing of PAX8 in HeyA8 (PGSEA=0.025) and IGROV1 (PGSEA=0.004) SOC cells and several PAX8 targets near SOC risk loci demonstrated in vitro transcriptomic perturbation.CONCLUSIONS: Putative PAX8 target genes are enriched for common SOC risk variants. This finding from our agnostic evaluation is of particular interest given that PAX8 is well-established as a specific marker for the cell of origin of SOC.

INTRODUCTION: Robot-assisted surgery has become more widespread in gynecological oncology. The purpose of this systematic review is to present current knowledge on robot-assisted surgery, and to clarify and discuss controversies that have arisen alongside the development and deployment.MATERIAL AND METHODS: A database search in PubMed and EMBASE was performed up until 4 March 2016. The search strategy was developed in collaboration with an information specialist, and by application of the PRISMA guidelines. Human participants and English language were the only restrictive filters applied. Selection was performed by screening of titles and abstracts, and by full text scrutiny. From 2001 to 2016, a total of 76 references were included.RESULTS: Robot-assisted surgery in gynecological oncology has increased, and current knowledge supports that the oncological safety is similar, compared with previous surgical methods. Controversies arise because current knowledge does not clearly document the benefit of robot-assisted surgery, on perioperative outcome compared with the increased costs of the acquisition and application.CONCLUSION: The rapid development in robot-assisted surgery calls for long-term detailed prospective cohorts or randomized controlled trials. The costs associated with acquisition, application, and maintenance have an unfavorable impact on cost-benefit evaluations, especially when compared with laparoscopy. Future developments in robot-assisted surgery will hopefully lead to competition in the market, which will decrease costs.

BACKGROUND: In vitro and observational epidemiological studies suggest that vitamin D may play a role in cancer prevention. However, the relationship between vitamin D and ovarian cancer is uncertain, with observational studies generating conflicting findings. A potential limitation of observational studies is inadequate control of confounding. To overcome this problem, we used Mendelian randomization (MR) to evaluate the association between single nucleotide polymorphisms (SNPs) associated with circulating 25-hydroxyvitamin D [25(OH)D] concentration and risk of ovarian cancer.METHODS: We employed SNPs with well-established associations with 25(OH)D concentration as instrumental variables for MR: rs7944926 (DHCR7), rs12794714 (CYP2R1) and rs2282679 (GC). We included 31 719 women of European ancestry (10 065 cases, 21 654 controls) from the Ovarian Cancer Association Consortium, who were genotyped using customized Illumina Infinium iSelect (iCOGS) arrays. A two-sample (summary data) MR approach was used and analyses were performed separately for all ovarian cancer (10 065 cases) and for high-grade serous ovarian cancer (4121 cases).RESULTS: The odds ratio for epithelial ovarian cancer risk (10 065 cases) estimated by combining the individual SNP associations using inverse variance weighting was 1.27 (95% confidence interval: 1.06 to 1.51) per 20 nmol/L decrease in 25(OH)D concentration. The estimated odds ratio for high-grade serous epithelial ovarian cancer (4121 cases) was 1.54 (1.19, 2.01).CONCLUSIONS: Genetically lowered 25-hydroxyvitamin D concentrations were associated with higher ovarian cancer susceptibility in Europeans. These findings suggest that increasing plasma vitamin D levels may reduce risk of ovarian cancer.

BACKGROUND: The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study.METHODS: We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant.RESULTS: For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10(-5)), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10(-8)) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants.CONCLUSIONS: This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

OBJECTIVE: The aim of this systematic review is to analyze data on risk factors, epidemiology, clinicopathology and molecular biology from studies comparing primary peritoneal cancer, fallopian tube cancer and ovarian cancer of serous histology, in order to achieve a greater understanding of whether or not these disorders should be considered as separate entities.METHODS: A systematic literature search was conducted in PubMed and MEDLINE. Case-control studies comparing primary serous peritoneal or fallopian tube carcinomas with primary serous ovarian carcinomas or a control group were included.RESULTS: Twenty-eight studies were found eligible. Primary peritoneal cancer patients were older, had higher parity, were more often obese and had poorer survival compared to ovarian cancer patients. Differences in protein expression patterns of Her2/neu, estrogen and progestin receptors and frequency of loss of heterozygosity differed between primary peritoneal cancer and primary ovarian cancer patients. No major differences were found between primary fallopian tube cancer and primary ovarian cancer. The proportion of serous tubal intraepithelial carcinomas (STIC) was lower in primary peritoneal cancer and primary ovarian cancer compared to primary fallopian tube cancer.CONCLUSION: Except from differences in the proportion of STIC only few differences between primary fallopian tube cancer and primary ovarian cancer have been found. In contrast, observed differences in risk factor profile, clinicopathologic and prognostic factors, as well as in the molecular patterns, indicate that peritoneal cancer and ovarian cancer may be linked to different carcinogenic pathways.

PURPOSE: The aim of this study was to estimate the contribution of deleterious mutations in the RAD51B, RAD51C, and RAD51D genes to invasive epithelial ovarian cancer (EOC) in the population and in a screening trial of individuals at high risk of ovarian cancer.PATIENTS AND METHODS: The coding sequence and splice site boundaries of the three RAD51 genes were sequenced and analyzed in germline DNA from a case-control study of 3,429 patients with invasive EOC and 2,772 controls as well as in 2,000 unaffected women who were BRCA1/BRCA2 negative from the United Kingdom Familial Ovarian Cancer Screening Study (UK_FOCSS) after quality-control analysis.RESULTS: In the case-control study, we identified predicted deleterious mutations in 28 EOC cases (0.82%) compared with three controls (0.11%; P < .001). Mutations in EOC cases were more frequent in RAD51C (14 occurrences, 0.41%) and RAD51D (12 occurrences, 0.35%) than in RAD51B (two occurrences, 0.06%). RAD51C mutations were associated with an odds ratio of 5.2 (95% CI, 1.1 to 24; P = .035), and RAD51D mutations conferred an odds ratio of 12 (95% CI, 1.5 to 90; P = .019). We identified 13 RAD51 mutations (0.65%) in unaffected UK_FOCSS participants (RAD51C, n = 7; RAD51D, n = 5; and RAD51B, n = 1), which was a significantly greater rate than in controls (P < .001); furthermore, RAD51 mutation carriers were more likely than noncarriers to have a family history of ovarian cancer (P < .001).CONCLUSION: These results confirm that RAD51C and RAD51D are moderate ovarian cancer susceptibility genes and suggest that they confer levels of risk of EOC that may warrant their use alongside BRCA1 and BRCA2 in routine clinical genetic testing.

AIM: To develop and validate a biomarker-based index to optimize referral and diagnosis of patients with suspected ovarian cancer. Furthermore, to compare this new index with the Risk of Malignancy Index (RMI) and Risk of Ovarian Malignancy Algorithm (ROMA).PATIENTS AND METHODS: A training study, consisting of patients with benign ovarian disease (n=809) and ovarian cancer (n=246), was used to develop the Copenhagen Index (CPH-I) utilizing the variables serum HE4, serum CA125 and patient age. Eight international studies provided the validation population; comprising 1060 patients with benign ovarian masses and 550 patients with ovarian cancer.RESULTS: Overall, 2665 patients were included. CPH-I was highly significant in discriminating benign from malignant ovarian disease. At the defined cut-off of 0.070 for CPH-I the sensitivity and specificity were 95.0% and 78.4% respectively in the training cohort and 82.0% and 88.4% in the validation cohort. Comparison of CPH-I, ROMA and RMI demonstrated area-under-curve (AUC) at 0.960, 0.954 and 0.959 respectively in the training study and 0.951, 0.953 and 0.935 respectively in the validation study. Using a sensitivity of 95.0%, the specificities for CPH-I, ROMA and RMI in the training cohort were 78.4%, 71.7% and 81.5% respectively, and in the validation cohort 67.3%, 70.7% and 69.5% respectively.CONCLUSION: All three indices perform well at the clinically relevant sensitivity of 95%, but CPH-I, unlike RMI and ROMA, is independent of ultrasound and menopausal status, and may provide a simple index to optimize referral of women with suspected ovarian cancer.

The primary objective of this study was to analyse Tetranectin (TN) expression in tumour tissues and TN serum concentration in 758 women with epithelial ovarian tumours. The second was to evaluate, whether TN tissue expression levels correlate with clinico-pathological parameters and prognosis of the disease. Using tissue arrays we analysed the expression levels in tissues from 166 women with borderline ovarian tumours (BOTs) and 592 women with ovarian cancer (OC). A panel of three antibodies was used for immunohistochemistry: a polyclonal and two monoclonal antibodies. Serum TN was measured using the polyclonal antibody A-371. Univariate survival analyses stratified for chemotherapy showed that positive tissue TN as demonstrated by the polyclonal antibody indicated a significantly longer overall survival (OS) (p = 0.0001) as well as cancer specific survival (CSS) (p < 0.0001). High serum TN was likewise found to imply longer OS (p < 0.0001) and CSS (p < 0.0001), whereas tissue staining with the two monoclonal antibodies failed to demonstrate any significant correlation with either survival type. Univariate Kaplan-Meier survival analysis performed on all OC cases showed a significantly longer OS (p = 0.0009) and CSS (p = 0.0006) for women with TN positive tumour tissue and in women with high serum TN levels (p < 0.0001 for both). However, in the multivariate Cox regression analysis, only serum TN was found to be an independent prognostic factor for OS (p = 0.01) and not for CSS (p = 0.08). In conclusion, our results predict that a positive TN expression of both tumour tissue and serum points to a more favourable outcome for OC patients.

INTRODUCTION: It is a comparative register study designed for data validation of surgery, pathology and recurrence for endometrial cancer in the Danish Gynaecological Cancer Database (DGCD) in the 2005-2009 period. The main outcomes were completeness of the data registered in the DGCD, agreement concerning data reported and comparability between the DGCD and a definite reference.MATERIAL AND METHODS: DGCD data on women with endometrial cancer or adenomatous hyperplasia supplemented with patient charts for data on recurrence were retrieved and compared with a definite reference (the pathology report and clinical journals).RESULTS: The completeness of data on pathology and surgery reported to the DGCD was 97.3%. The comparability between the DGCG and the definite reference was 94.4%. The agreement for the reported data in the DGCD was 88.3%. For recurrence, the comparability was 94.5% and the agreement was 71.6%. Completeness could not be determined due to the design of the database, where recurrence is composed of optional variables only.CONCLUSION: The data on endometrial cancer registered in the DGCD regarding surgery and pathology are valid and complete, and they provide a solid base for research. Due to the relatively infrequent incidence of recurrences, and the fact that these are rarely entered into the database when they do occur, agreement concerning recurrence is low. Based on this study, the DGCD cannot alone provide information on recurrence that will give a reliable foundation for research.FUNDING: Funding was provided by the Health Research Fund of the Region of Central Jutland and the Department of Gynaecology and Obstetrics, Aarhus University Hospital.TRIAL REGISTRATION: not relevant.