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Women diagnosed with non-mucinous high-grade epithelial ovarian cancer (EOC) in England are often reflex-tested for germline and tumour BRCA1/2 variants. The value of germline BRCA1/2 testing in women diagnosed aged ≥80 is questionable. We performed an observational study of all women diagnosed with non-mucinous high-grade EOC who underwent germline and tumour BRCA1/2 testing by the North West of England Genomic Laboratory Hub. A subgroup of women also underwent germline testing using a panel of homologous recombination repair (HRR) genes and/or tumour testing for homologous recombination deficiency (HRD) using Myriad’s myChoice® companion diagnostic. Seven-hundred-two patients successfully underwent both germline and tumour BRCA1/2 testing. Of these, 48 were diagnosed with non-mucinous high-grade EOC aged ≥80. In this age group, somatic BRCA1/2 pathogenic/likely pathogenic variants (PV/LPVs) were detected nine times more often than germline BRCA1/2 PV/LPVs. The only germline PV reported in a patient aged ≥80 was detected in germline and tumour DNA (BRCA2 c.4478_4481del). No patient aged ≥80 had a germline PV/LPVs in a non-BRCA1/2 HRR gene. Thirty-eight percent of patients aged ≥80 had a tumour positive for HRD. Our data suggest that tumour BRCA1/2 and HRD testing is adequate for patients diagnosed with non-mucinous high-grade EOC aged ≥80, with germline BRCA1/2 testing reserved for women with a tumour BRCA1/2 PV/LPVs.

Simple Summary Endometrial cancer is the most common gynaecological cancer in high-income countries. Most women are diagnosed early and have an excellent prognosis, but those with advanced or recurrent disease have poor outcomes. The aim of this study was to determine whether clinical or biochemical thyroid dysfunction may contribute to survival outcomes following diagnosis and treatment for endometrial cancer. We analysed clinical data and serum thyroid hormone status of 333 women treated for endometrial cancer at a specialist cancer centre and followed up for a median of 35 months. Women with a diagnosis of hypothyroidism had improved overall, cancer-specific, and recurrence-free survival compared to those without. This may have important implications for our understanding of the mechanisms underpinning biologically aggressive disease and offer opportunities for therapeutic intervention. Abstract Endometrial cancer is the commonest gynaecological malignancy in developed countries, and women presenting with high risk or advanced disease have poor outcomes. Thyroid hormones play a key role in cellular metabolism and can influence cancer growth and invasion. Our aim was to evaluate the association between clinical and biochemical thyroid dysfunction and endometrial cancer survival outcomes. This was a prospective cohort study of women treated for endometrial cancer at a specialist centre. Clinical diagnosis of hypothyroidism was based on clinical and biochemical assessment, verified by general practitioner (GP) records. Pre-treatment serum samples were tested for thyrotropin (TSH), thyroid hormones (free T4 and total T3), and thyroid peroxidase antibodies. Kaplan–Meier survival estimates and log-rank tests were used to compare survival between groups, while Cox regression was used for multivariable analysis, adjusting for known confounders and effect modifications. In total, 333 women with median age and body mass index (BMI) of 66 years (interquartile range (IQR) 56, 73) and 33 kg/m2 (IQR 27, 41) respectively were included. A total of 51 (15.3%) women had a diagnosis of hypothyroidism, 39 (11.9%) had biochemical evidence of overt or subclinical hypothyroidism. Median follow-up was 35 months (IQR 21, 45) with 38 (11.7%) relapses and 50 (15.0%) deaths. Women with a diagnosis of hypothyroidism had improved overall survival (adjusted HR = 0.22, 95%CI 0.06–0.74, p = 0.02), cancer-specific survival (adjusted HR = 0.21, 95%CI 0.05–0.98, p = 0.04) and fewer recurrences (adjusted HR = 0.17, 95%CI 0.04–0.77, p = 0.02) than those who did not. Confirmatory studies should explore underlying mechanisms and the potential for therapeutic exploitation.

CA125 is widely used as an initial investigation in women presenting with symptoms of possible ovarian cancer. We sought to develop CA125-based diagnostic prediction models and to explore potential implications of implementing model-based thresholds for further investigation in primary care. This retrospective cohort study used routinely collected primary care and cancer registry data from symptomatic, CA125-tested women in England (2011–2014). A total of 29,962 women were included, of whom 279 were diagnosed with ovarian cancer. Logistic regression was used to develop two models to estimate ovarian cancer probability: Model 1 consisted of age and CA125 level, Model 2 incorporated further risk factors. Model discrimination (AUC) was evaluated using 10-fold cross-validation. The sensitivity and specificity of various model risk thresholds (≥1% to ≥3%) were compared with that of the current CA125 cut-off (≥35 U/mL). Model 1 exhibited excellent discrimination (AUC: 0.94) on cross-validation. The inclusion of additional variables (Model 2) did not improve performance. At a risk threshold of ≥1%, Model 1 exhibited greater sensitivity (86.4% vs. 78.5%) but lower specificity (89.1% vs. 94.5%) than CA125 (≥35 U/mL). Applying the ≥1% model threshold to the cohort in place of the current CA125 cut-off, 1 in every 74 additional women identified had ovarian cancer. Following external validation, Model 1 could be used as part of a ‘risk-based triage’ system in which women at high risk of undiagnosed ovarian cancer are selected for urgent specialist investigation, while women at ‘low risk but not no risk’ are offered non-urgent investigation or interval CA125 re-testing. Such an approach has the potential to expedite ovarian cancer diagnosis, but further research is needed to evaluate the clinical impact and health–economic implications.

A simple, noninvasive and accurate detection tool that can triage women with suspected endometrial cancer for definitive testing will transform patient care. The aim of this study was to evaluate urine CA125 and HE4 levels for the detection of endometrial cancer in symptomatic women. This was a cross-sectional diagnostic accuracy study of 153 symptomatic women who underwent urgent diagnostic investigations for suspected endometrial cancer at a large gynecological cancer center. Urine samples were collected prior to routine clinical procedures. Urine CA125 and HE4 levels were determined using automated chemiluminescent enzyme immunoassays. Univariate and multivariable receiver operating characteristic (ROC) curve analyses were performed. Urine CA125 and HE4 were discovered to be significantly elevated in women with endometrial cancer, compared to controls (p < 0.001 and p = 0.01, respectively). Urine CA125 and HE4 detected endometrial cancer with an area under the ROC curve (AUC) of 0.89 (0.81, 0.98) and 0.69 (0.55, 0.83), respectively. CA125 exhibited good discriminatory potential for Type I and early-stage tumors (AUC 0.93 and 0.90, respectively). A diagnostic model that combined urine CA125 and transvaginal ultrasound-measured endometrial thickness predicted endometrial cancer with an AUC of 0.96 (0.91, 1.00). Urine CA125 displays potential as a diagnostic tool for symptomatic women with suspected endometrial cancer. When combined with transvaginal ultrasound-measured endometrial thickness, this patient-friendly, urine-based test could help triage women for invasive diagnostics or safe reassurance, reducing costs and improving patient experience.

HER2 status has not been investigated in the context of the molecular endometrial cancer (EC) classification. Here, we aimed to determine the clinicopathological features and prognostic significance of the HER2 status in the molecularly classified PORTEC-3 trial population of patients with high-risk EC (HREC). HER2 testing was performed on tumor tissues of 407 molecularly classified HREC. HER2 status was determined by HER2 immunohistochemistry (IHC, all cases) and subsequent HER2 dual in situ hybridization for cases with any (in) complete moderate to strong membranous HER2 IHC expression. The &Chi, 2 test and Spearman&rsquo, s Rho correlation coefficient were used to compare clinicopathological and molecular features. The Kaplan&ndash, Meier method, log-rank test, and Cox proportional hazards models were used for survival analysis. We identified 24 (5.9%) HER2-positive EC of various histological subtypes including serous (n = 9, 37.5%), endometrioid (n = 6, 25.0%), and clear cell (n = 5, 20.8%). HER2 positivity was highly associated with the p53-abnormal subgroup (p53abn, 23/24 cases, p &lt, 0.0001). The correlation between p53abn and the HER2 status (&rho, = 0.438, 0.0001) was significantly stronger (p &lt, 0.0001) than between serous histology and the HER2 status (&rho, = 0.154, p = 0.002). HER2 status did not have independent prognostic value for survival after correction for the molecular classification. Our study strongly suggests that molecular subclass-directed HER2 testing is superior to histotype-directed testing. This insight will be relevant for future trials targeting HER2.

Human epididymis 4 (HE4) is a promising ovarian cancer biomarker, but it has not been evaluated in primary care. In this prospective observational study, we investigated the diagnostic accuracy of HE4 alone and in combination with CA125 for the detection of ovarian cancer in symptomatic women attending primary care. General practitioner (GP)-requested CA125 samples were tested for HE4 at a large teaching hospital in Manchester, and cancer outcomes were tracked for 12 months. We found a low incidence of ovarian cancer in primary care; thus, the cohort was enriched with pre-surgical samples from 81 ovarian cancer patients. The Risk of Ovarian Malignancy Algorithm (ROMA) was calculated using age (51) as a surrogate for menopause. Conventional diagnostic accuracy metrics were determined. A total of 1229 patients were included; 82 had ovarian cancer. Overall, ROMA performed best (AUC-0.96 (95%CI: 0.94-0.98, p =, Lumipulse®G HE4 immunoassay kits were generously donated by Fujirebio for use in this re-search. Fujirebio played no other role in the conduct of this study, analysis of the data or the deci-sion to publish. CEB was supported through an MFT Clinical Research Fellowship and EJC through the NIHR Manchester Biomedical Research Centre (IS-BRC-1215-20007). This work was supported by Wellbeing of Women (Award Reference ELS701) (GF, EJC). DJ was supported by Wellbeing of Women (Award Reference RTF707).

Endometrial cancer is the most common malignancy of the female genital tract and a major cause of morbidity and mortality in women. Early detection is key to ensuring good outcomes but a lack of minimally invasive screening tools is a significant barrier. Most endometrial cancers are obesity-driven and develop in the context of severe metabolomic dysfunction. Blood-derived metabolites may therefore provide clinically relevant biomarkers for endometrial cancer detection. In this study, we analysed plasma samples of women with body mass index (BMI) ≥30kg/m2 and endometrioid endometrial cancer (cases, n = 67) or histologically normal endometrium (controls, n = 69), using a mass spectrometry-based metabolomics approach. Eighty percent of the samples were randomly selected to serve as a training set and the remaining 20% were used to qualify test performance. Robust predictive models (AUC &gt, 0.9) for endometrial cancer detection based on artificial intelligence algorithms were developed and validated. Phospholipids were of significance as biomarkers of endometrial cancer, with sphingolipids (sphingomyelins) discriminatory in post-menopausal women. An algorithm combining the top ten performing metabolites showed 92.6% prediction accuracy (AUC of 0.95) for endometrial cancer detection. These results suggest that a simple blood test could enable the early detection of endometrial cancer and provide the basis for a minimally invasive screening tool for women with a BMI ≥ 30 kg/m2.

Endometrial cancer is the leading gynaecological malignancy in the western world and its incidence is rising in tandem with the global epidemic of obesity. Early diagnosis is key to improving survival, which at 5 years is less than 20% in advanced disease and over 90% in early-stage disease. As yet, there are no validated biological markers for its early detection. Advances in high-throughput technologies and machine learning techniques now offer unique and promising perspectives for biomarker discovery, especially through the integration of genomic, transcriptomic, proteomic, metabolomic and imaging data. Because the proteome closely mirrors the dynamic state of cells, tissues and organisms, proteomics has great potential to deliver clinically relevant biomarkers for cancer diagnosis. In this review, we present the current progress in endometrial cancer diagnostic biomarker discovery using proteomics. We describe the various mass spectrometry-based approaches and highlight the challenges inherent in biomarker discovery studies. We suggest novel strategies for endometrial cancer detection exploiting biologically important protein biomarkers and set the scene for future directions in endometrial cancer biomarker research.