Clinical Studies of Endometrial Cytology and Cervical Methylation Assays in Endometrial Cancer Screening and Fertility-Preservation Evaluation

FIGO 2023 endometrial staging: a leap of faith into the new “prognostic based’ rather than “anatomical based” staging—too fast too furious??

Abstract Background In 2023 FIGO revised the endometrial cancer staging system after 13 years. There is a lacuna of data regarding the performance and practicality of the revised 2023 FIGO staging schema for endometrial cancer from Low Middle-Income Countries (LMIC). Objective To estimate the shift of stage and adjuvant management of endometrial cancer based on the FIGO 2023 system compared to the FIGO 2009 system and assess the predictive potential of the FIGO 2023 system. Material and methods A retrospective study was conducted from 1st January 2017 to 31st December 2022. All patients with endometrial cancer were staged according to the FIGO 2023 and FIGO 2009 staging system. Follow-up of patients was done to determine recurrence. Results A total of 152 patients were included. Aggressive histology was seen in 66 (45%) patients. Eighteen (11%) had subserosal involvement. Substantial LVSI was noted in 23 (15%) of patients. Twenty-four (47%) patients of FIGO 2009 Stage IA and 26 patients (63%) of FIGO 2009 Stage IB were upstaged. Eleven (50%) patients of FIGO 2009 Stage IIIA were down staged to IA3. Overall 23 patients (15%) had a shift of stage. Fifteen out of 152 patients (15%) would have had a possible risk stratification change which would imply 23 patients (15%) would have needed a more radical treatment. Molecular classification was done in 32 patients; however, only 2 patients could afford POLE testing. Kaplan–Meier curves showed significant PFS differences in FIGO 2009 Stage IB and Stage IIIA when restaged according to the FIGO 2023 system. Conclusion The FIGO 2023 endometrial staging is a more robust prognosticator; however, the practicality of molecular classification in LMICs is still a distant dream.

Proteogenomic insights into early-onset endometrioid endometrial carcinoma: predictors for fertility-sparing therapy response

Endometrial carcinoma remains a public health concern with a growing incidence, particularly in younger women. Preserving fertility is a crucial consideration in the management of early-onset endometrioid endometrial carcinoma (EEEC), particularly in patients under 40 who maintain both reproductive desire and capacity. To illuminate the molecular characteristics of EEEC, we undertook a large-scale multi-omics study of 215 patients with endometrial carcinoma, including 81 with EEEC. We reveal an unexpected association between exposome-related mutational signature and EEEC, characterized by specific CTNNB1 and SIGLEC10 hotspot mutations and disruption of downstream pathways. Interestingly, SIGLEC10

Diagnostic accuracy of endometrial sampling tests for detecting endometrial cancer: a systematic review and meta-analysis

Objectives To determine the diagnostic accuracy of different endometrial sampling tests for detecting endometrial carcinoma. Design Systematic review and meta-analysis of studies of diagnostic accuracy. Data sources Cochrane Library, MEDLINE/PubMed, CINAHL, Web of Science and Scopus, from the date of inception of the databases to 18 January 2023. Additionally, the reference lists of included studies and other systematic reviews were thoroughly searched. Eligibility criteria We included published cross‐sectional studies that evaluated any endometrial sampling test (index tests) in women (participants) with clinical suspicion of endometrial carcinoma (target condition) in comparison with histopathology of hysterectomy specimens (reference standard). We excluded case–control and case series studies. No restrictions on language or date of publication were applied. Data extraction and synthesis Two independent reviewers extracted study data and assessed study quality using the revised quality assessment tool for diagnostic accuracy studies (QUADAS-2). We used bivariate diagnostic random-effects meta-analysis and presented the results in a summary receiver operating characteristic curve. We assessed the certainty of evidence as recommended by the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) approach. Results Twelve studies (1607 participants), published between 1986 and 2022, contributed data to the meta-analysis results. Seven studies were judged to be at a low risk of bias in all domains and all studies had low applicability concerns. The most studied index tests were Pipelle and conventional dilation and curettage (D&C). The sensitivity, specificity, positive likelihood ratio and negative likelihood ratio (95% CIs) for Pipelle were 0.774 (0.565 to 0.900), 0.985 (0.927 to 0.997), 97.000 (14.000 to 349.000) and 0.241 (0.101 to 0.442) and for conventional D&C were 0.880 (0.281 to 0.993), 0.984 (0.956 to 0.995), 59.300 (14.200 to 153.000) and 0.194 (0.007 to 0.732), respectively. Conclusion High certainty evidence indicates that endometrial sampling using Pipelle or conventional D&C is accurate in diagnosing endometrial cancer. Studies assessing other endometrial sampling tests were sparse. Trial registration number https://osf.io/h8e9z.

The WID‐EC test for the detection and risk prediction of endometrial cancer

AbstractThe incidence of endometrial cancer is rising. Measures to identify women at risk and to detect endometrial cancer earlier are required to reduce the morbidity triggered by the aggressive treatment required for advanced endometrial cancer. We developed the WID‐EC (Women's cancer risk IDentification‐Endometrial Cancer) test, which is based on DNA methylation at 500 CpG sites, in a discovery set of cervical liquid‐based cytology samples from 1086 women with and without an endometrial cancer (217 cancer cases and 869 healthy controls) with a worse prognosis (grade 3 or ≥stage IB). We validated the WID‐EC test in an independent external validation set of 64 endometrial cancer cases and 225 controls. We further validated the test in 150 healthy women (prospective set) who provided a cervical sample as part of the routine Swedish cervical screening programme, 54 of whom developed endometrial cancer within 3 years of sample collection. The WID‐EC test identified women with endometrial cancer with a receiver operator characteristic area under the curve (AUC) of 0.92 (95% CI: 0.88‐0.97) in the external set and of 0.82 (95% CI: 0.74‐0.89) in the prospective validation set. Using an optimal cutoff, cancer cases were detected with a sensitivity of 86% and a specificity of 90% in the external validation set, and a sensitivity and specificity of 52% and 98% respectively in the prospective validation set. The WID‐EC test can identify women with or at risk of endometrial cancer.

Fluorescence in situ hybridization test for detection of endometrial carcinoma cells by non‐invasive vaginal swab

AbstractEndometrial cancer (EC) is the most common gynaecological malignancy with increasing incidence in developed countries. As gold standard, hysteroscopy confirms only 30% of suspected ECs. The detection of EC cells in the vagina by fluorescence in situ hybridization (FISH) after a smear test could reduce invasive procedures in the future. Using array‐based comparative genome hybridization (aCGH) on 65 endometrial carcinomas, most frequently imbalanced regions of the tumour genome were identified. Bacterial artificial chromosomes were used to generate FISH‐probes homologue to these human regions. The FISH test was hybridized on swabs specimens collected from the vaginal cavity. Samples from six patients without EC were selected as a negative control and on 13 patients with known EC as a positive control. To distinguish between benign and EC cases, the cut‐off value has been defined. A first validation of this EC‐FISH Test was performed with swabs from 41 patients with suspected EC. The most common genomic imbalances in EC are around the CTNNB1, FBXW7 and APC genes. The cut‐off is defined at 32% of analysed cells without diploid signal pattern. This differs significantly between the positive and negative controls (p < 0.001). In a first validation cohort of 41 patients with suspected EC, the EC‐FISH Test distinguishes patients with and without EC with a sensitivity of 91% and a specificity of 83%. The negative predictive value is 96%. This is the first report of a non‐invasive EC‐FISH Test to predict EC in women with suspected EC.

Potential serum metabolites and long‐chain noncoding RNA biomarkers for endometrial cancer tissue

AbstractBackgroundEndometrial carcinoma (EC) is one of the most common tumors in the female reproductive system. There are nearly 200 000 new cases every year. It is the third most common gynecological malignant tumor leading to female death. The incidence rate is closely related to lifestyle, and the incidence rate varies in different regions. The incidence rate of EC is ranking the first in the female reproductive system cancer just second only to breast, lung, and colorectal cancer in North America and Europe and the incidence rate of EC is only second, followed by breast cancer and cervical cancer in China.PurposeThe potential metabolic markers of endometrial cancer were screened by liquid chromatograph mass spectrometer (LC‐MS), and the tissues of patients with hysteromyoma and endometrial cancer were sequenced to explore the relationship between the disease and change in the content of long‐chain noncoding RNA (lncRNA).MethodsSerum and tissue samples were collected from patients with endometrial dysplasia, endometrial cancer stage I, and endometrial cancer stage III. The metabolites in all serum samples were extracted, and the metabolites in all samples were detected by LC–MS/MS technology. The Pareto‐scaling method was used for normalization, and the MetaboAnalyst 4.0 software was used for different analyses. The T test between groups showed that p ≤ 0.05 was regarded as the metabolite with a difference. Further, the function of differential metabolites was determined by metabolite function enrichment and co‐expression analysis. Meanwhile, the differentially expressed lncRNA was detected by Illumina second‐generation high‐throughput sequencing technology, and the expression was analyzed by DEGseq software. Different lncRNA were screened according to p < 0.05. LncRNA with significant differences were screened by p < 0.01, q < 0.001, fold change ≥2, and false discovery rate (FDR) ≤0.001.ResultsThrough synthesis of T test, cluster heatmap, and ROC curve analysis, five biomarkers with potential diagnostic ability were obtained, including 2,3‐Pyridinedicarboxylic acid (area under the curve (AUC) = 0.69), Hematommic acid, ethyl ester (AUC = 0.69), Maltitol (AUC = 0.69), 13(S)‐HODE (AUC = 0.88), and D‐Mannitol (AUC = 0.69) had potential diagnostic ability between EC phase I versus EC phase III. At the same time, lncRNA sequencing results showed that when endometrial atypical hyperplasia continued to change, including LINC00511, PVT1, and IQCH‐AS1 (downregulated), and only changed significantly in the endometrial dysplasia group, including MALAT1, CARMN (downregulated) and LINC00648, BISPR, LINC01534, and LINC00930 (upregulated). Moreover, both differential metabolites and differential lncRNA were annotated to the lipid metabolism pathway, suggesting that this pathway played an important role in the occurrence and development of endometrial carcinoma.ConclusionsIt can combine the results of metabolomics and lncRNA sequencing to assist in the early diagnosis of endometrial precancerous lesions and endometrial cancer patients, to enhance the sensitivity and specificity of diagnosis, which has a certain clinical application prospect.

A Simple Cervicovaginal Epigenetic Test for Screening and Rapid Triage of Women With Suspected Endometrial Cancer: Validation in Several Cohort and Case/Control Sets

PURPOSE Endometrial cancer (EC) incidence has been rising over the past 10 years. Delays in diagnosis reduce survival and necessitate more aggressive treatment. We aimed to develop and validate a simple, noninvasive, and reliable triage test for EC to reduce the number of invasive diagnostic procedures and improve patient survival. METHODS We developed a test to screen and triage women with suspected EC using 726 cervical smear samples from women with and without EC, and validated the test in 562 cervicovaginal samples using three different collection methods (cervical smear: n = 248; vaginal swab: n = 63; and self-collection: n = 251) and four different settings (case/control: n = 388; cohort of women presenting with postmenopausal bleeding: n = 63; a cohort of high-risk women with Lynch syndrome: n = 25; and a nested case/control setting from a screening cohort and samples taken up to 3 years before EC diagnosis: n = 86). RESULTS We describe the Women's cancer risk IDentification – quantitative polymerase chain reaction test for Endometrial Cancer (WID-qEC), a three-marker test that evaluates DNA methylation in gene regions of GYPC and ZSCAN12. In cervical, self-collected, and vaginal swab samples derived from symptomatic patients, it detected EC with sensitivities of 97.2% (95% CI, 90.2 to 99.7), 90.1% (83.6 to 94.6), and 100% (63.1 to 100), respectively, and specificities of 75.8% (63.6 to 85.5), 86.7% (79.3 to 92.2), and 89.1% (77.8 to 95.9), respectively. The WID-qEC identified 90.9% (95% CI, 70.8 to 98.9) of EC cases in samples predating diagnosis up to 1 year. Test performance was similar across menopausal status, age, stage, grade, ethnicity, and histology. CONCLUSION The WID-qEC is a noninvasive reliable test for triage of women with symptoms suggestive of ECs. Because of the potential for self-collection, it could improve early diagnosis and reduce the reliance for in-person visits.

MicroRNA expression profile in serum reveals novel diagnostic biomarkers for endometrial cancer

AbstractPurpose: Circulating microRNAs (miRNAs) prove to be promising diagnostic biomarkers for various cancers, including endometrial cancer (EC). The present study aims to identify serum microRNAs that can serve as potential biomarkers for EC diagnosis.Patients and methods: A total of 92 EC and 102 normal control (NC) serum samples were analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) in this four-phase experiment. The logistic regression method was used to construct a diagnostic model based on the differentially expressed miRNAs in serum. The receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value. To further validate the diagnostic capacity of the identified signature, the 6-miRNA marker was compared with previously reported biomarkers and verified in three public datasets. In addition, the expression characteristics of the identified miRNAs were further explored in tissue and serum exosomes samples.Results: Six miRNAs (miR-143-3p, miR-195-5p, miR-20b-5p, miR-204-5p, miR-423-3p, and miR-484) were significantly overexpressed in the serum of EC compared with NCs. Areas under the ROC of the 6-miRNA signatures were 0.748, 0.833, and 0.967 for the training, testing, and the external validation phases, respectively. The identified signature has a very stable diagnostic performance in the large cohorts of three public datasets. Compared with previously identified miRNA biomarkers, the 6-miRNA signature in the present study has superior performance in diagnosing EC. Moreover, the expression of miR-143-3p and miR-195-5p in tissues and the expression of miR-20b-5p in serum exosomes were consistent with those in serum.Conclusions: We established a 6-miRNA signature in serum and they could function as potential non-invasive biomarker for EC diagnosis.

Ashraf Fawzy Nabhan

Professor of Obstetrics and Gynecology at Ain Shams University, Egypt with a special interest in high-risk pregnancy, postpartum hemorrhage, and preterm birth. Chairman of the National Guidelines Committee, Egyptian Health Council. Member of the guideline development group at the Department of Reproductive Health and Research, World Health Organization. Contributing to Knowledge Translation by authoring Cochrane Clinical Answers. Director of the Egyptian Center for Evidence Based medicine leading a team of enthusiastic research follows to conduct continuous training to strengthen research capacity, to develop and disseminate systematic reviews, to develop evidence-based clinical practice guidelines, and to support evidence-informed policy making. Senior Editorial Board Member of BMC Pregnancy and Childbirth.

Beatriz Pelegrina

Chao Wang

Chaoyang Sun

Chiara Herzog

David Cibula

Ding Ma

Emma J Crosbie

Fátima Marin

Gang Chen

Gordon B. Mills

Jiangrong Wang

Joakim Dillner

Joan Brunet

Jordi Ponce

Jörg Weimer

Junpeng Fan

Karin Sundström

Kezhen Li

Laura Costas

Lena Schreiberhuber

Line Bjørge

Lukas Dostalek

Álvaro Carmona

Álvaro Carmona Pestaña es Licenciado en Bioquímica (Universidad de Sevilla, 2008-2013), con un Máster en Neurociencias (Universidad Autónoma de Barcelona, ​​2013-2014), Máster en Investigación Médica Clínica y Experimental (Universidad de Sevilla, 2015-2016) y un Máster en Educación especializado en Biología y Geología (UCAM, 2020-2021). Obtuvo una beca internacional de doctorado en la Universidad de Roma, La Sapienza (2016-2020), donde su tesis abordó las modificaciones epigenéticas y los modificadores de histonas en la señalización Notch y la proliferación de células tumorales en leucemia linfoblástica aguda de células T (T-ALL). Posee experiencia en técnicas avanzadas de biología molecular y celular, como rtPCR, qPCR, inmunoprecipitación de cromatina y secuenciación de nueva generación. Ha trabajado en proyectos de investigación traslacional en oncología, incluyendo el desarrollo de nuevas moléculas con actividad antiproliferativa en colaboración con instituciones como el CSIC (Madrid), la Universidad de Milán y la Universidad de Siena. Posteriormente, fue investigador postdoctoral en el Institut Català d'Oncología (ICO-IDIBELL), donde lideró el ensayo clínico SCREENWIDE, enfocado en el diagnóstico molecular no invasivo de cáncer ginecológico. En este rol, gestionó la captación de pacientes, bases de datos y análisis bioinformático de biomarcadores genéticos. En el ámbito académico, ha desempeñado roles de coordinación e innovación docente. Actualmente es Coordinador Académico del Grado en Enfermería en la Universidad Loyola Andalucía, tras haber ocupado un puesto similar en la Universidad Alfonso X el Sabio, donde lideró estrategias de enseñanza con inteligencia artificial y simulación clínica. Su enfoque en innovación educativa le valió el Premio Carmen Domínguez Alcón por integrar el arte y la medicina en la enseñanza de la enfermería a través de obras del Museo del Prado. Ha dirigido numerosos Trabajos de Fin de Grado y Máster en oncología y salud digital, y ha participado en la evaluación de proyectos científicos. En investigación, su producción incluye publicaciones en revistas de alto impacto como Clinical Cancer Research, The Lancet - eBiomedicine y Journal of Clinical Oncology, con estudios sobre epigenética, cáncer y desinformación médica en redes sociales. También ha desarrollado estudios sobre el impacto de la inteligencia artificial en enfermería y alfabetización en salud. Como divulgador científico, ha participado en eventos como Naukas, Desgranando Ciencia y la Feria de la Ciencia de Jerez, además de colaborar en el programa No es un día cualquiera de RNE. Su trabajo en transferencia de conocimiento ha generado un impacto tangible en la educación, la biomedicina y la comunicación científica, consolidándolo como un referente en la intersección entre ciencia, docencia e innovación digital.

Marta Pineda

Martin Widschwendter

Prof Martin Widschwendter is Professor for Cancer Prevention and Screening and Director of the European Translational Oncology Prevention and Screening (EUTOPS) Institute, Leopold-Franzens-University of Innsbruck, Austria. Prof Widschwendter also holds the positions of Professor in Women’s Cancer at University College London (UCL), UK, (where he was the Head of Department of Women’s Cancer, UCL EGA Institute for Women's Health for almost 10 years until March 2020), Consultant Gynaecological Oncologist, LKH Hall in Tirol, Austria, Guest Professor at the Department of Women’s and Children’s Health, Karolinska Institutet, Sweden and FRCOG (Fellows ad eundem) of the Royal College of Obstetricians and Gynaecologists (RCOG), London, UK. In 2001, having completed his training in Gynaecology and Obstetrics in Austria, Prof Widschwendter worked at the Norris Comprehensive Cancer Centre in Los Angeles (USA) on translational epigenetics (Prof Peter A Jones group) and spent three years as the lead clinician and surgeon of a large breast cancer centre before embarking on a career at UCL/UCLH from 2005 where he undertook sub-speciality training in gynaecological oncology. As the Head of Department of Women’s Cancer within the UCL EGA Institute for Women’s Health, he established a research group focusing on the role of early detection, risk prediction, and prevention of breast and gynaecological cancers within several major research programmes (EpiFemCare, FORECEE, BRCA PROTECT and BRCA PREVENT). In 2016, Martin was awarded a Fellowship ad eundem of the Royal Academy of Obstetrics and Gynaecology (FRCOG) and since March 2020, he has been Professor for Cancer Prevention and Screening, as well as the Director of the European Translational Oncology Prevention & Screening (EUTOPS) Institute at the Leopold-Franzens-University of Innsbruck, Austria. In July 2020, Martin was conferred a Guest Professorship at the Karolinska Institutet, Stockholm, Sweden. Prof Widschwendter was the PI and Coordinator of several EU projects including the 7th Framework Programme (FP7), Horizon 2020 (H2020), and was also awarded a European Research Council (ERC) Advanced Grant. He is an author on more than 215 papers in high impact journals, has contributed to numerous textbooks, secured substantial grant income in the last 10 years, lectured widely on his research and clinical experience in the UK and abroad and is an Editor for the International Journal of Gynecological Cancer.

Michael Wong

Consultant Obstetrician & Gynaecologist

Michal Zikan

Paula Peremiquel-Trillas

Qinglei Gao

Sonia Paytubi

Wei Zhu

Wenju Peng

Xiaojun Chen

YanQiu Li

Zhe Hu