Molecular Classification in Relation to Prevention of Endometrial Cancer Recurrence and Lifestyle Factors

Molecular testing for endometrial cancer: An SGO clinical practice statement

The Cancer Genome Atlas publication first described the genomic landscape of endometrial cancer and characterized these cancers into four molecular subtypes with different prognoses. The Proactive Molecular Classifier for Endometrial Cancer was developed to more easily and inexpensively classify endometrial cancers into four similar molecular subtypes which are termed POLE, mismatch repair deficient, p53 abnormal and no specific molecular profile. Beyond these four subtypes, other molecular biomarkers may influence clinical behavior and response to targeted therapies and include beta-catenin, Her2 amplification, PI3K/mTOR/AKT alterations, L1CAM, hormone receptor expression, tumor mutational burden, and ARID1A. There are numerous clinical trials exploring treatment escalation and de-escalation within the four molecular subtypes as well as matching targeted therapies to specific mutational or biomarker profiles. All endometrial cancers should undergo basic molecular classification that includes assessment of mismatch repair status. POLE and p53 status are prognostic and may become actionable in the future. Clinicians who treat patients with endometrial cancer should understand the role of molecular classification in guiding treatment. The goal of this practice statement is to guide appropriate testing, interpretation, and application of molecular information in endometrial cancer.

Whole-exome sequencing of epithelial ovarian carcinomas differing in resistance to platinum therapy

Epithelial ovarian carcinoma (EOC) is highly fatal because of the risk of resistance to therapy and recurrence. We performed whole-exome sequencing of blood and tumor tissue pairs of 50 patients with surgically resected EOC. Compared with sensitive patients, platinum-resistant patients had a significantly higher somatic mutational rate inTP53and lower in several genes from the Hippo pathway. We confirmed the pivotal role of somatic mutations in homologous recombination repair genes in platinum sensitivity and favorable prognosis of EOC patients. Implementing the germline homologous recombination repair profile significantly improved the prediction. In addition, distinct mutational signatures, for example, SBS6, and overall mutational load, somatic mutations inPABPC1,PABPC3, andTFAMco-segregated with the resistance status, high-grade serous carcinoma subtype, or overall survival of patients. We generated germline and somatic genetic landscapes of prognostically different subgroups of EOC patients for further follow-up studies focused on utilizing the observed associations in precision oncology.

Molecular classification in endometrial cancer: Opportunities for precision oncology in a changing landscape

Lay summary Endometrial carcinoma (EC) classification and risk stratification have undergone a global transformation in the last decade, shifting from a reliance on poorly reproducible histomorphological parameters such as grade and histotype, toward a molecular classification that is consistent and biologically informative. Molecular classification enables reliable categorization of ECs, provides prognostic information, and is now beginning to drive clinical management, including surgery and adjuvant therapy. Within this framework, we now have the ability to further refine both the prognostic and predictive value of molecular classification. As we move toward the routine implementation of this classification system as a stratification tool for research, clinical trials, and patient care, it is imperative that access to these tests be equitable. Furthermore, continued education will be critical for patients and providers to understand the value that this molecular information provides.

Lymphadenectomy, obesity and open surgery are associated with surgical complications in endometrial cancer

To investigate surgical complications related to the staging procedure for endometrial cancer (EC) and to explore complication associations towards patient characteristics and survival. A population-based cohort study of women diagnosed with EC where primary surgery was performed at a tertiary centre between 2012 and 2016. The Swedish Quality Registry for Gynecological Cancer was used for identification, medical records reviewed and surgical outcomes, including complications according to Clavien-Dindo (CD), and comorbidity (Charlson's index) registered. Uni- and multivariable logistic regression analyses were performed with complications as outcome and multivariable Cox regression analysis with overall survival (OS) as endpoint. In total 549 women were identified where 108 (19.7%) had CD grade II-V complications. In the multivariable regression analysis; surgical technique, BMI and lymph node dissection, but not comorbidity or age, were found to be risk factors for complications CD grade II-V, with OR of 0.32 (95%CI:0.18-0.56) for minimalinvasive surgery (MIS) compared to open, OR 2.18 (95%CI:1.37-3.49) for BMI ≥30 and OR 2.63 (95%CI:1.32-5.31) for pelvic and paraaortic lymphnode dissection. In Cox regression analysis, a significant lower OS was found within the first 1.5 years for the cohort of complications (CD II-V) compared to no complications. Surgical staging with lymphadenectomy was found a risk factor for complications together with high BMI in EC. Using MIS was significantly associated with less complications. Overall survival was found to be negatively affected within the first years after complications. Our results may be taken into consideration when performing updated treatment guidelines including surgical staging.

Variations in incidence and mortality rates of endometrial cancer at the global, regional, and national levels, 1990–2019

Endometrial cancer (EC) is a commonly diagnosed cancer in women. A comprehensive knowledge of its epidemiological features is essential for understanding the disease burden and guiding prevention strategies. We retrieved the incidence and mortality data of EC from the Global Burden of Disease database. Estimated average percentage change (EAPC) was used to quantify the trends of the age-standardized incidence and mortality rates (ASIR and ASMR, respectively) of EC from 1990 to 2019. Globally, the ASIR of EC significantly increased by 0.69% (95% confidence interval [CI] 0.57-0.81%) per year between 1990 and 2019. This increasing trend was also observed in 160 countries or territories, regardless of the sociodemographic status. The most pronounced increase was found in Italy (EAPC = 4.81, 95% CI, 4.10-5.53), followed by Saudi Arabia and Singapore. Between 1990 and 2019, the ASMR of EC decreased significantly worldwide (EAPC = -0.85, 95% CI, -0.93 to -0.76) but increased significantly in 91 countries or territories, with the highest increase in Lesotho (EAPC = 3.27, 95% CI, 2.81-3.74). The ASMR-ASIR ratio of EC was higher in developing countries than in developed countries. This ratio showed a decreasing trend at the national level over the past three decades. EC incidence has ubiquitously increased worldwide. EC mortality has decreased at the global level but increased in many countries. More efforts are required to alleviate the disease burden of EC.

Molecular Classification of the PORTEC-3 Trial for High-Risk Endometrial Cancer: Impact on Prognosis and Benefit From Adjuvant Therapy

PURPOSE The randomized Adjuvant Chemoradiotherapy Versus Radiotherapy Alone in Women With High-Risk Endometrial Cancer (PORTEC-3) trial investigated the benefit of combined adjuvant chemotherapy and radiotherapy (CTRT) versus radiotherapy alone (RT) for women with high-risk endometrial cancer (EC). Because The Cancer Genome Atlas defined an EC molecular classification with strong prognostic value, we investigated prognosis and impact of chemotherapy for each molecular subgroup using tissue samples from PORTEC-3 trial participants. METHODS Paraffin-embedded tissues of 423 consenting patients were collected. Immunohistochemistry for p53 and mismatch repair (MMR) proteins, and DNA sequencing for POLE exonuclease domain were done to classify tumors as p53 abnormal (p53abn), POLE-ultramutated ( POLEmut), MMR-deficient (MMRd), or no specific molecular profile (NSMP). The primary end point was recurrence-free survival (RFS). Kaplan-Meier method, log-rank test, and Cox model were used for analysis. RESULTS Molecular analysis was successful in 410 high-risk EC (97%), identifying the 4 subgroups: p53abn EC (n = 93; 23%), POLEmut (n = 51; 12%), MMRd (n = 137; 33%), and NSMP (n = 129; 32%). Five-year RFS was 48% for patients with p53abn EC, 98% for POLEmut EC, 72% for MMRd EC, and 74% for NSMP EC ( P < .001). The 5-year RFS with CTRT versus RT for p53abn EC was 59% versus 36% ( P = .019); 100% versus 97% for patients with POLEmut EC ( P = .637); 68% versus 76% ( P = .428) for MMRd EC; and 80% versus 68% ( P = .243) for NSMP EC. CONCLUSION Molecular classification has strong prognostic value in high-risk EC, with significantly improved RFS with adjuvant CTRT for p53abn tumors, regardless of histologic type. Patients with POLEmut EC had an excellent RFS in both trial arms. EC molecular classification should be incorporated in the risk stratification of these patients as well as in future trials to target specific subgroups of patients.

Endometrial cancer

Endometrial cancer is the most common gynaecological cancer in high income countries and its incidence is rising globally. Although an ageing population and fewer benign hysterectomies have contributed to this trend, the growing prevalence of obesity is the major underlying cause. Obesity poses challenges for diagnosis and treatment and more research is needed to offer primary prevention to high-risk women and to optimise endometrial cancer survivorship. Early presentation with postmenopausal bleeding ensures most endometrial cancers are cured by hysterectomy but those with advanced disease have a poor prognosis. Minimally invasive surgical staging and sentinel-lymph-node biopsy provides a low morbidity alternative to historical surgical management without compromising oncological outcomes. Adjuvant radiotherapy reduces loco-regional recurrence in intermediate-risk and high-risk cases. Advances in our understanding of the molecular biology of endometrial cancer have paved the way for targeted chemotherapeutic strategies, and clinical trials will establish their benefit in adjuvant, advanced, and recurrent disease settings in the coming years.

Molecular Monitoring in Endometrial Cancer—Ready for Prime Time?

Summary Efforts are under way to define the role of minimally invasive strategies for molecular monitoring and risk stratification in endometrial cancer. A recent publication aims to define the association between circulating tumor DNA level and disease stage in patients with newly diagnosed endometrial cancer and determine whether sequencing of longitudinal cell-free DNA samples can be used for disease monitoring and detection of progression or recurrence. These results accelerate the current knowledge of molecular follow-up in endometrial cancer. See related article by Ashley et al., p. 410

Endometrial Cancer

High-Sensitivity Mutation Analysis of Cell-Free DNA for Disease Monitoring in Endometrial Cancer

Abstract Purpose: We sought to determine whether sequencing analysis of circulating cell-free DNA (cfDNA) in patients with prospectively accrued endometrial cancer captures the mutational repertoire of the primary lesion and allows for disease monitoring. Experimental Design: Peripheral blood was prospectively collected from 44 newly diagnosed patients with endometrial cancer over a 24-month period (i.e., baseline, postsurgery, every 6 months after). DNA from the primary endometrial cancers was subjected to targeted next-generation sequencing (NGS) of 468 cancer-related genes, and cfDNA to a high-depth NGS assay of 129 genes with molecular barcoding. Sequencing data were analyzed using validated bioinformatics methods. Results: cfDNA levels correlated with surgical stage in endometrial cancers, with higher levels of cfDNA being present in advanced-stage disease. Mutations in cfDNA at baseline were detected preoperatively in 8 of 36 (22%) patients with sequencing data, all of whom were diagnosed with advanced-stage disease, high tumor volume, and/or aggressive histologic type. Of the 38 somatic mutations identified in the primary tumors also present in the cfDNA assay, 35 (92%) and 38 (100%) were detected at baseline and follow-up, respectively. In 6 patients with recurrent disease, changes in circulating tumor DNA (ctDNA) fraction/variant allele fractions in cfDNA during follow-up closely mirrored disease progression and therapy response, with a lead time over clinically detected recurrence in two cases. The presence of ctDNA at baseline (P < 0.001) or postsurgery (P = 0.014) was significantly associated with reduced progression-free survival. Conclusions: cfDNA sequencing analysis in patients with endometrial cancer at diagnosis has prognostic value, and serial postsurgery cfDNA analysis enables disease and treatment response monitoring. See related commentary by Grant et al., p. 305

Alexia Iasonos

Amir Momeni-Boroujeni

Amit M. Oza

Antonio Marra

Arnaud Da Cruz Paula

Britta Weigelt

Brooke M. Grant

Carol Aghajanian

Charles W. Ashley

Claire F. Friedman

David N. Brown

Dmitriy Zamarin

I am a Professor in Medical Oncology at Icahn School of Medicine at Mount Sinai (ISMMS) where I serve as the Section Head of Gynecologic Medical Oncology. I obtained my MD and PhD degrees from the Mount Sinai School of Medicine in New York where my research was focused on cellular responses to influenza viral infection and interactions of the influenza virus with the host immune system. I completed residency in Internal Medicine at the Mount Sinai Hospital in New York and fellowship in Hematology/Oncology at MSK, where I studied the mechanisms of response and resistance to immunomodulatory antibody therapy and oncolytic virus-based therapeutics. From 2014 to 2023 I was a faculty on the Gynecologic Medical Oncology service at MSK, where I served as the Translational Research Director. In August 2023 I joined ISMMS as the Section Head of Gynecologic Medical Oncology. My clinical practice and my clinical and laboratory research are focused on diagnosis and treatment of gynecologic cancers. In line with this work, I serve as the Translational co-Chair on the NRG Oncology Cervical Cancer Committee and a member of the NCI GCSC Ovarian Cancer Task Force. Since my academic appointment I have served as a clinical and translational PI on multiple investigator-sponsored and NCI-sponsored immunotherapy clinical trials in gynecologic cancers. In the laboratory, my research focuses on understanding of mechanisms of immune recognition in gynecologic cancers and on development of novel immunotherapeutics. My work has been funded by several agencies, including the Damon Runyon Cancer Research Foundation, Ovarian Cancer Research Alliance, National Cancer Institute, and Department of Defense.

Elizabeth L Jewell

Ian Milsom

Jennifer Mueller

Jessica N McAlpine

Jorge S Reis‐Filho

Josip Nincevic

Juber Patel

Kaled M. Alektiar

Kara Long Roche

Karen A. Cadoo

Lora H. Ellenson

Lukas Rob

Mario M Leitao

Michael F. Berger

Michelle Wu

Nadeem R Abu-Rustum

Oliver Zivanovic

Pavel Souček

Petr Holy

Pier Selenica

Qin Zhou

Ronak H. Shah

As a results-driven computational biologist and bioinformatics leader, I utilize my expertise in developing and executing computational methods to analyze genomic and molecular data. I effectively communicate technical insights and solutions to both technical and non-technical audiences. At Memorial Sloan Kettering Cancer Center, I direct an informatics group focused on developing tools to process and analyze genomic data generated from liquid biopsy assays. I am responsible for the computational infrastructure supporting research and production of cfDNA assays on clinical trials. I lead a team developing bioinformatics pipelines, databases, and systems to manage and automate the analysis. My skills include designing and implementing large-scale genomic data analysis tools, developing cloud-based computational solutions, mentoring junior bioinformaticians, collaborating with experimental and clinical teams, and communicating results clearly and succinctly. Throughout my career, I have worked to establish best practices for reproducible and robust computational research. My passion is applying genomic data and computational methods to generate biological insights that advance cancer research and clinical care. I strive to build collaborative teams and develop innovative solutions that impact meaningfully.

Trevor Pugh

Vance A. Broach

Viktor Hlaváč

Yukio Sonoda

Yulia Lakhman