Risk Reclassification of Patients with Endometrial Cancer Based on Tumor Molecular Profiling: First Real World Data

Prognostic role of transcription factor ARID1A in patients with endometrial cancer of no specific molecular profile (NSMP) subtype

OBJECTIVE

As more than 50% of newly diagnosed endometrial cancers remain classified as 'no specific molecular subtype' (NSMP) due to a lack of established biomarkers to further improve molecular subtyping, this study aims to evaluate the prognostic value of ARID1A in endometrial cancers of NSMP subtype.

METHODS

Prospectively collected molecular profiling data of all consecutive patients with endometrial cancer who underwent primary surgery at our department between August 2017 and June 2022 and for whom both molecular profiling and clinical follow-up data were available were retrospectively evaluated. Tumor specimens were evaluated by combined mismatch repair protein immunohistochemistry and targeted next-generation hotspot sequencing. ARID1A mutational status, as defined by full-length gene sequencing, was matched with risk of recurrence, progression-free and disease-specific survival within the NSMP cohort.

RESULTS

A total of 127 patients with endometrial cancer were included. Among 72 patients with tumors of NSMP subtype (56.7%), ARID1A mutations were identified in 24 cases (33.3%). ARID1A mutations were significantly associated with a higher risk of recurrence (37.5% vs 12.5%, OR 4.20, 95% CI 1.28 to 13.80, p=0.018) and impaired progression-free survival (HR 3.96, 95% CI 1.41 to 11.15, p=0.009), but not with disease-specific survival. The results for both risk of recurrence (OR 3.70, 95% CI 1.04 to 13.13, p=0.043) and progression-free survival (HR 3.19, 95% CI 1.10 to 9.25, p=0.033) were confirmed in multivariable analysis compared with advanced tumor stage International Federation of Gynecology and Obstetrics (2009) (FIGO ≥III) and impaired Eastern Clinical Oncology Group performance status (ECOG ≥1).

CONCLUSION

ARID1A appears to identify patients with endometrial cancer of NSMP subtypes with a higher risk of recurrence and could be used as a future prognostic biomarker. After clinical validation, ARID1A assessment could help to further sub-classify selected endometrial cancers and improve personalized treatment strategies.

Molecular subtypes of endometrial cancer: Implications for adjuvant treatment strategies

BACKGROUND

When determining adjuvant treatment for endometrial cancer, the decision typically relies on factors such as cancer stage, histologic grade, subtype, and a few histopathologic markers. The Cancer Genome Atlas revealed molecular subtyping of endometrial cancer, which can provide more accurate prognostic information and guide personalized treatment plans.

OBJECTIVE

To summarize the expression and molecular basis of the main biomarkers of endometrial cancer.

SEARCH STRATEGY

PubMed was searched from January 2000 to March 2023.

SELECTION CRITERIA

Studies evaluating molecular subtypes of endometrial cancer and implications for adjuvant treatment strategies.

DATA COLLECTION AND ANALYSIS

Three authors independently performed a comprehensive literature search, collected and extracted data, and assessed the methodological quality of the included studies.

MAIN RESULTS

We summarized the molecular subtyping of endometrial cancer, including mismatch repair deficient, high microsatellite instability, polymerase epsilon (POLE) exonuclease domain mutated, TP53 gene mutation, and non-specific molecular spectrum. We also summarized planned and ongoing clinical trials and common therapy methods in endometrial cancer. POLE mutated endometrial cancer consistently exhibits favorable patient outcomes, regardless of adjuvant therapy. Genomic similarities between p53 abnormality endometrial cancer and high-grade serous ovarian cancer suggested possible overlapping treatment strategies. High levels of immune checkpoint molecules, such as programmed cell death 1 and programmed cell death 1 ligand 1 can counterbalance mismatch repair deficient endometrial cancer immune phenotype. Hormonal treatment is an appealing option for high-risk non-specific molecular spectrum endometrial cancers, which are typically endometrioid and hormone receptor positive. Combining clinical and pathologic characteristics to guide treatment decisions for patients, including concurrent radiochemotherapy, chemotherapy, inhibitor therapy, endocrine therapy, and immunotherapy, might improve the management of endometrial cancer and provide more effective treatment options for patients.

CONCLUSIONS

We have characterized the molecular subtypes of endometrial cancer and discuss their value in terms of a patient-tailored therapy in order to prevent significant under- or overtreatment.

Development and external validation of a clinical-radiomics nomogram for preoperative prediction of LVSI status in patients with endometrial carcinoma

PURPOSE

To develop and validate a model that incorporates radiomics based on MRI scans and clinical characteristics to predict lymphovascular invasion (LVSI) in endometrial cancer (EC) patients.

METHODS

There were 332 patients with EC enrolled retrospectively in this multicenter study. Radiomics score (Radscore) were computed using the valuable radiomics features. The independent predictors of LVSI were identified by univariate logistic analysis. Multivariate logistic regression was used to develop a clinical-radiomics predictive model. Based on the model, a nomogram was developed and validated internally and externally. The nomogram was evaluated with discrimination, calibration, decision curve analysis (DCA), and clinical impact curves (CIC).

RESULTS

Three predictive models were constructed based on clinicopathological features, radiomic factors and a combination of them, and that the clinic-radiomic model performed best among the three models. Four independent factors comprised the clinical-radiomics model: dynamic contrast enhancement rate of late arterial phase (DCE2), deep myometrium invasion (DMI), lymph node metastasis (LNM), and Radscore. Clinical-radiomics model performance was 0.901 (95% CI 0.84-0.96) in the training cohort, 0.80 (95% CI 0.68-0.92) in the internal validation cohort, and 0.81 (95% CI 0.73-0.9) in the external validation cohort for identifying patients with LVSI, respectively. The model is used to develop a nomogram for clinical use.

CONCLUSIONS

The MRI-based radiomics nomogram could serve as a noninvasive tool to predict LVSI in EC patients.

Practical lessons learned from real-world implementation of the molecular classification for endometrial carcinoma

OBJECTIVES

This study aimed to explore the practical organisational aspects and difficulties in the implementation of the molecular classification of endometrial carcinoma (EC), and to demonstrate its potential impact in prognostic risk group classification.

METHODS

We conducted a multicentre, retrospective cohort study of 230 patients with EC diagnosed between 2019 and 2022. Sample processing, clinicopathological, treatment and follow-up data were collected. Molecular classification was obtained by p53 and mismatch repair proteins immunohistochemistry, and POLE next-generation sequencing.

RESULTS

Implementation was achieved through centralization of molecular analysis. In practice, it was possible to optimise turnaround times of complete integrative reports for hysterectomy specimens to a median time of 18 workdays. If genetic study was started in endometrial biopsies before surgery, 82.0% were available at the time of multidisciplinary tumour board, compared to 8.4% if performed in hysterectomy. ECs were classified as follows: 37.8% no specific molecular profile, 31.7% p53 abnormal, 24.3% mismatch repair deficient, and 6.1% POLE mutant. Integration of these results with traditional clinicopathologic factors led to a change in prognostic risk group in 15 (6.5%) patients, most being initially allocated to high-intermediate (n = 8) and low (n = 5) risk groups. Eight patients changed to a higher risk, and 7 to a lower risk group, whereas 2 remained in the same group.

CONCLUSIONS

Centralization of EC molecular classification is a feasible option for countries with limited resources. Optimization of workflows may be achieved by earlier analysis in biopsies and prioritisation of patients whose results imply changes in risk group classification.

Integration of Molecular Data in the Prognostic Stratification and Management of Endometrial Carcinoma

In the last years, the TCGA-based molecular classifier have been progressively integrated in the management of endometrial carcinoma. While molecular assays are increasingly available across pathology laboratories, the additional costs will expectedly be compensated by a reduction in overtreatments and a prevention of recurrences. The additional time might be shortened by assessing molecular markers on biopsy specimens. Retrospective data suggest that the molecular classifier will have a major impact of on the risk stratification, with many patients having their risk class down- or upstaged based on POLE mutations or p53 abnormalities, respectively. However, there are still several issues to be resolved, such as the prognostic value of the TCGA classifier in each FIGO stage, or the type of adjuvant treatment most suitable for each molecular group. Other issues regard the prognostic stratification of the mismatch repair-deficient and "no specific molecular profile" groups, which currently follows the same criteria; however, the former seems to be prognostically consistent regardless of FIGO grade and histotype, whereas the latter appears highly heterogeneous. Numerous clinical, histological, immunohistochemical and molecular markers have been proposed to refine the TCGA classification, but their prognostic value is still undefined. Hopefully, prospective data collected in the next years will help resolving these issues.

Diagnostic and Therapeutic Values of Angiogenic Factors in Endometrial Cancer

Endometrial cancer (EC) is the most frequent gynecological malignancy in developed countries and requires a relatively invasive diagnostic evaluation and operative therapy as the primary therapeutic approach. Angiogenesis is one of the main processes needed for cancer growth and spread. The production of angiogenic factors (AFs) appears early in the process of carcinogenesis. The detection of AFs in plasma and tissue and a better understanding of the angiogenic properties of EC may contribute not only to earlier but also more specific diagnosis and consequently tailored and individual therapeutic approaches. AFs and their receptors also have high potential as binding sites for targeted cancer therapy. In this review, we discuss angiogenesis in EC and the characteristics of the AFs that most contribute to angiogenesis in EC. We also highlight therapeutic strategies that target angiogenesis as potential EC therapy.

Overweight as a Favorable Clinical Biomarker for Checkpoint Inhibitor Therapy Response in Recurrent Gynecologic Cancer Patients

Despite increasing clinical interest in adapting checkpoint inhibitor (CPI) therapies for patients with gynecologic malignancies, no accurate clinical biomarkers to predict therapy response and prognosis are currently available. Therefore, we aimed to assess the predictive and prognostic value of pretherapeutic body mass index (BMI) for recurrent gynecologic cancer patients as previously validated for other solid tumors. We evaluated patients with programmed cell death ligand 1 (PD-L1) positive and, in endometrial cancer, also mismatch repair deficient (MMR) gynecologic malignancies, who received the PD-1 inhibitor pembrolizumab as monotherapy (200 mg fixed-dose q3 w) from 2017 to 2020 (n = 48). Thirty-six patients receiving at least four courses were included in the final analysis. Associations between a BMI increase per 5 kg/m2 and overall response rate (ORR; complete + partial response), disease control rate (DCR; ORR + stable disease), progression-free (PFS), and overall survival (OS) were assessed. An elevated BMI was univariately associated with ORR (OR 10.93 [CI 2.39-49.82], p = 0.002), DCR (OR 2.19 [CI 0.99-4.83], p = 0.048), prolonged PFS (HR 1.54 [CI 1.03-2.34], p = 0.038), and OS (HR 1.87 [CI 1.07-3.29], p = 0.028). All results could be confirmed in the multivariate analyses. Pretherapeutic BMI therefore appears to be a promising readily available biomarker to identify patients with PD-L1-positive and/or MMR-deficient gynecologic malignancies who could particularly benefit from CPI treatment.

Molecular Profiling of Endometrial Cancer: An Exploratory Study in Aotearoa, New Zealand

BACKGROUND

Aotearoa, New Zealand, has one of the fastest-rising rates of endometrial cancer (EC) worldwide, increasing particularly in younger Māori and Pasifika women. There is a move towards using molecular profiling to direct treatment for each EC subtype.

AIM

This study aimed to explore the molecular profiling of primary EC tissue in Aotearoa.

METHODS

We used the PORTEC guidelines for the molecular subtyping of 90 patients' samples into four categories: POLE-mutated, p53 abnormal, mismatch repair deficient (MMRd) and no specific molecular profile (NSMP). The CTNNB1 mutation and L1CAM expression were also included in the analysis. POLE and CTNNB1 mutations were analysed using targeted next-generation sequencing (NGS). Novel mutations were assessed using VarSome. MMRd, L1CAM and p53 abnormalities were analysed using immunohistochemistry.

RESULTS

In total, 15 samples were MMRd, 9 were p53 abnormal, 8 were POLE-mutated and the rest (56) were NSMP. Eleven samples had exon 3 CTNNB1 mutations and eleven novel POLE mutations were described.

CONCLUSION

Surrogate markers for POLE mutations should be investigated. The validation of POLE variants and CTNNB1 mutations as part of an Aotearoa-based molecular panel is warranted.

Pre-treatment risk assessment of women with endometrial cancer: differences in outcomes of molecular and clinical classifications in the Slovenian patient cohort

Background

The aim of this study was to evaluate changes in prognostic risk profiles of women with endometrial cancer by comparing the clinical risk assessment with the integrated molecular risk assessment profiling.

Patients and methods

This prospective study recruited patients with biopsy proven endometrial cancer treated at the University Medical Centre Maribor between January 2020 to February 2021. Patient clinical data was assessed and categorized according to the currently valid European Society of Gynaecological Oncology, European SocieTy for Radiotherapy and Oncology, and European Society of Pathology (ESGO/ESTRO/ESP) guidelines on endometrial cancer. Molecular tumour characterization included determination of exonuclease domain of DNA polymerase-epsilon (POLE) mutational status by Sanger sequencing and imunohistochemical specimen evaluation on the presence of mismatch repair deficiencies (MMRd) and p53 abnormalities (p53abn).

Results

Fourty-five women were included in the study. Twenty-two tumours were of non-specific mutational profile (NSMP) (56.4%), 13 were classified as MMRd (33.3%), 3 were classified as p53abn (7.7%) and 1 was classified as POLE mutated (2.6%). Six tumours (15.4%) had multiple molecular classifiers, these were studied separately and were not included in the risk assessment. The clinical risk-assessment classified 21 women (53.8%) as low-risk, 5 women (12.8%) as intermediate risk, 2 women as high-intermediate risk (5.1%), 10 women (25.6%) as high risk and 1 patient as advanced metastatic (2.6%). The integrated molecular classification changed risk for 4 women (10.3%).

Conclusions

Integrated molecular risk improves personalized risk assessment in endometrial cancer and could potentially improve therapeutic precision. Further molecular stratification with biomarkers is especially needed in the NSMP group to improve personalized risk-assessment.

A Personalized Medical Decision Support System Based on Explainable Machine Learning Algorithms and ECC Features: Data from the Real World

Artificial intelligence can help physicians improve the accuracy of breast cancer diagnosis. However, the effectiveness of AI applications is limited by doctors’ adoption of the results recommended by the personalized medical decision support system. Our primary purpose is to study the impact of external case characteristics (ECC) on the effectiveness of the personalized medical decision support system for breast cancer assisted diagnosis (PMDSS-BCAD) in making accurate recommendations. Therefore, we designed a novel comprehensive framework for case-based reasoning (CBR) that takes the impact of external features of cases into account, made use of the naive Bayes and k-nearest neighbor (KNN) algorithms (CBR-ECC), and developed a PMDSS-BCAD system by using the CBR-ECC model and external features as system components. Under the new case-based reasoning framework, the accuracy of the combined model of naive Bayes and KNN with an optimal K value of 2 is 99.40%. Moreover, in a real hospital scenario, users rated the PMDSS-BCAD system, which takes into account the external characteristics of the case, better than the original personalized system. These results suggest that PMDSS-BCD can not only provide doctors with more personalized and accurate results for auxiliary diagnosis, but also improve doctors’ trust in the results, so as to encourage doctors to adopt the results recommended by the personalized system.

Molecular Pathology of Cancer: The Past, the Present, and the Future

Clinical pathology developed from the study of macroscopic organ and tissue changes at autopsies [...].

A Narrative Review of the Role of Diet and Lifestyle Factors in the Development and Prevention of Endometrial Cancer

Simple Summary

The incidence and prevalence of endometrial cancer is increasing globally. The main factors involved in this increase have been the way women live today and what they eat and drink. In fact, the obesity pandemic that is sweeping across the planet is considered to be the main contributory feature. This review aims to introduce to a new audience, those that are not experts in the field, what is known about the different types of endometrial cancer and the mechanisms for their induction and protection. We also seek to summarise the existing knowledge on dietary and lifestyle factors that prevent endometrial development in susceptible populations and identify the main problem in this arena; the paucity of research studies and clinical trials that investigate the interaction(s) between diet, lifestyle and endometrial cancer risk whilst highlighting those areas of promise that should be further investigated.

Abstract

Endometrial cancer is the most common cancer affecting the reproductive organs of women living in higher-income countries. Apart from hormonal influences and genetic predisposition, obesity and metabolic syndrome are increasingly recognised as major factors in endometrial cancer risk, due to changes in lifestyle and diet, whereby high glycaemic index and lipid deposition are prevalent. This is especially true in countries where micronutrients, such as vitamins and minerals are exchanged for high calorific diets and a sedentary lifestyle. In this review, we will survey the currently known lifestyle factors, dietary requirements and hormonal changes that increase an individual’s risk for endometrial cancer and discuss their relevance for clinical management. We also examine the evidence that everyday factors and clinical interventions have on reducing that risk, such that informed healthy choices can be made. In this narrative review, we thus summarise the dietary and lifestyle factors that promote and prevent the incidence of endometrial cancer.

Tie-2, G-CSF, and Leptin as Promising Diagnostic Biomarkers for Endometrial Cancer: A Pilot Study

Preoperative determination of the extent of endometrial cancer (EC) would avoid the complications associated with radical surgery. Screening of patients' plasma biomarkers might enable a more precise diagnosis of EC and a tailored treatment approach. This prospective case-control monocentric pilot study included 76 postmenopausal women (38 endometrioid EC patients and 38 control patients with benign gynecological conditions), and 37 angiogenic factors (AFs) were investigated as potential biomarkers for EC. AF concentrations in preoperative plasma samples were measured using Luminex xMAP™ multiplexing technology. The plasma levels of sTie-2 and G-CSF were significantly lower in EC compared to control patients, whereas the plasma levels of leptin were significantly higher in EC patients. Neuropilin-1 plasma levels were significantly higher in patients with type 2 EC (grade 3) compared to patients with lower grade cancer or controls. Follistatin levels were significantly higher in patients with lymphovascular invasion, and IL-8 plasma levels were significantly higher in patients with metastases. If validated, the plasma concentrations of the indicated AFs could represent an important additional diagnostic tool for the early detection and characterization of EC. This could guide the decision-making on the extent of surgery. Further studies with larger patient numbers are currently ongoing.