A Modern Approach to Endometrial Carcinoma: Will Molecular Classification Improve Precision Medicine in the Future?

Predictive Value of Magnetic Resonance Imaging in Risk Stratification and Molecular Classification of Endometrial Cancer

This study evaluated the magnetic resonance imaging (MRI) findings of endometrial cancer (EC) patients and identified differences based on risk group and molecular classification. The study involved a total of 175 EC patients. The MRI data were retrospectively reviewed and compared based on the risk of recurrence. Additionally, the associations between imaging phenotypes and genomic signatures were assessed. The low-risk and non-low-risk groups (intermediate, high-intermediate, high, metastatic) showed significant differences in tumor diameter (p < 0.001), signal intensity and heterogeneity on diffusion-weighted imaging (DWI) (p = 0.003), deep myometrial invasion (involvement of more than 50% of the myometrium), cervical invasion (p < 0.001), extrauterine extension (p = 0.002), and lymphadenopathy (p = 0.003). Greater diffusion restriction and more heterogeneity on DWI were exhibited in the non-low-risk group than in the low-risk group. Deep myometrial invasion, cervical invasion, extrauterine extension, lymphadenopathy, recurrence, and stage discrepancy were more common in the non-low-risk group (p < 0.001). A significant difference in microsatellite stability status was observed in the heterogeneity of the contrast-enhanced T1-weighted images (p = 0.027). However, no significant differences were found in MRI parameters related to TP53 mutation. MRI features can be valuable predictors for differentiating risk groups in patients with EC. However, further investigations are needed to explore the imaging markers based on molecular classification.

Artificial Intelligence and Radiomics for Endometrial Cancer MRI: Exploring the Whats, Whys and Hows

Endometrial cancer (EC) is intricately linked to obesity and diabetes, which are widespread risk factors. Medical imaging, especially magnetic resonance imaging (MRI), plays a major role in EC assessment, particularly for disease staging. However, the diagnostic performance of MRI exhibits variability in the detection of clinically relevant prognostic factors (e.g., deep myometrial invasion and metastatic lymph nodes assessment). To address these challenges and enhance the value of MRI, radiomics and artificial intelligence (AI) algorithms emerge as promising tools with a potential to impact EC risk assessment, treatment planning, and prognosis prediction. These advanced post-processing techniques allow us to quantitatively analyse medical images, providing novel insights into cancer characteristics beyond conventional qualitative image evaluation. However, despite the growing interest and research efforts, the integration of radiomics and AI to EC management is still far from clinical practice and represents a possible perspective rather than an actual reality. This review focuses on the state of radiomics and AI in EC MRI, emphasizing risk stratification and prognostic factor prediction, aiming to illuminate potential advancements and address existing challenges in the field.

Clear cell endometrial carcinoma with high microsatellite instability in a complicated pregnancy: a case report

BACKGROUND

Endometrial carcinomas are the most common female genital malignancies. They are very rare in pregnancy and worldwide less than 60 cases associated with pregnancy are published. No clear cell carcinoma has been described in a pregnancy with a live birth.

CASE PRESENTATION

We present the course of a 43-year-old Uyghur female patient with the diagnosis of endometrial carcinoma with a deficiency in the DNA mismatch repair system in the pregnancy. The malignancy with clear cell histology was confirmed by biopsy following the delivery via caesarean section due to preterm birth of a fetus with sonographically suspected tetralogy of Fallot. Earlier whole exome sequencing after amniocentesis had shown a heterozygous mutation in the MSH2 gene, which was unlikely to be related to the fetal cardiac defect. The uterine mass was initially deemed an isthmocervical fibroid by ultrasound and was confirmed as stage II endometrial carcinoma. The patient was consequently treated with surgery, radiotherapy and chemotherapy. Six months after the adjuvant therapy, re-laparotomy was performed due to ileus symptoms and an ileum metastasis was found. The patient is currently undergoing immune checkpoint inhibitor therapy with pembrolizumab.

CONCLUSION

Rare endometrial carcinoma should be included in the differential diagnosis of uterine masses in pregnant women with risk factors.

MRI- and Histologic-Molecular-Based Radio-Genomics Nomogram for Preoperative Assessment of Risk Classes in Endometrial Cancer

High- and low-risk endometrial carcinoma (EC) differ in whether or not a lymphadenectomy is performed. We aimed to develop MRI-based radio-genomic models able to preoperatively assess lymph-vascular space invasion (LVSI) and discriminate between low- and high-risk EC according to the ESMO-ESGO-ESTRO 2020 guidelines, which include molecular risk classification proposed by "ProMisE". This is a retrospective, multicentric study that included 64 women with EC who underwent 3T-MRI before a hysterectomy. Radiomics features were extracted from T2WI images and apparent diffusion coefficient maps (ADC) after manual segmentation of the gross tumor volume. We constructed a multiple logistic regression approach from the most relevant radiomic features to distinguish between low- and high-risk classes under the ESMO-ESGO-ESTRO 2020 guidelines. A similar approach was taken to assess LVSI. Model diagnostic performance was assessed via ROC curves, accuracy, sensitivity and specificity on training and test sets. The LVSI predictive model used a single feature from ADC as a predictor; the risk class model used two features as predictors from both ADC and T2WI. The low-risk predictive model showed an AUC of 0.74 with an accuracy, sensitivity, and specificity of 0.74, 0.76, 0.94; the LVSI model showed an AUC of 0.59 with an accuracy, sensitivity, and specificity of 0.60, 0.50, 0.61. MRI-based radio-genomic models are useful for preoperative EC risk stratification and may facilitate therapeutic management.

A comparison of malignant histopathological diagnoses on uterine curettings and hysterectomy specimens

Background. Endometrial carcinoma (EC) is a common gynaecological malignancy in postmenopausal females. Diagnosis is made onendometrial biopsy, where histological subtype and tumour grade are used to predict disease progression and to plan surgical management.Objectives. To determine the accuracy of preoperative biopsies compared with the final diagnosis on hysterectomy specimens.Methods. This was a retrospective, cross-sectional study in which 126 biopsies and corresponding hysterectomy specimens, collected over a 3-year period, were reviewed. Patient demographics and histological features were recorded and statistically analysed.Results. The most prevalent tumours were endometrioid endometrial carcinoma (EEC) (48.5%), serous carcinomas (25.4%) and carcinosarcomas (16.7%). The majority (66.7%) of tumours were high-grade tumours on biopsy and hysterectomy specimens (58.7%). EECs had a poor sensitivity level (65.1%) compared with other subtypes but had a high specificity rate (90%). There was moderateagreement between biopsy and excision specimen diagnoses. High-grade tumours had a high sensitivity level (94.3%).Conclusions. Our study showed moderate agreement between histopathological diagnoses on biopsy and excision specimens. There was a high sensitivity level for biopsies of high-grade tumours, concordant with other studies. Accurate preoperative tumour subtyping and grading are needed to guide surgical management. It is envisaged that use of a combined histological and molecular tumour classificationwill better guide patient treatment and allow for reproducible results.

Fucoxanthin prevents cell growth and induces apoptosis in endometrial cancer HEC-1A cells by the inhibition of the PI3K/Akt/mTOR pathway

Endometrial cancer is the major type of gynecological cancer and ranks as the sixth most common cancer in women. Endometrial cancer usually is diagnosed in an advanced stage, complicating the treatments in many cases. The present research was focused on unveiling the in vitro anticancer role of fucoxanthin against the endometrial cancer HEC-1A cells by inhibiting the phosphatidylinositol-3-kinase/Akt/mammalian target of rapamycin (PI3K/Akt/mTOR) signaling axis. The cytotoxicity of fucoxanthin against the endometrial cancer HEC-1A cells was studied using the MTT test. The level of reactive oxygen species (ROS) production, mitochondrial membrane potential (MMP) status, and apoptotic cell death in the 7.5 and 10 µM administered HEC-1A cells were assayed using fluorescent staining techniques. The messenger RNA expression was analyzed using RT-PCR for PI3K/Akt/mTOR signaling molecules, proapoptotic (Bax and caspase-3) antiapoptotic (cyclin D1 and Bcl-2) genes, and inflammatory markers like tumour necrosis factor α (TNFα), nuclear factor kappa B (NF-κB), Cox-2, and interleukin (IL)-6. The cell viability assay proved that fucoxanthin effectively prevented HEC-1A cell viability, where the IC₅₀ was 7.5 µM. Fucoxanthin at 7.5  and 10 µM remarkably improved ROS production and apoptosis and decreased the MMP in HEC-1A cells. The fucoxanthin effectively inhibited the PI3K/Akt/mTOR cascade along with the expression of TNF-α, NF-κB, Cox-2, and IL-6 and antiapoptotic genes cyclin D1 and Bcl-2 in the HEC-1A cells. Fucoxanthin treatment also enhanced the Bax and caspase-3 expressions in the HEC-1A cells. Our results from this work unveiled that fucoxanthin triggered growth inhibition and apoptosis in endometrial cancer HEC-1A cells. Besides, fucoxanthin inhibited the PI3K/Akt/mTOR cascade and improved apoptotic marker expressions in the HEC-1A cells.

Can miRNAs be useful biomarkers in improving prognostic stratification in endometrial cancer patients? An update review

Endometrial cancer (EC) is the most common gynecological cancer, with annual incidence rates in Western countries ranging between 15 and 25 per 100 000 women. About 15% to 20% of patients with EC have high-risk disease and follow an aggressive clinical course. Unfortunately, the assessment of histologic parameters is poorly reproducible and conventional clinicopathological and molecular features do not reliably predict either the patient's response to the available treatments or the definition of personalized therapeutic approaches. In this context, the identification of novel diagnostic and prognostic biomarkers, which can be integrated in the current classification schemes, represents an unmet clinical need and an important challenge. miRNAs are key players in cancer by regulating the expression of specific target genes. Their role in EC, in association with clinical and prognostic tumor biomarkers, has been investigated but, so far, with little consensus among the studies. The present review aims to describe the recent advances in miRNAs research in EC taking into consideration the current classification schemes and to highlight the most promising miRNAs. Finally, a perspective point of view sheds light on the challenges ahead in the landscape of EC.

Role of Precision Oncology in Type II Endometrial and Prostate Cancers in the African Population: Global Cancer Genomics Disparities

Precision oncology can be defined as molecular profiling of tumors to identify targetable alterations. Emerging research reports the high mortality rates associated with type II endometrial cancer in black women and with prostate cancer in men of African ancestry. The lack of adequate genetic reference information from the African genome is one of the major obstacles in exploring the benefits of precision oncology in the African context. Whilst external factors such as the geography, environment, health-care access and socio-economic status may contribute greatly towards the disparities observed in type II endometrial and prostate cancers in black populations compared to Caucasians, the contribution of African ancestry to the contribution of genetics to the etiology of these cancers cannot be ignored. Non-coding RNAs (ncRNAs) continue to emerge as important regulators of gene expression and the key molecular pathways involved in tumorigenesis. Particular attention is focused on activated/repressed genes and associated pathways, while the redundant pathways (pathways that have the same outcome or activate the same downstream effectors) are often ignored. However, comprehensive evidence to understand the relationship between type II endometrial cancer, prostate cancer and African ancestry remains poorly understood. The sub-Saharan African (SSA) region has both the highest incidence and mortality of both type II endometrial and prostate cancers. Understanding how the entire transcriptomic landscape of these two reproductive cancers is regulated by ncRNAs in an African cohort may help elucidate the relationship between race and pathological disparities of these two diseases. This review focuses on global disparities in medicine, PCa and ECa. The role of precision oncology in PCa and ECa in the African population will also be discussed.

A radiogenomics application for prognostic profiling of endometrial cancer

Prognostication is critical for accurate diagnosis and tailored treatment in endometrial cancer (EC). We employed radiogenomics to integrate preoperative magnetic resonance imaging (MRI, n = 487 patients) with histologic-, transcriptomic- and molecular biomarkers (n = 550 patients) aiming to identify aggressive tumor features in a study including 866 EC patients. Whole-volume tumor radiomic profiling from manually (radiologists) segmented tumors (n = 138 patients) yielded clusters identifying patients with high-risk histological features and poor survival. Radiomic profiling by a fully automated machine learning (ML)-based tumor segmentation algorithm (n = 336 patients) reproduced the same radiomic prognostic groups. From these radiomic risk-groups, an 11-gene high-risk signature was defined, and its prognostic role was reproduced in orthologous validation cohorts (n = 554 patients) and aligned with The Cancer Genome Atlas (TCGA) molecular class with poor survival (copy-number-high/p53-altered). We conclude that MRI-based integrated radiogenomics profiling provides refined tumor characterization that may aid in prognostication and guide future treatment strategies in EC.

Endometrial Cancer Molecular Characterization: The Key to Identifying High-Risk Patients and Defining Guidelines for Clinical Decision-Making?

Endometrial carcinomas (EC) are the sixth most common cancer in women worldwide and the most prevalent in the developed world. ECs have been historically sub-classified in two major groups, type I and type II, based primarily on histopathological characteristics. Notwithstanding the usefulness of such classification in the clinics, until now it failed to adequately stratify patients preoperatively into low- or high-risk groups. Pieces of evidence point to the fact that molecular features could also serve as a base for better patients' risk stratification and treatment decision-making. The Cancer Genome Atlas (TCGA), back in 2013, redefined EC into four main molecular subgroups. Despite the high hopes that welcomed the possibility to incorporate molecular features into practice, currently they have not been systematically applied in the clinics. Here, we outline how the emerging molecular patterns can be used as prognostic factors together with tumor histopathology and grade, and how they can help to identify high-risk EC subpopulations for better risk stratification and treatment strategy improvement. Considering the importance of the use of preclinical models in translational research, we also discuss how the new patient-derived models can help in identifying novel potential targets and help in treatment decisions.

Managing Difficulties of Microsatellite Instability Testing in Endometrial Cancer-Limitations and Advantages of Four Different PCR-Based Approaches

Microsatellite instability (MSI), a common alteration in endometrial cancers (EC) is known as a biomarker for immune checkpoint therapy response alongside screening for Lynch Syndrome (LS). However, former studies described challenging MSI profiles in EC hindering analysis by using MSI testing methods intensively validated for colorectal cancer (CRC) only. In order to reduce false negatives, this study examined four different PCR-based approaches for MSI testing using 25 EC samples already tested for mismatch repair deficiency (dMMR). In a follow up validation set of 75 EC samples previously tested both for MMR and MSI, the efficiency of a seven-marker system corresponding to the Idylla system was further analyzed. Both Bethesda and Promega marker panels require trained operators to overcome interpretation complexities caused by either hardly visible additional peaks of one and two nucleotides, or small shifts in microsatellite repeat length. Using parallel sequencing adjustment of bioinformatics is needed. Applying the Idylla MSI assay, an evaluation of input material is more crucial for reliable results and is indispensable. Following MMR deficiency testing as a first-line screening procedure, additional testing with a PCR-based method is necessary if inconclusive staining of immunohistochemistry (IHC) must be clarified.

Evaluation of Prognosticators and Treatment-Related Side Effects in Patients Irradiated Postoperatively for Endometrial Cancer

Simple Summary

Several trials sought to improve outcomes in endometrial cancer patients with multimodal strategies. Histopathological, clinical, and molecular tumor characteristics were demonstrated to correlate with outcomes. We tested the hypothesis that specific histopathological and clinical parameters are prognosticators for outcomes in patients irradiated postoperatively at our Gynecological Cancer Center. First, we found a significant influence of grading and nodal stage on outcomes. These findings underline the recommendations of more intense treatment in these patient groups, as reflected in current guidelines. Secondly, age had a significant influence on survival be it due to comorbidities and/or due to too hesitant treatment regimen in elderly. Thus, here, it should be aimed at particular treatment strategies. Lastly, we found low rates of side effects associated with brachytherapy and moderate rates of side effects associated with teletherapy. Overall, our study serves as basis for further improvement of treatment strategies and for conceptualization of clinical trials.

Abstract

Numerous clinical trials sought to improve outcomes in endometrial cancer patients with multimodal treatment strategies. We tested the hypothesis that specific histopathological and clinical parameters are prognosticators for outcomes at our Gynecological Cancer Center. A total of 203 patients (median age, 69.5 years) was included. They were irradiated postoperatively (n = 184: Brachytherapy, n = 19: Teletherapy) between 05/2007 and 03/2020. The median follow-up was 37.2 months. As statistical methods, we used the univariable Cox proportional hazards regression, and log-rank statistics. First, we found a significant influence of grading and nodal stage on outcomes. These findings underline the recommendations of more intense treatment in these patient groups, as already reflected in current guidelines. Secondly, we found that patient age had a significant influence on survival be it due to comorbidities and/or due to too hesitant treatment regimen in the elderly. Thus, it should be aimed at particular strategies in treatment of these patients. Lastly, we found very low rates of treatment-related side effects in patients treated with brachytherapy and moderate rates of side effects in patients treated with teletherapy. Overall, our study serves as basis for further improvement of treatment strategies and for conceptualization of clinical trials.