Incorporation of molecular characteristics into endometrial cancer management

Combination of circulating tumor cells, lncRNAs and DNA methylation for the diagnosis of endometrial carcinoma

Endometrial carcinoma (EC) is one of the most common gynecological malignant neoplasms, the prognosis of which is strongly related to the time of diagnosis, with an earlier diagnosis leading to a better prognosis. Therefore, effective diagnostic indicators and methods are needed to ensure early detection. The present study explored the following in EC: Circulating tumor cells (CTCs); the long noncoding RNAs (lncRNAs) RP4-616B8.5, RP11-389G6.3 and carboxy-terminal domain (CTD)-2377D24.6; and the methylation of cysteine dioxygenase type 1 (CDO1) and CUGBP Elav-like family member 4 (CELF4). In total, 85 patients, including 71 with EC, and 14 without EC (NO-EC) but with uterine fibroids or polyps, were included in the present study. In total, 46 patients with EC and 8 NO-EC patients underwent CTC detection. In the evaluation of the EC vs. NO-EC groups, the results showed that the CTC-positive rate of the EC group was 80.43% and that the area under the curve (AUC) value of CTCs was 0.8872 (P=0.0098). A total of 35 patients with EC and 14 NO-EC patients underwent detection of the RP4-616B8.5, RP11-389G6.3 and CTD-2377D24.6 lncRNAs. When the levels of the three lncRNAs RP4-616B8.5, RP11-389G6.3 and CTD-2377D24.6 were compared between the EC and NO-EC groups, they were higher in the EC group; the P-values were 0.0002, 0.0001 and <0.0001, respectively, and the AUC values were 0.8184, 0.8347 and 0.8265, respectively. In addition, a total of 35 patients with EC and 8 NO-EC patients underwent CDO1 and CELF4 DNA methylation analysis. The positive rates of the methylated genes CDO1 and CELF4 were 20% (7/35) and 5.71% (2/35), and the P-values of the comparisons between the EC and NO-EC groups were 0.1748 and 0.5004, respectively; the AUC values were 0.6000 and 0.5286. Furthermore, the combination of CTCs, and lncRNAs RP4-616B8.5, RP11-389G6.3 and CTD-2377D24.6 exhibited high performance in the detection of EC (AUC=0.9375).

Molecular classification of metastatic and recurrent endometrial endometrioid carcinoma: prognostic relevance among low- and high-stage tumours

AIMS

Molecular classification according to The Cancer Genome Atlas (TCGA) improves endometrial endometrioid carcinoma (EEC) prognostication and has specific treatment implications; however, original data were skewed towards low-grade and low-stage tumours. Herein, we molecularly classify EECs metastatic at the time of diagnosis or with subsequently documented recurrent/metastatic disease to examine correlation with clinical outcomes.

METHODS

TCGA categories include POLE-mutated, microsatellite instability (MSI), p53 abnormal (p53 abnl) and no specific molecular profile (NSMP). POLE targeted sequencing at exons 9, 11, 13 and 14 and immunohistochemistry (IHC) for PMS2, MSH6 and p53 were performed to establish molecular classification.

RESULTS

The distribution in our cohort of 141 EECs was similar to that generally reported in EEC, with nine POLE-mutated (6%), 45 MSI (32%), 16 p53 abnl (11%) and 71 NSMP (50%), with similar distributions between low- and high-stage cohorts. We demonstrate that when stratified by molecular subtype, disease-specific survival from the time of high-stage (stages III-IV) presentation or time of recurrence in low-stage (stages I-II) disease among metastatic and/or recurrent EEC is strongly associated with TCGA classification (high-stage P = 0.02, low-stage P = 0.017). Discordant molecular classification between primary and metastatic/recurrent tumours occurred in four of 105 (3.8%) patients, two related to PMS2/MSH6 IHC and two related to p53 IHC.

CONCLUSIONS

We demonstrate that molecular classification is prognostically relevant not only at the time of diagnosis, but also at the time of recurrence and in the metastatic setting. Rare subclonal alterations occur and suggest a role for confirming TCGA classification in recurrent/metastatic tumours.

[Endometrial carcinoma: molecular classification in routine pathology]

The molecular classification of endometrial carcinoma defines four main groups: polymerase‑ɛ(PolE) gene mutated, microsatellite unstable (MSI), p53 abnormal tumors and tumors with no specific molecular profile (NSMP). This classification provides significant insights into the prognosis and therapeutic decisions. Each group exhibits unique genetic profiles identified through immunohistochemistry and molecular diagnostics, enabling personalized treatment. The identification of these molecular signatures necessitates precise analytical methods, selected based on the local circumstances at each site. The approach to molecular classification highlights the critical role of pathology in the diagnosis and emphasizes the necessity of collaboration between the clinic and pathology.

p53 Abnormal (Copy Number High) Endometrioid Endometrial Carcinoma Has a Prognosis Indistinguishable From Serous Carcinoma

Among the 4 molecular subgroups of endometrial carcinoma, the p53 abnormal (copy number high) subgroup has the worst prognosis; however, the histologic characteristics of this subgroup are not well established. Also, it is not well established whether low-grade tumors can belong to the p53 abnormal molecular subgroup and if so, what is the prognostic significance of the p53-mutated molecular subgroup in low-grade tumors. In the current study, we included 146 p53-mutated endometrial carcinomas and performed molecular subgrouping either based on a combination of immunohistochemical studies for p53 and MMR protein expression and POLE mutation testing (81 cases) or based on array-based and sequencing-based technologies (65 cases). We excluded cases that belonged to the POLE mutant or MSI molecular subgroups and only studied p53 abnormal (molecular subgroup) endometrial carcinomas (125 cases). In 71 cases, the molecular subgroup was determined by a combination of immunohistochemical studies and POLE mutation testing, and in 54 cases by array-based and sequencing-based methods. We reviewed 1 to 2 representative digital slides from each case and recorded the morphologic characteristics as well as clinical, treatment, and survival follow-up data. Overall, 47 cases were classified as endometrioid carcinoma, 55 serous carcinoma, and 23 other histotypes. Eight cases were FIGO 1, 21 were FIGO 2, and 91 were FIGO 3. A significant proportion of the cases (24.2%) were histologically classified as low-grade (FIGO 1 or 2) endometrioid carcinoma. There was no morphologic characteristic that showed prognostic implication. There was no significant difference in survival among different histotypes (P=0.60). There was no significant difference in survival among low-grade endometrioid (FIGO 1 or 2) versus high-grade (FIGO 3) tumors (P=0.98). Early-stage (stage I), low-grade tumors showed no significant survival advantage over early-stage, high-grade tumors (P=0.16) and this was more evident in FIGO 2 tumors. Although not statistically significant, the FIGO 2 tumors showed a trend toward worse survival than FIGO 3 tumors. Among the cases with available treatment data, more patients with early-stage high-grade tumors received adjuvant treatment, compared to patients with early-stage low-grade tumors, possibly explaining this trend (P=0.03). In conclusion, the findings of our study suggest that low-grade p53 abnormal endometrioid endometrial carcinomas (especially FIGO 2 tumors) have an aggressive course, with a prognosis similar to high-grade tumors. Furthermore, our study suggests that patients who had early-stage low-grade p53 abnormal disease might have been undertreated because of the "low-grade" histotype.

Biomolecular Classification in Endometrial Cancer: Onset, Evolution, and Further Perspectives: A Critical Review

Since the new guidelines for endometrial cancer risk classification have been published, many reviews have proposed a critical re-evaluation. In this review, we look back to how the molecular classification system was built and its evolution in time to highlight the major flaws, particularly the biases stemming from the inherent limitations of the cohorts involved in the discoveries. A significant drawback in some cohorts is the inclusion criteria, as well as the retrospective nature and the notably sparse numbers, especially in the POLEmut (nonsynonymous mutation in EDM domain of POLE) risk groups, all of which impact the reliability of outcomes. Additionally, a disregard for variations in follow-up duration leads to a non-negligible bias, which raises a substantial concern in data interpretation and guideline applicability. Finally, according to the results that we obtained through a re-analysis of the confirmation cohort, the p53abn (IHC positive for p53 protein) subgroup, which is predominant in non-endometrioid histology (73-80%), loses its predictivity power in the endometrioid cohort of patients. The exclusion of non-endometrioid subtypes from the cohort led to a complete overlap of three molecular subgroups (all except POLEmut) for both overall and progression-free survival outcomes, suggesting the need for a more histotype-specific approach. In conclusion, this review challenges the current ESGO/ESTRO/ESP guidelines on endometrial cancer risk classification and highlights the limitations that must be addressed to better guide the clinical decision-making process.

Molecular Classification Outperforms Histologic Classification in Prognostication of High-grade Endometrial Carcinomas With Undifferentiated and Sarcomatous Components

Since the establishment of 4 molecular subgroups of endometrial carcinoma (EC), there has been significant interest in understanding molecular classification in the context of histologic features and diagnoses. ECs with undifferentiated, spindle, and/or sarcomatous components represent a diagnostically challenging subset of tumors with overlapping clinical and histologic features. We examined the clinicopathologic, morphologic, immunohistochemical, and molecular features of these tumors identified in our institutions' pathology databases using immunohistochemistry and targeted sequencing. Disease-specific survival (DSS) and progression-free survival (PFS) were analyzed using Kaplan-Meier curves and log-rank tests. One hundred sixty-two ECs were included: carcinosarcomas (UCS; n=96), dedifferentiated/undifferentiated EC (DDEC/UDEC; n=49), and grade 3 endometrioid EC with spindled growth (GR3spEEC) (n=17). All molecular subgroups were represented in all histologic subtypes and included 12 (7%) POLE -mutated ( POLE mut), 43 (27%) mismatch repair-deficient (MMRd), 77 (48%) p53-abnormal (p53abn), and 30 (19%) no specific molecular profile (NSMP) tumors. However, the molecular classification (irrespective of histologic diagnosis) was a significant predictor for both DSS ( P =0.008) and P≤0.0001). POLE mut EC showed an excellent prognosis with no recurrences or deaths from the disease. MMRd tumors also showed better outcomes relative to NSMP and p53abn tumors. In conclusion, molecular classification provides better prognostic information than histologic diagnosis for high-grade EC with undifferentiated and sarcomatous components. Our study strongly supports routine molecular classification of these tumors, with emphasis on molecular group, rather than histologic subtyping, in providing prognostication.

Determination of endometrial cancer molecular subtypes using a whole exome-sequencing based single-method approach

AIM

Endometrial cancer (EC) is heterogeneous with respect to epidemiology, clinical course, histopathology and tumor biology. Recently, The Cancer Genome Atlas (TCGA) network has identified four molecular subtypes with distinct clinical courses by an integrated multi-omics approach. These subtypes are of critical importance in the clinical management of EC. However, determination of TCGA molecular subtypes requires a complex methodological approach that is resource intensive and difficult to implement in diagnostic routine procedures. In this context, Talhouk et al. reported the precise determination of modified subtypes based on molecular surrogates obtained by a two-method approach comprising immunohistochemistry and DNA-sequence analysis (Proactive Molecular Risk Classifier for Endometrial Cancer; ProMisE). In this study, we aimed to identify EC molecular subtypes in analogy to TCGA and ProMisE applying an innovative whole exome-sequencing (WES) based single-method approach.

METHODS

WES was performed in a cohort comprising N = 114 EC patients. WES data were analyzed using the oncology treatment decision support software MH Guide (Molecular Health, Heidelberg, Germany) and EC molecular subtypes in analogy to TCGA and ProMisE were determined. Results from both classifications were compared regarding their prognostic values using overall survival and progression-free survival analyses.

RESULTS

Applying a single-method WES-approach, EC molecular subtypes analogue to TCGA and ProMisE were identified in the study cohort. The surrogate marker-analogue classification precisely identified high-risk and low-risk EC, whereas the TCGA-analogue classification failed to obtain significant prognostic values in this regard.

CONCLUSION

Our data demonstrate that determination of EC molecular subtypes analogue to TCGA and ProMisE is feasible by using a single-method WES approach. Within our EC cohort, prognostic implications were only reliably provided by applying the surrogate marker-analogue approach. Designation of molecular subtypes in EC will be increasingly important in routine clinical practice. Thus, the single-method WES approach provides an important simple tool to tailor therapeutic decisions in EC.

Prospective Clinical Prognostication of Endometrial Carcinomas Based on Next-Generation Sequencing and Immunohistochemistry-Real-World Implementation and Results at a Tertiary Care Center

Based on findings from The Cancer Genome Atlas and the Proactive Molecular Risk Classifier for Endometrial Cancer algorithm, endometrial carcinoma can now be stratified into 4 prognostically distinct subgroups based on molecular alterations and immunohistochemical (IHC) aberrations. In this study, we describe the de novo adoption and clinical reporting of prognostic subgroup classification based on next-generation sequencing (NGS) and IHC analyses of all endometrial carcinoma resections at a single institution, framed by the Exploration, Preparation, Implementation, and Sustainment model. Results from the first 13 months show 188 tumors underwent analysis by a combination of IHC and a medium-sized (56 analyzed genes) NGS-based assay. All cases were assigned as either POLE ( POLE -mutated) (5.3%), mismatch repair deficient (27.7%), no specific molecular profile (45.7%), or p53 abnormal (21.3%) inclusive of multiple-classifier cases. NGS-based analysis revealed additional distinctions among the subgroups, including reduced levels of PI3K pathway activation in the p53 abnormal subgroup, an increased rate of CTNNB1 activating mutation in the no specific molecular profile subgroup, and lower TP53 mutation variant allele frequencies in POLE and mismatch repair deficient subgroups compared with the p53 abnormal subgroup. Overall, we describe the testing protocol, reporting, and results of a combination of NGS and IHC to prospectively prognosticate endometrial carcinomas at a single tertiary care center.

Endometrioid Endometrial RNA Index Predicts Recurrence in Stage I Patients

PURPOSE

Risk prediction with genomic and transcriptomic data has the potential to improve patient outcomes by enabling clinicians to identify patients requiring adjuvant treatment approaches, while sparing low-risk patients from unnecessary interventions. Endometrioid endometrial carcinoma (EEC) is the most common cancer in women in developed countries, and rates of endometrial cancer are increasing.

EXPERIMENTAL DESIGN

We collected a 105-patient case-control cohort of stage I EEC comprising 45 patients who experienced recurrence less than 6 years after excision, and 60 Fédération Internationale de Gynécologie et d'Obstétrique grade-matched controls without recurrence. We first utilized two RNA-based, previously validated machine learning approaches, namely, EcoTyper and Complexity Index in Sarcoma (CINSARC). We developed Endometrioid Endometrial RNA Index (EERI), which uses RNA expression data from 46 genes to generate a personalized risk score for each patient. EERI was trained on our 105-patient cohort and tested on a publicly available cohort of 263 patients with stage I EEC.

RESULTS

EERI was able to predict recurrences with 94% accuracy in the training set and 81% accuracy in the test set. In the test set, patients assigned as EERI high-risk were significantly more likely to experience recurrence (30%) than the EERI low-risk group (1%) with a hazard ratio of 9.9 (95% CI, 4.1-23.8; P < 0.001).

CONCLUSIONS

Tumors with high-risk genetic features may require additional treatment or closer monitoring and are not readily identified using traditional clinicopathologic and molecular features. EERI performs with high sensitivity and modest specificity, which may benefit from further optimization and validation in larger independent cohorts.

AI-based histopathology image analysis reveals a distinct subset of endometrial cancers

Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) is assigned after exclusion of the defining features of the other three molecular subtypes and includes patients with heterogeneous clinical outcomes. In this study, we employ artificial intelligence (AI)-powered histopathology image analysis to differentiate between p53abn and NSMP EC subtypes and consequently identify a sub-group of NSMP EC patients that has markedly inferior progression-free and disease-specific survival (termed 'p53abn-like NSMP'), in a discovery cohort of 368 patients and two independent validation cohorts of 290 and 614 from other centers. Shallow whole genome sequencing reveals a higher burden of copy number abnormalities in the 'p53abn-like NSMP' group compared to NSMP, suggesting that this group is biologically distinct compared to other NSMP ECs. Our work demonstrates the power of AI to detect prognostically different and otherwise unrecognizable subsets of EC where conventional and standard molecular or pathologic criteria fall short, refining image-based tumor classification. This study's findings are applicable exclusively to females.

Prognostic value of molecular classification in stage IV endometrial cancer

OBJECTIVES

Multiple studies have proven the prognostic value of molecular classification for stage I-III endometrial cancer patients. However, studies on the relevance of molecular classification for stage IV endometrial cancer patients are lacking. Hypothetically, poor prognostic molecular subtypes are more common in higher stages of endometrial cancer. Considering the poor prognosis of stage IV endometrial cancer patients, it is questionable whether molecular classification has additional prognostic value. Therefore, we determined which molecular subclasses are found in stage IV endometrial cancer and if there is a correlation with progression-free and overall survival.

METHODS

A retrospective multicenter cohort study was conducted using data from five Dutch hospitals. Patients with stage IV endometrial cancer at diagnosis who were treated with primary cytoreductive surgery or cytoreductive surgery after induction chemotherapy between January 2000 and December 2018 were included. Exclusion criteria were age <18 years or recurrent disease. The molecular classification was performed centrally on all tumor samples according to the World Health Organization 2020 classification (including POLE and estrogen receptor status). The Kaplan-Meier method was used to calculate progression free and overall survival in the molecular subclasses, for the different histological subtypes and for estrogen receptor positive versus estrogen receptor negative tumors. Groups were compared using the log-rank test.

RESULTS

164 stage IV endometrial cancer patients were molecularly classified. Median age of the patients was 67 years (range 33-86). Most patients presented with a non-endometrioid histological subtype (58%). Intra-abdominal complete cytoreductive surgery was achieved in 60.4% of the patients. 101 tumors (61.6%) were classified as p53 abnormal, 35 (21.3%) as no specific molecular profile, 21 (12.8%) as mismatch repair deficient, and 6 (3%) as POLE mutated. Molecular classification had no significant impact on progression free (p=0.056) or overall survival (p=0.12) after cytoreductive surgery. Overall survival was affected by histologic subtype (p<0.0001) and estrogen receptor status (p=0.013).

CONCLUSION

The distribution of the molecular subclasses in stage IV endometrial cancer patients differed substantially from the distribution in stage I-III endometrial cancer patients, with the unfavorable subclasses being more frequently present. Although the molecular classification was not prognostic in stage IV endometrial cancer, it could guide adjuvant treatment decisions.

Immunotherapy plus chemotherapy in patients with advanced endometrial cancer: a cost-effectiveness analysis

OBJECTIVE

Pembrolizumab and dostarlimab are immune checkpoint inhibitors that target programmed death receptor 1 (PD-1). Combination anti-PD-1 regimens have been shown to exhibit favorable survival benefits when treating advanced endometrial cancer (EC). Which treatment was preferable will need to be confirmed by a cost-effectiveness comparison between them.

METHODS

Based on patient and clinical parameters from RUBY and NRG-GY018 phase III randomized controlled trials, the Markov model with a 20-year time horizon was established to evaluate the cost-effectiveness of dostarlimab plus chemotherapy (DC), pembrolizumab plus chemotherapy (PC), and chemotherapy alone (C) treatment for patients with mismatch repair-proficient microsatellite-stable (pMMR-MSS) and mismatch repair-deficient microsatellite instability-high (dMMR-MSI-H) advanced EC from the American payers' perspective. The main results include total cost, life-years (LYs), quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio (ICER) at a $150,000/QALY of willingness-to-pay.

RESULTS

In the pMMR-MSS population, DC, PC, and C produced costs (QALYs) of $99,205 (3.02), $322,530 (3.25), and $421,923 (4.40), resulting in corresponding ICERs of $974,177/QALY (PC vs. C), $234,527/QALY (DC vs. C), $86,671/QALY (DC vs. PC), respectively; In the dMMR-MSI-H population, DC, PC, and C obtained costs (QALYs) of $120,177 (5.73), $691,399 (8.43), and $708,787 (11.26), yielding ICERs of $266,423/QALY (PC vs. C), $135,165/QALY (DC vs. C), $7,866/QALY (DC vs. PC), respectively.

CONCLUSION

In the US, DC was a more cost-effective treatment than PC for patients with advanced EC irrespective of MMR status. However, compared to C, DC was associated with more cost-effectiveness in the dMMR-MSI-H population.

Promoter methylation status of RASSF1A and RASSF2A tumor suppressor genes in endometrial endometrioid carcinomas

We aimed to investigate the promoter methylation status of RASSF1A and RASSF2A tumor suppressor genes in endometrial endometrioid carcinomas with p53 wild type and mismatch repair proficient. Genomic DNAs were isolated from 50 specimens (15 formalin-fixed paraffin embedded tumor tissues, 15 paired blood samples and 20 normal endometrial tissues). Bisulfide modification and methylation-specific polymerase chain reaction were performed. As a result of the study, while no significance was found for RASSF1A gene (p = 0.08), a statistically significance was found for RASSF2A gene (p < 0.001), RASSF2A gene methylation status was also found higher in high grade tumors, advanced age (≥50) and nonsmokers groups. Our results indicate that RASSF2A gene may play a role in the carcinogenesis of endometrioid and it could be potential biomarker for early detection for endometrioid carcinoma. Further and larger investigations are needed to confirm our results.

Molecular Classification of Endometrial Cancer and Its Impact on Therapy Selection

Endometrial cancer (EC) accounts for 90% of uterine cancer cases. It is considered not only one of the most common gynecological malignancies but also one of the most frequent cancers among women overall. Nowadays, the differentiation of EC subtypes is based on immunohistochemistry and molecular techniques. It is considered that patients' prognosis and the implementation of the appropriate treatment depend on the cancer subtype. Patients with pathogenic variants in POLE have the most favorable outcome, while those with abnormal p53 protein have the poorest. Therefore, in patients with POLE mutation, the de-escalation of postoperative treatment may be considered, and patients with abnormal p53 protein should be subjected to intensive adjuvant therapy. Patients with a DNA mismatch repair (dMMR) deficiency are classified in the intermediate prognosis group as EC patients without a specific molecular profile. Immunotherapy has been recognized as an effective treatment method in patients with advanced or recurrent EC with a mismatch deficiency. Thus, different adjuvant therapy approaches, including targeted therapy and immunotherapy, are being proposed depending on the EC subtype, and international guidelines, such as those published by ESMO and ESGO/ESTRO/ESP, include recommendations for performing the molecular classification of all EC cases. The decision about adjuvant therapy selection has to be based not only on clinical data and histological type and stage of cancer, but, following international recommendations, has to include EC molecular subtyping. This review describes how molecular classification could support more optimal therapeutic management in endometrial cancer patients.

Prediction of Mismatch Repair Status in Endometrial Cancer from Histological Slide Images Using Various Deep Learning-Based Algorithms

The application of deep learning algorithms to predict the molecular profiles of various cancers from digital images of hematoxylin and eosin (H&E)-stained slides has been reported in recent years, mainly for gastric and colon cancers. In this study, we investigated the potential use of H&E-stained endometrial cancer slide images to predict the associated mismatch repair (MMR) status. H&E-stained slide images were collected from 127 cases of the primary lesion of endometrial cancer. After digitization using a Nanozoomer virtual slide scanner (Hamamatsu Photonics), we segmented the scanned images into 5397 tiles of 512 × 512 pixels. The MMR proteins (PMS2, MSH6) were immunohistochemically stained, classified into MMR proficient/deficient, and annotated for each case and tile. We trained several neural networks, including convolutional and attention-based networks, using tiles annotated with the MMR status. Among the tested networks, ResNet50 exhibited the highest area under the receiver operating characteristic curve (AUROC) of 0.91 for predicting the MMR status. The constructed prediction algorithm may be applicable to other molecular profiles and useful for pre-screening before implementing other, more costly genetic profiling tests.

2023 FIGO staging system for endometrial cancer: The evolution of the revolution

INTRODUCTION

Embracing the complex and diverse nature of the heterogenous group of malignancies that are included under the umbrella of "endometrial cancer" (EC) to better align prognosis with treatment recommendations, requires a more comprehensive staging system. Our goal at the development of the new FIGO staging was to provide 1) high accuracy in the predictive prognosis for a patient with EC, which is the genuine purpose of a staging system, and 2) identification of distinct treatment relevant subgroups. Since the publication of the 2009 staging system by the International Federation of Gynecology and Obstetrics (FIGO) 14  years ago (1, 2), our understanding of the biology and natural history of EC has undergone a radical transformation. The TGCA results in 2013 (3), and the many validation reports published since then (4-9), have taught us that "EC" is composed of at least four distinct molecularly defined diseases. Strong histopathologic markers reflecting tumor biology such as lymph vascular space invasion (LVSI) were identified. Importantly, anatomical borders were shown to lose their prognostic relevance for EC patients in the presence of dominant tumor biology-markers such as molecular subtypes/LVSI (10, 11). This emphasizes the integration of these novel markers into a prognostic staging system that aims to be relevant to patients. The 2023 FIGO staging system for EC harmonizes and integrates old and new knowledge on anatomic, histopathologic, and molecular features (12). It requires a change in our perception of a staging system, from a traditional purely anatomical borders-based system to an integrated staging system integrating anatomical borders and tumor biology as pivotal prognostic factors for EC patients while providing important information for treatment decision making. Therefore, the 2023 FIGO staging system demonstrates the logical next step in the evolution of the revolution in a patient-centric staging approach. Below, we elucidate the rationale for the FIGO 2023 endometrial cancer staging system.

EPPK1 as a Prognostic Biomarker in Type I Endometrial Cancer and Its Correlation with Immune Infiltration

Purpose

Approximately 20% of patients with type I endometrial cancer (EC) of the uterus experience recurrence and metastasis. However, existing data do not provide sufficient evidence for the utility of protein levels as prognostic biomarkers in type I EC. This study aims to determine whether epiplakin1 (EPPK1) and progesterone receptor (PR) play a role in the recurrence and metastasis of type I EC.

Methods

Following the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) for assessing the quality of biomarker research results, a retrospective analysis was conducted on clinical information and tissue samples of type I EC patients. Protein expression data and clinical data for type I EC were downloaded from The Cancer Proteome Atlas (TCPA) database. We utilized the Kaplan-Meier (K-M) method and Cox proportional hazards regression analyses to evaluate whether epiplakin1 (EPPK1), progesterone receptor (PR) and certain clinical parameters can serve as independent prognostic factors. The Immune Cell Abundance Identifier (ImmuCellAI) and Cancer Immunome Atlas (TCIA) were employed to predict responses to immunotherapy. Immunohistochemistry was carried out to assess the expression of EPPK1 in type I EC.

Results

Type I EC patients with high EPPK1 and low PR expression had higher International Federation of Gynecology and Obstetrics (FIGO) stage, recurrence, and metastasis rates. Furthermore, EPPK1 was identified as an independent prognostic factor, and low expression of EPPK1 was predominantly observed in the POLE ultramutated (POLEmut) group, indicating a favorable prognosis. Additionally, the high EPPK1 expression group had a lower Immune Prognostic Score (IPS), suggesting that the high-expression group may not benefit from immune checkpoint inhibitors.

Conclusion

High expression of EPPK1 is an independent prognostic factor in type I EC patients with low PR expression. It can identify a subgroup of patients at high risk of recurrence. A more aggressive treatment approach is recommended for these patients.

Research on the toxicological prognostic significance of age-related genes in endometrial cancer unveiling key factors in patient prognosis

This study investigates the influence of aging-related genes on endometrial cancer, a prominent gynecological malignancy with rising incidence and mortality. By analyzing gene expression differences between cancerous and normal endometrial tissues, 42 aging-related genes were identified as differentially expressed. Utilizing the TCGA-UCEC sample, consensus clustering divided the samples into two molecular subgroups, Aging low and Aging high, based on their expression profiles. These subgroups showed distinct prognoses and survival rates, with the Aging high group associated with DNA repair and cell cycle pathways, and the Aging low group showing suppressed metabolic pathways and increased immune cell infiltration, suggesting a potential for better immunotherapy outcomes. Mutation analysis did not find significant differences in mutation frequencies between the groups, but a high Tumor Mutation Burden (TMB) correlated with better prognosis. A risk score model was also developed, showcasing significant prognostic power. Further analysis of the SIX1 gene revealed its overexpression in cancer cells. Drug sensitivity tests indicated that the low-risk group might respond better to chemotherapy. This research underscores the significance of aging-related genes in endometrial cancer, offering insights into their prognostic value and therapeutic potential, which could lead to personalized treatment approaches and enhanced patient management.

Special Considerations in Classification and Workup of Endometrial Carcinomas

CONTEXT.—

A variety of uncommon malignant endometrial tumors can be challenging to diagnose because of overlapping morphology with more common entities. In some cases, immunohistochemical stains and/or molecular testing allow for more definitive diagnosis or prognostication.

OBJECTIVE.—

To review classic morphologic features of uncommon endometrial tumors, pathologic features of these tumors and their mimics, and the evidence for use of immunohistochemistry and molecular testing in the diagnosis of these tumors.

DATA SOURCES.—

University of Michigan (Ann Arbor) cases and review of pertinent literature about each entity.

CONCLUSIONS.—

Although each of these uncommon endometrial tumors has morphologic mimics, key histologic features, immunohistochemical stains, and molecular testing allow for accurate classification.

Abnormal p53 expression is associated with poor outcomes in grade I or II, stage I, endometrioid carcinoma: a retrospective single-institute study

OBJECTIVE

The Cancer Genome Atlas study revealed an association between copy-number high (p53 abnormal) genetic mutation and poor prognosis in endometrial cancer in 2013. This retrospective study investigated outcomes in patients with abnormal p53 expression and stage I, low-grade endometrial endometrioid carcinoma (EEC).

METHODS

We enrolled women with stage I, grade 1 or 2 EEC who received comprehensive staging and adjuvant therapy between January 2019 and December 2022 at MacKay Memorial Hospital, Taipei, Taiwan. Pathologists interpreted immunohistochemistry stains of cancerous tissues to detect p53 mutation. We compared recurrence, survival, progression-free survival, and overall survival between p53 abnormal and p53 normal groups.

RESULTS

Of the 115 patients included, 26 had pathologically confirmed abnormal p53 expression. Of these 26 patients, five (19.2%) experienced recurrence, and two died due to disease progression. By contrast, no patients in the normal p53 group experienced disease recurrence or died due to disease progression. Significant intergroup differences were discovered in recurrent disease status (19.4% vs. 0%, p<0.001), mortality (7.7% vs. 0%, p<0.001), and progression-free survival (p<0.001). The overall survival (p=0.055) also showed powerful worse trend.

CONCLUSION

For patients with stage I, low-grade EEC, abnormal p53 expression may be used as an indicator of poor prognosis. Therefore, we suggest considering aggressive adjuvant therapies for these patients.

Molecular and Clinicopathologic Characterization of Mismatch Repair-Deficient Endometrial Carcinoma Not Related to MLH1 Promoter Hypermethylation

Universal tumor screening in endometrial carcinoma (EC) is increasingly adopted to identify individuals at risk of Lynch syndrome (LS). These cases involve mismatch repair-deficient (MMRd) EC without MLH1 promoter hypermethylation (PHM). LS is confirmed through the identification of germline MMR pathogenic variants (PV). In cases where these are not detected, emerging evidence highlights the significance of double-somatic MMR gene alterations as a sporadic cause of MMRd, alongside POLE/POLD1 exonuclease domain (EDM) PV leading to secondary MMR PV. Our understanding of the incidence of different MMRd EC origins not related to MLH1-PHM, their associations with clinicopathologic characteristics, and the prognostic implications remains limited. In a combined analysis of the PORTEC-1, -2, and -3 trials (n = 1254), 84 MMRd EC not related to MLH1-PHM were identified that successfully underwent paired tumor-normal tissue next-generation sequencing of the MMR and POLE/POLD1 genes. Among these, 37% were LS associated (LS-MMRd EC), 38% were due to double-somatic hits (DS-MMRd EC), and 25% remained unexplained. LS-MMRd EC exhibited higher rates of MSH6 (52% vs 19%) or PMS2 loss (29% vs 3%) than DS-MMRd EC, and exclusively showed MMR-deficient gland foci. DS-MMRd EC had higher rates of combined MSH2/MSH6 loss (47% vs 16%), loss of >2 MMR proteins (16% vs 3%), and somatic POLE-EDM PV (25% vs 3%) than LS-MMRd EC. Clinicopathologic characteristics, including age at tumor onset and prognosis, did not differ among the various groups. Our study validates the use of paired tumor-normal next-generation sequencing to identify definitive sporadic causes in MMRd EC unrelated to MLH1-PHM. MMR immunohistochemistry and POLE-EDM mutation status can aid in the differentiation between LS-MMRd EC and DS-MMRd EC. These findings emphasize the need for integrating tumor sequencing into LS diagnostics, along with clear interpretation guidelines, to improve clinical management. Although not impacting prognosis, confirmation of DS-MMRd EC may release patients and relatives from burdensome LS surveillance.

Predictive and prognostic biomarkers in female genital tract tumours: an update highlighting their clinical relevance and practical issues

The evaluation of biomarkers by molecular techniques and immunohistochemistry has become increasingly relevant to the treatment of female genital tract tumours as a consequence of the greater availability of therapeutic options and updated disease classifications. For ovarian cancer, mutation testing for BRCA1/2 is the standard predictive biomarker for poly(ADP-ribose) polymerase inhibitor therapy, while homologous recombination deficiency testing may allow the identification of eligible patients among cases without demonstrable BRCA1/2 mutations. Clinical recommendations are available which specify how these predictive biomarkers should be applied. Mismatch repair (MMR) protein and folate receptor alpha immunohistochemistry may also be used to guide treatment in ovarian cancer. In endometrial cancer, MMR immunohistochemistry is the preferred test for predicting benefit from immune checkpoint inhibitor (ICI) therapy, but molecular testing for microsatellite instability may have a supplementary role. HER2 testing by immunohistochemistry and in situ hybridisation is applicable to endometrial serous carcinomas to assess trastuzumab eligibility. Immunohistochemistry for oestrogen receptor and progesterone receptor expression may be used for prognostication in endometrial cancer, but its predictive value for hormonal therapy is not yet proven. POLE mutation testing and p53 immunohistochemistry (as a surrogate for TP53 mutation status) serve as prognostic markers for favourable and adverse outcomes, respectively, in endometrial cancer, especially when combined with MMR testing for molecular subtype designation. For cervical cancer, programmed death ligand 1 immunohistochemistry may be used to predict benefit from ICI therapy although its predictive value is under debate. In vulvar cancer, p16 and p53 immunohistochemistry has established prognostic value, stratifying patients into three groups based on the human papillomavirus and TP53 mutation status of the tumour. Awareness of the variety and pitfalls of expression patterns for p16 and p53 in vulvar carcinomas is crucial for accurate designation. It is hoped that collaborative efforts in standardising and optimising biomarker testing for gynaecological tumours will contribute to evidence-based therapeutic decisions.

Reviving peritoneal cytology: Exploring its role in endometrial cancer molecular classification

OBJECTIVE

The prognostic significance of positive peritoneal cytology in endometrial cancer has long been debated. In 2009, the Fédération Internationale de Gynécologie et d'Obstétrique (FIGO) removed cytology as a staging criterion from the endometrial cancer staging system. However, there is still evidence that positive peritoneal cytology may decrease survival among patients with endometrial cancer. The aim of this study was to determine the prognostic significance of positive peritoneal cytology among the different molecular subgroups.

METHODS

This study included patients with endometrial cancer who underwent primary surgical treatment between 2004 and 2015 at the Bern University Hospital, Switzerland, with molecular classification of the primary tumor and peritoneal cytology performed.

RESULTS

A total, 250 patients with endometrial cancer were enrolled. Peritoneal cytology was assessed in 206 patients, of whom 24% were positive: 25% of the POLEmut, 16% of the MMRd, 41% of the p53abn, and 24% of the NSMP cases. The mean follow-up was 128.7 months. Presence of positive peritoneal cytology was associated with significantly decreased mean recurrence-free and overall survival in patients with p53abn (p = .003 and p = .001) and NSMP (p = .020 and p = .049) endometrial cancer. In multivariable Cox regression analysis, positive peritoneal cytology remained an independent predictor of recurrence (p = .033) and death (p = .008) in p53abn endometrial cancer patients.

CONCLUSION

Positive peritoneal cytology is associated with worse oncologic outcomes in NSMP and p53abn endometrial cancer and remains an independent predictor of recurrence and death in patients with p53abn endometrial cancer.

ENST00000534735 inhibits proliferation and migration, promotes apoptosis and pyroptosis of endometrial cancer via OSBPL3 through APMK/SIRT1/NF-κB pathway

Background

The complete understanding of the biological roles of long non-coding RNAs (lncRNAs) in cancer remains elusive. The findings of this study indicate that the newly discovered lncRNA ENST00000534735 exhibited a decreased expression in both endometrial cancer (EC) tissues and cell lines.

Methods

The expression of ENST00000534735 in EC tissues was detected using RNA-sequencing analysis. The effects of ENST00000534735 on cell proliferation, migration, apoptosis, and pyroptosis were determined via in vitro and in vivo experiments. The proteins that interact with ENST00000534735 were confirmed by RNA pull-down assay. Furthermore, an investigation was conducted on the impact of ENST00000534735 on the in vivo growth of EC through a tumorigenicity assay in nude mice.

Results

We found that ENST00000534735 was significantly down-regulated in EC tissues compared to their adjacent non-cancerous tissues. The ectopic expression of ENST00000534735 drastically inhibited lung cancer cell proliferation and migration ability and facilitated apoptosis and pyroptosis. Knockdown of ENST00000534735 increased OSBPL3 expression, and the tumor-suppressing effects of ENST00000534735 overexpression were reversed by upregulation of OSBPL3 via the APMK/SIRT1/NF-κB pathway. The in vivo tumorigenic assays conducted on nude mice revealed that the excessive expression of ENST00000534735 impeded the growth of EC.

Conclusions

All results elucidated the role and molecular mechanism of ENST00000534735 in the malignant development of EC. ENST00000534735, a new antioncogene in EC, may serve as a survival biomarker or therapeutic target for EC.

Detection of driver mutations and genomic signatures in endometrial cancers using artificial intelligence algorithms

Analyzed endometrial cancer (EC) genomes have allowed for the identification of molecular signatures, which enable the classification, and sometimes prognostication, of these cancers. Artificial intelligence algorithms have facilitated the partitioning of mutations into driver and passenger based on a variety of parameters, including gene function and frequency of mutation. Here, we undertook an evaluation of EC cancer genomes deposited on the Catalogue of Somatic Mutations in Cancers (COSMIC), with the goal to classify all mutations as either driver or passenger. Our analysis showed that approximately 2.5% of all mutations are driver and cause cellular transformation and immortalization. We also characterized nucleotide level mutation signatures, gross chromosomal re-arrangements, and gene expression profiles. We observed that endometrial cancers show distinct nucleotide substitution and chromosomal re-arrangement signatures compared to other cancers. We also identified high expression levels of the CLDN18 claudin gene, which is involved in growth, survival, metastasis and proliferation. We then used in silico protein structure analysis to examine the effect of certain previously uncharacterized driver mutations on protein structure. We found that certain mutations in CTNNB1 and TP53 increase protein stability, which may contribute to cellular transformation. While our analysis retrieved previously classified mutations and genomic alterations, which is to be expected, this study also identified new signatures. Additionally, we show that artificial intelligence algorithms can be effectively leveraged to accurately predict key drivers of cancer. This analysis will expand our understanding of ECs and improve the molecular toolbox for classification, diagnosis, or potential treatment of these cancers.

Fanconi anemia complementation group D2 promotes sensitivity of endometrial cancer cells to chemotherapeutic agents by inhibiting the ferroptosis pathway

BACKGROUND

Resistance can develop during treatment of advanced endometrial cancer (EC), leading to unsatisfactory results. Fanconi anemia complementation group D2 (Fancd2) has been shown to be closely related to drug resistance in cancer cells. Therefore, this study was designed to explore the correlation of Fancd2 with EC resistance and the mechanism of Fancd2.

METHODS

Real-time quantitative PCR (RT-qPCR) was used to detect the expression of Fancd2 in EC tissues and cells. EC cells (Ishikawa) and paclitaxel-resistant EC cells (Ishikawa/TAX) were transfected to knock down Fancd2. In addition, the ferroptosis inhibitor Ferrostatin-1 was adopted to treat Ishikawa/TAX cells. The sensitivity of cancer cells to chemotherapeutic agents was observed via 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay, and inhibitory concentration (IC)50 was calculated. Reactive oxygen species (ROS) levels were measured by flow cytometry, the activity of malondialdehyde (MDA) and the levels of glutathione (GSH) and Fe2+ in cells were detected by corresponding kits, and protein expression of solute farrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4) was obtained through western blot.

RESULTS

Compared with the normal tissues and endometrial epithelial cells, Fancd2 expression was significantly increased in EC tissues and Ishikawa cells, respectively. After knock-down of Fancd2, Ishikawa cells showed significantly increased sensitivity to chemotherapeutic agents. Besides, compared with Ishikawa cells, the levels of ROS, the activity of MDA, and the levels of GSH and Fe2+ were significantly decreased in Ishikawa/TAX cells, while the expression levels of SLC7A11 and GPX4 were significantly increased. Knock-down of Fancd2 significantly increased the ferroptosis levels in Ishikawa/TAX cells, but this effect could be reversed by Ferrostatin-1.

CONCLUSION

Fancd2 increases drug resistance in EC cells by inhibiting the cellular ferroptosis pathway.

Cervical Cytology Preserves Histologically Detected Surface Epithelial Slackening, Unique to the POLE Mutation-subtype in Endometrial Cancer

BACKGROUND/AIM

Among the four genomic subtypes of endometrial cancer, distinguishing between the DNA polymerase epsilon mutation (POLEmut) and no specific molecular profile (NSMP) subtypes requires genomic profiling owing to the lack of surrogate immunohistochemical markers. We have previously found that, histologically, the POLEmut-subtype exhibits surface epithelial slackening (SES). Therefore, to improve subtype identification, we aimed to extract cytological features corresponding to SES in POLEmut-subtype cervical cytology specimens.

MATERIALS AND METHODS

We analyzed 104 endometrial cancer cervical cytology specimens, with integrative diagnosis confirmation via histology, immunohistochemistry, and genomic profiling. Cytological features were evaluated for the presence of atypical glandular cells, atypical cell appearance in single cells and clusters, and cytological SES and the presence of tumor-infiltrating inflammatory cells in clusters.

RESULTS

Based on cervical cytology, the POLEmut- and p53mut-subtypes exhibited more frequent atypical cells in smaller clusters, giant tumor cells, and cytological SES patterns than the NSMP-subtype. Tumor-infiltrating lymphocytes were frequent in the POLEmut- and mismatch repair-deficient subtypes.

CONCLUSION

Histologically-detected SES as well as other endometrial cancer features may be preserved in the atypical cell clusters observed in cervical cytology specimens. Cytological detection of SES and of smaller clusters of atypical cells and inflammatory cells with moderate atypia are suggestive of POLEmut-subtype. Integrative diagnosis including genomic profiling remains critical for diagnostic confirmation.

The identification of a PTEN-associated gene signature for the prediction of prognosis and planning of therapeutic strategy in endometrial cancer

Background

Endometrial cancer (EC) is one of the most common malignancies among women. To improve the prognosis and treatment of EC, finding out a phosphatase and tensin homolog deleted on chromosome 10 (PTEN)-associated prognostic signature would be beneficial.

Methods

EC clinical data, genetic mutation data, and transcriptome data were downloaded from The Cancer Genome Atlas (TCGA) database. To clarify the specific PTEN-associated signature, cox regression analyses were performed. The clinical value of the selected signature on the overall survival (OS) and the secretoglobin family 2A member 1 (SCGB2A1)-independent analysis, immune and functional analysis were investigated respectively.

Results

Five hundred and fourteen EC samples were screened and PTEN mutation occupied 57%. Enrichment analysis indicated that mutant-type PTEN was enriched for pathways related to the upregulated human T-cell leukemia virus-1 (HTLV-1) infection and estrogen signaling pathway. SCGB2A1 was identified by cox regression analysis. Immune analysis exhibited significant immune infiltration with higher expression of T cells, B cells, and macrophage groups. Immune-checkpoint transcripts CD274 molecule (CD274), and cytotoxic T-lymphocyte associated protein 4 (CTLA4), hepatitis A virus cellular receptor 2 (HAVCR2), lymphocyte activation gene 3 (LAG3), programmed cell death 1 (PDCD1), PDCD1 ligand 2 (PDCD1LG2), T cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibition motif domains (TIGIT), and sialic acid binding immunoglobulin like lectin 15 (SIGLEC15) were discovered statistically different. In addition, the low-SCGB2A1 group had worse OS than the high-SCGB2A1 group. SCGB2A1 showed significant area under the curve (AUC) values in a time-dependent receiver operating characteristic (ROC) analysis. Prevalence of microsatellite instability (MSI) was detected and SCGB2A1 showed a negative correlation with EC. Immune checkpoint blockade (ICB) response indicated a worse immune response in the low-SCGB2A1 group. The distribution of one-class linear regression (OCLR) scores reflected the negative correlation between messenger RNA expression-based stemness index (mRNAsi) and prognostic gene expression. Furthermore, several SCGB2A1-related signaling pathways in EC were identified.

Conclusions

SCGB2A1 is a prognostic immunometabolic signature for patients with EC, which may help improve the prognosis and therapeutic effect.

Validation of Modaplex POLE mutation assay in endometrial carcinoma

The TCGA-based molecular classification of endometrial cancer has emerged as an important tool to stratify patients according to prognosis. A simplified scheme has been proposed, by using immunohistochemistry for p53, MSH6, and PMS2 and a molecular test for POLE mutations (NGS or Sanger sequencing, techniques that are not available in many centers worldwide). In this study, we validate a novel method that allows simultaneous analysis of multiple pathogenic POLE mutations. The Modaplex technology integrates polymerase chain reaction and capillary electrophoresis. The design of this study encompassed 4 different steps: (1) a retrospective-pilot phase, with 80 tumors, balancing the four molecular subgroups. (2) A retrospective phase of 25 tumors obtained between 2016 and 2020, and 30 tumors obtained between 2000 and 2015. (3) An inter-laboratory corssavalidation step with 19 cases (belonging to phases 1 and 2). (4) A prospective cohort of 123 tumors, of unknown POLE status, with simultaneous validation by Sanger sequencing. A total of 258 samples were analyzed. In the first and second phases, the test showed positive/negative predictive values of 100%, by correctly identifying POLE mutation status in 79/79 and 55/55 cases. Phase 3 showed 100% of inter-laboratory consistency. Phase 4 showed 16 positive samples out of the 123 prospective cases. Overall, the test has revealed sensitivity and specificity of 100%, identifying a total of 47 POLE-mutated tumors. We have shown that this technique allows faster and easier identification of multiple pathogenic POLE mutations with high robustness and confidence when comparing to other tests such as Sanger sequencing.

Clinical Behavior and Molecular Landscape of Stage I p53-Abnormal Low-Grade Endometrioid Endometrial Carcinomas

PURPOSE

The clinical significance of the p53-abnormal (p53abn) molecular subtype in stage I low-grade endometrioid endometrial carcinoma (EEC) is debated. We aimed to review pathologic and molecular characteristics, and outcomes of stage I low-grade p53abn EEC in a large international cohort.

EXPERIMENTAL DESIGN

Previously diagnosed stage I p53abn EC (POLE-wild-type, mismatch repair-proficient) low-grade EEC from Canadian retrospective cohorts and PORTEC-1&2 trials were included. Pathology review was performed by six expert gynecologic pathologists blinded to p53 status. IHC profiling, next-generation sequencing, and shallow whole-genome sequencing was performed. Kaplan-Meier method was used for survival analysis.

RESULTS

We identified 55 stage I p53abn low-grade EEC among 3,387 cases (2.5%). On pathology review, 17 cases (31%) were not diagnosed as low-grade EEC by any pathologists, whereas 26 cases (47%) were diagnosed as low-grade EEC by at least three pathologists. The IHC and molecular profile of the latter cases were consistent with low-grade EEC morphology (ER/PR positivity, patchy p16 expression, PIK3CA and PTEN mutations) but they also showed features of p53abn EC (TP53 mutations, many copy-number alterations). These cases had a clinically relevant risk of disease recurrence (5-year recurrence-free survival 77%), with pelvic and/or distant recurrences observed in 12% of the patients.

CONCLUSIONS

A subset of p53abn EC is morphologically low-grade EEC and exhibit genomic instability. Even for stage I disease, p53abn low-grade EEC are at substantial risk of disease recurrence. These findings highlight the clinical relevance of universal p53-testing, even in low-grade EEC, to identify women at increased risk of recurrence.

Development and validation of a prognostic nomogram model incorporating routine laboratory biomarkers for preoperative patients with endometrial cancer

BACKGROUND

Some biomarkers collected from routine laboratory tests have shown important value in cancer prognosis. The study aimed to evaluate the prognostic significance of routine laboratory biomarkers in patients with endometrial cancer (EC) and to develop credible prognostic nomogram models for clinical application.

METHODS

A total of 727 patients were randomly divided into a training set and a validation set. Cox proportional hazards models were used to evaluate each biomarker's prognostic value, and independent prognostic factors were used to generate overall survival (OS) and progression-free survival (PFS) nomgrams. The efficacy of the nomograms were evaluated by Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, X-tile analysis and Kaplan‒Meier curves.

RESULTS

Ten significant biomarkers in multivariate Cox analysis were integrated to develop OS and PFS nomograms. The C-indices of the OS- nomogram in the training and validation sets were 0.885 (95% confidence interval (CI), 0.810-0.960) and 0.850 (95% CI, 0.761-0.939), respectively; those of the PFS- nomogram in the training and validation sets were 0.903 (95% CI, 0.866-0.940) and 0.825 (95% CI, 0.711-0.939), respectively. ROC, DCA and calibration curves showed better clinical application value for the nomograms incorporating routine laboratory biomarkers. X-tile analysis and Kaplan‒Meier curves showed that the nomograms were stable and credible in evaluating patients at different risks.

CONCLUSIONS

Nomogram models incorporating routine laboratory biomarkers, including NLR, MLR, fibrinogen, albumin and AB blood type, were demonstrated to be simple, reliable and favourable in predicting the outcomes of patients with EC.

Outcomes of fertility preservation treatments in patients with endometrial cancer with different molecular classifications based on an NGS panel

Background

The molecular classification of endometrial cancer has previously been shown to be associated with clinical outcomes. However, there are insufficient data to support the routine use of molecular classification for the treatment of patients seeking fertility preservation.

Methods

Here, we retrospectively investigated 90 patients received fertility-sparing treatment. We used a next generation sequencing (NGS) panel to classify these patients into four subtypes. All patients received hormonal therapy combined with hysteroscopy. Therapeutic effects were evaluated by hysteroscopy every three months during the treatment.

Results

Patients with POLE mutations had the highest disease progression rate (50.0%, P=0.013), while the microsatellite instability-high (MSI-H) group had the highest recurrence rate (50.0%, P=0.042). PIK3CA mutation (hazard ratio (HR): 0.61; 95% confidence interval (CI): 0.37-0.99; P=0.046), overweight (HR: 0.56; 95% CI: 0.32-0.96; P=0.033) and obesity (HR: 0.44; 95% CI: 0.20-0.95; P=0.036) were associated with a significantly lower cumulative complete response (CR) rate. The combination of gonadotropin-releasing hormone analogues (GnRH-a) and letrozole (HR: 3.43; 95% CI: 1.81-6.52; P< 0.001) was associated with a significantly higher cumulative CR rate. KRAS mutation was significantly associated with disease progression (P=0.002). In wild-type TP53 patients, PTEN and PIK3CA mutations significantly prolonged the duration of treatment to achieve CR (log rank P=0.034; P=0.018).

Conclusion

The implementation of molecular classification for EC patients undergoing fertility-sparing treatment is promising and can facilitate the selection of appropriate medical regimes to achieve better outcomes in patients with EC who require fertility preservation treatment.

Prognostic value of lymphovascular space invasion according to the molecular subgroups in endometrial cancer

OBJECTIVE

Lymphovascular space invasion (LVSI) is a known prognostic factor for oncological outcome in endometrial cancer patients. However, little is known about the prognostic value of LVSI among the different molecular subgroups. The aim of this study was to determine the prognostic dependence of LVSI from the molecular signature.

METHODS

This study included endometrial cancer patients who underwent primary surgical treatment between February 2004 and February 2016 at the Karolinska University Hospital, Sweden and the Bern University Hospital, Switzerland (KImBer cohort). All cases had complete molecular analysis performed on the primary tumor according to the WHO Classification of Tumors, 5th edition. LVSI was reviewed by reference pathologists for all pathology slides.

RESULTS

A total of 589 endometrial cancer patients were included in this study, consisting of 40 POLEmut (polymerase epsilon ultramutated), 198 MMRd (mismatch repair deficient), 83 p53abn (p53 abnormal), and 268 NSMP (non-specific molecular profile) cases. Altogether, 17% of tumors showed LVSI: 25% of the POLEmut, 19% of the MMRd, 30% of the p53abn, and 10% of the NSMP cases. There was a significant correlation of LVSI with lymph node metastasis in the entire study cohort (p<0.001), remaining significant in the MMRd (p=0.020), p53abn (p<0.001), and NSMP (p<0.001) subgroups. Mean follow-up was 89 months (95% CI 86 to 93). The presence of LVSI significantly decreased recurrence-free survival among patients with MMRd, p53abn, and NSMP endometrial cancer, and overall survival in patients with p53abn and NSMP tumors. In patients with NSMP endometrial cancer, evidence of substantial LVSI remained a significant independent predictor of recurrence in multivariable Cox regression analysis including tumor stage and grade (HR 7.5, 95% CI 2.2 to 25.5, p=o.001).

CONCLUSION

The presence of LVSI was associated with recurrence in each subgroup of patients with MMRd, p53abn, and NSMP endometrial cancer, and LVSI remained an independent predictor of recurrence in NSMP endometrial cancer patients.

[Molecular classification of endometrial carcinoma-a short summary for clinical use]

BACKGROUND

Histopathological examination is still the backbone for the diagnosis and treatment decision making in endometrial carcinoma (EC). The binary classification of EC into type 1 (mostly endometrioid) and type 2 (mostly serous), although still helpful, showed overlapping clinical, morphological and molecular features and was not very prognostic discriminatory for all subtypes of EC.

METHODS

Analysing the most recent studies dealing with the molecular classification of EC and the recommendations of the German S3-guidelines for EC.

RESULTS AND CONCLUSION

Based on the comprehensive molecular study of The Cancer Genome Atlas Project (TCGA) four distinct molecular subtypes have been identified: EC with POLE mutation (POLEmut), with loss of mismatch repair proteins (MMR deficiency; dMMR), or with TP53 mutation (p53mut) and without any of these alterations, termed NSMP (no specific molecular profile). The molecular classification of EC presents a morphomolecular approach, based on histopathological evaluation (tumor diagnosis, subtyping, grading), immunohistochemistry (MMR, p53) and molecular analyses for POLE. The incorporation of this molecular classification is recommended for clinical use by the World Health Organisation (WHO) as well as many national guidelines and international societies. Due to the heterogeneity of NSMP-EC, which is the largest molecular group, additional research is indicated to further characterise these tumors.

Molecular Classification Predicts Response to Radiotherapy in the Randomized PORTEC-1 and PORTEC-2 Trials for Early-Stage Endometrioid Endometrial Cancer

PURPOSE

The molecular classification of endometrial cancer (EC) has proven to have prognostic value and is predictive of response to adjuvant chemotherapy. Here, we investigate its predictive value for response to external beam radiotherapy (EBRT) and vaginal brachytherapy (VBT) in early-stage endometrioid EC (EEC).

METHODS

Data of the randomized PORTEC-1 trial (n = 714) comparing pelvic EBRT with no adjuvant therapy in early-stage intermediate-risk EC and the PORTEC-2 trial (n = 427) comparing VBT with EBRT in early-stage high-intermediate-risk EC were used. Locoregional (including vaginal and pelvic) recurrence-free survival was compared between treatment groups across the four molecular classes using Kaplan-Meier's methodology and log-rank tests.

RESULTS

A total of 880 molecularly classified ECs, 484 from PORTEC-1 and 396 from PORTEC-2, were included. The majority were FIGO-2009 stage I EEC (97.2%). The median follow-up was 11.3 years. No locoregional recurrences were observed in EC with a pathogenic mutation of DNA polymerase-ε (POLEmut EC). In mismatch repair-deficient (MMRd) EC, locoregional recurrence-free survival was similar after EBRT (94.2%), VBT (94.2%), and no adjuvant therapy (90.3%; P = .74). In EC with a p53 abnormality (p53abn EC), EBRT (96.9%) had a substantial benefit over VBT (64.3%) and no adjuvant therapy (72.2%; P = .048). In EC with no specific molecular profile (NSMP EC), both EBRT (98.3%) and VBT (96.2%) yielded better locoregional control than no adjuvant therapy (87.7%; P < .0001).

CONCLUSION

The molecular classification of EC predicts response to radiotherapy in stage I EEC and may guide adjuvant treatment decisions. Omitting radiotherapy seems to be safe in POLEmut EC. The benefit of radiotherapy seems to be limited in MMRd EC. EBRT yields a significantly better locoregional recurrence-free survival than VBT or no adjuvant therapy in p53abn EC. VBT is the treatment of choice for NSMP EC as it is as effective as EBRT and significantly better than no adjuvant therapy for locoregional tumor control.

FIGO staging of endometrial cancer: 2023

INTRODUCTION

Many advances in the understanding of the pathologic and molecular features of endometrial cancer have occurred since the FIGO staging was last updated in 2009. Substantially more outcome and biological behavior data are now available regarding the several histological types. Molecular and genetic findings have accelerated since the publication of The Cancer Genome Atlas (TCGA) data and provide improved clarity on the diverse biological nature of this collection of endometrial cancers and their differing prognostic outcomes. The goals of the new staging system are to better define these prognostic groups and create substages that indicate more appropriate surgical, radiation, and systemic therapies.

METHODS

The FIGO Women's Cancer Committee appointed a Subcommittee on Endometrial Cancer Staging in October 2021, represented by the authors. Since then, the committee members have met frequently and reviewed new and established evidence on the treatment, prognosis, and survival of endometrial cancer. Based on these data, opportunities for improvements in the categorization and stratification of these factors were identified in each of the four stages. Data and analyses from the molecular and histological classifications performed and published in the recently developed ESGO/ESTRO/ESP guidelines were used as a template for adding the new subclassifications to the proposed molecular and histological staging system.

RESULTS

Based on the existing evidence, the substages were defined as follows: Stage I (IA1): non-aggressive histological type of endometrial carcinoma limited to a polyp or confined to the endometrium; (IA2) non-aggressive histological types of endometrium involving less than 50% of the myometrium with no or focal lymphovascular space invasion (LVSI) as defined by WHO criteria; (IA3) low-grade endometrioid carcinomas limited to the uterus with simultaneous low-grade endometrioid ovarian involvement; (IB) non-aggressive histological types involving 50% or more of the myometrium with no LVSI or focal LVSI; (IC) aggressive histological types, i.e. serous, high-grade endometrioid, clear cell, carcinosarcomas, undifferentiated, mixed, and other unusual types without any myometrial invasion. Stage II (IIA): non-aggressive histological types that infiltrate the cervical stroma; (IIB) non-aggressive histological types that have substantial LVSI; or (IIC) aggressive histological types with any myometrial invasion. Stage III (IIIA): differentiating between adnexal versus uterine serosa infiltration; (IIIB) infiltration of vagina/parametria and pelvic peritoneal metastasis; and (IIIC) refinements for lymph node metastasis to pelvic and para-aortic lymph nodes, including micrometastasis and macrometastasis. Stage IV (IVA): locally advanced disease infiltrating the bladder or rectal mucosa; (IVB) extrapelvic peritoneal metastasis; and (IVC) distant metastasis. The performance of complete molecular classification (POLEmut, MMRd, NSMP, p53abn) is encouraged in all endometrial cancers. If the molecular subtype is known, this is recorded in the FIGO stage by the addition of "m" for molecular classification, and a subscript indicating the specific molecular subtype. When molecular classification reveals p53abn or POLEmut status in Stages I and II, this results in upstaging or downstaging of the disease (IICmp53abn or IAmPOLEmut).

SUMMARY

The updated 2023 staging of endometrial cancer includes the various histological types, tumor patterns, and molecular classification to better reflect the improved understanding of the complex nature of the several types of endometrial carcinoma and their underlying biologic behavior. The changes incorporated in the 2023 staging system should provide a more evidence-based context for treatment recommendations and for the more refined future collection of outcome and survival data.

Molecular Classification of Endometrial Cancer and the 2023 FIGO Staging: Exploring the Challenges and Opportunities for Pathologists

This commentary explores the complexities of the FIGO 2023 staging system and the inclusion of The Cancer Genome Atlas's (TCGA) molecular classification in the management of endometrial cancer. It highlights the importance of histology as a prognostic tool, while scrutinizing the merits and demerits of its application to aggressive endometrial cancers. The commentary review sheds light on the recent introductions of lymphovascular space invasion (LVSI) and lymph node metastasis size in cancer staging. It outlines the difficulties in differentiating between synchronous and metastatic endometrial and ovarian cancers, underlining their implications on treatment strategies. Furthermore, the commentary discusses the integration of molecular classifications within the FIGO 2023 framework, emphasizing the pivotal yet challenging implementation of the pathogenic POLE mutation test. The commentary concludes by reaffirming the vital role of pathologists in executing the FIGO 2023 staging system.

Etiological relationship between lipid metabolism and endometrial carcinoma

Endometrial carcinoma (EC) has become one of the most common gynecological malignant neoplasms in developed countries worldwide. Studies have shown that this may be closely related to the abnormal metabolism of blood lipids, which was the most significant metabolic change in the human body in this cancer. In this review, we focus on the correlation between lipid metabolism and EC and discuss the evidence that abnormal lipid metabolism promotes an increase in EC growth and metabolism, as well as the regulatory mechanism and related signaling pathways involved in this relationship. In addition, we also discussed the research progress of targeted therapies and drug treatments for EC that act on lipid metabolism, and statins are expected to become adjuvant drugs for EC in the future. This review will provide a systematic view for a better understanding of the etiological relationship between lipid metabolism and EC and further open up new therapeutic possibilities and effective treatments for EC by targeting lipid metabolism.

Endometrial carcinoma: association between mutational status, sites of metastasis, recurrence, and correlation with overall survival

PURPOSE

To investigate the association between sites of endometrial carcinoma (EC) recurrence and metastases, mutational status, race, and overall survival (OS).

METHODS

This single-center retrospective study evaluated patients with biopsy-proven EC that underwent genomic molecular testing between January 2015 and July 2021. Association between genomic profile and sites of metastases or recurrence was performed using Pearson's chi-squared or Fisher exact test. Survival curves for ethnicity and race, mutations, sites of metastases or recurrence were estimated using the Kaplan-Meier method. Univariable and multivariable Cox proportional hazard regression models were used.

RESULTS

The study included 133 women [median age 64 years (IQR 57-69)]. The most common mutation was TP53 (65/105 patients, 62%). The most common site of metastasis was the peritoneum (35/43, 81%). The most common recurrence was in lymph nodes (34/75, 45%). Mutations of TP53 and PTEN were significantly associated with Black women (p = 0.048, p = 0.004, respectively). In the univariable Cox regression analyses, TP53 mutation and presence of recurrence or metastases to the peritoneum were associated with lower OS (HR 2.1; 95% CI 1.1, 4.3; p = 0.03/ HR 2.9; 95% CI 1.6, 5.4; p = 0.0004; respectively). On multivariable Cox proportional hazards model ER expression (HR 0.4; 95% CI 0.22, 0.91; p = 0.03), peritoneal recurrence or metastases (HR 3.55; 95% CI 1.67, 7.57; p = 0.001), and Black race (HR 2.2; 95% CI 1.1, 4.6; p = 0.03) were significant independent predictors of OS.

CONCLUSIONS

The integration of EC mutational status and clinicopathological risk assessment demonstrated potential implications on the patterns of metastasis, recurrence, and OS.

FIGO staging of endometrial cancer: 2023

INTRODUCTION

Many advances in the understanding of the pathologic and molecular features of endometrial cancer have occurred since the FIGO staging was last updated in 2009. Substantially more outcome and biological behavior data are now available regarding the several histological types. Molecular and genetic findings have accelerated since the publication of The Cancer Genome Atlas (TCGA) data and provide improved clarity on the diverse biological nature of this collection of endometrial cancers and their differing prognostic outcomes. The goals of the new staging system are to better define these prognostic groups and create substages that indicate more appropriate surgical, radiation, and systemic therapies.

METHODS

The FIGO Women's Cancer Committee appointed a Subcommittee on Endometrial Cancer Staging in October 2021, represented by the authors. Since then, the committee members have met frequently and reviewed new and established evidence on the treatment, prognosis, and survival of endometrial cancer. Based on these data, opportunities for improvements in the categorization and stratification of these factors were identified in each of the four stages. Data and analyses from the molecular and histological classifications performed and published in the recently developed ESGO/ESTRO/ESP guidelines were used as a template for adding the new subclassifications to the proposed molecular and histological staging system.

RESULTS

Based on the existing evidence, the substages were defined as follows: Stage I (IA1): non-aggressive histological type of endometrial carcinoma limited to a polyp or confined to the endometrium; (IA2) non-aggressive histological types of endometrium involving less than 50% of the myometrium with no or focal lymphovascular space invasion (LVSI) as defined by WHO criteria; (IA3) low-grade endometrioid carcinomas limited to the uterus with simultaneous low-grade endometrioid ovarian involvement; (IB) non-aggressive histological types involving 50% or more of the myometrium with no LVSI or focal LVSI; (IC) aggressive histological types, i.e. serous, high-grade endometrioid, clear cell, carcinosarcomas, undifferentiated, mixed, and other unusual types without any myometrial invasion. Stage II (IIA): non-aggressive histological types that infiltrate the cervical stroma; (IIB) non-aggressive histological types that have substantial LVSI; or (IIC) aggressive histological types with any myometrial invasion. Stage III (IIIA): differentiating between adnexal versus uterine serosa infiltration; (IIIB) infiltration of vagina/parametria and pelvic peritoneal metastasis; and (IIIC) refinements for lymph node metastasis to pelvic and para-aortic lymph nodes, including micrometastasis and macrometastasis. Stage IV (IVA): locally advanced disease infiltrating the bladder or rectal mucosa; (IVB) extrapelvic peritoneal metastasis; and (IVC) distant metastasis. The performance of complete molecular classification (POLEmut, MMRd, NSMP, p53abn) is encouraged in all endometrial cancers. If the molecular subtype is known, this is recorded in the FIGO stage by the addition of "m" for molecular classification, and a subscript indicating the specific molecular subtype. When molecular classification reveals p53abn or POLEmut status in Stages I and II, this results in upstaging or downstaging of the disease (IICmp53abn or IAmPOLEmut ).

SUMMARY

The updated 2023 staging of endometrial cancer includes the various histological types, tumor patterns, and molecular classification to better reflect the improved understanding of the complex nature of the several types of endometrial carcinoma and their underlying biologic behavior. The changes incorporated in the 2023 staging system should provide a more evidence-based context for treatment recommendations and for the more refined future collection of outcome and survival data.

Endometrial Cancer. Guideline of the DGGG, DKG and DKH (S3-Level, AWMF Registry Number 032/034-OL, September 2022). Part 1 with Recommendations on the Epidemiology, Screening, Diagnosis and Hereditary Factors of Endometrial Cancer, Geriatric Assessment and Supply Structures

Summary The S3-guideline on endometrial cancer, first published in April 2018, was reviewed in its entirety between April 2020 and January 2022 and updated. The review was carried out at the request of German Cancer Aid as part of the Oncology Guidelines Program and the lead coordinators were the German Society for Gynecology and Obstetrics (DGGG), the Gynecology Oncology Working Group (AGO) of the German Cancer Society (DKG) and the German Cancer Aid (DKH). The guideline update was based on a systematic search and assessment of the literature published between 2016 and 2020. All statements, recommendations and background texts were reviewed and either confirmed or amended. New statements and recommendations were included where necessary. Aim The use of evidence-based risk-adapted therapies to treat women with endometrial cancer of low risk prevents unnecessarily radical surgery and avoids non-beneficial adjuvant radiation therapy and/or chemotherapy. For women with endometrial cancer and a high risk of recurrence, the guideline defines the optimum level of radical surgery and indicates whether chemotherapy and/or adjuvant radiation therapy is necessary. This should improve the survival rates and quality of life of these patients. The S3-guideline on endometrial cancer and the quality indicators based on the guideline aim to provide the basis for the work of certified gynecological cancer centers. Methods The guideline was first compiled in 2018 in accordance with the requirements for S3-level guidelines and was updated in 2022. The update included an adaptation of the source guidelines identified using the German Instrument for Methodological Guideline Appraisal (DELBI). The update also used evidence reviews which were created based on selected literature obtained from systematic searches in selected literature databases using the PICO process. The Clinical Guidelines Service Group was tasked with carrying out a systematic search and assessment of the literature. Their results were used by interdisciplinary working groups as a basis for developing suggestions for recommendations and statements which were then modified during structured online consensus conferences and/or additionally amended online using the DELPHI process to achieve a consensus. Recommendations Part 1 of this short version of the guideline provides recommendations on epidemiology, screening, diagnosis, and hereditary factors. The epidemiology of endometrial cancer and the risk factors for developing endometrial cancer are presented. The options for screening and the methods used to diagnose endometrial cancer are outlined. Recommendations are given for the prevention, diagnosis, and therapy of hereditary forms of endometrial cancer. The use of geriatric assessment is considered and existing structures of care are presented.

Prediction of Prognosis, Immunotherapy and Chemotherapy with an Immune-Related Risk Score Model for Endometrial Cancer

Endometrial cancer (EC) is the most common gynecologic cancer. The overall survival remains unsatisfying due to the lack of effective treatment screening approaches. Immunotherapy as a promising therapy has been applied for EC treatment, but still fails in many cases. Therefore, there is a strong need to optimize the screening approach for clinical treatment. In this study, we employed co-expression network (GCN) analysis to mine immune-related GCN modules and key genes and further constructed an immune-related risk score model (IRSM). The IRSM was proved effective as an independent predictor of poor prognosis. The roles of IRSM-related genes in EC were confirmed by IHC. The molecular basis, tumor immune microenvironment and clinical characteristics of the IRSM were revealed. Moreover, the IRSM effectiveness was associated with immunotherapy and chemotherapy. Patients in the low-risk group were more sensitive to immunotherapy and chemotherapy than those in the high-risk group. Interestingly, the patients responding to immunotherapy were also more sensitive to chemotherapy. Overall, we developed an IRSM which could be used to predict the prognosis, immunotherapy response and chemotherapy sensitivity of EC patients. Our analysis not only improves the treatment of EC but also offers targets for personalized therapeutic interventions.

Integration of clinical sequencing and immunohistochemistry for the molecular classification of endometrial carcinoma

PURPOSE

Using next generation sequencing (NGS), The Cancer Genome Atlas (TCGA) found that endometrial carcinomas (ECs) fall under one of four molecular subtypes, and a POLE mutation status, mismatch repair (MMR) and p53 immunohistochemistry (IHC)-based surrogate has been developed. We sought to retrospectively classify and characterize a large series of unselected ECs that were prospectively subjected to clinical sequencing by utilizing clinical molecular and IHC data.

EXPERIMENTAL DESIGN

All patients with EC with clinical tumor-normal MSK-IMPACT NGS from 2014 to 2020 (n = 2115) were classified by integrating molecular data (i.e., POLE mutation, TP53 mutation, MSIsensor score) and MMR and p53 IHC results. Survival analysis was performed for primary EC patients with upfront surgery at our institution.

RESULTS

Utilizing our integrated approach, significantly more ECs were molecularly classified (1834/2115, 87%) as compared to the surrogate (1387/2115, 66%, p < 0.001), with an almost perfect agreement for classifiable cases (Kappa 0.962, 95% CI 0.949-0.975). Discrepancies were primarily due to TP53 mutations in p53-IHC-normal ECs. Of the 1834 ECs, most were of copy number (CN)-high molecular subtype (40%), followed by CN-low (32%), MSI-high (23%) and POLE (5%). Histologic and genomic variability was present amongst all molecular subtypes. Molecular classification was prognostic in early- and advanced-stage disease, including early-stage endometrioid EC.

CONCLUSIONS

The integration of clinical NGS and IHC data allows for an algorithmic approach to molecularly classifying newly diagnosed EC, while overcoming issues of IHC-based genetic alteration detection. Such integrated approach will be important moving forward given the prognostic and potentially predictive information afforded by this classification.

Targeted Molecular Testing in Endometrial Carcinoma: Validation of a Clinically Driven Selective ProMisE Testing Protocol

Incorporation of molecular classification into clinicopathologic assessment of endometrial carcinoma (EC) improves risk stratification. Four EC molecular subtypes, as identified by The Cancer Genome Atlas, can be diagnosed through a validated algorithm Pro active M olecular R is k Classifier for E ndometrial Cancer (ProMisE) using p53 and mismatch repair (MMR) protein immunohistochemistry (IHC), and DNA polymerase epsilon ( POLE) mutational testing. Cost and access are major barriers to universal testing, particularly POLE analysis. We assessed a selective ProMisE algorithm (ProMisE-S): p53 and MMR IHC on all EC's with POLE testing restricted to those with abnormal MMR or p53 IHC (to identify POLEmut EC with secondary abnormalities in MMR and/or p53) and those with high-grade or non-endometrioid morphology, stage >IA or presence of lymphovascular space invasion (so as to avoid testing on the lowest risk tumors). We retrospectively compared the known ProMisE molecular classification to ProMisE-S in 912 EC. We defined a group of "very low-risk" EC (G1/G2, endometrioid, MMR-proficient, p53 wild-type, stage IA, no lymphovascular space invasion) in whom POLE testing will not impact on patient care; using ProMisE-S, POLE testing would not be required in 55% of biopsies and 38% of all EC's, after evaluation of the hysterectomy specimen, in a population-based cohort. "Very low-risk" endometrioid EC with unknown POLE status showed excellent clinical outcomes. Fifteen of 166 (9%) of all p53abn EC showed G1/G2 endometrioid morphology, supporting the potential value of universal p53 IHC. The addition of molecular testing changed the risk category in 89/896 (10%) EC's. In routine practice, POLE testing could be further restricted to only those patients in whom this would alter adjuvant therapy recommendations.

Construction of the novel immune risk scoring system related to CD8+ T cells in uterine corpus endometrial carcinoma

BACKGROUND

Uterine corpus endometrial carcinoma (UCEC) is a gynecological malignant tumor with high incidence and poor prognosis. Although immunotherapy has brought significant survival benefits to advanced UCEC patients, traditional evaluation indicators cannot accurately identify all potential beneficiaries of immunotherapy. Consequently, it is necessary to construct a new scoring system to predict patient prognosis and responsiveness of immunotherapy.

METHODS

CIBERSORT combined with weighted gene co-expression network analysis (WGCNA), non-negative matrix factorization (NMF), and random forest algorithms to screen the module associated with CD8⁺ T cells, and key genes related to prognosis were selected out by univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses to develop the novel immune risk score (NIRS). Kaplan-Meier (K-M) analysis was used to compare the difference of survival between high- and low- NIRS groups. We  also explored the correlations between NIRS, immune infiltration and immunotherapy, and three external validation sets were used to verify the predictive performance of NIRS. Furthermore, clinical subgroup analysis, mutation analysis, differential expression of immune checkpoints, and drug sensitivity analysis were performed to generate individualized treatments for patients with different risk scores. Finally, gene set variation analysis (GSVA) was conducted to explore the biological functions of NIRS, and qRT-PCR was applied to verify the differential expressions of three trait genes at cellular and tissue levels.

RESULTS

Among the modules clustered by WGCNA, the magenta module was most positively associated with CD8⁺ T cells. Three genes (CTSW, CD3D and CD48) were selected to construct NIRS after multiple screening procedures. NIRS was confirmed as an independent prognostic factor of UCEC, and patients with high NIRS had significantly worse prognosis compared to those with low NIRS. The high NIRS group showed lower levels of infiltrated immune cells, gene mutations, and expression of multiple immune checkpoints, indicating reduced sensitivity to immunotherapy. Three module genes were identified as protective factors positively correlated with the level of CD8⁺ T cells.

CONCLUSIONS

In this study, we constructed NIRS as a novel predictive signature of UCEC. NIRS not only differentiates patients with distinct prognoses and immune responsiveness, but also guides their therapeutic regimens.

Cost-effectiveness analysis of tumor molecular testing in stage III endometrial cancer

BACKGROUND

Standard of care for adjuvant treatment of stage III endometrial cancer includes chemotherapy and radiation. In addition to stage, tumor molecular profiles may predict treatment outcomes, and prospective clinical trials are ongoing. However, tumor molecular testing is costly and time-consuming. Our objective was to evaluate the cost-effectiveness of tumor molecular testing in stage III endometrial cancer.

METHODS

A Markov decision model compared two strategies for stage III endometrial cancer: Tumor Molecular Testing (TMT) versus No TMT. TMT included sequential POLE next generation sequencing, mismatch repair immunohistochemistry (IHC), and p53 IHC. POLE-mutated patients were assigned to adjuvant radiation therapy; all others including controls were assigned to adjuvant chemoradiation. First recurrences were treated with 6 cycles of carboplatin and paclitaxel. Second recurrences were treated with pembrolizumab alone for mismatch repair deficient patients and both pembrolizumab and lenvatinib for other patients. Sensitivity analyses were performed to test model robustness.

RESULTS

Compared to No TMT, TMT was cost saving with equivalent effectiveness. On one-way sensitivity analysis, TMT remained cost saving over all parameter ranges. TMT was also favored on probabilistic sensitivity analysis in 80% of iterations at a willingness-to-pay threshold of $100,000/quality adjusted life-year (QALY) gained. However, when TMT was compared to mismatch repair IHC alone, TMT cost $182,798/QALY gained.

CONCLUSIONS

In this model of patients with stage III endometrial cancer, TMT was cost saving compared to No TMT. However, when compared to mismatch repair IHC alone, TMT was economically unfavorable.

"Surface epithelial slackening" pattern in endometrioid carcinoma: A morphological feature for differentiating the POLE mutation-subtype from the no specific molecular profile subtype

Endometrial cancers are classified into mismatch repair (MMR) deficient- (MMRd), p53 mutation- (p53mut), DNA polymerase epsilon (POLE) mutation (POLEmut), and no specific molecular profile (NSMP) subtypes according to The Cancer Genome Atlas (TCGA). The distinction between POLEmut and NSMP subtypes is made on the basis of molecular analysis because the specific histological and immunohistochemical features of these two subtypes are still unknown. In this study, we analyzed histological features by scoring the presence of a mucinous pool, giant cells, clear cells, keratinization, neutrophilic abscess, and surface proliferating pattern in 82 cases of endometrial cancers in which an integrative diagnosis was confirmed by immunohistochemistry and genomic profiles showing POLE mutations, tumor mutation burden, and microsatellite instability. In contrast to the hierarchical branching of micropapillary proliferation observed in serous carcinoma, POLEmut-subtype endometrioid carcinomas often showed a surface epithelial slackening (SES) pattern in the tumor cells facing the uterine surface. The POLEmut subtype exhibited higher scores for clear cells and SES patterns than the other three subtypes. The scores for giant cells, clear cells, and the SES pattern were significantly higher in the POLEmut subtype than in the NSMP subtype, suggesting that these morphometric parameters are useful for differentiating POLEmut- and NSMP-subtype endometrioid carcinomas, although genomic profiling is still necessary for a definite molecular diagnosis.

Circulating and Endometrial Tissue microRNA Markers Associated with Endometrial Cancer Diagnosis, Prognosis, and Response to Treatment

In developed countries, endometrial cancer (EC) is one of the most common neoplasms of the female reproductive system. MicroRNAs (miRs) are a class of single-stranded noncoding RNA molecules with lengths of 19-25 nucleotides that bind to target messenger RNA (mRNA) to regulate post-transcriptional gene expression. Although there is a large amount of research focused on identifying miRs with a diagnostic, prognostic, or response to treatment capacity in EC, these studies differ in terms of experimental methodology, types of samples used, selection criteria, and results obtained. Hence, there is a large amount of heterogeneous information that makes it difficult to identify potential miR biomarkers. We aimed to summarize the current knowledge on miRs that have been shown to be the most suitable potential markers for EC. We searched PubMed and Google Scholar without date restrictions or filters. We described 138 miRs with potential diagnostic, prognostic, or treatment response potential in EC. Seven diagnostic panels showed higher sensitivity and specificity for the diagnosis of EC than individual miRs. We further identified miRs up- or downregulated depending on the FIGO stage, precursor lesions, and staging after surgery, which provides insight into which miRs are expressed chronologically depending on the disease stage and/or that are modulated depending on the tumor grade based on histopathological evaluation.