High-Grade Endometrial Carcinomas: Classification with Molecular Insights

Features of the immunosuppressive tumor microenvironment in endometrial cancer based on molecular subtype

Endometrial cancer (EC) is one of the three most prevalent gynecological tumors affecting women and is the most prevalent gynecological malignancy in the developed world. Its incidence is rapidly increasing worldwide, mostly affecting postmenopausal women, whereas recently its prevalence has increased in younger people. EC is an immune gene disease and many studies have shown that the tumor-immunosuppressive microenvironment plays an important role in cancer progression. In recent years, findings regarding the immunosuppressive tumor microenvironment (ITME) of EC have included immune evasion mechanisms and immunotherapy, which are mostly immune checkpoint inhibitors (ICI) for EC. Recently studies on the ITME of different molecular types of EC have found that different molecular types may have different ITME. With the research on the immune microenvironment of EC, a new immunophenotype classification based on the immune microenvironment has been carried out in recent years. However, the impact of the ITME on EC remains unclear, and the immunophenotype of EC remains limited to the research stage. Our review describes recent findings regarding the ITME features of different EC molecular types. The advent of immunotherapy has brought hope for improved efficacy and prognosis in patients with advanced or recurrent EC. The efficacy and safety of ICIs combination therapy remains the focus of future research.

Metabolism-associated molecular classification of uterine corpus endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is one of the most common gynecologic malignancies. Currently, for UCEC cancer, molecular classification based on metabolic gene characteristics is rarely established. Here, we describe the molecular subtype features of UCEC by classifying metabolism-related gene profiles. Therefore, integrative analysis was performed on UCEC patients from the TCGA public database. Consensus clustering of RNA expression data on 2,752 previously reported metabolic genes identified two metabolic subtypes, namely, C1 and C2 subtypes. Two metabolic subtypes for prognostic characteristics, immune infiltration, genetic alteration, and responses to immunotherapy existed with distinct differences. Then, differentially expressed genes (DEGs) among the two metabolic subtypes were also clustered into two subclusters, and the aforementioned features were similar to the metabolic subtypes, supporting that the metabolism-relevant molecular classification is reliable. The results showed that the C1 subtype has high metabolic activity, high immunogenicity, high gene mutation, and a good prognosis. The C2 subtype has some features with low metabolic activity, low immunogenicity, high copy number variation (CNV) alteration, and poor prognosis. Finally, a model was identified, with three gene metabolism-related signatures, which can predict the prognosis. These findings of this study demonstrate a new classification in UCEC based on the metabolic pattern, thereby providing valuable information for understanding UCEC's molecular characteristics.

COVID-19–associated lncRNAs as predictors of survival in uterine corpus endometrial carcinoma: A prognostic model

Background: Patients with uterine corpus endometrial carcinoma (UCEC) may be susceptible to the coronavirus disease-2019 (COVID-19). Long non–coding RNAs take on a critical significance in UCEC occurrence, development, and prognosis. Accordingly, this study aimed to develop a novel model related to COVID-19–related lncRNAs for optimizing the prognosis of endometrial carcinoma.

Methods: The samples of endometrial carcinoma patients and the relevant clinical data were acquired in the Carcinoma Genome Atlas (TCGA) database. COVID-19–related lncRNAs were analyzed and obtained by coexpression. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were performed to establish a COVID-19–related lncRNA risk model. Kaplan–Meier analysis, principal component analysis (PCA), and functional enrichment annotation were used to analyze the risk model. Finally, the potential immunotherapeutic signatures and drug sensitivity prediction targeting this model were also discussed.

Results: The risk model comprising 10 COVID-19–associated lncRNAs was identified as a predictive ability for overall survival (OS) in UCEC patients. PCA analysis confirmed a reliable clustering ability of the risk model. By regrouping the patients with this model, different clinic-pathological characteristics, immunotherapeutic response, and chemotherapeutics sensitivity were also observed in different groups.

Conclusion: This risk model was developed based on COVID-19–associated lncRNAs which would be conducive to the precise treatment of patients with UCEC.

Identification of the prognostic value of a 2-gene signature of the WNT gene family in UCEC using bioinformatics and real-world data

Background

The WNT gene family plays an important role in the occurrence and development of malignant tumors, but its involvement has not been systematically analyzed in uterine corpus endometrial carcinoma (UCEC). This study aimed to evaluate the prognostic value of the WNT gene family in UCEC.

Methods

Pan-cancer transcriptome data of the UCSC Xena database and Genotype-Tissue Expression (GTEx) normal tissue data were downloaded to analyze the expression and prognosis of 19 WNT family genes in UCEC. A cohort from The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma (TCGA-UCEC) was used to analyze the expression of the WNT gene family in different immune subtypes and clinical subgroups. The STRING database was used to analyze the interaction of the WNT gene family and its biological function. Univariate Cox regression analysis and Lasso cox analysis were used to identify the genes associated with significant prognosis and to construct multi signature prognosis model. An immunohistochemical assay was used to verify the predictive ability of the model. Risk score and the related clinical features were used to construct a nomogram.

Results

The expression levels of WNT2, WNT3, WNT3A, WNT5A, WNT7A, and WNT10A were significantly different among different immune subtypes and correlated with TP53 mutation. According to the WNT family genes related to the prognosis of UCEC, UCEC was classified into two subtypes (C1, C2). The prognosis of subtype C1 was significantly better than that of subtype C2. A 2-gene signature (WNT2 and WNT10A) was constructed and the two significantly prognostic groups can be divided based on median Risk score. These results were verified using real-world data, and the nomogram constructed using clinical features and Risk score had good prognostic ability.

Conclusions

The 2-gene signature including WNT2 and WNT10A can be used to predict the prognosis of patients with UCEC, which is important for clinical decision-making and individualized therapy for patients with UCEC.

Researches on the Correlation Between Estrogen and Progesterone Receptors Expression and Disease-Free Survival of Endometrial Cancer

Objective

In this study, 345 patients with endometrial carcinoma (EC) were selected to investigate the correlation between ER/PR status and the EC disease-free survival (DFS) rate.

Methods

The intensity and proportion of tumor cell expression of estrogen receptors and progesterone receptors (ER/PR) status of 345 postoperative tumor specimens in ECs were independently assessed semi-quantitatively by two pathologists using immunohistochemistry, the summed score ranged from 0 to 8 points was worked out by adding proportion score and intensity score based on the breast cancer hormone receptor immunohistochemical Allred scoring system. The association between DFS in ECs and ER/PR expression (intensity, proportion and summed score) was assessed using Cox regression analysis. Gene expression data were obtained from The Cancer Genome Atlas research network (TCGA).

Results

According to inclusion criteria, 201 type I and 144 type II EC patients were enrolled in this study. In the univariate analysis of type I endometrial carcinoma, the intensity, proportion and summed score of ER/PR status were significantly correlated with DFS. After adjusting for factors known to significantly impact survival, the influence of ER/PR status on DFS is generally decreased but the correlation is still significant. In the univariate analysis of type II endometrial carcinoma, the intensity, proportion and summed score of ER/PR status were significantly correlated with DFS. After adjusting for factors known to significantly impact survival, the influence of ER status on DFS is generally decreased, but the correlation is still significant, the effect of PR expression on DFS is not statistically significant.

Conclusion

Higher ER/PR expression status was associated with better DFS in patients with type I endometrial cancer after adjusting for known factors that significantly affect survival. In patients with type II endometrial cancer, patients with positive ER expression were significantly associated with better DFS. However, the effect of PR expression on DFS was not statistically significant.

Interobserver diagnostic reproducibility in advanced-stage endometrial carcinoma

Background

The accurate pathologic diagnosis and subtyping of high-grade endometrial carcinoma are often problematic, due to its atypical and overlapping histopathological features.

Methods

Three pathologists reviewed 21 surgically resected cases of advanced-stage endometrial carcinoma. The primary diagnosis was based only on hematoxylin and eosin stained slides. When a discrepancy arose, a secondary diagnosis was made by additional review of immunohistochemical (IHC) stains. Finally, three pathologists discussed all cases and rendered a consensus diagnosis.

Results

The primary diagnoses were identical in 13/21 cases (62%). The secondary diagnosis based on the addition of IHC results was concordant in four of eight discrepant cases. Among four cases with discrepancies occurring in this step, two cases subsequently reached a consensus diagnosis after a thorough discussion between three reviewers. Next-generation sequencing (NGS) study was performed in two cases in which it was difficult to distinguish between serous carcinoma and endometrioid carcinoma. Based on the sequencing results, a final diagnosis of serous carcinoma was rendered. The overall kappa for concordance between the original and consensus diagnosis was 0.566 (moderate agreement).

Conclusions

We investigated stepwise changes in interobserver diagnostic reproducibility in advanced-stage endometrial carcinoma. We demonstrated the utility of IHC and NGS study results in the histopathological diagnosis of advanced-stage endometrial carcinoma.

DNA Mismatch Repair-deficient Endometrial Carcinosarcomas Portend Distinct Clinical, Morphologic, and Molecular Features Compared With Traditional Carcinosarcomas

Uterine carcinosarcomas (UCSs) are aggressive neoplasms composed of high-grade malignant epithelial and mesenchymal elements with most (∼90%) showing TP53 abnormalities. A subset, however, shows mismatch repair deficiency (MMR-D). We sought to describe their clinical, morphologic, and molecular features. Clinicopathologic data of MMR-D UCSs were recorded including age, stage, follow-up, mismatch repair and p53 immunohistochemistry (IHC), MLH1 promoter methylation status, and germline alterations, TP53 mutation status, microsatellite instability and mutational burden by massively parallel sequencing. Seventeen (6.2%) MMR-D were identified among 276 UCSs. Of MMR-D UCSs, the median age was 60 years. mismatch repair IHC loss is as follows: MLH1/PMS2 65%, MSH2/MSH6 18%, MSH6 12%, and PMS2 6%. MLH1 promoter methylation and Lynch syndrome was identified in 47% and 12% of cases, respectively. Cases with p53 IHC showed the following patterns: wild-type 70%, aberrant 20%, and equivocal 10%. Of cases with sequencing, 88% were hypermutated and microsatellite instability high. High-grade endometrioid, undifferentiated, and clear cell carcinoma was present in 53%, 41%, and 6% of cases, respectively and 47% also showed a low-grade endometrioid component. Most patients presented at an early stage (67%) and upon follow-up, 18% died of disease, 65% showed no evidence of disease, while 18% are alive with disease. Patients with MMR-D UCS are younger than the reported median age (70 y) for traditional UCS and most do not show p53 abnormalities. Low-grade endometrioid and undifferentiated carcinoma were seen in approximately half of all cases. Although UCSs have a high tendency for early extrauterine spread, most patients in our cohort presented at an early stage and at follow-up were no evidence of disease. MMR-D UCSs display distinct clinical, morphologic, and molecular features compared with traditional UCSs.

ACE2 correlated with immune infiltration serves as a prognostic biomarker in endometrial carcinoma and renal papillary cell carcinoma: implication for COVID-19

Angiotensin-converting enzyme 2 (ACE2) is a member of the renin-angiotension system, however, the correlation between ACE2 and prognosis in UCEC (Uterine Corpus Endometrial Carcinoma) and KIRP (Kidney Renal Papillary Cell Carcinoma) is not clear. We analyzed the expression levels of ACE2 in the Oncomine and TIMER databases, the correlation between ACE2 and overall survival in the PrognoScan, GEPIA and Kaplan-Meier plotter databases. The correlation between ACE2 and immune infiltration level and the type markers of immune cells was investigated in TIMER database. A prognosis analysis based on the expression levels of ACE2 was further performed in related immune cells subgroup. The ACE2 promoter methylation profile was tested in the UALCAN database. In addition, we used GSE30589 and GSE52920 databases to elucidate the changes of ACE2 expression in vivo and in vitro after SARS-CoV infection. ACE2 was elevated in UCEC and KIRP, and high ACE2 had a favorable prognosis. The expression of ACE2 was positively correlated with the level of immune infiltration of macrophage in KIRP, B cell, CD4+T cell, neutrophil and dendritic cell immune infiltration levels in UCEC. ACE2 was significantly positively correlated with the type markers of B cells and neutrophils, macrophages in UCEC, while ACE2 in KIRP was positively correlated with the type markers of macrophages. High ACE2 expression level had a favorable prognosis in different enriched immune cells subgroups in UCEC and KIRP. And the promoter methylation levels of ACE2 in UCEC and KIRP were significantly reduced. What's more, we found that the expression of ACE2 decreased in vivo and in vitro after SARS-CoV infection. In conclusion, ACE2 expression increased significantly in UCEC and KIRP, elevated ACE2 was positively correlated with immune infiltration and prognosis. Moreover, tumor tissues may be more susceptible to SARS-CoV-2 infection in COVID-19 patients with UCEC and KIRP, which may worsen the prognosis.