The landscape and prognostic value of immune characteristics in uterine corpus endometrial cancer

Comprehensive analysis of a NAD+ metabolism-derived gene signature to predict the prognosis and immune landscape in endometrial cancer

As a crucial regulator influencing tumor progression, nicotinamide adenine dinucleotide (NAD+) is widely acknowledged. However, its role in endometrial cancer (EC) is not completely understood. In this study, we aimed to develop an NAD+metabolic-related genes (NMRGs) risk signature that could reflect the prognosis of EC patients and their responsiveness to immunotherapy and chemotherapy. Data from The Cancer Genome Atlas (TCGA) databases and the Molecular Signatures Database (MSigDB) confirmed two distinct NMRG subtypes in EC patients using consensus clustering, and a risk score was constructed utilizing an NAD+-related prognostic signature depending on the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Receiver operating characteristic (ROC) curves were employed to assess the model's precision. Additionally, we used Gene Set Enrichment Analysis (GSEA) to predict the biological signaling pathways that might be involved. We also explored the role of the risk score in immune cell infiltration, tumor mutation burden (TMB), immunotherapy, and chemotherapy. Our study established a prognostic risk signature based on six NMRGs, and we observed that the high-risk group was associated with a poorer prognosis. Furthermore, we identified a strong correlation between the high-risk group and several pathways, including DNA replication, cell cycle, and mismatch repair. Lastly, our findings highlighted the influence of NMRGs on the regulation of immune infiltration in EC. Therefore, this signature holds potential value in predicting the prognosis of EC patients and guiding their management, including decisions regarding immunotherapy and chemotherapy, ultimately improving the accuracy of EC patient care.

Machine learning endometrial cancer risk prediction model: integrating guidelines of European Society for Medical Oncology with the tumor immune framework

OBJECTIVE

Current prognostic factors for endometrial cancer are not sufficient to predict recurrence in early stages. Treatment choices are based on the prognostic factors included in the risk classes defined by the ESMO-ESGO-ESTRO (European Society for Medical Oncology-European Society of Gynaecological Oncology-European Society for Radiotherapy and Oncology) consensus conference with the new biomolecular classification based on POLE, TP53, and microsatellite instability status. However, a minority of early stage cases relapse regardless of their low risk profiles. Integration of the immune context status to existing molecular based models has not been fully evaluated. This study aims to investigate whether the integration of the immune landscape in the tumor microenvironment could improve clinical risk prediction models and allow better profiling of early stages.

METHODS

Leveraging the potential of in silico deconvolution tools, we estimated the relative abundances of immune populations in public data and then applied feature selection methods to generate a machine learning based model for disease free survival probability prediction.

RESULTS

We included information on International Federation of Gynecology and Obstetrics (FIGO) stage, tumor mutational burden, microsatellite instability, POLEmut status, interferon γ signature, and relative abundances of monocytes, natural killer cells, and CD4+T cells to build a relapse prediction model and obtained a balanced accuracy of 69%. We further identified two novel early stage profiles that undergo different pathways of recurrence.

CONCLUSION

This study presents an extension of current prognostic factors for endometrial cancer by exploiting machine learning models and deconvolution techniques on available public biomolecular data. Prospective clinical trials are advisable to validate the early stage stratification.

Killer Cell Immunoglobulin-like Receptor Genotypes and Reproductive Outcomes in a Group of Infertile Women: A Romanian Study

A growing body of evidence suggests that endometrial immune disorders may be responsible for endometrial dysfunctions that can lead to gynecological and obstetrical pathology. The aim of this study was to explore the potential relationship between different killer cell immunoglobulin-like receptor (KIR) genotypes and reproductive outcomes. We conducted a prospective cohort study that included 104 infertile patients undergoing an in vitro fertilization procedure. All participants underwent clinical and ultrasound examination, genetic evaluation (KIR genotyping), endometrial washing fluid sampling for cytokine determination, endometrial tissue sampling for histologic assessment and hysteroscopic evaluation. Our analysis showed statistically significant lower levels of uterine cytokines TNF-α (p = 0.001) and IL-1beta (p = 0.000) in the KIR AA genotype group as compared to KIR AB and BB among study participants with chronic endometritis. The study results suggest that the KIR AA genotype population subgroups may be more susceptible to developing endometrial disorders such as chronic endometritis. The changes in the behavior of NK cells seem to be subtle and expressed as an altered regulatory pattern.

Case Report: Cord blood-derived natural killer cells as new potential immunotherapy drug for solid tumor: a case study for endometrial cancer

Adoptive transfer of natural killer (NK) cells represents a viable treatment method for patients with advanced malignancies. Our team previously developed a simple, safe, and cost-effective method for obtaining high yields of pure and functional NK cells from cord blood (CB) without the need for cell sorting, feeder cells, or multiple cytokines. We present the case of a 52-year-old female patient diagnosed with poorly differentiated stage IVB (T3N2M1) endometrial cancer, who exhibited leukemoid reaction and pretreatment thrombocytosis as paraneoplastic syndromes. The patient received two courses of CB-derived NK (CB-NK) cell immunotherapy between March and September 2022, due to her extremely low NK cell activity. Two available CB units matched at 8/10 HLA with KIR-mismatch were chosen, and we were able to produce NK cells with high yield (>1.0×10¹⁰ NK cells), purity (>90%), and function (>80%) from CB without cell sorting, feeder cells, or multiple cytokines. These cells were then adoptively transferred to the patient. No adverse effects or graft-versus-host disease were observed after infusion of CB-NK cells. Our clinical experience supports the efficacy of CB-NK cell treatment in increasing NK cell activity, depleting tumor activity, improving quality of life, and reducing the size of abdominal and pelvic masses with the disappearance of multiple lymph node metastases through the regulation of systemic antitumor immunity. Remarkably, the white blood cell and platelet counts decreased to normal levels after CB-NK cell immunotherapy. This clinical work suggests that CB-NK cell immunotherapy holds promise as a therapeutic approach for endometrial cancer.

Tumor-Infiltrating CD8-Positive T-Cells Associated with MMR and p53 Protein Expression Can Stratify Endometrial Carcinoma for Prognosis

BACKGROUND

Inspired by the molecular classification of endometrial carcinoma (EC) proposed by The Cancer Genome Atlas Research Network (TCGA), we investigated tumor-infiltrating CD8-positive T-cell as well as DNA mismatch repair (MMR) protein and p53 protein expression, and we developed a new classification system for ECs to predict patients' prognosis using immunohistochemical methods.

METHODS

The study included 128 patients with ECs who underwent surgery. Paraffin-embedded tissue sections of the tumor were stained using antibodies against MMR protein, p53, and CD8. Cases were stratified into four classes by a sequential algorithm. An immunohistochemical classification system for ECs (ICEC) was created, including HCD8, MMR-D, LCD8, and p53 LCD8.

RESULTS

In ICEC, 16 cases (12.5%), 27 cases (21.09%), 67 cases (52.34%), and 18 cases (14.06%) belonged to HCD8, MMR-D, LCD8, and p53 LCD8, respectively. ICEC did not show any correlation with clinical stage, lymphovascular space invasion, or lymph node metastasis. However, the p53 LCD8 class contained a significantly higher proportion of G3 ECs and serous carcinoma (p < 0.0001). ICEC showed prognostic significance in overall survival (OS) (p < 0.0001) and disease-free survival (DFS) (p < 0.0001). The class of p53 LCD8 showed the worst prognosis among the classes.

CONCLUSIONS

ICEC classification is useful in predicting the prognosis of ECs.

PHF6 promotes the progression of endometrial carcinoma by increasing cancer cells growth and decreasing T-cell infiltration

Uterine corpus endometrial carcinoma (UCEC) is the most common cancer of the female reproductive tract. The overall survival of advanced and recurrent UCEC patients is still unfavourable nowadays. It is urgent to find a predictive biomarker and block tumorgenesis at an early stage. Plant homeodomain finger protein 6 (PHF6) is a key player in epigenetic regulation, and its alterations lead to various diseases, including tumours. Here, we found that PHF6 expression was upregulated in UCEC tissues compared with normal tissues. The UCEC patients with high PHF6 expression had poor survival than UCEC patients with low PHF6 expression. PHF6 mutation occurred in 12% of UCEC patients, and PHF6 mutation predicted favourable clinical outcome in UCEC patients. Depletion of PHF6 effectively inhibited HEC-1-A and KLE cell proliferation in vitro and decreased HEC-1-A cell growth in vivo. Furthermore, high PHF6 level indicated a subtype of UCECs characterized by low immune infiltration, such as CD3⁺ T-cell infiltration. While knockdown of PHF6 in endometrial carcinoma cells increased T-cell migration by promoting IL32 production and secretion. Taken together, our findings suggested that PHF6 might play an oncogenic role in UCEC patients. Thus, PHF6 could be a potential biomarker in predicting the prognosis of UCEC patients. Depletion of PHF6 may be a novel therapeutic strategy for UCEC patients.

Endothelin-3 is epigenetically silenced in endometrioid endometrial cancer

Purpose

Changes in the activity of endothelins and their receptors may promote neoplastic processes. They can be caused by epigenetic modifications and modulators, but little is known about endothelin-3 (EDN3), particularly in endometrial cancer. The aim of the study was to determine the expression profile of endothelin family and their interactions with miRNAs, and to assess the degree of EDN3 methylation.

Methods

The study enrolled 45 patients with endometrioid endometrial cancer and 30 patients without neoplastic changes. The expression profile of endothelins and their receptors was determined with mRNA microarrays and RT-qPCR. The miRNA prediction was based on the miRNA microarray experiment and the mirDB tool. The degree of EDN3 methylation was assessed by MSP.

Results

EDN1 and EDNRA were overexpressed regardless of endometrial cancer grade, which may be due to the lack of regulatory effect of miR-130a-3p and miR-485-3p, respectively. In addition, EDN3 and EDNRB were significantly downregulated.

Conclusion

The endothelial axis is disturbed in endometrioid endometrial cancer. The observed silencing of EDN3 activity may be mainly due to DNA methylation.

HiTIMED: hierarchical tumor immune microenvironment epigenetic deconvolution for accurate cell type resolution in the tumor microenvironment using tumor-type-specific DNA methylation data

Background

Cellular compositions of solid tumor microenvironments are heterogeneous, varying across patients and tumor types. High-resolution profiling of the tumor microenvironment cell composition is crucial to understanding its biological and clinical implications. Previously, tumor microenvironment gene expression and DNA methylation-based deconvolution approaches have been shown to deconvolve major cell types. However, existing methods lack accuracy and specificity to tumor type and include limited identification of individual cell types.

Results

We employed a novel tumor-type-specific hierarchical model using DNA methylation data to deconvolve the tumor microenvironment with high resolution, accuracy, and specificity. The deconvolution algorithm is named HiTIMED. Seventeen cell types from three major tumor microenvironment components can be profiled (tumor, immune, angiogenic) by HiTIMED, and it provides tumor-type-specific models for twenty carcinoma types. We demonstrate the prognostic significance of cell types that other tumor microenvironment deconvolution methods do not capture.

Conclusion

We developed HiTIMED, a DNA methylation-based algorithm, to estimate cell proportions in the tumor microenvironment with high resolution and accuracy. HiTIMED deconvolution is amenable to archival biospecimens providing high-resolution profiles enabling to study of clinical and biological implications of variation and composition of the tumor microenvironment.

RPP40 is a prognostic biomarker and correlated with tumor microenvironment in uterine corpus endometrial carcinoma

Ribonuclease P/MRP Subunit P40 (RPP40), a component of ribonuclease P and multimeric ribonuclease P complex, was reported as one of the promoting factors for the chemoresistance of acute myeloid leukemia and a recurrence predictor of early-stage triple-negative breast cancer. However, the functional role of RPP40 in uterine corpus endometrial carcinoma (UCEC) is unclear. In this study, comprehensive bioinformatic analyses were conducted to explore the predictive role of RPP40 on UCEC diagnosis and prognosis, as well as the underlying mechanism. Differential analyses of multiple databases showed that both messenger RNA (mRNA) and the protein expression of RPP40 were significantly upregulated in UCEC tumor tissues. Furthermore, the RPP40 mRNA expression level was significantly correlated with the clinicopathological characteristics of UCEC patients, including the clinical stage, primary therapy outcome, histological type, histologic grade, overall survival event, disease-specific survival event, and progression-free interval event. Receiver operating characteristic (ROC) analysis showed that RPP40 was a reliable predictor for UCEC diagnosis with an area under the curve (AUC) of 0.775, a sensitivity of 0.829, and a specificity of 0.719. Kaplan–Meier, Cox regression, and nomogram analyses showed that high RPP40 expression was an independent prognostic factor for the 1-year, 3-year, and 5-year survival of UCEC patients. In addition, the enrichment analysis of RPP40-associated differentially expressed genes and correlation analyses showed that the expression of RPP40 was correlated with the regulation of extracellular matrix and immune cell infiltration. In conclusion, the upregulation of RPP40 is significantly correlated with the poor survival and tumor microenvironment of UCEC, suggesting that RPP40 is a promising biomarker of poor prognosis and a potential target of chemotherapy or immunotherapy in UCEC.

Immune Infiltrates of m5C RNA Methylation-Related LncRNAs in Uterine Corpus Endometrial Carcinoma

Aberrant 5-methylcytidine (m5C) modification plays an essential role in the progression of different cancers. More and more researchers are focusing on developing a lncRNA-based risk model to assess the clinical prognosis of cancer patients. However, the impact of m5C-related lncRNAs on the prognosis of patients with uterine corpus endometrial carcinoma (UCEC), as well as the immune microenvironment of UCEC, remains unclear. Here, we comprehensively analyzed the predictive value of m5C-associated lncRNAs in UCEC and their association with the tumor immune microenvironment, according to the information extracted from the TCGA-UCEC dataset. We identified a total of 32 m5C-associated lncRNAs that were significantly correlated with the prognosis of UCEC patients. Two molecular subtypes were determined by consensus clustering analysis of these 32 m5C-associated prognostic lncRNAs. Further data showed that cluster 1 was associated with poor clinical prognosis, advanced tumor grade, higher PD-L1 expression levels, higher ESTIMATEScore, and higher immuneScore, as well as the immune cell infiltration. Then, 17 m5C-associated lncRNAs with prognostic values were obtained using LASSO regression analysis. And a risk model was constructed based on these 17 lncRNAs. It was revealed that the risk model could be used as an independent factor for UCEC prognosis. In addition, patients with UCEC in the high-risk group had higher tumor grades and immune scores. The risk model based on m5C-related lncRNAs was also closely associated with infiltrating immune cells. In conclusion, our study elucidated the crucial roles of the identified m5C-related lncRNAs in the UCEC patients' prognoses, as well as in the immune microenvironment in UCEC. The results suggest that the components of risk models based on the m5C-related lncRNAs may serve as important mediators of the immune microenvironment in UCEC.

Protein-based prognostic signature for predicting the survival and immunotherapeutic efficiency of endometrial carcinoma

Background

Endometrial cancer (EC) is the most frequent malignancy of the female genital tract worldwide. Our study aimed to construct an effective protein prognostic signature to predict prognosis and immunotherapy responsiveness in patients with endometrial carcinoma.

Methods

Protein expression data, RNA expression profile data and mutation data were obtained from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA). Prognosis-related proteins in EC patients were screened by univariate Cox regression analysis. Least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis were performed to establish the protein-based prognostic signature. The CIBERSORT algorithm was used to quantify the proportions of immune cells in a mixed cell population. The Immune Cell Abundance Identifier (ImmuCellAI) and The Cancer Immunome Atlas (TCIA) web tools were used to predict the response to immunochemotherapy. The pRRophetic algorithm was used to estimate the sensitivity of chemotherapeutic and targeted agents.

Results

We constructed a prognostic signature based on 9 prognostic proteins, which could divide patients into high-risk and low-risk groups with distinct prognoses. A novel prognostic nomogram was established based on the prognostic signature and clinicopathological parameters to predict 1, 3 and 5-year overall survival for EC patients. The results obtained with Clinical Proteomic Tumor Analysis Consortium (CPTAC), Human Protein Atlas (HPA) and immunohistochemical (IHC) staining data from EC samples in our hospital supported the predictive ability of these proteins in EC tumors. Next, the CIBERSORT algorithm was used to estimate the proportions of 22 immune cell types. The proportions of CD8 T cells, T follicular helper cells and regulatory T cells were higher in the low-risk group. Moreover, we found that the prognostic signature was positively associated with high tumor mutation burden (TMB) and high microsatellite instability (MSI-H) status in EC patients. Finally, ImmuCellAI and TCIA analyses showed that patients in the low-risk group were more inclined to respond to immunotherapy than patients in the high-risk group. In addition, drug sensitivity analysis indicated that our signature had potential predictive value for chemotherapeutics and targeted therapy.

Conclusion

Our study constructed a novel prognostic protein signature with robust predictive ability for survival and efficiency in predicting the response to immunotherapy, chemotherapy and targeted therapy. This protein signature represents a promising predictor of prognosis and response to cancer treatment in EC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09402-w.

CDKN2B-AS1 Promotes Malignancy as a Novel Prognosis-Related Molecular Marker in the Endometrial Cancer Immune Microenvironment

The prognosis of patients with endometrial cancer (EC) is closely associated with immune cell infiltration. Although abnormal long non-coding RNA (lncRNA) expression is also linked to poor prognosis in patients with EC, the function and action mechanism of immune infiltration-related lncRNAs underlying the occurrence and development of EC remains unclear. In this study, we analyzed lncRNA expression using The Cancer Genome Atlas and clinical data and identified six lncRNAs as prognostic markers for EC, all of which are associated with the infiltration of immune cell subtypes, as illustrated by ImmLnc database and ssGSEA analysis. Real-time quantitative polymerase chain reaction showed that CDKN2B-AS1 was significantly overexpressed in EC, whereas its knockdown inhibited the proliferation and invasion of EC cells and the in vivo growth of transplanted tumors in nude mice. Finally, we constructed a competing endogenous RNA regulatory network and conducted Gene Ontology enrichment analysis to elucidate the potential molecular mechanism underlying CDKN2B-AS1 function. Overall, we identified molecular targets associated with immune infiltration and prognosis and provide new insights into the development of molecular therapies and treatment strategies against EC.

A Brief Analysis of Tissue-Resident NK Cells in Pregnancy and Endometrial Diseases: The Importance of Pharmacologic Modulation

NK cells are lymphocytes involved in the innate and adaptative immune response. These cells are located in peripheral blood and tissues with ample functions, from immune vigilant to tolerogenic reactions. In the endometrium, NK cell populations vary depending on age, hormones, and inflammation. When pregnancy occurs, tissue-resident NK cells and conventional NK cells are recruited to protect the fetus, a tolerogenic response. On the contrary, in the inflamed endometrium, various inflammatory cells down-regulate NK tolerance and impair embryo implantation. Therefore, NK cells’ pharmacological modulation is difficult to achieve. Several strategies have been used, from progesterone, lipid emulsions to steroids; the success has not been as expected. However, new therapeutic approaches have been proposed to decrease the endometrial inflammatory burden and increase pregnancy success based on understanding NK cell physiology.