Immune checkpoint inhibitors in endometrial cancer

Tumoral programmed cell death 1 (PD1) expression in endometrial carcinoma is a prognostic marker for patient outcome

OBJECTIVE

Immune checkpoint inhibitors have recently demonstrated benefit in patients with advanced and recurrent endometrial carcinoma. This retrospective study investigated immune checkpoint molecules in endometrial carcinoma as they pertain to the molecular subtypes, clinical outcomes, and predictive value.

METHODS

Tumoral RNA expression of genes controlling the immune checkpoint, programmed cell death 1 (PD1, encoded by PDCD1), its ligand (PDL1, encoded by CD274), and interferon gamma (IFNG) was determined in 239 endometrial carcinoma tissues by quantitative polymerase chain reaction (qPCR) and compared with endometrial tissue from 25 controls. A total of 81 endometrial carcinoma tissues were analyzed using the ProMiSe molecular classification, and patient trajectories were analyzed for the entire cohort. Findings were validated in an independent cohort from The Cancer Genome Atlas (TCGA; n=548).

RESULTS

PD1, PDL1, and IFNG expression was significantly higher in endometrial carcinoma when compared with non-malignant control tissue with a mean expression of 0.12, 0.05, and 0.05 in control tissue and 0.44, 0.31, and 0.35 in endometrial carcinoma, respectively. POLE-mutated and mismatch repair-deficient (MMRd) (immunologically hot) tumors showed the highest expression of PD1 and IFNG. Increased expression of PD1, PDL1, and IFNG was associated with improved recurrence-free (HR 0.32, p<0.001; HR 0.30, p<0.001; HR 0.47, p=0.012, respectively), disease-specific (HR 0.38, p<0.001; HR 0.29, p<0.001; HR 0.45, p=0.017, respectively), and overall survival (HR 0.56, p=0.003; HR 0.38, p<0.001; HR 0.58, p=0.006, respectively). Cox regression confirmed the prognostic significance of PD1 for recurrence-free survival (HR 0.39, p=0.009) and PDL1 for overall survival (HR 0.55, p=0.037). The prognostic value of tumoral PD1 on recurrence-free survival, disease-specific survival, and overall survival was confirmed in the TCGA cohort.

CONCLUSIONS

Tumoral gene expression controlling the PD1 immune checkpoint, particularly expressed in "hot tumors", predicted recurrence-free, disease-specific, and overall survival in patients with endometrial carcinoma in two independent cohorts. Evaluation of these genes could be used to stratify patients who qualify for immune checkpoint inhibitors, which warrants prospective clinical trials.

Complete response to disitamab vedotin in HER2-low metastatic endometrial carcinoma: a case report and review of the literature

Endometrial cancer (EC) is one of the most common gynecologic malignancies with increasing morbidity. The prognosis for patients diagnosed with early-stage EC remains favorable; however, for patients with recurrent or metastatic EC, the prognosis is poor and treatment options, until recently, are limited. Antibody drug conjugates (ADCs) represent innovative strategies in cancer treatment; however, there are less investigations regarding their efficacy in EC. This report describes an EC case with low human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) expression score (IHC 2+) that experienced recurrent metastasis in the abdominal and peritoneal following post-surgical chemotherapy and radiotherapy. Subsequently, the commencement of HER2-targeted ADC, disitamab vedotin (RC48; 2.5 mg/kg), administered intravenously every two weeks, was initiated. The tumor lesions shrunk markedly after three cycles of treatment and disappeared by the completion of ten cycles of therapy. The patient is still in remission at present. The current findings imply the potential efficacy of HER2-targeted ADCs for patients with HER2-low metastatic EC.

Machine learning combined with single-cell analysis reveals predictive capacity and immunotherapy response of T cell exhaustion-associated lncRNAs in uterine corpus endometrial carcinoma

BACKGROUND

The exhaustion of T-cells is a primary factor contributing to immune dysfunction in cancer. Long non-coding RNAs (lncRNAs) play a significant role in the advancement, survival, and treatment of Uterine Corpus Endometrial Carcinoma (UCEC). Nevertheless, there has been no investigation into the involvement of lncRNAs associated with T-cell exhaustion (TEXLs) in UCEC. The goal of this work is to establish predictive models for TEXLs in UCEC and study their related immune features.

METHODS

Using transcriptome and single-cell sequencing data from The Cancer Genome Atlas and Gene Expression Omnibus databases, we employed co-expression analysis and univariate Cox regression to identify prognostic-associated TEXLs (pTEXLs). The prognostic model was developed using the Least Absolute Contraction and Selection Operator. The immunotherapy characteristics of the prognostic model risk score were studied. Then molecular subgroups were identified through non-negative Matrix Factorization based on pTEXLs. The identification of co-expressed genes was done using a weighted correlation network analysis. Subsequently, a diagnostic model for UCEC was created. In-depth investigations, both in vitro and in vivo, were carried out to elucidate the molecular mechanism of the key gene within the diagnostic model.

RESULTS

Receiver operating characteristic curve, calibration curve, and decision curve analysis proved the validity of the predictive models established according to pTEXLs. The subgroup with lower risk scores in the prognostic model has better responses to blocking immune checkpoint therapy. Single-cell analysis suggests that the expression level of MIEN1 is relatively high in immune cells among diagnostic genes. Furthermore, the targeted suppression of MIEN1 via sh-MIEN1 diminishes the proliferative, migratory, and invasive capacities of UCEC cells, potentially associated with CD8+ T cell exhaustion.

CONCLUSIONS

The association between TEXLs and UCEC was methodically elucidated by our investigation. A stable pTEXLs risk prediction model and a diagnosis model for UCEC were also established.

Prognostic value of pretreatment systemic immune-inflammation index in patients with endometrial cancer: a meta-analysis

Background: The present work focused on evaluating the systemic immune-inflammation index (SII) for its role in predicting endometrial cancer (EC) patient prognosis by meta-analysis. Methods: SII's role in predicting the prognosis of EC patients was analyzed by calculating combined hazard ratios (HRs) and 95% CIs. Results: As revealed by combined analysis, an increased SII predicted poor overall survival (HR = 2.01; 95% CI = 1.58-2.57; p < 0.001) as well as inferior progression-free survival (HR = 1.87; 95% CI = 1.36-2.58; p < 0.001) of EC. Conclusion: An increased SII score significantly predicted poor overall survival and progression-free survival in subjects with EC. The SII is suitable for predicting short- and long-term prognoses of patients with EC.

Network-based drug repurposing identifies small molecule drugs as immune checkpoint inhibitors for endometrial cancer

Endometrial cancer (EC) is the 6th most common cancer in women around the world. Alone in the United States (US), 66,200 new cases and 13,030 deaths are expected to occur in 2023 which needs the rapid development of potential therapies against EC. Here, a network-based drug-repurposing strategy is developed which led to the identification of 16 FDA-approved drugs potentially repurposable for EC as potential immune checkpoint inhibitors (ICIs). A network of EC-associated immune checkpoint proteins (ICPs)-induced protein interactions (P-ICP) was constructed. As a result of network analysis of P-ICP, top key target genes closely interacting with ICPs were shortlisted followed by network proximity analysis in drug-target interaction (DTI) network and pathway cross-examination which identified 115 distinct pathways of approved drugs as potential immune checkpoint inhibitors. The presented approach predicted 16 drugs to target EC-associated ICPs-induced pathways, three of which have already been used for EC and six of them possess immunomodulatory properties providing evidence of the validity of the strategy. Classification of the predicted pathways indicated that 15 drugs can be divided into two distinct pathway groups, containing 17 immune pathways and 98 metabolic pathways. In addition, drug-drug correlation analysis provided insight into finding useful drug combinations. This fair and verified analysis creates new opportunities for the quick repurposing of FDA-approved medications in clinical trials.

New insights for gynecological cancer therapies: from molecular mechanisms and clinical evidence to future directions

Advanced and recurrent gynecological cancers lack effective treatment and have poor prognosis. Besides, there is urgent need for conservative treatment for fertility protection of young patients. Therefore, continued efforts are needed to further define underlying therapeutic targets and explore novel targeted strategies. Considerable advancements have been made with new insights into molecular mechanisms on cancer progression and breakthroughs in novel treatment strategies. Herein, we review the research that holds unique novelty and potential translational power to alter the current landscape of gynecological cancers and improve effective treatments. We outline the advent of promising therapies with their targeted biomolecules, including hormone receptor-targeted agents, inhibitors targeting epigenetic regulators, antiangiogenic agents, inhibitors of abnormal signaling pathways, poly (ADP-ribose) polymerase (PARP) inhibitors, agents targeting immune-suppressive regulators, and repurposed existing drugs. We particularly highlight clinical evidence and trace the ongoing clinical trials to investigate the translational value. Taken together, we conduct a thorough review on emerging agents for gynecological cancer treatment and further discuss their potential challenges and future opportunities.

The past, present, and future of immunotherapy for endometrial adenocarcinoma

Incidences of endometrial adenocarcinoma are increasing in the USA with poor prognosis for patients with advanced disease. The current treatment standard is surgery including total hysterectomy and bilateral oophorectomy with surgical staging and adjunct treatment, such as chemotherapy or radiation. However, these methods do not present as an effective treatment option for poorly differentiated advanced cancers. Advancements in immunotherapy now offer a new approach for various types of cancer and specifically show promise in the treatment of endometrial adenocarcinoma. This review summarizes immunotherapeutic treatment options relevant to endometrial adenocarcinoma, such as immune checkpoint blockades, bispecific T-cell engager antibodies, vaccinations, and adoptive cell transfer. This study could be helpful for clinicians to identify treatment options more suitable for women with late-stage endometrial adenocarcinoma.

Noninvasive detection of microsatellite instability in patients with endometrial cancer

The analysis of mismatch repair proteins in solid tissue is the standard of care (SoC) for the microsatellite instability (MSI) characterization in endometrial cancer (EC). Uterine aspirates (UAs) or circulating-DNA (cfDNA) samples capture the intratumor heterogeneity and provide a more comprehensive and dynamic molecular diagnosis. Thus, MSI analysis by droplet-digital PCR (ddPCR) in UAs and cfDNA can provide a reliable tool to characterize and follow-up the disease. The UAs, paraffin-embedded tumor tissue (FFPE) and longitudinal plasma samples from a cohort of 90 EC patients were analyzed using ddPCR panel and compared to the SoC. A high concordance (96.67%) was obtained between the analysis of MSI markers in UAs and the SoC. Three discordant cases were validated as unstable by ddPCR on FFPE samples. Besides, a good overall concordance (70.27%) was obtained when comparing the performance of the ddPCR assay on UAs and cfDNA in high-risk tumors. Importantly, our results also evidenced the value of MSI analysis to monitor the disease evolution. MSI evaluation in minimally invasive samples shows great accuracy and sensitivity and provides a valuable tool for the molecular characterization and follow-up of endometrial tumors, opening new opportunities for personalized management of EC.

Cancer-specific functional profiling in microsatellite-unstable (MSI) colon and endometrial cancers using combined differentially expressed genes and biclustering analysis

Microsatellite-unstable (MSI) cancers have distinct genetic and clinical features from microsatellite-stable cancers, but the molecular functional differences between MSI cancers originating from different tissues or organs have not been well studied because the application of usual differentially expressed gene (DEG) analysis is error-prone, producing too many noncancer-specific normally functioning genes. To maximize therapeutic efficacy, biomarkers reflecting cancer-specific differences between MSI cancers of different tissue origins should be identified. To identify functional differences between MSI colon and endometrial cancers, we combined DEG analysis and biclustering instead of DEG analysis alone and refined functionally relevant biclusters reflecting genuine functional differences between the 2 tumors. Specifically, using The Cancer Genome Atlas and genome-tissue expression as data sources, gene ontology (GO) enrichment tests were performed after routinely identifying DEGs between the 2 tumors with the exclusion of DEGs identified in their normal counterparts. Cancer-specific biclusters and associated enriched GO terms were obtained by biclustering with enrichment tests for the preferences for cancer type (either colon or endometrium) and GO enrichment tests for each cancer-specific bicluster, respectively. A novel childness score was developed to select functionally relevant biclusters among cancer-specific biclusters based on the extent to which the enriched GO terms of the biclusters tended to be child terms of the enriched GO terms in DEGs. The selected biclusters were tested using survival analysis to validate their clinical significance. We performed multiple sequential analyses to produce functionally relevant biclusters from the RNA sequencing data of MSI colon and endometrial cancer samples and their normal counterparts. We identified 3066 cancer-specific DEGs. Biclustering analysis revealed 153 biclusters and 41 cancer-specific biclusters were selected using Fisher exact test. A mean childness score over 0.6 was applied as the threshold and yielded 8 functionally relevant biclusters from cancer-specific biclusters. Functional differences appear to include gland cavitation and the TGF-β receptor, G protein, and cytokine pathways. In the survival analysis, 6 of the 8 functionally relevant biclusters were statistically significant. By attenuating noise and applying a synergistic contribution of DEG results, we refined candidate biomarkers to complement tissue-specific features of MSI tumors.

Exploitation of a shared genetic signature between obesity and endometrioid endometrial cancer

Aims

The findings in epidemiological studies suggest that endometrioid endometrial cancer (EEC) is associated with obesity. However, evidence from gene expression data for the relationship between the two is still lacking. The purpose of this study was to explore the merits of establishing an obesity-related genes (ORGs) signature in the treatment and the prognostic assessment of EEC.

Methods

Microarray data from GSE112307 were utilized to identify ORGs by using weighted gene co-expression network analysis. Based on the sequencing data from TCGA, we established the prognostic ORGs signature, confirmed its value as an independent risk factor, and constructed a nomogram. We further investigated the association between grouping based on ORGs signature and clinicopathological characteristics, immune infiltration, tumor mutation burden and drug sensitivity.

Results

A total of 10 ORGs were identified as key genes for the construction of the signature. According to the ORGs score computed from the signature, EEC patients were divided into high and low-scoring groups. Overall survival (OS) was shorter in EEC patients in the high-scoring group compared with the low-scoring group (P < 0.001). The results of the Cox regression analysis showed that ORGs score was an independent risk factor for OS in EEC patients (HR = 1.017, 95% confidence interval = 1.011-1.023; P < 0.001). We further revealed significant disparities between scoring groups in terms of clinical characteristics, tumor immune cell infiltration, and tumor mutation burden. Patients in the low-scoring group may be potential beneficiaries of immunotherapy and targeted therapies.

Conclusions

The ORGs signature established in this study has promising prognostic predictive power and may be a useful tool for the selection of EEC patients who benefit from immunotherapy and targeted therapies.

miR-548ag functions as an oncogene by suppressing MOB1B in the development of obesity-related endometrial cancer

Obesity is a high-risk factor in the development of endometrial cancer (EC). Our previous study observed that miR-548ag was significantly overexpressed in the sera of obese individuals. Here, we report the function of miR-548ag and its mechanism in promoting the obesity-related progression of EC. The content of miR-548ag was increased in the serum of obese EC individuals. Bioinformatics analysis indicated that the survival rate of EC patients with a higher expression of miR-548ag was significantly reduced. The Mps One Binder Kinase Activator 1B (MOB1B, the core member of the Hippo signaling pathway) is a direct target gene of miR-548ag, which is inversely correlated with the expression of miR-548ag. The overexpression of miR-548ag enhances the proliferation, invasion, and migration, and inhibits apoptosis by downregulating the expression of MOB1B, leading to the deactivation of the Hippo pathway in EC cell lines and contributing to tumor progression in vivo. Our study has established that miR-548ag functions as an oncogene by suppressing MOB1B in the development of obesity-related EC.

Construction of N-7 methylguanine-related mRNA prognostic model in uterine corpus endometrial carcinoma based on multi-omics data and immune-related analysis

N-7 methylguanine (m7G) is one of the most common RNA base modifications in post-transcriptional regulation, which participates in multiple processes such as transcription, mRNA splicing and translation during the mRNA life cycle. However, its expression and prognostic value in uterine corpus endometrial carcinoma (UCEC) have not been systematically studied. In this paper, the data such as gene expression profiles, clinical data of UCEC patients, somatic mutations and copy number variants (CNVs) are obtained from the cancer genome atlas (TCGA) and UCSC Xena. By analyzing the expression differences of m7G-related mRNA in UCEC and plotting the correlation network maps, a risk score model composed of four m7G-related mRNAs (NSUN2, NUDT3, LARP1 and NCBP3) is constructed using least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression in order to identify prognosis and immune response. The correlation of clinical prognosis is analyzed between the m7G-related mRNA and UCEC via Kaplan-Meier method, receiver operating characteristic (ROC) curve, principal component analysis (PCA), t-SNE, decision curve analysis (DCA) curve and nomogram etc. It is concluded that the high risk is significantly correlated with (P < 0.001) the poorer overall survival (OS) in patients with UCEC. It is one of the independent risk factors affecting the OS. Differentially expressed genes are identified by R software in the high and low risk groups. The functional analysis and pathway enrichment analysis have been performed. Single sample gene set enrichment analysis (ssGSEA), immune checkpoints, m6A-related genes, tumor mutation burden (TMB), stem cell correlation, tumor immune dysfunction and rejection (TIDE) scores and drug sensitivity are also used to study the risk model. In addition, we have obtained 3 genotypes based on consensus clustering, which are significantly related to (P < 0.001) the OS and progression-free survival (PFS). The deconvolution algorithm (CIBERSORT) is applied to calculate the proportion of 22 tumor infiltrating immune cells (TIC) in UCEC patients and the estimation algorithm (ESTIMATE) is applied to work out the number of immune and matrix components. In summary, m7G-related mRNA may become a potential biomarker for UCEC prognosis, which may promote UCEC occurrence and development by regulating cell cycles and immune cell infiltration. It is expected to become a potential therapeutic target of UECE.

A novel chromatin regulator-related immune checkpoint related gene prognostic signature and potential candidate drugs for endometrial cancer patients

Background

Endometrial cancer (EC) is the most common gynecologic malignancy in developed countries and its prevalence is increasing. As an emerging therapy with a promising efficacy, immunotherapy has been extensively applied in the treatment of solid tumors. In addition, chromatin regulators (CRs), as essential upstream regulators of epigenetics, play a significant role in tumorigenesis and cancer development.

Methods

CRs and immune checkpoint-related genes (ICRGs) were obtained from the previous top research. The Genome Cancer Atlas (TCGA) was utilized to acquire the mRNA expression and clinical information of patients with EC. Correlation analysis was utilized for screen CRs-related ICRGs (CRRICRGs). By Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, prognosis related CRRICRGs were screened out and risk model was constructed. The Kaplan–Meier curve was used to estimate the prognosis between high- and low-risk group. By comparing the IC50 value, the drugs sensitivity difference was explored. We obtained small molecule drugs for the treatment of UCEC patients based on CAMP dataset.

Results

We successfully constructed a 9 CRRICRs-based prognostic signature for patients with UCEC and found the riskscore was an independent prognostic factor. The results of functional analysis suggested that CRRICRGs may be involved in immune processes associated with cancer. Immune characteristics analysis provided further evidence that the CRRICRGs-based model was correlated with immune cells infiltration and immune checkpoint. Eight small molecule drugs that may be effective for the treatment of UCEC patients were screened. Effective drugs identified by drug sensitivity profiling in high- and low-risk groups.

Conclusion

In summary, our study provided novel insights into the function of CRRICRGs in UCEC. We also developed a reliable prognostic panel for the survival of patients with UCEC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-022-00253-w.

The IFN-γ-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma

Background

One of the most common diseases that have a negative impact on women’s health is endometrial carcinoma (EC). Advanced endometrial cancer has a dismal prognosis and lacks solid prognostic indicators. IFN-γ is a key cytokine in the inflammatory response, and it has also been suggested that it has a role in the tumor microenvironment. The significance of IFN-γ-related genes and long non-coding RNAs in endometrial cancer, however, is unknown.

Methods

The Cancer Genome Atlas (TCGA) database was used to download RNA-seq data from endometrial cancer tissues and normal controls. Genes associated with IFN-γ were retrieved from the gene set enrichment analysis (GSEA) website. Co-expression analysis was performed to find lncRNAs linked to IFN-γ gene. The researchers employed weighted co-expression network analysis (WGCNA) to find lncRNAs that were strongly linked to survival. The prognostic signature was created using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. The training cohort, validation cohort, and entire cohort of endometrial cancer patients were then split into high-risk and low-risk categories. To investigate variations across different risk groups, we used survival analysis, enrichment analysis, and immune microenvironment analysis. The platform for analysis is R software (version X64 3.6.1).

Results

Based on the transcript expression of IFN-γ-related lncRNAs, two distinct subgroups of EC from TCGA cohort were formed, each with different outcomes. Ten IFN-γ-related lncRNAs were used to build a predictive signature using Cox regression analysis and the LASSO regression, including CFAP58, LINC02014, UNQ6494, AC006369.1, NRAV, BMPR1B-DT, AC068134.2, AP002840.2, GS1-594A7.3, and OLMALINC. The high-risk group had a considerably worse outcome (p < 0.05). In the immunological microenvironment, there were also substantial disparities across different risk categories.

Conclusion

Our findings give a reference for endometrial cancer prognostic type and immunological status assessment, as well as prospective molecular markers for the disease.

Mutation burden-orthogonal tumor genomic subtypes delineate responses to immune checkpoint therapy

Background

In cancer therapy, higher-resolution tumor-agnostic biomarkers that predict response to immune checkpoint inhibitor (ICI) therapy are needed. Mutation signatures reflect underlying oncogenic processes that can affect tumor immunogenicity, and thus potentially delineate ICI treatment response among tumor types.

Methods

Based on mutational signature analysis, we developed a stratification for all solid tumors in The Cancer Genome Atlas (TCGA). Subsequently, we developed a new software (Genomic Subtyping and Predictive Response Analysis for Cancer Tumor ICi Efficacy, GS-PRACTICE) to classify new tumors submitted to whole-exome sequencing. Using existing data from 973 pan-cancer ICI-treated cases with outcomes, we evaluated the subtype-response predictive performance.

Results

Systematic analysis on TCGA samples identified eight tumor genomic subtypes, which were characterized by features represented by smoking exposure, ultraviolet light exposure, APOBEC enzyme activity, POLE mutation, mismatch repair deficiency, homologous recombination deficiency, genomic stability, and aging. The former five subtypes were presumed to form an immune-responsive group acting as candidates for ICI therapy because of their high expression of immune-related genes and enrichment in cancer types with FDA approval for ICI monotherapy. In the validation cohort, the samples assigned by GS-PRACTICE to the immune-reactive subtypes were significantly associated with ICI response independent of cancer type and TMB high or low status.

Conclusions

The new tumor subtyping method can serve as a tumor-agnostic biomarker for ICI response prediction and will improve decision making in cancer treatment.

Analysis of the immune checkpoint lymphocyte activation gene-3 (LAG-3) in endometrial cancer: An emerging target for immunotherapy

BACKGROUND

Lymphocyte activation gene-3 (LAG-3) is a novel molecule that participates in the immune escape of tumor cells and is a target for immunotherapy. However, the expression of LAG-3 in patients with endometrial cancer (EC) has not been comprehensively characterized.

OBJECTIVES

We elucidated the expression of LAG-3 and investigated its correlation with clinicopathological parameters, ProMisE subtypes, CD8⁺ T-cell infiltration and relapse-free survival (RFS) in a retrospective cohort of 421 patients with endometrial cancer.

METHODS

Next-generation sequencing of the polymerase epsilon (POLE) and immunohistochemistry of mismatch repair (MMR)-related protein (MLH1, PMS2, MSH2, and MSH6), p53, CD8 and LAG-3 protein in whole sections were performed.

RESULTS

Positive LAG-3 was detected in tumor cells (TCs) and immune cells (ICs) in 31.6% (133/421) and 24.0% (101/421) of the patients, respectively. LAG-3 positivity in ICs was more common in high-grade, high-intermediate risk, high-risk, and advanced/metastatic subgroups and was relevant to lymphovascular space invasion, while that in TCs was more common in older individuals (≥54 years). LAG-3 expression was more prevalent in POLE ultramutated (POLEmut) and MMR-deficient (MMRd) EC than in p53-abnormal (p53abn) and p53-wild (p53wt) EC in TCs (34.4 % and 66.3% in POLEmut and MMRd versus 28.6% and 19.5% in p53abn and p53wt, P < 0.001) and ICs (78.1 % and 65.1% in POLEmut and MMRd versus 2.9% and 5.2% in p53abn and p53wt, P < 0.001). Positive expression of LAG-3 in TCs and ICs was associated with high levels of tumor-associated CD8⁺ T-cell immune infiltration. Additionally, LAG-3 positivity in TCs was related to improved RFS.

CONCLUSIONS

This study suggests that immunotherapy targeting LAG-3 may play a role in EC patients with POLEmut or MMRd molecular markers. Positive LAG-3 expression in TCs may be a predictor of improved RFS.

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.

Recurrence Features and Factors influencing Post-relapse Survival in Early-stage Endometrial Cancer after Adjuvant Radiotherapy

Purpose: To evaluate the recurrent patterns and effect of clinicopathological factors on survival after recurrence (R-OS) in early stage endometrial cancer (EC). Methods: Patients with FIGO stage I-II EC, who underwent post-surgery radiotherapy (RT) at our institution between 2000 and 2017, were enrolled. First recurrent patterns, overall survival (OS), and R-OS were evaluated. Univariate and multivariate analyses (MVA) were used to evaluate factors associated with R-OS. Results: 756 patients were analyzed including 510 patients who received vaginal brachytherapy (VBT) and 246 patients who received external beam radiotherapy (EBRT) ± VBT, of whom 66 patients experienced recurrence, including 21 locoregional relapses and 45 distant metastases. Outside RT field recurrence predominated intra-RT field recurrence (106 versus 10 lesions). The 5-year OS rates for patients with and without recurrence were 62.2% and 98.2%, respectively (p<0.001). Among patients who underwent previous VBT, the 5-year OS rates were 61.1%, 92.3%, and 99.1% for distant metastasis, locoregional relapse, and non-recurrence, respectively (p<0.001); among patients who received EBRT ± VBT, the 5-year OS rates were 51.4%, 50.0%, and 98.3%, respectively (p<0.001).On Cox MVA of R-OS for locoregional recurrence patients, para-aortic lymph node metastasis was associated with poorer R-OS (hazard ratio [HR] 10.047, p=0.039), and salvage RT was superior to other therapies (HR 0.06, p=0.026). On Cox MVA of R-OS for distant metastasis, patients with brain metastasis (p=0.041) had the worst R-OS and patients benefited most from combined therapy (HR 0.02, p=0.001). Conclusion: Recurrent patterns were dominated by outside RT field and distant metastasis for early-stage ECs after adjuvant RT. The modality of prior RT had an impact on the choice of salvage therapy. RT could still be an effective salvage treatment for patients who develop locoregional recurrence. Patients with distant metastasis may benefit from combined therapies.

Identification of ZEB2 as an Immune-Associated Gene in Endometrial Carcinoma and Associated with Macrophage Infiltration by Bioinformatic Analysis

Endometrial cancer (EC) is the most common gynecological tumor arising from the endometrium. In this study, we use a published single-cell transcriptome profile of endometrial carcinoma (EC) to reveal the composition of immune cells and found an immunosuppressive environment since the presence of macrophage subtype M2 and exhausted CD8+ T cell markers. We focused on ZEB2 (Zinc finger E-box binding homeobox 2), a well-known player in epithelial to mesenchymal transition process, and we showed that ZEB2 is exclusively expressed in immune cells in single-cell transcriptome and, at the same time, downregulated in TCGA-UCEC (The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma) bulk RNA-seq data and negatively associated with tumor purity. Loss of ZEB2 protein in EC in normal endometrium and EC samples was validated in samples using immunohistochemistry (IHC) from HPA (Human Protein Atlas) database. Furthermore, we found ZEB2 was associated with immune infiltrations especially for macrophage using TIMER 2.0. Interestingly, ZEB2 prognostic significance differed under various macrophage and Th2 helper cell content using Kaplan-Meier Plotter analysis. More importantly, we showed that over 11% EC patients have somatic mutations of ZEB2 in EC samples collected from cBioportal and they have a lower body weight, earlier diagnosis age, and better overall survival and disease-free survival status compared with the unaltered group. Analysis in TIMER2.0 suggested that ZEB2 mutation would possibly change the composition of tumor-infiltrating lymphocytes. Taken together, by combining the results from single-cell data, bulk TCGA RNA-seq, and other online bioinformatic tools, we provided evidence that ZEB2 might have a unique role in the immune environment of EC. These results would provide a better insight into the pathogenetic process and ZEB2 might further be used an immunotherapeutic target of EC.

Pembrolizumab in endometrial cancer: Where we stand now

Recently, immunotherapy has shown promising results in solid tumors. To the best of our knowledge, this is the first systematic review of published literature synthesizing all the available data and evaluating both the efficacy and safety of pembrolizumab in endometrial cancer. The present study was performed in accordance with the PRISMA guidelines. Eligible articles were identified by searching the MEDLINE and ClinicalTrials.gov databases, using a predefined combination of the terms 'endometrial cancer' and 'pembrolizumab'. Overall, nine articles incorporating data from 712 patients were eligible. Pembrolizumab was demonstrated to be an effective and safe therapeutic option for the management of advanced/metastatic endometrial cancer. Results of ongoing trials evaluating either pembrolizumab alone or in combination with other antineoplastic regimens are expected to confirm its efficacy in this setting of patients. Pembrolizumab appears to be both durable and robust in endometrial cancer. However, there is an emerging need for novel predictive biomarkers to guide clinical practice.

Molecular Basis of Endometriosis and Endometrial Cancer: Current Knowledge and Future Perspectives

The human endometrium is a unique tissue undergoing important changes through the menstrual cycle. Under the exposure of different risk factors in a woman's lifetime, normal endometrial tissue can give rise to multiple pathologic conditions, including endometriosis and endometrial cancer. Etiology and pathophysiologic changes behind such conditions remain largely unclear. This review summarizes the current knowledge of the pathophysiology of endometriosis and its potential role in the development of endometrial cancer from a molecular perspective. A better understanding of the molecular basis of endometriosis and its role in the development of endometrial pathology will improve the approach to clinical management.