Facts and Hopes in Immunotherapy of Endometrial Cancer

Efficacy comparison of PD-1/PD-L1 inhibitor monotherapy and combination with PARPis or antiangiogenic agents in advanced or recurrent endometrial cancer: a systematic review and network meta-analysis

PURPOSE

The network meta-analysis (NMA) was aimed to compare and assess the effectiveness of programmed cell death 1 (PD-1)/ programmed cell death ligand 1 (PD-L1) inhibitor monotherapy or combination therapy with other agents for individuals with advanced or recurrent endometrial cancer (EC).

METHODS

The NMA was registered on the PROSPERO website (ID: CRD42024545968) and multiple databases were queried to retrieve the articles. It assessed the progression-free survival (PFS) and overall survival (OS) of persons with advanced or recurrent EC, as well as those with deficient mismatch repair (dMMR) and proficient mismatch repair (pMMR) in terms of PFS.

RESULTS

The NMA included 12 studies involving a total of 4,515 patients. Compared to chemotherapy, the PD-1/PD-L1 inhibitor monotherapy (hazard ratio [HR], 0.59; 95% confidence interval [CI]: 0.44-0.78) in PFS, combination therapy with poly (ADP-ribose) polymerase inhibitors (PARPis) (HR, 0.53; 95% CI: 0.32-0.89) or with antiangiogenic agents (HR, 0.48; 95% CI: 0.25-0.83) all showed significant improvements in PFS. PD-1/PD-L1 inhibitor monotherapy resulted in a significantly higher OS (HR, 0.61; 95% CI: 0.37-0.97) compared to chemotherapy. Combination therapy with antiangiogenic agents demonstrated the highest efficacy in extending PFS, while the combination with PARPis had the best performance in extending OS. Patients with dMMR and pMMR subtypes derive greater benefits from PD-1/ PD-L1 inhibitor monotherapy and PD-1/PD-L1 inhibitors combined with PARPis respectively.

CONCLUSION

Monotherapy with PD-1/PD-L1 inhibitors and combination therapies with PARPis or antiangiogenic agents demonstrate significant potential for individuals with advanced or recurrent EC.

Inhibition of lanosterol synthase linking with MAPK/JNK signaling pathway suppresses endometrial cancer

Endometrial cancer (EC) is a significant health threat to women, with recurrence after treatment posing a major challenge. While abnormal cholesterol metabolism has been implicated in EC progression, the underlying mechanisms remain unclear. In this study, we identified lanosterol synthase (LSS) as a key mediator in cholesterol metabolism associated with EC. We found that LSS is significantly upregulated in EC tissues. Functional assays revealed that LSS promotes cell proliferation and migration, inhibits apoptosis, and drives tumor growth in vivo. Mechanistically, LSS exerts dual effects by accumulating cholesterol esters, thereby enhancing EC cell growth, and activating the MAPK/JNK signaling pathway. Importantly, inhibition of LSS with the specific inhibitor Ro 48-8071 not only reduced EC cell proliferation and suppressed xenograft tumor growth but also inhibited the growth of patient-derived tumor-like cell clusters (PTCs). These findings establish LSS as a novel oncogene in EC, promoting tumor progression through MAPK/JNK signaling activation and cholesterol ester accumulation, and highlight the therapeutic potential of targeting LSS in EC treatment.

The Multi-Kinase Inhibitor GZD824 (Olverembatinib) Shows Pre-Clinical Efficacy in Endometrial Cancer

OBJECTIVE

Endometrial cancer is one of the few cancers for which mortality is still increasing. A lack of treatment options remains a major challenge, particularly for some subtypes of the disease. GZD824, also known as olverembatinib, is a multi-kinase inhibitor previously investigated in clinical trials for chronic myeloid leukaemia and Ph+ acute lymphoblastic leukaemia as a BCR-ABL inhibitor. This study aimed to investigate the pre-clinical efficacy of GZD824 for the treatment of EC.

METHODS

Here, we undertook pre-clinical evaluation of GZD824 in seven endometrial cancer cell lines (HEC-1-A, HEC-1-B, MFE296, RL95-2, Ishikawa, KLE and ARK-1), one normal immortalised endometrium derived cell line (E6E7hTERT) and primary mesothelial and fibroblast cells isolated from normal omentum samples.

RESULTS

GZD824 inhibited the proliferation of all endometrial cancer cell lines, which were significantly more sensitive to GZD824 compared to normal cells (p = 0.030). GZD824 significantly inhibited migration in Ishikawa (endometrioid) and ARK1 (serous) endometrial cancer cell lines and significantly inhibited invasion in the ARK1 cells. Whole transcriptome regulation following two doses (0.1 and 1 μM) of GZD824 in Ishikawa and ARK1 cells was investigated via RNA-seq, and key components of enriched pathways were investigated at the translational level. Key pathways altered included ROR1/Wnt, GCN2-ATF4, epithelial to mesenchymal transition (EMT) and PI3K-AKT.

CONCLUSION

Together, these studies support further investigation of GZD824 as a potential therapeutic agent in endometrial cancer, potentially in combination with immune checkpoint inhibitors.

A machine learning-based immune response signature to facilitate prognosis prediction in patients with endometrial cancer

Endometrial cancer is the most prevalent form of gynecologic malignancy, with a significant surge in incidence among youngsters. Although the advent of the immunotherapy era has profoundly improved patient outcomes, not all patients benefit from immunotherapy; some patients experience hyperprogression while on immunotherapy. Hence, there is a pressing need to further delineate the distinct immune response profiles in patients with endometrial cancer to enhance prognosis prediction and facilitate the prediction of immunotherapeutic responses. The ssGSEA method was used to evaluate the activities of the immune response pathways in patients with endometrial cancer. Unsupervised clustering was employed to identify the different immune response patterns. WGCNA was employed to identify the genes that highly correlated with the immune response patterns observed. Ninety-five machine learning combinations were utilized to identify the optimal prognosis model and the novel biomarker, SLC38A3. Experiments such as cell invasion, migration, scratch, and in vivo tumorigenicity were performed to determine the function of SLC28A3. Molecular docking techniques were employed to determine the targeted action of periodate-oxidized adenosine on SLC38A3. Patients exhibited both immune response-suppressing C1 phenotypes and immune response-activating C2 phenotypes, with significant differences in prognosis between these two phenotypes. WGCNA identified 418 genes that highly correlated with the immune response phenotypes, of which 69 genes were associated with prognosis. The immune response-related score (IRRS) established by multiple machine learning frameworks demonstrated stability in predicting patient prognosis and immune status. High expression of SLC38A3 contributes to cellular malignant traits, and periodate-oxidized adenosine bound stably to SLC38A3. IRRS accurately predicts disease prognosis and immune status in patients with endometrial cancer. SLC38A3 serves as a prognostic marker for these patients and can be stably targeted by periodate-oxidized adenosine.

Targeting TOP2A in Ovarian Cancer: Biological and Clinical Implications

The enzyme topoisomerase II alpha (TOP2A) plays a critical role in DNA replication and cell proliferation, making it a promising target for cancer therapy. In epithelial ovarian cancer (EOC), TOP2A overexpression is associated with poor prognosis and resistance to conventional treatments. This review explores the biological functions of TOP2A in EOC and discusses its potential as a therapeutic target. We highlight studies on the mechanisms through which TOP2A contributes to tumor progression and recurrence. Additionally, we evaluate the clinical implications of targeting TOP2A, including the use of TOP2A inhibitors and their combination with novel drugs. We provide a comprehensive overview of the current understanding and future directions for targeting TOP2A in the management of EOC.

Identification of genetic and immune mechanisms linking preeclampsia and endometrial cancer: a prognostic model for survival and treatment response

Preeclampsia (PE) and endometrial cancer (EC) are two distinct conditions that share common genetic and molecular mechanisms involving immune dysregulation, endothelial dysfunction, and angiogenesis. This study aimed to investigate the potential genetic links between PE and EC, identify key prognostic genes, and develop a risk model to predict overall survival in EC patients. We conducted comprehensive genetic and molecular analyses, revealing significant overlaps in immune and angiogenic pathways between PE and EC. Through LASSO regression and multivariate Cox analysis, we identified five core prognostic genes-FSTL3, PRSS23, IGFBP4, MYDGF, and TSC22D3-that were used to construct a risk model. This model effectively stratified EC patients into high- and low-risk groups, with significant differences in overall survival. Patients in the low-risk group exhibited better 1-, 3-, and 5-year survival outcomes and had higher immune cell infiltration and expression of immune checkpoint-related genes, indicating a more favorable tumor microenvironment. Additionally, the analysis showed that these genes are also implicated in the pathogenesis of PE, highlighting potential shared molecular mechanisms. Our findings suggest that these PE-related genes may serve as valuable prognostic biomarkers for EC and could lead to improved prognostic tools and personalized treatment strategies for EC patients.

Lactate dehydrogenase A is a diagnostic biomarker associated with immune infiltration, m6A modification and ferroptosis in endometrial cancer

Background

Lactate dehydrogenase A (LDHA) has been confirmed as a tumor promoter in various cancers, but its role in endometrial cancer remains unclear.

Methods

The Cancer Genome Atlas (TCGA), quantitative real-time polymerase chain reaction and the Human Protein Atlas were utilized to analyzed the LDHA expression in EC. The LDHA levels of patients with different clinical features were compared based on the TCGA cohort. The Genome Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis of LDHA-related genes were conducted by R language. The influence of LDHA knockdown on cell proliferation, apoptosis, migration and invasion was detected by in vitro experiment. The relationship between LDHA expression and immune infiltration was explored by Tumor Immune Estimation Resource 2.0 and Gene Expression Profiling Interactive Analysis. The association of LDHA level with N6-methyladenosine (m6A) modification and ferroptosis was investigated based on the TCGA-UCEC and the GEO cohort.

Results

The LDHA was overexpressed in EC tissues and EC cell lines, and had high predictive accuracy for the EC diagnosis. The LDHA level was associated with age, histological type, histologic grade, and radiation therapy. LDHA-related genes participated in multiple biological functions and signaling pathways. LDHA downregulation significantly promoted cell apoptosis and inhibited the proliferation, migration, and invasion of EC cells. LDHA expression was connected to multiple tumor-infiltrating lymphocytes (TILs), m6A-related genes, and ferroptosis-related genes.

Conclusion

LDHA has the potential to work as an EC biomarker associated with TILs, m6A modification, and ferroptosis in EC.

Artificial intelligence-assisted magnetic resonance imaging technology in the differential diagnosis and prognosis prediction of endometrial cancer

It aimed to analyze the value of deep learning algorithm combined with magnetic resonance imaging (MRI) in the risk diagnosis and prognosis of endometrial cancer (EC). Based on the deep learning convolutional neural network (CNN) architecture residual network with 101 layers (ResNet-101), spatial attention and channel attention modules were introduced to optimize the model. A retrospective collection of MRI image data from 210 EC patients was used for model segmentation and reconstruction, with 140 cases as the test set and 70 cases as the validation set. The performance was compared with traditional ResNet-101 model, ResNet-101 model based on spatial attention mechanism (SA-ResNet-101), and ResNet-101 model based on channel attention mechanism (CA-ResNet-101), using accuracy (AC), precision (PR), recall (RE), and F1 score as evaluation metrics. Among the 70 cases in the validation set, there were 45 cases of low-risk EC and 25 cases of high-risk EC. Using ROC curve analysis, it was found that the area under the curve (AUC) for the diagnosis of high-risk EC of the proposed model in this article (0.918) was visibly larger as against traditional ResNet-101 (0.613), SA-ResNet-101 (0.760), and CA-ResNet-101 models (0.758). The AC, PR, RE, and F1 values of the proposed model for the diagnosis of EC risk were visibly higher (P  < 0.05). In the validation set, postoperative recurrence occurred in 13 cases and did not occur in 57 cases. Using ROC curve analysis, it was found that the AUC for postoperative recurrence prediction of the patients by the proposed model (0.926) was visibly larger as against traditional ResNet-101 (0.620), SA-ResNet-101 (0.729), and CA-ResNet-101 models (0.767). The AC, PR, RE, and F1 values of the proposed model for postoperative recurrence prediction were visibly higher (P  < 0.05). The proposed model in this article, assisted by MRI, presented superior performance in diagnosing high-risk EC patients, with higher sensitivity (Sen) and specificity (Spe), and also demonstrated excellent predictive AC in postoperative recurrence prediction.

Crosstalk between O-GlcNAcylation and ubiquitination: a novel strategy for overcoming cancer therapeutic resistance

Developing resistance to cancer treatments is a major challenge, often leading to disease recurrence and metastasis. Understanding the underlying mechanisms of therapeutic resistance is critical for developing effective strategies. O-GlcNAcylation, a post-translational modification that adds GlcNAc from the donor UDP-GlcNAc to serine and threonine residues of proteins, plays a crucial role in regulating protein function and cellular signaling, which are frequently dysregulated in cancer. Similarly, ubiquitination, which involves the attachment of ubiquitin to to proteins, is crucial for protein degradation, cell cycle control, and DNA repair. The interplay between O-GlcNAcylation and ubiquitination is associated with cancer progression and resistance to treatment. This review discusses recent discoveries regarding the roles of O-GlcNAcylation and ubiquitination in cancer resistance, their interactions, and potential mechanisms. It also explores how targeting these pathways may provide new opportunities to overcome cancer treatment resistance in cancer, offering fresh insights and directions for research and therapeutic development.

The immunological and prognostic significance of the diabetes mellitus-related gene WFS1 in endometrial cancer

Background

Diabetes is associated with the incidence and prognosis of various malignancies, most notably endometrial cancer (EC). This study investigated the connection between diabetes and EC, with a specific focus on elucidating the biological implications of the diabetes mellitus (DM)-related gene WFS1.

Methods

Using the CTD, GeneCards, and GSEA databases, we identified WFS1 as a diabetes-related gene and then conducted an extensive investigation focusing on WFS1 in the context of EC. First, we identified WFS1 as the target gene and obtained EC data from the TCGA database. Then, comprehensive analyses and verification experiments, including differential expression analysis, prognostic modeling, functional enrichment analysis, gene mutation profiling, assessment of immune cell infiltration, immunophenoscore (IPS), tumor stemness index scoring, drug sensitivity analysis, single-cell transcriptomic analysis, glycolytic pathway analysis, and clinical verification, were performed to comprehensively evaluate the clinical value of WFS1 in EC.

Results

The EC group had significantly lower WFS1 expression, with an AUC of 0.857 for the ROC diagnostic curve. Overall survival analysis revealed that WFS1 was an independent risk factor for EC; low WFS1 expression was correlated with a poor prognosis. Stemness index analysis revealed that decreased WFS1 expression was associated with increased tumor grade and enhanced tumor stemness, suggesting increased malignancy of EC. In addition, WFS1 expression was correlated with tumor microenvironment features such as immune cell infiltration. WFS1 was also associated with tumor drug resistance.

Conclusion

EC patients with low WFS1 expression have a worse prognosis. WFS1 can be used as diagnostic and prognostic marker for EC.

Lipid metabolism reprogramming in endometrial cancer: biological functions and therapeutic implications

BACKGROUND

Endometrial cancer is one of the major gynecological cancers, with increasing incidence and mortality in the past decades. Emerging preclinical and clinical data have indicated its close association with obesity and dyslipidemia. Metabolism reprogramming has been considered as the hallmark of cancer, to satisfy the extensive need of nutrients and energy for survival and growth. Particularly, lipid metabolism reprogramming has aroused the researchers' interest in the field of cancer, including tumorigenesis, invasiveness, metastasis, therapeutic resistance and immunity modulation, etc. But the roles of lipid metabolism reprogramming in endometrial cancer have not been fully understood. This review has summarized how lipid metabolism reprogramming induces oncogenesis and progression of endometrial cancer, including the biological functions of aberrant lipid metabolism pathway and altered transcription regulation of lipid metabolism pathway. Besides, we proposed novel therapeutic strategies of targeting lipid metabolism pathway and concentrated on its potential of sensitizing immunotherapy and hormonal therapy, to further optimize the existing treatment modalities of patients with advanced/metastatic endometrial cancer. Moreover, we expect that targeting lipid metabolism plus hormone therapy may block the endometrial malignant transformation and enrich the preventative approaches of endometrial cancer.

CONCLUSION

Lipid metabolism reprogramming plays an important role in tumor initiation and cancer progression of endometrial cancer. Targeting the core enzymes and transcriptional factors of lipid metabolism pathway alone or in combination with immunotherapy/hormone treatment is expected to decrease the tumor burden and provide promising treatment opportunity for patients with advanced/metastatic endometrial cancer.

Effectiveness and safety of PD-1/PD-L1 inhibitors monotherapy in patients with endometrial cancer

BACKGROUND

Studies evaluating the effectiveness of immune checkpoint inhibitors (ICI) for endometrial cancer (EC) are limited. This study aimed to assess the efficacy of PD-1/PD-L1 inhibitors as monotherapy for EC by conducting a meta-analysis. The predictive significance of MMR status, a biomarker for ICI response, also required further investigation.

METHODS

A systematic literature search was conducted in English databases until September 2023. The analysis included objective response rate (ORR), disease control rate (DCR), adverse events (AEs), and odds ratios (OR), along with their corresponding 95% confidence intervals (CI).

RESULTS

There were twelve trials totaling 685 individuals. PD-1/PD-L1 inhibitor monotherapy resulted in an ORR for 34% (95% CI = 24-44%) of the pooled EC patients. Subgroup analysis revealed a significantly higher ORR in dMMR EC (45%) compared to pMMR EC (8%), with an OR of 6.36 (95% CI = 3.64-11.13). The overall DCR was 42%, with dMMR EC at 51% and pMMR EC at 30% (OR = 2.61, 95% CI = 1.69-4.05). Grade three or higher adverse events (AEs) occurred in 15% of cases (95% CI = 9-24%) of the pooled incidence of AEs, which was 68% (95% CI = 65-72%).

CONCLUSIONS

This meta-analysis provides significant evidence for the effectiveness of PD-1/PD-L1 inhibitors as monotherapy for EC. Notably, dMMR EC patients demonstrated superior treatment efficacy with PD-1/PD-L1 inhibitor immunotherapy. Further research is required to explore subclassifications of EC based on dMMR molecular subtypes, enabling improved treatment strategies and outcomes for EC patients.

Endometrial Cancer: 2023 Revised FIGO Staging System and the Role of Imaging

The FIGO endometrial cancer staging system recently released updated guidance based on clinical evidence gathered after the previous version was published in 2009. Different imaging modalities are beneficial across various stages of endometrial cancer (EC) management. Additionally, ongoing research studies are aimed at improving imaging in EC. Gynecological cancer is a crucial element in the practice of a body radiologist. With a new staging system in place, it is important to address the role of radiology in the EC diagnostic pathway. This article is a comprehensive review of the changes made to the FIGO endometrial cancer staging system and the impact of imaging in the staging of this disease.

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.

Construction and Validation of a Prognostic Risk Prediction Model for Lactate Metabolism-Related lncRNA in Endometrial Cancer

Endometrial cancer (EC) is a common group of malignant epithelial tumors that mainly occur in the female endometrium. Lactate is a key regulator of signal pathways in normal and malignant tissues. However, there is still no research on lactate metabolism-related lncRNA in EC. Here, we intended to establish a prognostic risk model for EC based on lactate metabolism-related lncRNA to forecast the prognosis of EC patients. First, we found that 38 lactate metabolism-associated lncRNAs were significantly overall survival through univariate Cox regression analysis. Using minimum absolute contraction and selection operator (LASSO) regression analysis and multivariate Cox regression analysis, six lactate metabolism-related lncRNAs were established as independent predictor in EC patients and were used to establish a prognostic risk signature. We next used multifactorial COX regression analysis and receiver operating characteristic (ROC) curve analysis to confirm that risk score was an independent prognostic factor of overall patient survival. The survival time of patients with EC in different high-risk populations was obviously related to clinicopathological factors. In addition, lactate metabolism-related lncRNA in high-risk population participated in multiple aspects of EC malignant progress through Gene Set Enrichment Analysis, Genomes pathway and Kyoto Encyclopedia of Genes and Gene Ontology. And risk scores were strongly associated with tumor mutation burden, immunotherapy response and microsatellite instability. Finally, we chose a lncRNA SRP14-AS1 to validate the model we have constructed. Interestingly, we observed that the expression degree of SRP14-AS1 was lower in tumor tissues of EC patients than in normal tissues, which was consistent with our findings in the TCGA database. In conclusion, our study constructed a prognostic risk model through lactate metabolism-related lncRNA and validated the model, confirming that the model can be used to predict the prognosis of EC patients and providing a molecular analysis of potential prognostic lncRNA for EC.

A novel immune-related gene signature for diagnosis and potential immunotherapy of microsatellite stable endometrial carcinoma

An immune-related gene signature (IRGS) was established to better understand the molecular and immunologic characteristics of microsatellite instable (MSI) and microsatellite stable (MSS) endometrial carcinoma (EC), and provide potential immunotherapy directions for MSS patients. Top 20 immune-related hub genes were screened by weight gene coexpression network analysis (WGCNA), and an IRGS was further established through Cox regression analysis. The molecular and immune characteristics were clarified in IRGS high and low risk groups. Expression and MS status validation of the IRGS were conducted through quantitative real-time Polymerase Chain Reaction (rt-qPCR) and immunohistochemistry (IHC) analysis. The IRGS includes 2 oncogenes (AGTR1 and HTR3C) and 2 tumor suppressor genes (CD3E and SERPIND1). Patients in IRGS high-risk group were more with MSS status, higher tumor grade, later FIGO stage, serous histology and elder ages compared with IRGS low-risk group (P < 0.05). Besides, patients in MSS group were more FIGO stages II-IV (42.7% vs. 26%), serous histology (35.7% vs. 5.3%) and with higher IRGS risk score (1.51 ± 3.11 vs. 1.02 ± 0.67) (P < 0.05) than patients in MSI group. Furthermore, patients in IRGS high-risk group had higher tumor purity, more Macrophages M1 and Macrophages M2 infiltrating, higher proportion of Macrophages M2 and Dendritic cells activated, lower proportion of T cells regulatory (Tregs), lower tumor mutation burden (TMB). Correspondingly, subjects in IRGS low-risk group had higher immunphenoscores than IRGS high-risk group. The relative mRNA level of AGTR1 and HTR3C were gradually increase, while CD3E and SERPIND1 were reversed in rt-qPCR. Through IHC experiments, AGTR1(69.2% vs 30%, P = 0.074) and HTR3C (76.9% vs 30%, P = 0.024) had higher positive staining rates in ECs than non-ECs. While SERPIND1 (84.6% vs 20%, P = 0.003) and CD3E (61.5% vs 40%, P = 0.000) had higher positive staining rates in non-ECs. IRGS is a potential diagnostic and prognostic biomarker for EC. IRGS low risk group might benefit from immune checkpoint inhibitors, while IRGS high risk group deserve other potential immunotherapy.

The role and participation of immune cells in the endometrial tumor microenvironment

The tumor microenvironment is surrounded by blood vessels and consists of malignant, non-malignant, and immune cells, as well as signalling molecules, which primarily affect the therapeutic response and curative effects of drugs in clinical studies. Tumor-infiltrating immune cells participate in tumor progression, impact anticancer therapy, and eventually lead to the development of immune tolerance. Immunotherapy is evolving as a promising therapeutic intervention to stimulate and activate the immune system to suppress cancer cell growth. Endometrial cancer (EC) is an immunogenic disease, and in recent years, immunotherapy has shown benefit in the treatment of recurrent and advanced EC. This review discusses the key molecular pathways associated with the intra-tumoral immune response and the involvement of circulatory signalling molecules. Specific immunologic signatures in EC which offer targets for immunomodulating agents, are also discussed. We have summarized the available literature in support of using immunotherapy in EC. Lastly, we have also discussed ongoing clinical trials that may offer additional promising immunotherapy options in the future. The manuscript also explored innovative approaches for screening and identifying effective drugs, and to reduce the financial burdens for the development of personalized treatment strategies. Collectively, we aim to provide a comprehensive review of the role of immune cells and the tumor microenvironment in the development, progression, and treatment of EC.

Association Between Intermediate End Points, Progression-free Survival, and Overall Survival in First-line Advanced or Recurrent Endometrial Cancer

PURPOSE

Advanced/recurrent endometrial cancer is associated with poor long-term outcomes. Clinical studies of novel regimens are ongoing, but given that data on overall survival (OS) take a long time to mature, surrogate end points are often used to support clinical-research interpretation. The aim of this study was to explore the correlation between progression-free survival (PFS)/time to progression (TTP) and OS across multiple time points in the first-line treatment of advanced/recurrent endometrial cancer.

METHODS

This study comprised meta-analyses of Phase 2/3 randomized, controlled trials of first-line treatments in patients with advanced primary or first-recurrent endometrial cancer identified via systematic literature review. The strength of the surrogacy relationship was assessed by correlation analyses (estimated with Spearman and Pearson correlation coefficients) and weighted linear regression.

FINDINGS

Data from 15 studies were included. PFS and TTP (TTP was reported in one study only) were highly correlated with future OS at multiple time points (Spearman values, 0.83-0.90; Pearson values, 0.86-0.93), suggesting that a change in PFS/TTP would likely be correlated with a change in OS in the same direction. On weighted linear regression, a 10% increase in PFS/TTP probability was significantly associated with a 9.3% to 13.3% increase in the probability of future OS. The strong positive association between PFS/TTP and OS was supported by findings from sensitivity analyses based on identified sources of interstudy heterogeneity.

IMPLICATIONS

PFS/TTP is a good potential candidate for predicting long-term OS outcomes in trials of first-line treatment in patients with advanced/recurrent endometrial cancer. The findings from this report may help to inform health-authority and clinical decision makers that PFS/TTP improvements are likely to translate into subsequent OS improvements once data mature.

The role of tumor-associated macrophages in the progression, prognosis and treatment of endometrial cancer

Tumor-associated macrophages (TAMs) are the main immune cells in the tumor microenvironment (TME) of endometrial cancer (EC). TAMs recruitment and polarization in EC is regulated by the TME of EC, culminating in a predominantly M2-like macrophage infiltration. TAMs promote lymphatic angiogenesis through cytokine secretion, aid immune escape of EC cells by synergizing with other immune cells, and contribute to the development of EC through secretion of exosomes so as to promoting EC development. EC is a hormone- and metabolism-dependent cancer, and TAMs promote EC through interactions on estrogen receptor (ER) and metabolic factors such as the metabolism of glucose, lipids, and amino acids. In addition, we have explored the predictive significance of some TAM-related indicators for EC prognosis, and TAMs show remarkable promise as a target for EC immunotherapy.

Targeting DNA Damage Repair and Immune Checkpoint Proteins for Optimizing the Treatment of Endometrial Cancer

The dependence of cancer cells on the DNA damage response (DDR) pathway for the repair of endogenous- or exogenous-factor-induced DNA damage has been extensively studied in various cancer types, including endometrial cancer (EC). Targeting one or more DNA damage repair protein with small molecules has shown encouraging treatment efficacy in preclinical and clinical models. However, the genes coding for DDR factors are rarely mutated in EC, limiting the utility of DDR inhibitors in this disease. In the current review, we recapitulate the functional role of the DNA repair system in the development and progression of cancer. Importantly, we discuss strategies that target DDR proteins, including PARP, CHK1 and WEE1, as monotherapies or in combination with cytotoxic agents in the treatment of EC and highlight the compounds currently being evaluated for their efficacy in EC in clinic. Recent studies indicate that the application of DNA damage agents in cancer cells leads to the activation of innate and adaptive immune responses; targeting immune checkpoint proteins could overcome the immune suppressive environment in tumors. We further summarize recently revolutionized immunotherapies that have been completed or are now being evaluated for their efficacy in advanced EC and propose future directions for the development of DDR-based cancer therapeutics in the treatment of EC.

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.

Tumor-TME Bipartite Landscape of PD-1/PD-L1 in Endometrial Cancers

The bipartite landscape of tumor cells and stromal cells determines a tumor's response to treatment during disease management. In endometrial cancers (ECs), the mechanistic contribution of PD-L1/L2 and PD-1 signaling of the host's tumor microenvironment (TME) (CAF and immune cells) in the context of the tumor cells is elusive. To understand the tumor-stroma-immune crosstalk, we studied the compartmental pattern of PD-L1/L2 and PD-1 expression in EC tissues and their matched CAFs. Over 116 surgically resected tumors (T) and the tumor-adjacent normal tissues (N) were obtained from consented unselected consecutive patients. IHC was performed in T, N-epi-thelium, and the stromal mesenchymal environment (SME; mesenchyme) in the T and N tissues. The staining intensity and distribution patterns of PD-L1/L2 and PD-1 in the FFPE sections of T and N were evaluated by a pathologist using a standard scoring system of TPS and CPS. We tested the PD-L1/L2 and PD-1 immune landscape of tumor-TME pair and normal epithelial-stromal mesenchyme pairs from patients with different grades of disease vis-à-vis their CAF PD-L1 levels. We used qRT-PCR to determine the expressions of mRNAs, while the flow cytometry and ICC determined the level of expression of proteins. We observed higher levels of PD-L1 mRNA and protein expression in primary CAFs from the resected tumor tissue compared to the tumor-adjacent normal tissues. We also determined the expression of patients' soluble PD-L1/L2 as peripheral readouts of PD-L1/L2 and PD-1. As we evaluated the results in the context of their pathological parameters, such as grades, stages, lymphovascular invasion, percentage of myometrial invasion, and dMMR in patients, the dominance of PD-L1 expression in TME was positively correlated to the higher pathological grades of tumors, and its relationship with the dMMR. Since the neutralization of CD8-positive cytotoxic T-cells is PD-L1-dependent, our data indicate that irrespective of the PD-L1 positivity of tumor cells, the PD-L1-positive CAFs can play a critical role in bringing out an additional load of PD-L1 for an effective engagement of PD-1 within a tumor mass.

Screening and validation of potential markers associated with uterine corpus endometrial carcinoma and polycystic ovary syndrome based on bioinformatics methods

Background: Endometrial cancer (UCEC) is a commonly occurring tumor in females, and polycystic ovary syndrome (PCOS) is closely related to UCEC, but the molecular mechanisms remain unclear. This article aims to explore potential molecular mechanisms in UCEC and PCOS, as well as identify prognostic genes for UCEC. Methods: Bioinformatics methods were employed to screen for DEGs in UCEC and PCOS. The shared DEGs were analyzed by constructing a protein-protein interaction (PPI) network using the String database and Cytoscape software. The enrichment analysis was performed using Metascape. The shared DEGs associated with the prognosis of UCEC were identified through univariate and lasso Cox regression methods. A multivariate Cox regression model was constructed and internally validated. The expression and test efficiency of the key prognostic genes were verified using external datasets for UCEC and PCOS. Furthermore, the Gepia database was utilized to analyze the expression of key prognostic genes and their correlation with the disease-free survival (RFS) of UCEC. Tumor mutation burden (TMB), immune infiltration, and the correlation of immune cells were assessed for the prognostic genes of UCEC. Results: There were 151 shared DEGs identified between UCEC and PCOS through bioinformatics screening. These shared DEGs were primarily enriched in leukocyte activation. Following model construction and verification, nine genes were determined to be prognostic for UCEC from the shared DEGs. Among them, TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 were confirmed as prognostic genes in UCEC through external validation. Additionally, RTN1 was identified as a key gene in both UCEC and PCOS. Gepia analysis revealed that higher expression of RTN1 was associated with RFS in UCEC. Immune infiltration analysis of the shared DEGs demonstrated significant differences in the expression of various immune cells between UCEC high and low TMB groups. The seven key prognostic genes in UCEC exhibited regulatory relationships with immune cells. Conclusion: This study identified TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 as the key prognostic DEGs of UCEC. These genes are associated with UCEC survival, TMB, immune cell infiltration, and immune cell regulation. Among them, RTN1 may serve as a potential biomarker for both UCEC and PCOS.

Identification of an endoplasmic reticulum stress-related gene signature to predict prognosis and potential drugs of uterine corpus endometrial cancer

Uterine corpus endometrial cancer (UCEC) is the sixth most common female cancer worldwide, with an increasing incidence. Improving the prognosis of patients living with UCEC is a top priority. Endoplasmic reticulum (ER) stress has been reported to be involved in tumor malignant behaviors and therapy resistance, but its prognostic value in UCEC has been rarely investigated. The present study aimed to construct an ER stress-related gene signature for risk stratification and prognosis prediction in UCEC. The clinical and RNA sequencing data of 523 UCEC patients were extracted from TCGA database and were randomly assigned into a test group (n = 260) and training group (n = 263). An ER stress-related gene signature was established by LASSO and multivariate Cox regression in the training group and validated by Kaplan-Meier survival analysis, Receiver Operating Characteristic (ROC) curves and nomograms in the test group. Tumor immune microenvironment was analyzed by CIBERSORT algorithm and single-sample gene set enrichment analysis. R packages and the Connectivity Map database were used to screen the sensitive drugs. Four ERGs (ATP2C2, CIRBP, CRELD2 and DRD2) were selected to build the risk model. The high-risk group had significantly reduced overall survival (OS) (P < 0.05). The risk model had better prognostic accuracy than clinical factors. Tumor-infiltrating immune cells analysis depicted that CD8+ T cells and regulatory T cells were more abundant in the low-risk group, which may be related to better OS, while activated dendritic cells were active in the high-risk group and associated with unfavorable OS. Several kinds of drugs sensitive to the high-risk group were screened out. The present study constructed an ER stress-related gene signature, which has the potential to predict the prognosis of UCEC patients and have implications for UCEC treatment.

Advances in Chemotherapy and Targeted Therapies in Endometrial Cancer

Endometrial cancer is now recognized to be several diseases with differing biology and responses to treatment. Improved molecular characterization has furthered the development and testing of targeted therapies in the different cohorts of endometrial cancer. Lessons are being learned from other cancers that share similar molecular typing, and hence, potentially similar tumor behavior. This commentary serves as a broad overview of the types of advances to which our patients now have access.