Identification of Hypoxia Signature to Assess the Tumor Immune Microenvironment and Predict Prognosis in Patients with Ovarian Cancer

TGF β1 promotes the polarization of M2-type macrophages and activates PI3K/mTOR signaling pathway by inhibiting ISG20 to sensitize ovarian cancer to cisplatin

The involvement of Interferon-stimulated exonuclease gene 20 (ISG20) has been reported in renal clear cell carcinoma, hepatocellular carcinoma, and cervical cancer. However, its role in ovarian cancer chemotherapy remains unclear. In this study, we conducted a comparative analysis of TGF-β1 and ISG20 in cisplatin-sensitive and cisplatin-resistant ovarian cancer cells and tissues using qRT-PCR and a tissue immunofluorescence analysis. We also investigated the impact of ISG20-targeted drugs (IFN-γ) and TGF-β1 inhibitors on cisplatin response both in vivo and in vitro. Additionally, we assessed the effects of TGF-β1 or ISG20 on the polarization of tumor-associated macrophages through flow cytometry and ELISA analysis. Our findings revealed that ISG20 expression was lower in cisplatin-resistant tissues compared to cisplatin-sensitive tissues; however, overexpression of ISG20 sensitized ovarian cancer to cisplatin treatment. Furthermore, activation of ISG20 expression with IFN-γ or TGF-β1 inhibitors enhanced the sensitivity of ovarian cancer cells to cisplatin therapy. Notably, our results demonstrated that TGF-β1 promoted M2-type macrophage polarization as well as PI3K/mTOR pathway activation by suppressing ISG20 expression both in vivo and in vitro. In conclusion, our study highlights the critical role played by ISG20 within the network underlying cisplatin resistance in ovarian cancer. Targeting ISG20 using IFN-γ or TGF-β1 inhibitors may represent a promising therapeutic strategy for treating ovarian cancer.

HIF-2α-dependent TGFBI promotes ovarian cancer chemoresistance by activating PI3K/Akt pathway to inhibit apoptosis and facilitate DNA repair process

Hypoxia-mediated chemoresistance plays a crucial role in the development of ovarian cancer (OC). However, the roles of hypoxia-related genes (HRGs) in chemoresistance and prognosis prediction and theirs underlying mechanisms remain to be further elucidated. We intended to identify and validate classifiers of hub HRGs for chemoresistance, diagnosis, prognosis as well as immune microenvironment of OC, and to explore the function of the most crucial HRG in the development of the malignant phenotypes. The RNA expression and clinical data of HRGs were systematically evaluated in OC training group. Univariate and multivariate Cox regression analysis were applied to construct hub HRGs classifiers for prognosis and diagnosis assessment. The relationship between classifiers and chemotherapy response and underlying pathways were detected by GSEA, CellMiner and CIBERSORT algorithm, respectively. OC cells were cultured under hypoxia or transfected with HIF-1α or HIF-2α plasmids, and the transcription levels of TGFBI were assessed by quantitative PCR. TGFBI was knocked down by siRNAs in OC cells, CCK8 and in vitro migration and invasion assays were performed to examine the changes in cell proliferation, motility and metastasis. The difference in TGFBI expression was examined between cisplatin-sensitive and -resistant cells, and the effects of TGFBI interference on cell apoptosis, DNA repair and key signaling molecules of cisplatin-resistant OC cells were explored. A total of 179 candidate HRGs were extracted and enrolled into univariate and multivariate Cox regression analysis. Six hub genes (TGFBI, CDKN1B, AKAP12, GPC1, TGM2 and ANGPTL4) were selected to create a HRGs prognosis classifier and four genes (TGFBI, AKAP12, GPC1 and TGM2) were selected to construct diagnosis classifiers. The HRGs prognosis classifier could precisely distinguish OC patients into high-risk and low-risk groups and estimate their clinical outcomes. Furthermore, the high-risk group had higher percentage of Macrophages M2 and exhibited higher expression of immunecheckpoints such as PD-L2. Additionally, the diagnosis classifiers could accurately distinguish OC from normal samples. TGFBI was further verified as a specific key target and demonstrated that its high expression was closely correlated with poor prognosis and chemoresistance of OC. Hypoxia upregulated the expression level of TGFBI. The hypoxia-induced factor HIF-2α but not HIF-1α could directly bind to the promoter region of TGFBI, and facilitate its transcription level. TGFBI was upregulated in cisplatin-sensitive and resistant ovarian cancer cells in a cisplatin time-dependent manner. TGFBI interference downregulated DNA repair-related markers (p-p95/NBS1, RAD51, p-DNA-PKcs, DNA Ligase IV and Artemis), apoptosis-related marker (BCL2) and PI3K/Akt pathway-related markers (PI3K-p110 and p-Akt) in cisplatin-resistant OC cells. In summary, the HRGs prognosis risk classifier could be served as a predictor for OC prognosis and efficacy evaluation. TGFBI, upregulated by HIF-2α as an HRG, promoted OC chemoresistance through activating PI3K/Akt pathway to reduce apoptosis and enhance DNA damage repair pathway.

Metabolic reprogramming in the tumor microenvironment: unleashing T cell stemness for enhanced cancer immunotherapy

T cells play a pivotal role in the immune system by distinguishing between various harmful pathogens and cancerous cells within the human body and initiating an immune response. Within the tumor microenvironment (TME), immune effector T cells encounter both immunosuppressive cells and factors that hinder their functionality. Additionally, they endure robust and persistent antigenic stimulation, often leading to exhaustion and apoptosis. However, the stemness of T cells, characterized by their ability to survive and self-renew over extended periods, represents a primary target in immune checkpoint therapies such as anti-PD-1 therapy. T cell stemness encompasses specific memory T cell subsets and progenitor-exhausted T cells with stem cell-like properties. Therefore, understanding the impact of the TME on T cell stemness, including factors like K+, lactate, and H+, holds significant importance and can facilitate the mitigation of terminal T-cell depletion, the identification of potential resilient biomarkers or therapeutic targets resistant to immune checkpoint therapies, and ultimately lead to sustained anti-tumor effects. Thus, it offers a novel perspective for advancing tumor immunotherapy.

Proteomic analysis of exosomes secreted during the epithelial-mesenchymal transition and potential biomarkers of mesenchymal high-grade serous ovarian carcinoma

BACKGROUND

The epithelial-mesenchymal transition (EMT) promotes cell signaling and morphology alterations, contributing to cancer progression. Exosomes, extracellular vesicles containing proteins involved in cell-cell communication, have emerged as a potential source of biomarkers for several diseases.

METHODS

Our aim was to assess the proteome content of exosomes secreted after EMT-induction to identify potential biomarkers for ovarian cancer classification. EMT was induced in the ovarian cancer cell line CAOV3 by treating it with EGF (10 ng/mL) for 96 h following 24 h of serum deprivation. Subsequently, exosomes were isolated from the supernatant using selective centrifugation after decellularization, and their characteristics were determined. The proteins present in the exosomes were extracted, identified, and quantified using Label-Free-Quantification (LFQ) via Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). To identify potential biomarkers, the obtained proteomic data was integrated with the TGGA database for mRNA expression using principal component analysis and a conditional inference tree.

RESULTS

The exosomes derived from CAOV3 cells exhibited similar diameter and morphology, measuring approximately 150 nm, regardless of whether they were subjected to EMT stimulation or not. The proteomic analysis of proteins from CAOV3-derived exosomes revealed significant differential regulation of 157 proteins, with 100 showing upregulation and 57 downregulation upon EMT induction. Further comparison of the upregulated proteins with the TCGA transcriptomic data identified PLAU, LAMB1, COL6A1, and TGFB1 as potential biomarkers of the mesenchymal HGSOC subtype.

CONCLUSIONS

The induction of EMT, the isolation of exosomes, and the subsequent proteomic analysis highlight potential biomarkers for an aggressive ovarian cancer subtype. Further investigation into the role of these proteins is warranted to enhance our understanding of ovarian cancer outcomes.

The TGFBI gene and protein expression in topotecan resistant ovarian cancer cell lines

PURPOSE

The primary limiting factor in achieving cures for patients with cancer, particularly ovarian cancer, is drug resistance. The mechanisms of drug resistance of cancer cells during chemotherapy may include compounds of the extracellular matrix, such as the transforming growth factor-beta-induced protein (TGFBI). In this study, we aimed to analyze the TGFBI gene and protein expression in different sensitive and drug-resistant ovarian cancer cell lines, as well as test if TGFBI can be involved in the response to topotecan (TOP) at the very early stages of treatment.

MATERIALS AND METHODS

In this study, we conducted a detailed analysis of TGFBI expression in different ovarian cancer cell lines (A2780, A2780TR1, A2780TR2, W1, W1TR, SKOV-3, PEA1, PEA2 and PEO23). The level of TGFBI mRNA (QPCR), intracellular and extracellular protein (Western blot analysis) were assessed in this study.

RESULTS

We observed upregulation of TGFBI mRNA in drug-resistant cell lines and estrogen-receptor positive cell lines, which was supported by overexpression of both intracellular and extracellular TGFBI protein. We also showed the TGFBI expression after a short period of treatment of sensitive ovarian cancer cell lines with TOP.

CONCLUSION

The expression of TGFBI in ovarian cancer cell lines suggests its role in the development of drug resistance.

Angiopoietin-like 4 induces head and neck squamous cell carcinoma cell migration through the NRP1/ABL1/PXN pathway

OBJECTIVES

The molecular mechanisms whereby angiopoietin-like 4 (ANGPTL4), a pluripotent protein implicated in cancer development, contributes to head and neck squamous cell carcinoma (HNSCC) growth and dissemination are unclear.

MATERIALS AND METHODS

We investigated ANGPTL4 expression in human normal oral keratinocytes (NOKs), dysplastic oral keratinocytes (DOKs), oral leukoplakia cells (LEUK1), and HNSCC cell lines, as well as in tissue biopsies from patients with oral dysplasia, and primary and metastatic HNSCC. We further examined the contribution of ANGPTL4 cancer progression in an HNSCC orthotopic floor-of mouth tumor model and the signaling pathways linking ANGPTL4 to cancer cell migration.

RESULTS

ANGPTL4 expression was upregulated in premalignant DOKs and HNSCC cell lines compared to NOKs and was increased in tissue biopsies from patients with oral dysplasia, as well as in primary and metastatic HNSCC. We also observed that downregulation of ANGPTL4 expression inhibited primary and metastatic cancer growth in an HNSCC orthotopic tumor model. Interestingly, ANGPTL4 binding to the neuropilin1 (NRP1) receptor led to phosphorylation of the focal adhesion protein, paxillin (PXN), and tumor cell migration; this was dependent on the tyrosine kinase ABL1. Treatment with the ABL1 inhibitor, dasatinib and small interfering RNA silencing of NRP1 or ABL1 expression blocked PXN phosphorylation and tumor cell migration.

CONCLUSION

Our findings suggest an early, sustained, and angiogenesis-independent autocrine role for ANGPTL4 in HNSCC progression and expose ANGPTL4/NRP1/ABL1/PXN as an early molecular marker and vulnerable target for the prevention of HNSCC growth and metastasis.

An artificial intelligence prediction model based on extracellular matrix proteins for the prognostic prediction and immunotherapeutic evaluation of ovarian serous adenocarcinoma

Background: Ovarian Serous Adenocarcinoma is a malignant tumor originating from epithelial cells and one of the most common causes of death from gynecological cancers. The objective of this study was to develop a prediction model based on extracellular matrix proteins, using artificial intelligence techniques. The model aimed to aid healthcare professionals to predict the overall survival of patients with ovarian cancer (OC) and determine the efficacy of immunotherapy. Methods: The Cancer Genome Atlas Ovarian Cancer (TCGA-OV) data collection was used as the study dataset, whereas the TCGA-Pancancer dataset was used for validation. The prognostic importance of 1068 known extracellular matrix proteins for OC were determined by the Random Forest algorithm and the Lasso algorithm establishing the ECM risk score. Based on the gene expression data, the differences in mRNA abundance, tumour mutation burden (TMB) and tumour microenvironment (TME) between the high- and low-risk groups were assessed. Results: Combining multiple artificial intelligence algorithms we were able to identify 15 key extracellular matrix genes, namely, AMBN, CXCL11, PI3, CSPG5, TGFBI, TLL1, HMCN2, ESM1, IL12A, MMP17, CLEC5A, FREM2, ANGPTL4, PRSS1, FGF23, and confirm the validity of this ECM risk score for overall survival prediction. Several other parameters were identified as independent prognostic factors for OC by multivariate COX analysis. The analysis showed that thyroglobulin (TG) targeted immunotherapy was more effective in the high ECM risk score group, while the low ECM risk score group was more sensitive to the RYR2 gene-related immunotherapy. Additionally, the patients with low ECM risk scores had higher immune checkpoint gene expression and immunophenoscore levels and responded better to immunotherapy. Conclusion: The ECM risk score is an accurate tool to assess the patient's sensitivity to immunotherapy and forecast OC prognosis.

ANGPTL4 functions as an oncogene through regulation of the ETV5/CDH5/AKT/MMP9 axis to promote angiogenesis in ovarian cancer

BACKGROUND

Angiopoietin-like 4 (ANGPTL4) is highly expressed in a variety of neoplasms and promotes cancer progression. Nevertheless, the mechanism of ANGPTL4 in ovarian cancer (OC) metastasis remains unclear. This study aimeds to explore whether ANGPTL4 regulates OC progression and elucidate the underlying mechanism.

METHODS

ANGPTL4 expression in clinical patient tumor samples was determined by immunohistochemistry (IHC) and high-throughput sequencing. ANGPTL4 knockdown (KD) and the addition of exogeneous cANGPTL4 protein were used to investigate its function. An in vivo xenograft tumor experiment was performed by intraperitoneal injection of SKOV3 cells transfected with short hairpin RNAs (shRNAs) targeting ANGPTL4 in nude mice. Western blotting and qRT-PCR were used to detect the levels of ANGPTL4, CDH5, p-AKT, AKT, ETV5, MMP2 and MMP9 in SKOV3 and HO8910 cells transfected with sh-ANGPTL4 or shRNAs targeting ETV5.

RESULTS

Increased levels of ANGPTL4 were associated with poor prognosis and metastasis in OC and induced the angiogenesis and metastasis of OC cells both in vivo and in vitro. This tumorigenic effect was dependent on CDH5, and the expression levels of ANGPTL4 and CDH5 in human OC werepositively correlated. In addition, CDH5 activated p-AKT, and upregulated the expression of MMP2 and MMP9. We also found that the expression of ETV5 was upregulated by ANGPTL4, which could bind the promoter region of CDH5, leading to increased CDH5 expression.

CONCLUSION

Our data indicated that an increase in the ANGPTL4 level results in increased ETV5 expression in OC, leading to metastasis via activation of the CDH5/AKT/MMP9 signaling pathway.

Identification of fatty acid signature to predict prognosis and guide clinical therapy in patients with ovarian cancer

High-grade serous ovarian cancer (HGSOC) is a heterogeneous cancer characterized by high relapse rate. Approximately 80% of women are diagnosed with late-stage disease, and 15–25% of patients experience primary treatment resistance. Ovarian cancer brings tremendous suffering and is the most malignant type in all gynecologic malignancies. Metabolic reprogramming in tumor microenvironment (TME), especially fatty acid metabolism, has been identified to play a crucial role in cancer prognosis. Yet, the underlying mechanism of fatty acid metabolism on ovarian cancer progression is severely understudied. Recently, studies have demonstrated the role of fatty acid metabolism reprogramming in immune cells, but their roles on cancer cell metastasis and cancer immunotherapy response are poorly characterized. Here, we reported that the fatty acid–related genes are aberrantly varied between ovarian cancer and normal samples. Using samples in publicly databases and bio-informatic analyses with fatty acid–related genes, we disentangled that cancer cases can be classified into high- and low-risk groups related with prognosis. Furthermore, the nomogram model was constructed to predict the overall survival. Additionally, we reported that different immune cells infiltration was presented between groups, and immunotherapy response differed in two groups. Results showed that our signature may have good prediction value on immunotherapy efficacy, especially for anti–PD-1 and anti–CTLA-4. Our study systematically marked the critical association between cancer immunity in TME and fatty acid metabolism, and bridged immune phenotype and metabolism programming in tumors, thereby constructed the metabolic-related prognostic model and help to understand the underlying mechanism of immunotherapy response.

Comprehensive analysis of immune ferroptosis gene in renal clear cell carcinoma: prognosis and influence of tumor microenvironment

OBJECTIVE

We conducted an in-depth study of the immune system and ferroptosis to identify prognostic biomarkers and therapeutic targets for renal clear cell carcinoma.

METHODS

Immune ferroptosis-related differentially expressed genes (IFR-DEGs) were selected from The Cancer Genome Atlas (TCGA). A lasso-Cox risk scoring model was established; its prognostic value was determined using prognostic analysis and single multivariate Cox analysis. Model genes were subjected to subcellular fluorescence localization, mRNA and protein expression analyses, and single-cell RNA sequencing localization analysis. Risk score was analyzed using the immune score, immune infiltrating cell correlation, immune checkpoint, TIDE, and drug sensitivity.

RESULTS

A total of 103 IFR-DEGs were identified; a risk model comprising ACADSB, CHAC1, LURAP1L, and PLA2G6 was established. The survival curve, single multivariate Cox regression, and receiver operating characteristic (ROC) curve analysis showed that the model had good predictive ability (p < 0.05). It was also validated using the validation set and total cohort. Subcellular fluorescence localization revealed that ACADSB, CHAC1, and PLA2G6 were distributed in the cytoplasm and LURAP1L in the nucleus. The mRNA and protein expression trends were consistent. Single-cell RNA sequencing mapping revealed that ACADSB was enriched in distal tubule cell clusters. In the Kidney renal clear cell carcinoma (KIRC) mutation correlation analysis, 1.56% of the patients were found to have genetic alterations; The Spearman correlation analysis of model gene mutations showed that ACADSB was positively correlated with LURAP1L, which may have a synergistic effect; it was negatively correlated with CHAC1 and PLA2G6, and CHAC1 was negatively correlated with LURAP1L, which may have an antagonistic effect. Model and immune correlation analyses found that high-risk patients had significantly higher levels of CD8+ T cells, regulatory T cells (Tregs), immune checkpoints, immune scores, and immune escape than those in low-risk patients. High-risk patients had a higher susceptibility to small-molecule drugs.

CONCLUSION

A novel prognostic model of immune ferroptosis-related genes (ACADSB, CHAC1, LURAP1L, and PLA2G6), which plays an important role in immune infiltration, microenvironment, and immune escape, was constructed. It effectively predicts the survival of patients with KIRC.

Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer

Purpose

The hypoxic microenvironment is involved in the tumorigenesis of ovarian cancer (OC). Therefore, we aim to develop a non-invasive radiogenomics approach to identify a hypoxia pattern with potential application in patient prognostication.

Methods

Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. Meanwhile, multiple hypoxia-related subtypes were identified by unsupervised consensus analysis and LASSO–Cox regression analysis. Subsequently, diversified bioinformatics algorithms were used to explore the immune microenvironment, prognosis, biological pathway alteration, and drug sensitivity among different subtypes. Finally, optimal radiogenomics biomarkers for predicting the risk status of patients were developed by machine learning algorithms.

Results

One hundred forty sHRGs and three types of hypoxia-related subtypes were identified. Among them, hypoxia-cluster-B, gene-cluster-B, and high-risk subtypes had poor survival outcomes. The subtypes were closely related to each other, and hypoxia-cluster-B and gene-cluster-B had higher hypoxia risk scores. Notably, the low-risk subtype had an active immune microenvironment and may benefit from immunotherapy. Finally, a four-feature radiogenomics model was constructed to reveal hypoxia risk status, and the model achieved area under the curve (AUC) values of 0.900 and 0.703 for the training and testing cohorts, respectively.

Conclusion

As a non-invasive approach, computed tomography-based radiogenomics biomarkers may enable the pretreatment prediction of the hypoxia pattern, prognosis, therapeutic effect, and immune microenvironment in patients with OC.

Matrine Combined with Mammalian Target of Rapamycin Inhibitor Enhances Anti-Tumor Efficacy of dendritic cell Vaccines in hepatocellular carcinoma

Dendritic cells (DCs), as the most important antigen-presenting cells, play a crucial role in T cell activation. The latest research showed that inhibition of the mammalian target of rapamycin (mTOR) could enhance DCs maturation, promoting antigen presentation. Matrine has been identified as one of the key alkaloids isolated from the roots of Sophora flavescens. In present study, we combined matrine and mTOR inhibitor KU0063794 to observe the DCs functions, especially the antigen presentation ability. DCs were activated by phosphate-buffered saline (PBS), lipopolysaccharide (LPS), LPS+KU0063794, LPS+Matrine, and LPS+KU0063794+Matrine. The surface markers in DCs, proliferation of T cells and cytokines were detected by flow cytometry, cell counting kit-8 (CCK-8) and enzyme-linked immunosorbent assay (ELISA), respectively. The lactate dehydrogenase (LDH) release test was used to detect the antitumor efficacy. The tumor growth curves were plotted by calculating tumor volume. The apoptosis was detected by Terminal-deoxynucleoitidyl Transferase-Mediated Nick End Labeling (TUNEL) method. Matrine combined with KU0063794 could enhance the maturity of DCs, T cells proliferation and cytokines secretion (P < 0.05). The cytotoxic T lymphocytes (CTL) killing efficacy of LPS+KU0063794+Matrine group was higher than other groups (P < 0.05). In vivo, the tumor weights and volumes in LPS+KU0063794+Matrine group were lower than other groups. The detections of tumor apoptosis were increased in LPS+KU0063794+Matrine group (P < 0.05). DC vaccine with mTOR inhibitor and matrine could significantly improve the efficacy of antitumor immunity in vitro and vivo. These findings illustrated that mTOR inhibitor and matrine, as two immunomodulators, could enhance DC activation and differentiation.

miR-149-3p Is a Potential Prognosis Biomarker and Correlated with Immune Infiltrates in Uterine Corpus Endometrial Carcinoma

BACKGROUND

Endocrine disruption is an important factor in the development of endometrial cancer. Expression of miR-149-3p is observed in some cancer types, while its role in uterine corpus endometrial carcinoma (UCEC) is unclear.

METHODS

The clinical and genomic data and prognostic information on UCEC were obtained for patients from the TCGA database. The Kruskal-Wallis test, Wilcoxon signed-rank test, and logistic regression were used to analyze the relationship between clinical characteristics and miR-149-3p expression. Kaplan-Meier survival curve analysis was used to study the influence of miR-149-3p expression and miR-149-3p target genes on the prognosis of UCEC patients. The TargetScan, PicTar, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to determine the involvement of miR-149-3p target genes in function. Immune infiltration analysis was used to analyze the functional involvement of miR-149-3p. QRT-PCR was used to validate the expression of miR-149-3p in UCEC cell lines.

RESULTS

High expression of miR-149-3p in UCEC was significantly associated with age (P < 0.001), histological type (P < 0.001), histological grade (P < 0.001), tumor invasion (P=0.014), and radiation therapy (P=0.011). High miR-149-3p expression predicted poorer overall survival (OS) (HR: 2.56; 95% CI: 1.64-4.00; P < 0.001), progression-free interval (PFI) (HR: 1.85; 95% CI: 1.29-2.65; P=0.001), and disease-specific survival (DSS) (HR: 2.33; 95% CI: 1.37-3.99; P=0.002). Low expressions of miR-149-3p target genes, including ADCYAP1R1, CGNL1, CHST3, CYGB, DNAH9, ESR1, HHIP, HIC1, HOXD11, IGF1, INMT, LSP1, MTMR10, NFIC, PLCE1, RARA, SNTN, SPRYD3, and ZBTB7A, were associated with poor OS in UCEC. MiR-149-3p may be involved in the occurrence and development of UCEC via pathways including PI3K-Akt signaling pathway, Ras signaling pathway, AGE-RAGE signaling pathway in diabetic complications, focal adhesion, and MAPK signaling pathway. miR-149-3p may inhibit the function of CD8 T cells, cytotoxic cells, eosinophils, iDC, mast cells, neutrophils, NK CD56bright cells, NK CD56dim cells, pDC, T cells, T helper cells, TFH, Th17 cells, and Treg. miR-149-3p was significantly upregulated in UCEC cell lines compared with endometriotic stromal cells.

CONCLUSION

High expression of miR-149-3p was significantly associated with poor survival in UCEC patients. It may be a promising biomarker of prognosis and response to immunotherapy for UCEC patients.