Endothelial Rbpj is essential for the education of tumour-associated macrophages

Epithelial ovarian cancer (EOC) is one of the most lethal gynaecological cancers worldwide. EOC cells educate tumour-associated macrophages (TAMs) through CD44-mediated cholesterol depletion to generate an immunosuppressive tumour microenvironment (TME). In addition, tumour cells frequently activate Notch1 receptors on endothelial cells (ECs) to facilitate metastasis. However, little is known whether the endothelium would also influence the education of recruited monocytes. Here, we report that canonical Notch signalling through RBPJ in ECs is an important player in the education of TAMs and EOC progression. Deletion of Rbpj in the endothelium of adult mice reduced infiltration of monocyte-derived macrophages into the TME of EOC and prevented the acquisition of a typical TAM gene signature. This was associated with stronger cytotoxic activity of T cells and decreased tumour burden. Mechanistically, we identified CXCL2 as a novel Notch/RBPJ target gene. This angiocrine factor regulates the expression of CD44 on monocytes and subsequent cholesterol depletion of TAMs. Bioinformatic analysis of ovarian cancer patient data showed that increased CXCL2 expression is accompanied by higher expression of CD44 and TAM education. As such, EOC cells employ the tumour endothelium to secrete CXCL2 in order to facilitate an immunosuppressive microenvironment.

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189 High-resolution spatial analysis of the tumour microenvironment of high grade serous ovarian cancer (HGSOC) using single cell transcriptomics

10.1136/ijgc-2020-igcs.164 ◽

2020 ◽

Author(s):

J Lim ◽

T Parry ◽

C Gourley

Keyword(s):

Ovarian Cancer ◽

Spatial Analysis ◽

High Resolution ◽

Single Cell ◽

Tumour Microenvironment ◽

High Grade ◽

Serous Ovarian Cancer

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Mitochondrial DNA in the tumour microenvironment activates neutrophils and is associated with worse outcomes in patients with advanced epithelial ovarian cancer

British Journal of Cancer ◽

10.1038/s41416-018-0339-8 ◽

2018 ◽

Vol 120 (2) ◽

pp. 207-217 ◽

Cited By ~ 17

Author(s):

Kelly L. Singel ◽

Kassondra S. Grzankowski ◽

A. N. M. Nazmul H. Khan ◽

Melissa J. Grimm ◽

Anthony C. D’Auria ◽

...

Keyword(s):

Ovarian Cancer ◽

Mitochondrial Dna ◽

Epithelial Ovarian Cancer ◽

Tumour Microenvironment ◽

Advanced Epithelial Ovarian Cancer

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A Novel Defined Risk Signature of the Ferroptosis-Related Genes for Predicting the Prognosis of Ovarian Cancer

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.645845 ◽

2021 ◽

Vol 8 ◽

Author(s):

Ying Ye ◽

Qinjin Dai ◽

Shuhong Li ◽

Jie He ◽

Hongbo Qi

Keyword(s):

Ovarian Cancer ◽

High Risk ◽

Risk Model ◽

Cox Regression ◽

Ovarian Tissue ◽

Gene Signature ◽

High Risk Group ◽

Cancer Prognosis ◽

Consensus Clustering ◽

Gynecologic Tumor

Ferroptosis is an iron-dependent, regulated form of cell death, and the process is complex, consisting of a variety of metabolites and biological molecules. Ovarian cancer (OC) is a highly malignant gynecologic tumor with a poor survival rate. However, the predictive role of ferroptosis-related genes in ovarian cancer prognosis remains unknown. In this study, we demonstrated that the 57 ferroptosis-related genes were expressed differently between ovarian cancer and normal ovarian tissue, and based on these genes, all OC cases can be well divided into 2 subgroups by applying consensus clustering. We utilized the least absolute shrinkage and selection operator (LASSO) cox regression model to develop a multigene risk signature from the TCGA cohort and then validated it in an OC cohort from the GEO database. A 5-gene signature was built and reveals a favorable predictive efficacy in both TCGA and GEO cohort (P < 0.001 and P = 0.03). The GO and KEGG analysis revealed that the differentially expressed genes (DEGs) between the low- and high-risk subgroup divided by our risk model were associated with tumor immunity, and lower immune status in the high-risk group was discovered. In conclusion, ferroptosis-related genes are vital factors predicting the prognosis of OC and could be a novel potential treatment target.

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miR-93-5p Suppresses Ovarian Cancer Malignancy and Negatively Regulate CCND2 By Binding To Its 3’UTR Region

10.21203/rs.3.rs-1073707/v1 ◽

2021 ◽

Author(s):

Guotong Chen ◽

Yiwei Yan ◽

Xiaojv Qiu ◽

Chengfeng Ye ◽

Xingmei Jiang ◽

...

Keyword(s):

Ovarian Cancer ◽

Ovarian Cancer Patient ◽

Apoptotic Cell ◽

Gynecological Cancer ◽

Underlying Mechanism ◽

Bioinformatic Analysis ◽

Cell Analysis ◽

Wound Healing Assay ◽

Cancer Initiation ◽

Favorable Prognostic Factor

Abstract Ovarian cancer is the most lethal gynecological cancer worldwide, but the underlying mechanism of ovarian cancer malignancy acquirement is largely unknown. miRNA is ubiquitously implicated in disease especially in cancer initiation and progression. In current study, we firstly detected the expression level of miR-93-5p in ovarian cancer patient samples and conducted a survival analysis. Our data revealed miR-93-5p is a favorable prognostic factor but is downregulated in ovarian cancer patients. Secondly, CCK8 assay wound healing assay and flow cytometry-based cell cycle analysis and apoptotic cell analysis were performed respectively to study the function of miR-93-5p. Functional analysis show miR-93-5p promotes ovarian cancer malignancy in term of cell proliferation, migration but reduce cell death. Bioinformatic analysis showed Cyclin-D2(CCND2) is a candidate gene of miR-93-5p with the binding site in its 3’UTR region. Furthermore, quantitive-PCR and western blot were utilized to measure miR-93-5p, CCND2 levels in tissues samples and cell lines. Our data suggested miR-93-5p is negatively correlated to the level of CCND2 mRNA and protein. Finally, Luciferase report assay was conducted, and we demonstrated miR-93-5p reduces CCND2 expression by binding to the 3’UTR region. Our study revealed the function of miR-93-5p in ovarian cancer malignancy and declaimed CCND2 as a target of miR-93-5p.

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Identification of a Glycolysis-Related Gene Signature for Survival Prediction of Ovarian Cancer Patients

10.21203/rs.3.rs-76061/v1 ◽

2020 ◽

Author(s):

Dai Zhang ◽

Si Yang ◽

Yiche Li ◽

Meng Wang ◽

Jia Yao ◽

...

Keyword(s):

Ovarian Cancer ◽

Risk Model ◽

Cox Regression ◽

Expression Profiles ◽

Gynecological Cancer ◽

Predictive Ability ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Survival Prediction ◽

Test Sets

Abstract Background: Ovarian cancer (OV) is deemed as the most lethal gynecological cancer in women. The aim of this study was construct an effective gene prognostic model for OV patients.Methods: The expression profiles of glycolysis-related genes (GRGs) and clinical data of patients with OV were extracted from The Cancer Genome Atlas (TCGA) database. Univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analyses were conducted, and a prognostic signature based on GRGs was constructed. The predictive ability of the signature was analyzed in training and test sets.Results: Based on nine GRGs (ISG20, CITED2, PYGB, IRS2, ANGPTL4, TGFBI, LHX9, PC, and DDIT4), a gene risk signature was identified to predict the outcome of patients with OV. The signature showed a good prognostic ability for OV, particularly high-grade OV, in the TCGA dataset, with areas under the curve of 0.709, 0.762, and 0.808 for 3-, 5- and 10-year survival, respectively. Similar results were found in the test sets, and the signature was also an independent prognostic factor. Moreover, a nomogram combining the prediction model and clinical factors was constructed.Conclusion: Our study established a nine-GRG risk model and a nomogram to better perform on OV patients’ survival prediction. The risk model represents a promising and independent prognostic predictor for OV patients. Moreover, our study of GRGs could offer guidances for underlying mechanisms explorations in the future.

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A Liquid-Liquid Phase Separation-Related Gene Signature as Prognostic Biomarker for Epithelial Ovarian Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.671892 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yan Qiu ◽

Min Pan ◽

Xuemei Chen

Keyword(s):

Ovarian Cancer ◽

Phase Separation ◽

Prognostic Biomarker ◽

Risk Group ◽

Risk Index ◽

Gene Signature ◽

Related Gene ◽

Data Set ◽

Test Set ◽

Liquid Liquid Phase Separation

ObjectiveThe aim of the present study was to construct and test a liquid-liquid phase separation (LLPS)-related gene signature as a prognostic tool for epithelial ovarian cancer (EOC).Materials and MethodsThe data set GSE26712 was used to screen the differentially expressed LLPS-related genes. Functional enrichment analysis was performed to reveal the potential biological functions. GSE17260 and GSE32062 were combined as the discovery to construct an LLPS-related gene signature through a three-step analysis (univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox analyses). The EOC data set from The Cancer Genome Atlas as the test set was used to test the LLPS-related gene signature.ResultsThe differentially expressed LLPS-related genes involved in several cancer-related pathways, such as MAPK signaling pathway, cell cycle, and DNA replication. Eleven genes were selected to construct the LLPS-related gene signature risk index as prognostic biomarker for EOC. The risk index could successfully divide patients with EOC into high- and low-risk groups. The patients in high-risk group had significantly shorter overall survival than those with in low-risk group. The LLPS-related gene signature was validated in the test set and may be an independent prognostic factor compared to routine clinical features.ConclusionWe constructed and validated an LLPS-related gene signature as a prognosis tool in EOC through integrated analysis of multiple data sets.

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Development of a Hypoxia-Activated Trehalose Diester for the Treatment of Solid Tumours

10.26686/wgtn.17147243 ◽

2021 ◽

Author(s):

◽

Amy Jane Foster

Keyword(s):

Cell Wall ◽

Tumour Microenvironment ◽

Solid Tumours ◽

Great Promise ◽

Tumour Regression ◽

Tumour Burden ◽

Isolation And Identification ◽

Enzymatic Reduction ◽

Thesis Work ◽

Wall Components

The potential of bacterial cell wall components in the treatment of various cancers was initially realised in the late 1800s during pioneering work with Coley’s toxins. Since this preliminary work, efforts have been concentrated on the isolation and identification of bacterial components that lead to tumour regression. Trehalose dimycolates (TDMs) are compounds isolated from the M. tuberculosis cell wall and are known to activate macrophages to give a polarised Th1 immune response resulting in reduced tumour burden. Consequently, TDMs have shown great promise in the treatment of solid tumours. In this thesis, work is presented towards the synthesis of trehalose glycolipid prodrugs that will be specifically activated inside the hypoxic tumour microenvironment, and thereby lead to a more selective form of cancer therapy. These hypoxia-activated trehalose glycolipids incorporate a nitroimidazole trigger that fragments upon enzymatic reduction (in the absence of oxygen) to give the active glycolipid. Throughout the course of this work, it was determined that the nitroimidazole trigger group could not be directly attached to the glycolipid and thus, an alternative carbonate-linker strategy was explored through the use of a reporter fluoroprobe. The validity of this approach was determined in various enzyme and cell-based assays.

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