scholarly journals Modelling Epithelial Ovarian Cancer in Mice: Classical and Emerging Approaches

2020 ◽  
Vol 21 (13) ◽  
pp. 4806
Author(s):  
Razia Zakarya ◽  
Viive M. Howell ◽  
Emily K. Colvin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Genetically Engineered ◽  
The Cancer Genome Atlas ◽  
Genetically Engineered Mouse Models ◽  
Molecular Features ◽  
Somatic Gene ◽  
Cancer Genome Atlas ◽  
Serous Epithelial Ovarian Cancer ◽  
Aggressive Subtype

High-grade serous epithelial ovarian cancer (HGSC) is the most aggressive subtype of epithelial ovarian cancer. The identification of germline and somatic mutations along with genomic information unveiled by The Cancer Genome Atlas (TCGA) and other studies has laid the foundation for establishing preclinical models with high fidelity to the molecular features of HGSC. Notwithstanding such progress, the field of HGSC research still lacks a model that is both robust and widely accessible. In this review, we discuss the recent advancements and utility of HGSC genetically engineered mouse models (GEMMs) to date. Further analysis and critique on alternative approaches to modelling HGSC considers technological advancements in somatic gene editing and modelling prototypic organs, capable of tumorigenesis, on a chip.

scholarly journals Cyclooxygenase-1 Is Overexpressed in Multiple Genetically Engineered Mouse Models of Epithelial Ovarian Cancer

2006 ◽  
Vol 66 (5) ◽  
pp. 2527-2531 ◽  
Author(s):  
Takiko Daikoku ◽  
Susanne Tranguch ◽  
Irina N. Trofimova ◽  
Daniela M. Dinulescu ◽  
Tyler Jacks ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Mouse Models ◽  
Genetically Engineered ◽  
Genetically Engineered Mouse Models ◽  
Cyclooxygenase 1

scholarly journals Semi-supervised identification of cancer subgroups using survival outcomes and overlapping grouping information

2018 ◽  
Vol 28 (7) ◽  
pp. 2137-2149 ◽  
Author(s):  
Wei Wei ◽  
Zequn Sun ◽  
Willian A da Silveira ◽  
Zhenning Yu ◽  
Andrew Lawson ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Progression ◽  
High Throughput ◽  
Genomic Data ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
Integrative Genomics ◽  
Molecular Features ◽  
Biological Interpretation ◽  
Cancer Genome Atlas

Identification of cancer patient subgroups using high throughput genomic data is of critical importance to clinicians and scientists because it can offer opportunities for more personalized treatment and overlapping treatments of cancers. In spite of tremendous efforts, this problem still remains challenging because of low reproducibility and instability of identified cancer subgroups and molecular features. In order to address this challenge, we developed Integrative Genomics Robust iDentification of cancer subgroups (InGRiD), a statistical approach that integrates information from biological pathway databases with high-throughput genomic data to improve the robustness for identification and interpretation of molecularly-defined subgroups of cancer patients. We applied InGRiD to the gene expression data of high-grade serous ovarian cancer from The Cancer Genome Atlas and the Australian Ovarian Cancer Study. The results indicate clear benefits of the pathway-level approaches over the gene-level approaches. In addition, using the proposed InGRiD framework, we also investigate and address the issue of gene sharing among pathways, which often occurs in practice, to further facilitate biological interpretation of key molecular features associated with cancer progression. The R package “InGRiD” implementing the proposed approach is currently available in our research group GitHub webpage ( https://dongjunchung.github.io/INGRID/ ).

scholarly journals Two microRNA signatures for malignancy and immune infiltration predict overall survival in advanced epithelial ovarian cancer

2017 ◽  
Vol 65 (7) ◽  
pp. 1068-1076 ◽  
Author(s):  
Ilya Korsunsky ◽  
Janaki Parameswaran ◽  
Iuliana Shapira ◽  
John Lovecchio ◽  
Andrew Menzin ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
The Cancer Genome Atlas ◽  
Cytotoxic Lymphocytes ◽  
Strongly Correlated ◽  
Regulatory Structure ◽  
Data Set ◽  
Clinical Prognosis ◽  
Functional Roles ◽  
Cancer Genome Atlas

MicroRNAs have been established as key regulators of tumor gene expression and as prime biomarker candidates for clinical phenotypes in epithelial ovarian cancer (EOC). We analyzed the coexpression and regulatory structure of microRNAs and their co-localized gene targets in primary tumor tissue of 20 patients with advanced EOC in order to construct a regulatory signature for clinical prognosis. We performed an integrative analysis to identify two prognostic microRNA/mRNA coexpression modules, each enriched for consistent biological functions. One module, enriched for malignancy-related functions, was found to be upregulated in malignant versus benign samples. The second module, enriched for immune-related functions, was strongly correlated with imputed intratumoral immune infiltrates of T cells, natural killer cells, cytotoxic lymphocytes, and macrophages. We validated the prognostic relevance of the immunological module microRNAs in the publicly available The Cancer Genome Atlas data set. These findings provide novel functional roles for microRNAs in the progression of advanced EOC and possible prognostic signatures for survival.

scholarly journals Low-grade serous epithelial ovarian cancer: a comprehensive review and update for radiologists

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sofia Amante ◽  
Filipa Santos ◽  
Teresa Margarida Cunha
Keyword(s):  
Ovarian Cancer ◽  
Serous Carcinoma ◽  
Low Grade ◽  
Resonance Imaging ◽  
Clinicopathologic Characteristics ◽  
Borderline Tumour ◽  
Molecular Features ◽  
Serous Epithelial Ovarian Cancer ◽  
The Difference

AbstractLow-grade serous carcinoma (LGSC) is an infrequent subtype of ovarian cancer, corresponding to 5% of epithelial neoplasms. This subtype of ovarian carcinoma characteristically has molecular features, pathogenesis, clinical behaviour, sensitivity to chemotherapy, and prognosis distinct to high-grade serous carcinoma (HGSC). Knowing the difference between LGSC and other ovarian serous tumours is vital to guide clinical management, which currently is only possible histologically. However, imaging can provide several clues that allow differentiating LGSC from other tumours and enable precise staging and follow-up of ovarian cancer treatment. Characteristically, LGSC appears as mixed lesions with variable papillary projections and solid components, usually in different proportions from those detected in serous borderline tumour and HGSC. Calcified extracellular bodies, known as psammoma bodies, are also a common feature of LGSC, frequently detectable within lymphadenopathies and metastases associated with this type of tumour. In addition, the characterisation of magnetic resonance imaging enhancement also plays an essential role in calculating the probability of malignancy of these lesions. As such, in this review, we discuss and update the distinct radiological modalities features and the clinicopathologic characteristics of LGSC to allow radiologists to be familiarised with them and to narrow the differential diagnosis when facing this type of tumour.

scholarly journals HNRNPH1-stabilized LINC00662 promotes ovarian cancer progression by activating the GRP78/p38 pathway

Oncogene ◽  
2021 ◽  
Author(s):  
Yong Wu ◽  
Qinhao Guo ◽  
Xingzhu Ju ◽  
Zhixiang Hu ◽  
Lingfang Xia ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Progression ◽  
Prognostic Indicator ◽  
Mapk Signaling ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Proliferation And Metastasis ◽  
Nuclear Ribonucleoprotein

AbstractNumerous studies suggest an important role for copy number alterations (CNAs) in cancer progression. However, CNAs of long intergenic noncoding RNAs (lincRNAs) in ovarian cancer (OC) and their potential functions have not been fully investigated. Here, based on analysis of The Cancer Genome Atlas (TCGA) database, we identified in this study an oncogenic lincRNA termed LINC00662 that exhibited a significant correlation between its CNA and its increased expression. LINC00662 overexpression is highly associated with malignant features in OC patients and is a prognostic indicator. LINC00662 significantly promotes OC cell proliferation and metastasis in vitro and in vivo. Mechanistically, LINC00662 is stabilized by heterogeneous nuclear ribonucleoprotein H1 (HNRNPH1). Moreover, LINC00662 exerts oncogenic effects by interacting with glucose-regulated protein 78 (GRP78) and preventing its ubiquitination in OC cells, leading to activation of the oncogenic p38 MAPK signaling pathway. Taken together, our results define an oncogenic role for LINC00662 in OC progression mediated via GRP78/p38 signaling, with potential implications regarding therapeutic targets for OC.

scholarly journals Radiosensitivity index emerges as a potential biomarker for combined radiotherapy and immunotherapy

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Yang-Hong Dai ◽  
Ying-Fu Wang ◽  
Po-Chien Shen ◽  
Cheng-Hsiang Lo ◽  
Jen-Fu Yang ◽  
...  
Keyword(s):  
Dna Repair ◽  
Interferon Γ ◽  
The Cancer Genome Atlas ◽  
Differential Analysis ◽  
Macrophage Polarisation ◽  
Molecular Features ◽  
Kaplan Meier ◽  
M1 Macrophage ◽  
Potential Biomarker ◽  
Cancer Genome Atlas

AbstractIn the era of immunotherapy, there lacks of a reliable genomic predictor to identify optimal patient populations in combined radiotherapy and immunotherapy (CRI). The purpose of this study is to investigate whether genomic scores defining radiosensitivity are associated with immune response. Genomic data from Merged Microarray-Acquired dataset (MMD) were established and the Cancer Genome Atlas (TCGA) were obtained. Based on rank-based regression model including 10 genes, radiosensitivity index (RSI) was calculated. A total of 12832 primary tumours across 11 major cancer types were analysed for the association with DNA repair, cellular stemness, macrophage polarisation, and immune subtypes. Additional 585 metastatic tissues were extracted from MET500. RSI was stratified into RSI-Low and RSI-High by a cutpoint of 0.46. Proteomic differential analysis was used to identify significant proteins according to RSI categories. Gene Set Variance Analysis (GSVA) was applied to measure the genomic pathway activity (18 genes for T-cell inflamed activity). Kaplan-Meier analysis was performed for survival analysis. RSI was significantly associated with homologous DNA repair, cancer stemness and immune-related molecular features. Lower RSI was associated with higher fraction of M1 macrophage. Differential proteomic analysis identified significantly higher TAP2 expression in RSI-Low colorectal tumours. In the TCGA cohort, dominant interferon-γ (IFN-γ) response was characterised by low RSI and predicted better response to programmed cell death 1 (PD-1) blockade. In conclusion, in addition to radiation response, our study identified RSI to be associated with various immune-related features and predicted response to PD-1 blockade, thus, highlighting its potential as a candidate biomarker for CRI.

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