scholarly journals Examining the interaction between TGFBR3 and ESRRA in ovarian cancer prognosis

2016 ◽  
Author(s):  
Alun Passey ◽  
Robert Brown ◽  
Charlotte S. Wilhelm-Benartzi
Keyword(s):  
Ovarian Cancer ◽  
Conflicts Of Interest ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Serous Ovarian Cancer ◽  
Cancer Genome Atlas ◽  
A Cell ◽  
Funding Support ◽  
Functional Investigation ◽  
Ovarian Cancer Prognosis

ABSTRACTThe authors found that ESRRA when co-expressed at high levels with TGFβR3 may be prognostic for serous ovarian cancer overall survival in data from the Cancer Genome Atlas; however, this result was not validated in further datasets. A cell line was also identified in this study for future functional investigation of interactions between ESRRA and TGFβR3 in the context of oestrogen signaling in order to further elucidate their potential roles as prognostic biomarkers for serous ovarian cancer.FUNDING SUPPORTThis work was supported by Cancer Research UK program A6689 (RB and CSWB) and the Medical Research Council (AP)CONFLICT OF INTEREST DISCLOSURESThe authors have declared no conflicts of interest.AUTHOR CONTRIBUTIONSCSWB designed the study. AP, CSWB, and RB developed the methodology. AP and CSWB collected the data. AP, CSWB, and RB wrote the manuscript. CSWB is responsible for the overall content.

scholarly journals Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3343
Author(s):  
Mingjun Zheng ◽  
Junyu Long ◽  
Anca Chelariu-Raicu ◽  
Heather Mullikin ◽  
Theresa Vilsmaier ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Tumor Microenvironment ◽  
Risk Score ◽  
Malignant Tumors ◽  
Biological Response ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Serous Ovarian Cancer ◽  
Lasso Regression ◽  
Cancer Genome Atlas

(1) Background: The tumor microenvironment is involved in the growth and proliferation of malignant tumors and in the process of resistance towards systemic and targeted therapies. A correlation between the gene expression profile of the tumor microenvironment and the prognosis of ovarian cancer patients is already known. (2) Methods: Based on data from The Cancer Genome Atlas (379 RNA sequencing samples), we constructed a prognostic 11-gene signature (SNRPA1, CCL19, CXCL11, CDC5L, APCDD1, LPAR2, PI3, PLEKHF1, CCDC80, CPXM1 and CTAG2) for Fédération Internationale de Gynécologie et d’Obstétrique stage III and IV serous ovarian cancer through lasso regression. (3) Results: The established risk score was able to predict the 1-, 3- and 5-year prognoses more accurately than previously known models. (4) Conclusions: We were able to confirm the predictive power of this model when we applied it to cervical and urothelial cancer, supporting its pan-cancer usability. We found that immune checkpoint genes correlate negatively with a higher risk score. Based on this information, we used our risk score to predict the biological response of cancer samples to an anti-programmed death ligand 1 immunotherapy, which could be useful for future clinical studies on immunotherapy in ovarian cancer.

scholarly journals Role of tumor location on high-grade serous ovarian cancer prognosis

2021 ◽  
Author(s):  
Seval Ay ◽  
Deniz Tataroğlu Özyükseler ◽  
Mustafa Başak ◽  
Özgecan Dülgar ◽  
Serdar Arıcı ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Tumor Location ◽  
Cancer Prognosis ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Ovarian Cancer Prognosis

scholarly journals CD44 Splice Variant v8-10 as a Marker of Serous Ovarian Cancer Prognosis

PLoS ONE ◽  
2016 ◽  
Vol 11 (6) ◽  
pp. e0156595 ◽  
Author(s):  
Amanda Sosulski ◽  
Heiko Horn ◽  
Lihua Zhang ◽  
Caroline Coletti ◽  
Vinod Vathipadiekal ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Splice Variant ◽  
Cancer Prognosis ◽  
Serous Ovarian Cancer ◽  
Ovarian Cancer Prognosis

scholarly journals Radiogenomics of High-Grade Serous Ovarian Cancer: Multireader Multi-Institutional Study from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group

Radiology ◽  
2017 ◽  
Vol 285 (2) ◽  
pp. 482-492 ◽  
Author(s):  
Hebert Alberto Vargas ◽  
Erich P. Huang ◽  
Yulia Lakhman ◽  
Joseph E. Ippolito ◽  
Priya Bhosale ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Research Group ◽  
Cancer Imaging ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Imaging Research ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals AKT Isoforms Interplay in High-Grade Serous Ovarian Cancer Prognosis and Characterization

Cancers ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 304
Author(s):  
Eros Azzalini ◽  
Domenico Tierno ◽  
Michele Bartoletti ◽  
Renzo Barbazza ◽  
Giorgio Giorda ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Acquired Resistance ◽  
Digital Pcr ◽  
Parp Inhibitors ◽  
Clinicopathological Features ◽  
Cancer Prognosis ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Akt Isoforms ◽  
Ovarian Cancer Prognosis

High-grade serous ovarian cancer (HGSOC) is among the deadliest gynecological malignancies. The acquired resistance to platinum-based therapies and the intrinsic heterogeneity of the disease contribute to the low survival rate. To improve patients’ outcomes, new combinatorial approaches able to target different tumor vulnerabilities and enhance the efficacy of the current therapies are required. AKT inhibitors are promising antineoplastic agents able to act in synergy with PARP inhibitors, but the spectrum of patients who can benefit from this combination is unclear, since the role of the three different isoforms of AKT is still unknown. Here, we study the expression of AKT isoforms on a retrospective cohort of archive tissue by RT-droplet digital PCR (ddPCR) analyzing their association with the clinicopathological features of patients. Based on AKT1/AKT2 and AKT1/AKT3 ratios, we define four AKT classes which were related to patients’ survival, tumor morphology and BRCA1 expression. Moreover, our results show that high AKT3 expression levels were frequently associated with tumors having classic features, a low number of mitoses and the presence of psammoma bodies. Overall, our study obtains new insights on AKT isoforms and their associations with the clinicopathological features of HGSOC patients. These evidences could help to better define the subsets of patients who can benefit from AKT and PARP inhibitors therapy in future clinical trials.

scholarly journals Identification of Subpathway Signatures For Ovarian Cancer Prognosis by Integrated Analyses of High-Throughput miRNA and mRNA Expression

2017 ◽  
Vol 44 (4) ◽  
pp. 1325-1336 ◽  
Author(s):  
Songyu Tian ◽  
Jiangtian Tian ◽  
Xiuwei Chen ◽  
Lianwei Li ◽  
Yunduo Liu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Risk Scores ◽  
Data Sets ◽  
Global Risk ◽  
Gene Expressions ◽  
Validation Data ◽  
Data Set ◽  
Ovarian Cancer Prognosis

Background/Aims: Ovarian cancer (OC) causes more death and serious conditions than any other female reproductive cancers, and many expression signatures have been identified for OC prognoses. However, no significant overlap is found among signatures from different studies, indicating the necessity of signature identifications at the functional level. Methods: We performed an integrated analyses of miRNA and gene expressions to identify OC prognostic subpathways (pathway regions). Using The Cancer Genome Atlas data set, we identified core prognostic subpathways, and calculated subpathway risk scores using both miRNA and gene components. Finally, we performed global risk impact analyses to optimize core subpathways using the random walk algorithm. Results: Subpathway-level analyses displayed more robust results than the gene- and miRNA-level analyses. Moreover, we verified the advantage of core subpathways over the entire pathway-based results and their prognostic performance in two independent validation data sets. Based on the global impact score, 13 subpathway signatures were selected and a combined subpathway-based risk score was further calculated for OC patient prognoses. Conclusions: Overall, it was possible to systematically perform integrated analyses of the expression levels of miRNAs and genes to identify prognostic subpathways and infer subpathway risk scores for use in OC clinical applications.

scholarly journals Proteomic Studies on the Management of High-Grade Serous Ovarian Cancer Patients: A Mini-Review

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 2067
Author(s):  
Melissa Bradbury ◽  
Eva Borràs ◽  
Assumpció Pérez-Benavente ◽  
Antonio Gil-Moreno ◽  
Anna Santamaria ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
The Cancer Genome Atlas ◽  
Response To Treatment ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Post Translational Modifications ◽  
Platinum Based Chemotherapy ◽  
Standardized Treatment ◽  
Cancer Genome Atlas ◽  
New Biomarkers

High-grade serous ovarian cancer (HGSC) remains the most common and deadly subtype of ovarian cancer. It is characterized by its late diagnosis and frequent relapse despite standardized treatment with cytoreductive surgery and platinum-based chemotherapy. The past decade has seen significant advances in the clinical management and molecular understanding of HGSC following the publication of the Cancer Genome Atlas (TCGA) researchers and the introduction of targeted therapies with anti-angiogenic drugs and poly(ADP-ribose) polymerase inhibitors in specific subgroups of patients. We provide a comprehensive review of HGSC, focusing on the most important molecular advances aimed at providing a better understanding of the disease and its response to treatment. We emphasize the role that proteomic technologies are now playing in these two aspects of the disease, through the identification of proteins and their post-translational modifications in ovarian cancer tumors. Finally, we highlight how the integration of proteomics with genomics, exemplified by the work performed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), can guide the development of new biomarkers and therapeutic targets.

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 The Prognostic Significance of MAFK and its Methylation in Cervical Cancer

2021 ◽  
Author(s):  
Mengjun Zhang ◽  
Hao Li ◽  
Yuan Liu ◽  
Siyu Hou ◽  
Ping Cui ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Aberrant Methylation ◽  
Cancer Data ◽  
Drug Candidates ◽  
Cancer Genome Atlas ◽  
Cancer Tissues

Abstract Background: The purpose of this study was to determine the value of MAFK as a biomarker of cervical cancer prognosis and to explore its methylation and possible cellular signaling pathways. Methods: We analyzed the cervical cancer data of The Cancer Genome Atlas (TCGA) through bioinformatics, including MAFK expression, methylation, prognosis and genome enrichment analysis. Results: MAFK expression was higher in cervical cancer tissues and was negatively correlated with the methylation levels of five CpG sites. MAFK is an independent prognostic factor of cervical cancer and is involved in the Nod-like receptor signaling pathway. CMap analysis screened four drug candidates for cervical cancer treatment. Conclusions: We confirmed that MAFK is a novel prognostic biomarker for cervical cancer and aberrant methylation may also affect MAFK expression and carcinogenesis. This study provides a new molecular target for the prognostic evaluation and treatment of cervical cancer.

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