Literature DB >> 34320033

Integrated microRNA and mRNA signatures associated with overall survival in epithelial ovarian cancer.

Joanna Lopacinska-Jørgensen1, Douglas V N P Oliveira1, Guy Wayne Novotny1, Claus K Høgdall2, Estrid V Høgdall1.   

Abstract

Ovarian cancer (OC), the eighth-leading cause of cancer-related death among females worldwide, is mainly represented by epithelial OC (EOC) that can be further subdivided into four subtypes: serous (75%), endometrioid (10%), clear cell (10%), and mucinous (3%). Major reasons for high mortality are the poor biological understanding of the OC mechanisms and a lack of reliable markers defining each EOC subtype. MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression primarily by targeting messenger RNA (mRNA) transcripts. Their aberrant expression patterns have been associated with cancer development, including OC. However, the role of miRNAs in tumorigenesis is still to be determined, mainly due to the lack of consensus regarding optimal methodologies for identification and validation of miRNAs and their targets. Several tools for computational target prediction exist, but false interpretations remain a problem. The experimental validation of every potential miRNA-mRNA pair is not feasible, as it is laborious and expensive. In this study, we analyzed the correlation between global miRNA and mRNA expression patterns derived from microarray profiling of 197 EOC patients to identify the signatures of miRNA-mRNA interactions associated with overall survival (OS). The aim was to investigate whether these miRNA-mRNA signatures might have a prognostic value for OS in different subtypes of EOC. The content of our cohort (162 serous carcinomas, 15 endometrioid carcinomas, 11 mucinous carcinomas, and 9 clear cell carcinomas) reflects a real-world scenario of EOC. Several interaction pairs between 6 miRNAs (hsa-miR-126-3p, hsa-miR-223-3p, hsa-miR-23a-5p, hsa-miR-27a-5p, hsa-miR-486-5p, and hsa-miR-506-3p) and 8 mRNAs (ATF3, CH25H, EMP1, HBB, HBEGF, NAMPT, POSTN, and PROCR) were identified and the findings appear to be well supported by the literature. This indicates that our study has a potential to reveal miRNA-mRNA signatures relevant for EOC. Thus, the evaluation on independent cohorts will further evaluate the performance of such findings.

Entities:  

Year:  2021        PMID: 34320033     DOI: 10.1371/journal.pone.0255142

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  72 in total

1.  High Expression of miR-532-5p, a Tumor Suppressor, Leads to Better Prognosis in Ovarian Cancer Both In Vivo and In Vitro.

Authors:  Fan Wang; Jeremy T-H Chang; Chester Jingshiu Kao; R Stephanie Huang
Journal:  Mol Cancer Ther       Date:  2016-02-12       Impact factor: 6.261

2.  Integrated analyses identify a master microRNA regulatory network for the mesenchymal subtype in serous ovarian cancer.

Authors:  Da Yang; Yan Sun; Limei Hu; Hong Zheng; Ping Ji; Chad V Pecot; Yanrui Zhao; Sheila Reynolds; Hanyin Cheng; Rajesha Rupaimoole; David Cogdell; Matti Nykter; Russell Broaddus; Cristian Rodriguez-Aguayo; Gabriel Lopez-Berestein; Jinsong Liu; Ilya Shmulevich; Anil K Sood; Kexin Chen; Wei Zhang
Journal:  Cancer Cell       Date:  2013-02-11       Impact factor: 31.743

3.  Epithelial ovarian cancer: An overview.

Authors:  Arpita Desai; Jingyao Xu; Kartik Aysola; Yunlong Qin; Chika Okoli; Ravipati Hariprasad; Ugorji Chinemerem; Candace Gates; Avinash Reddy; Omar Danner; Geary Franklin; Anachebe Ngozi; Guilherme Cantuaria; Karan Singh; William Grizzle; Charles Landen; Edward E Partridge; Valerie Montgomery Rice; E Shyam P Reddy; Veena N Rao
Journal:  World J Transl Med       Date:  2014-04-12

4.  MicroRNA-373 induces expression of genes with complementary promoter sequences.

Authors:  Robert F Place; Long-Cheng Li; Deepa Pookot; Emily J Noonan; Rajvir Dahiya
Journal:  Proc Natl Acad Sci U S A       Date:  2008-01-28       Impact factor: 11.205

5.  DIANA-miRPath v3.0: deciphering microRNA function with experimental support.

Authors:  Ioannis S Vlachos; Konstantinos Zagganas; Maria D Paraskevopoulou; Georgios Georgakilas; Dimitra Karagkouni; Thanasis Vergoulis; Theodore Dalamagas; Artemis G Hatzigeorgiou
Journal:  Nucleic Acids Res       Date:  2015-05-14       Impact factor: 16.971

6.  Integration of MicroRNA, mRNA, and Protein Expression Data for the Identification of Cancer-Related MicroRNAs.

Authors:  Jiyoun Seo; Daeyong Jin; Chan-Hun Choi; Hyunju Lee
Journal:  PLoS One       Date:  2017-01-05       Impact factor: 3.240

7.  Discovery of HB-EGF binding peptides and their functional characterization in ovarian cancer cell lines.

Authors:  Yanting Shen; Lingling Ruan; Caixia Lian; Ruyan Li; Zhigang Tu; Hanqing Liu
Journal:  Cell Death Discov       Date:  2019-03-25

8.  Multi-view based integrative analysis of gene expression data for identifying biomarkers.

Authors:  Zi-Yi Yang; Xiao-Ying Liu; Jun Shu; Hui Zhang; Yan-Qiong Ren; Zong-Ben Xu; Yong Liang
Journal:  Sci Rep       Date:  2019-09-18       Impact factor: 4.379

9.  CRM197 reverses paclitaxel resistance by inhibiting the NAC-1/Gadd45 pathway in paclitaxel-resistant ovarian cancer cells.

Authors:  Xiao-Han Tang; Hui Li; Xiu-Shuang Zheng; Mei-Song Lu; Yuan An; Xiao-Lei Zhang
Journal:  Cancer Med       Date:  2019-09-06       Impact factor: 4.452

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