Publication: RNA-based ovarian cancer research from 'a gene to systems biomedicine' perspective
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Date
2017-07-04
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Volume Title
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TAYLOR & FRANCIS INC
Abstract
Ovarian cancer remains the leading cause of death from a gynecologic malignancy, and treatment of this disease is harder than any other type of female reproductive cancer. Improvements in the diagnosis and development of novel and effective treatment strategies for complex pathophysiologies, such as ovarian cancer, require a better understanding of disease emergence and mechanisms of progression through systems medicine approaches. RNA-level analyses generate new information that can help in understanding the mechanisms behind disease pathogenesis, to identify new biomarkers and therapeutic targets and in new drug discovery. Whole RNA sequencing and coding and non-coding RNA expression array datasets have shed light on the mechanisms underlying disease progression and have identified mRNAs, miRNAs, and lncRNAs involved in ovarian cancer progression. In addition, the results from these analyses indicate that various signalling pathways and biological processes are associated with ovarian cancer. Here, we present a comprehensive literature review on RNA-based ovarian cancer research and highlight the benefits of integrative approaches within the systems biomedicine concept for future ovarian cancer research. We invite the ovarian cancer and systems biomedicine research fields to join forces to achieve the interdisciplinary caliber and rigor required to find real-life solutions to common, devastating, and complex diseases such as ovarian cancer.Abbreviations: CAF: cancer-associated fibroblasts
COG: Cluster of Orthologous Groups
DEA: disease enrichment analysis
EOC: epithelial ovarian carcinoma
ESCC: oesophageal squamous cell carcinoma
GSI: gamma secretase inhibitor
GO: Gene Ontology
GSEA: gene set enrichment analyzes
HAS: Hungarian Academy of Sciences
lncRNAs: long non-coding RNAs
MAPK/ERK: mitogen-activated protein kinase/extracellular signal-regulated kinases
NGS: next-generation sequencing
ncRNAs: non-coding RNAs
OvC: ovarian cancer
PI3K/Akt/mTOR: phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin
RT-PCR: real-time polymerase chain reaction
SNP: single nucleotide polymorphism
TF: transcription factor
TGF-: transforming growth factor-
COG: Cluster of Orthologous Groups
DEA: disease enrichment analysis
EOC: epithelial ovarian carcinoma
ESCC: oesophageal squamous cell carcinoma
GSI: gamma secretase inhibitor
GO: Gene Ontology
GSEA: gene set enrichment analyzes
HAS: Hungarian Academy of Sciences
lncRNAs: long non-coding RNAs
MAPK/ERK: mitogen-activated protein kinase/extracellular signal-regulated kinases
NGS: next-generation sequencing
ncRNAs: non-coding RNAs
OvC: ovarian cancer
PI3K/Akt/mTOR: phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin
RT-PCR: real-time polymerase chain reaction
SNP: single nucleotide polymorphism
TF: transcription factor
TGF-: transforming growth factor-
Description
Keywords
Non-coding RNAs, ovarian cancer, systems biomedicine, transcriptome, LONG NONCODING RNA, DIFFERENTIALLY EXPRESSED GENES, PROTEIN-INTERACTION NETWORKS, WNT/BETA-CATENIN PATHWAY, PREDICTS POOR-PROGNOSIS, TRANSCRIPTIONAL REGULATION, CISPLATIN RESISTANCE, MICRORNA REGULATION, THERAPEUTIC TARGET, METABOLIC NETWORK