ArticleGenes & cancer2017
Dysregulation of AKT3 along with a small panel of mRNAs stratifies high-grade serous ovarian cancer from both normal epithelia and benign tumor tissues.
Article in Genes & cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 16 citations in OpenAlex.
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- Using Weighted Gene Co-Expression Network Analysis to Identify Increased MND1 Expression as a Predictor of Poor Breast Cancer Survival.International journal of general medicine · 2022Article
- Meiotic Genes and DNA Double Strand Break Repair in Cancer.Frontiers in genetics · 2022Review
- Identification of the Hub Genes Associated with the Prognosis of Ovarian Cancer Patients via Integrated Bioinformatics Analysis and Experimental Validation.Cancer management and research · 2021Article
- The ectopic expression of meiCT genes promotes meiomitosis and may facilitate carcinogenesis.Cell cycle (Georgetown, Tex.) · 2020Review
- MicroRNA-424-5p inhibits the proliferation, migration, and invasion of nasopharyngeal carcinoma cells by decreasing AKT3 expression.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2020Article
- Discovery and Validation of Novel Biomarkers for Detection of Epithelial Ovarian Cancer.Cells · 2019Article
- Identification of potential diagnostic and therapeutic target genes for lung squamous cell carcinoma.Oncology letters · 2019Article
- Association of PTTG1 polymorphism rs1895320, rs2910200 and rs6882742 with non-functioning pituitary adenomas in Chinese Han population: a case-control study.Metabolic brain disease · 2019Article
- A Comprehensive Bioinformatics Analysis ofInternational journal of molecular sciences · 2019Article
- Identifying miRNA-mRNA regulation network of major depressive disorder in ovarian cancer patients.Oncology letters · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Screening methods of High-Grade Serous Ovarian Cancer (HGSOC) lack specificity and sensitivity, partly due to benign tumors producing false-positive findings. We utilized a differential expression analysis pipeline on malignant tumor (MT) and normal epithelial (NE) samples, and also filtered the results to discriminate between MT and benign tumor (BT). We report that a panel of 26 dysregulated genes stratifies MT from both BT and NE. We further validated our findings by utilizing unsupervised clustering methods on two independent datasets. We show that the 26-genes panel completely distinguishes HGSOC from NE, and produces a more accurate classification between HGSOC and BT. Pathway analysis reveals that AKT3 is of particular significance, because of its high fold change and appearance in the majority of the dysregulated pathways. mRNA patterns of AKT3 suggest essential connections with tumor growth and metastasis, as well as a strong biomarker potential when used with 3 other genes (PTTG1, MND1, CENPF). Our results show that dysregulation of the 26-mRNA signature panel provides an evidence of malignancy and contribute to the design of a high specificity biomarker panel for detection of HGSOC, potentially in an early more curable stage.
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