Comprehensive Analysis of the Expression of Key Genes Related to Hippo Signaling and Their Prognosis Impact in Ovarian Cancer.
Milan Paul KubelacCornelia BraicuLajos-Zsolt RadulyPaul ChiroiAndreea Mihaela NutuRoxana Maria CojocneanuLiviuta BudisanIoana Berindan NeagoePatriciu Achimas-CadariuPublished in: Diagnostics (Basel, Switzerland) (2021)
The Hippo signaling pathway, one of the most conserved in humans, controlling dimensions of organs and tumor growth, is frequently deregulated in several human malignancies, including ovarian cancer (OC). The alteration of Hippo signaling has been reported to contribute to ovarian carcinogenesis and progression. However, the prognostic roles of individual Hippo genes in OC patients remain elusive. Herein we investigated the expression level and prognostic value of key Hippo genes in OC using online databases, followed by a qRT-PCR validation step in an additional patient cohort. Using the GEPIA database, we observed an increased level for TP53 and reduced expression level for LATS1, LATS2, MST1, TAZ, and TEF in tumor tissue versus normal adjacent tissue. Moreover, LATS1, LATS2, TP53, TAZ, and TEF expression levels have prognostic significance correlated with progression-free survival. The qRT-PCR validation step was conducted in an OC patient cohort comprising 29 tumor tissues and 20 normal adjacent tissues, endorsing the expression level for LATS1, LATS2, and TP53, as well as for two of the miRNAs targeting the TP53 gene, revealing miR-25-3p upregulation and miR-181c-5p downregulation. These results display that there are critical prognostic value dysregulations of the Hippo genes in OC. Our data demonstrate the major role the conserved Hippo pathway presents in tumor control, underlying potential therapeutic strategies and controlling several steps modulated by miRNAs and their target genes that could limit ovarian cancer progression.
Keyphrases
- poor prognosis
- genome wide
- signaling pathway
- genome wide identification
- long non coding rna
- binding protein
- bioinformatics analysis
- gene expression
- endothelial cells
- end stage renal disease
- transcription factor
- chronic kidney disease
- case report
- dna methylation
- ejection fraction
- newly diagnosed
- big data
- machine learning
- epithelial mesenchymal transition
- oxidative stress
- mass spectrometry
- prognostic factors
- emergency department
- pi k akt
- high speed
- social media
- endoplasmic reticulum stress
- induced pluripotent stem cells
- atomic force microscopy