PTH2R is related to cell proliferation and migration in ovarian cancer: a multi-omics analysis of bioinformatics and experiments

Wang, Xiaowei; Lu, Tong; Qu, Yue; Fan, Lili

doi:10.1186/s12935-022-02566-2

Cited by 5 publications

(2 citation statements)

References 49 publications

(39 reference statements)

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“…In this study, a total of 957 DEGs were screened, including 478 up regulated genes and 479 down regulated genes. Nodin et al [41], Xiaowei et al [42], Xu et al [43] and Callahan et al [44] showed that DACH2, PTH2R, AJAP1 and HLA-DMB were associated with cancer. Johnston et al [45] and Mangano et al [46] reported that LRFN5 and SCN2A were important target genes of neurological and psychological problems.…”

Section: Discussionmentioning

confidence: 99%

The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

Vastrad¹,

Vastrad²

2023

Preprint

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Polycystic ovary syndrome (PCOS) is is associated with infertility, obesity, insulin resistance, hyperinsulinemia, type 2 diabetes mellitus, hypertension, cardiovascular problems, neurological and psychological problems and cancer. The specific mechanism of PCOS and its complications remains unclear. The aim of this study was to apply a bioinformatics approach to reveal related pathways or genes involved in the development of PCOS and its complications. The next generation squancing (NGS) datset GSE199225 was downloaded from the gene expression omnibus (GEO) database. Differentially expressed gene (DEG) analysis was performed using DESeq2. The g:Profiler was utilized to analyze the functional enrichment, gene ontology (GO) and REACTOME pathway of the differentially expressed genes. A protein-protein interaction (PPI) network was constructed and module analysis was performed using HiPPIE and cytoscape. The miRNA-hub gene regulatory network and TF-hub gene regulatory network were also constructed for research. The expression of the hub genes was validated using receiver operating characteristic (ROC) curve analysis. We have identified 957 DEGs in total, including 478 up regulated genes and 479 down regulated gene. GO and REACTOME illustrated that DEGs in PCOS were significantly enriched in regulation of molecular function, developmental process, interferon signaling and platelet activation, signaling and aggregation. Finally, through analyzing the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, we screened hub genes HSPA5, PLK1, RIN3, DBN1, CCDC85B, DISC1, AR, MTUS2, LYN and TCF4 by the Cytoscape software. This study uses a series of bioinformatics technologies to obtain hug genes and key pathways related to PCOS and its complications. These analysis results provide us with novel ideas for finding biomarkers and treatment methods for PCOS and its complications.

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Section: Discussionmentioning

confidence: 99%

The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

Vastrad¹,

Vastrad²

2023

Preprint

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“…KM survival curve analysis demonstrated that overexpression of KLHL14 was correlated with a significantly shorter OS in patients with OV. Moreover, bioinformatic analyses indicated that KLHL14 played an important role in the microenvironment and drug sensitivity [ 35 ].…”

Section: Discussionmentioning

confidence: 99%

KLHL14: A Novel Prognostic Biomarker and Therapeutic Target for Ovarian Cancer

Wang

Sun

Xia

et al. 2022

Journal of Oncology

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Ovarian cancer (OV) is a gynaecological malignancy that poses a serious risk to the health status of women. To date, effective molecular markers are unavailable for the diagnosis and management of ovarian malignancies. In this study, we aimed to investigate the molecular markers associated with the development of this cancer. We used bioinformatic analysis to determine the molecules and genes related to ovarian cancer using the gene expression profiling interactive analysis (GEPIA) and the cancer genome Atlas (TCGA) databases. In addition, we examined the genes and mechanisms underlying ovarian cancer. Our results showed that the KLHL14 gene is overexpressed in some cancers. An increase in the KLHL14 expression indicates a poor prognosis in patients with ovarian cancer. Results of immune cell infiltration analysis and half-maximal inhibitory concentration (IC50) analysis provide novel insights into the treatment of ovarian cancer. KLHL14 is anticipated to emerge as a novel molecular marker specifically for ovarian carcinoma.

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Effect of bromodomain PHD-finger transcription factor (BPTF) on trophoblast epithelial-to-mesenchymal transition

Pan,

Zhu,

et al. 2024

Gene

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PTH2R is related to cell proliferation and migration in ovarian cancer: a multi-omics analysis of bioinformatics and experiments

Cited by 5 publications

References 49 publications

The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

KLHL14: A Novel Prognostic Biomarker and Therapeutic Target for Ovarian Cancer

Effect of bromodomain PHD-finger transcription factor (BPTF) on trophoblast epithelial-to-mesenchymal transition

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