Dataset Information

PDGFRA, HSD17B4 and HMGB2 are potential therapeutic targets in polycystic ovarian syndrome and breast cancer.

ABSTRACT: To explore the key genes associated with both PCOS and breast cancer, we overlapped the synchronously differently expressed genes in two obese insulin-resistant GEO datasets in muscle tissue and genes exert essential roles in breast cancer prognosis together base on the following reasons: (1) Androgens excess is believed to contribute to the onset of both PCOS and breast cancer. (2) PCOS is usually complicated with metabolic symptoms, such as obesity and insulin-resistance. (3) Muscle is the main place where energy metabolism and material metabolism take place. Consequently, 53 genes were found, functionally enriched in pathways such as pyruvate metabolism, muscle system process and development of primary male sexual characteristics etc. We further lay our eyes on genes correlated with male sexual characteristics, which may be involved in the onset of both PCOS and breast cancer. Three genes were indicated to be associated with this process, including hydroxysteroid (17-beta) dehydrogenase 4/HSD17B4, platelet-derived growth factor receptor, alpha polypeptide/PDGFRA and high-mobility group box 2/HMGB2. Gene-drug interaction network about the three genes were then constructed. Drugs or chemicals that contribute to correcting the disorder of lipid metabolism were detected to restore the abnormal expression of the three genes in PCOS, such as simvastatin, bezafibrate, fenofibrate et al, which provide further choices for managing patients with PCOS.

SUBMITTER: Xu H

PROVIDER: S-EPMC5642496 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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PDGFRA, HSD17B4 and HMGB2 are potential therapeutic targets in polycystic ovarian syndrome and breast cancer.

Xu Huiyu H Han Yong Y Lou Jiaying J Zhang Hongxian H Zhao Yue Y Győrffy Balázs B Li Rong R

Oncotarget 20170513 41

To explore the key genes associated with both PCOS and breast cancer, we overlapped the synchronously differently expressed genes in two obese insulin-resistant GEO datasets in muscle tissue and genes exert essential roles in breast cancer prognosis together base on the following reasons: (1) Androgens excess is believed to contribute to the onset of both PCOS and breast cancer. (2) PCOS is usually complicated with metabolic symptoms, such as obesity and insulin-resistance. (3) Muscle is the mai ...[more]

PMID: 29050221

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Project description:PurposeTriple-negative breast cancer (TNBC) is an aggressive tumor with poor prognosis, it has higher recurrence and metastatic rates than other breast cancer subtypes. This study aims to investigate biomarkers and potential targets for TNBC related to ferroptosis through data mining and bioinformatics analysis. The findings may provide new insights for treating TNBC.MethodsThe TNBC patients' data from the Cancer Genome Atlas (TCGA) database were extracted for differential expression and prognosis analysis. Consensus genes obtained by intersecting differential expressed and ferroptosis-related genes was used to establish the prognostic model by the univariate and multivariate Cox analyses. Besides, TNBC data from the Gene Expression Omnibus (GEO) database was used to confirm the reliability of the prognosis model. Moreover, clinical information was analyzed by multifactorial independent analysis to identify independent prognostic factors. The expression of genes constituting the prognostic model was further validated using the Human Protein Atlas (HPA) database. Finally, the Comparative Toxicogenomic Data (CTD) database was used to explore possible treatment drugs for TNBC.ResultsWe obtained 13,245 differential expressed genes, and 177 consensus genes. 98 genes with prognostic implication were obtained by univariable Cox. Then, a prognostic model including 12 ferroptosis-related genes was constructed by multivariable Cox. The area under curve (AUC) value of the prognostic model for TNBC was 0.82. The GEO database validated that the model (AUC = 0.77) could predict the patient outcomes. The staining results of 10 out of 12 prognostic model genes in HPA database showed that their expression was consistent with our predictions. Clinical risk analysis indicated that risk score of patients could act as an independent prognostic factor. Finally, six drugs that may have interaction with 12 ferroptosis-related genes were obtained using the CTD database.ConclusionThe prognostic model composed of 12 ferroptosis-related genes could predict the prognosis of TNBC patients, and seven genes (ASNS, LAMP2, CAV1, DPP4, HELLS, TF, ZFP69B) could be potential new therapeutic targets for TNBC, and two drugs (1-methyl-3-isobutylxanthine, rosiglitazone) could act as potential therapeutic drugs for the treatment of TNBC.

Dataset Information

PDGFRA, HSD17B4 and HMGB2 are potential therapeutic targets in polycystic ovarian syndrome and breast cancer.

Publications

PDGFRA, HSD17B4 and HMGB2 are potential therapeutic targets in polycystic ovarian syndrome and breast cancer.

Similar Datasets

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