PDF(Pubmed)
Abstract：
UNASSIGNED: Signal transducers and activators of transcription (STAT) transcription factors, a family of genes encoding transcription factors, have been linked to the development of numerous types of tumors. However, there is a relative paucity of a comprehensive investigation of the expression and functional analysis of STATs in ovarian cancer (OV).
UNASSIGNED: Gene expression profile interaction analysis (GEPI2A), Metascape, The Cancer Genome Atlas (TCGA), Kaplan-Meier Plotter, Linkedomics, and CancerSEA databases were used for expression analysis and functional enrichment of STATs in ovarian cancer patients. We screened potential predictive genes and evaluated their prognostic value by constructing the minor absolute shrinkage and selection operator (LASSO) Cox proportional risk regression model. We explored STAT5A expression and its effects on cell invasion using ovarian cancer cells and a tissue microarray.
UNASSIGNED: The expression level of STAT1 was higher, but that of STAT2-6 was lower in cancerous ovarian tissues compared to normal tissues, which were closely associated with the clinicopathological features. Low STAT1, high STAT4, and 6 mRNA levels indicated high overall survival. STAT1, 3, 4, and 5A were collectively constructed as prognostic risk models. STAT3, and 5A, up-regulating in the high-risk group, were regarded as risk genes. In subsequent validation, OV patients with a low level of P-STAT5A but not low STAT5A had a longer survival time (P=0.0042). Besides, a negative correlation was found between the expression of STAT5A and invasion of ovarian cancer cells (R= -0.38, p < 0.01), as well as DNA repair function (R= -0.36, p < 0.01). Furthermore, transient overexpression of STAT5A inhibited wound healing (21.8%, P<0.0001) and cell migration to the lower chamber of the Transwell system (29.3%, P<0.0001), which may be achieved by regulating the expression of MMP2.
UNASSIGNED: It is suggested that STAT1, STAT4, and STAT6 may be potential targets for the proper treatment of ovarian cancer. STAT5A and P-STAT5A, biomarkers identified in ovarian cancer, may offer new perspectives for predicting prognosis and assessing therapeutic effects.
UNASSIGNED: Gene expression profile interaction analysis (GEPI2A), Metascape, The Cancer Genome Atlas (TCGA), Kaplan-Meier Plotter, Linkedomics, and CancerSEA databases were used for expression analysis and functional enrichment of STATs in ovarian cancer patients. We screened potential predictive genes and evaluated their prognostic value by constructing the minor absolute shrinkage and selection operator (LASSO) Cox proportional risk regression model. We explored STAT5A expression and its effects on cell invasion using ovarian cancer cells and a tissue microarray.
UNASSIGNED: The expression level of STAT1 was higher, but that of STAT2-6 was lower in cancerous ovarian tissues compared to normal tissues, which were closely associated with the clinicopathological features. Low STAT1, high STAT4, and 6 mRNA levels indicated high overall survival. STAT1, 3, 4, and 5A were collectively constructed as prognostic risk models. STAT3, and 5A, up-regulating in the high-risk group, were regarded as risk genes. In subsequent validation, OV patients with a low level of P-STAT5A but not low STAT5A had a longer survival time (P=0.0042). Besides, a negative correlation was found between the expression of STAT5A and invasion of ovarian cancer cells (R= -0.38, p < 0.01), as well as DNA repair function (R= -0.36, p < 0.01). Furthermore, transient overexpression of STAT5A inhibited wound healing (21.8%, P<0.0001) and cell migration to the lower chamber of the Transwell system (29.3%, P<0.0001), which may be achieved by regulating the expression of MMP2.
UNASSIGNED: It is suggested that STAT1, STAT4, and STAT6 may be potential targets for the proper treatment of ovarian cancer. STAT5A and P-STAT5A, biomarkers identified in ovarian cancer, may offer new perspectives for predicting prognosis and assessing therapeutic effects.
摘要：
未经授权：信号转导和转录激活因子（STAT）转录因子，一个编码转录因子的基因家族，已经与许多类型的肿瘤的发展有关。然而,对卵巢癌(OV)中STATs的表达和功能分析的全面研究相对缺乏。
UNASSIGNED：基因表达谱相互作用分析（GEPI2A），Metascape,癌症基因组图谱(TCGA)Kaplan-Meier绘图仪,Linkedomics,和CancerSEA数据库用于卵巢癌患者中STATs的表达分析和功能富集。我们筛选了潜在的预测基因，并通过构建次要绝对收缩和选择算子（LASSO）Cox比例风险回归模型来评估其预后价值。我们使用卵巢癌细胞和组织微阵列研究了STAT5A的表达及其对细胞侵袭的影响。
UNASSIGNED：STAT1的表达水平较高，但是与正常组织相比，癌卵巢组织中的STAT2-6含量较低，与临床病理特征密切相关。低STAT1、高STAT4和6mRNA水平表明总生存率高。STAT1、3、4和5A被共同构建为预后风险模型。STAT3和5A，在高危人群中上调，被视为风险基因。在随后的验证中，P-STAT5A水平低但STAT5A不低的OV患者生存时间较长(P=0.0042)。此外,STAT5A的表达与卵巢癌细胞的侵袭性呈负相关（R=-0.38，p<0.01），以及DNA修复功能(R=-0.36,p<0.01)。此外，STAT5A的瞬时过表达抑制了伤口愈合（21.8%，P<0.0001）和细胞迁移到Transwell系统的下室（29.3％，P<0.0001),这可以通过调节MMP2的表达来实现。
UNASSIGNED：建议STAT1，STAT4和STAT6可能是正确治疗卵巢癌的潜在靶标。STAT5A和P-STAT5A,在卵巢癌中确定的生物标志物，可能为预测预后和评估治疗效果提供新的视角。
UNASSIGNED：基因表达谱相互作用分析（GEPI2A），Metascape,癌症基因组图谱(TCGA)Kaplan-Meier绘图仪,Linkedomics,和CancerSEA数据库用于卵巢癌患者中STATs的表达分析和功能富集。我们筛选了潜在的预测基因，并通过构建次要绝对收缩和选择算子（LASSO）Cox比例风险回归模型来评估其预后价值。我们使用卵巢癌细胞和组织微阵列研究了STAT5A的表达及其对细胞侵袭的影响。
UNASSIGNED：STAT1的表达水平较高，但是与正常组织相比，癌卵巢组织中的STAT2-6含量较低，与临床病理特征密切相关。低STAT1、高STAT4和6mRNA水平表明总生存率高。STAT1、3、4和5A被共同构建为预后风险模型。STAT3和5A，在高危人群中上调，被视为风险基因。在随后的验证中，P-STAT5A水平低但STAT5A不低的OV患者生存时间较长(P=0.0042)。此外,STAT5A的表达与卵巢癌细胞的侵袭性呈负相关（R=-0.38，p<0.01），以及DNA修复功能(R=-0.36,p<0.01)。此外，STAT5A的瞬时过表达抑制了伤口愈合（21.8%，P<0.0001）和细胞迁移到Transwell系统的下室（29.3％，P<0.0001),这可以通过调节MMP2的表达来实现。
UNASSIGNED：建议STAT1，STAT4和STAT6可能是正确治疗卵巢癌的潜在靶标。STAT5A和P-STAT5A,在卵巢癌中确定的生物标志物，可能为预测预后和评估治疗效果提供新的视角。
