{"title":"卵巢癌中MMP-9表达的诊断和预后价值:基于生物信息学分析和荟萃分析的研究","authors":"Changyu Liu, Ying Shen, Qiyan Tan","doi":"10.1177/03936155221140421","DOIUrl":null,"url":null,"abstract":"<p><p>This study aims to explore the expression of matrix metalloproteinase-9 (MMP-9) associated with both diagnostic and prognostic value in ovarian cancer by meta-analysis and bioinformatics analyses. We investigated the prognostic value of MMP-9 expression in ovarian cancer based on The Cancer Genome Atlas. Five databases were used to collect records about MMP-9 expression related to diagnostic and prognostic values in ovarian cancer from inception to June 2022. Using Stata 15.0 software, hazard ratio (HR) and odds ratio (OR) were calculated as the effect index of prognosis. We chose the pooled sensitivity, specificity, and area under the curve (AUC) to judge the diagnostic utility of MMP-9 for ovarian cancer. A total of 23 studies on prognosis, and five studies on diagnosis were entered into the meta-analysis. These suggest that high MMP-9 expression was detrimental to the overall survival of patients with ovarian cancer (HR = 1.34; 95% confidence interval (CI) 1.08∼1.66; <i>P<</i>0.01). High MMP-9 expression increased the risk of tumor stage (OR = 3.66; 95% CI 1.89∼7.07), but was not related to the tumor grade of ovarian cancer (<i>P></i>0.05). The pooled analysis of serum MMP-9 diagnosing for ovarian cancer gave the pooled sensitivity, specificity, and AUC the values of 0.72 (95% CI 0.61∼0.81), 0.81 (95% CI 0.77∼0.85), and 0.84 (95% CI 0.81∼0.87), respectively. High MMP-9 expression can increase the tumor stage, and a correlation exists between high MMP-9 expression and poor prognosis in patients with ovarian cancer. Also, serum MMP-9 has a good diagnostic value for ovarian cancer.</p>","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 1","pages":"15-24"},"PeriodicalIF":2.3000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Diagnostic and prognostic values of MMP-9 expression in ovarian cancer: A study based on bioinformatics analysis and meta-analysis.\",\"authors\":\"Changyu Liu, Ying Shen, Qiyan Tan\",\"doi\":\"10.1177/03936155221140421\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study aims to explore the expression of matrix metalloproteinase-9 (MMP-9) associated with both diagnostic and prognostic value in ovarian cancer by meta-analysis and bioinformatics analyses. We investigated the prognostic value of MMP-9 expression in ovarian cancer based on The Cancer Genome Atlas. Five databases were used to collect records about MMP-9 expression related to diagnostic and prognostic values in ovarian cancer from inception to June 2022. Using Stata 15.0 software, hazard ratio (HR) and odds ratio (OR) were calculated as the effect index of prognosis. We chose the pooled sensitivity, specificity, and area under the curve (AUC) to judge the diagnostic utility of MMP-9 for ovarian cancer. A total of 23 studies on prognosis, and five studies on diagnosis were entered into the meta-analysis. These suggest that high MMP-9 expression was detrimental to the overall survival of patients with ovarian cancer (HR = 1.34; 95% confidence interval (CI) 1.08∼1.66; <i>P<</i>0.01). High MMP-9 expression increased the risk of tumor stage (OR = 3.66; 95% CI 1.89∼7.07), but was not related to the tumor grade of ovarian cancer (<i>P></i>0.05). 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引用次数: 3
摘要
本研究旨在通过荟萃分析和生物信息学分析探讨基质金属蛋白酶-9 (MMP-9)在卵巢癌中的表达与诊断和预后的关系。我们基于癌症基因组图谱研究了卵巢癌中MMP-9表达的预后价值。使用5个数据库收集从成立到2022年6月卵巢癌中与诊断和预后价值相关的MMP-9表达记录。采用Stata 15.0软件计算风险比(HR)和优势比(OR)作为预后的影响指标。我们选择综合敏感性、特异性和曲线下面积(AUC)来判断MMP-9对卵巢癌的诊断价值。共有23项关于预后的研究和5项关于诊断的研究纳入meta分析。这些提示,高表达的MMP-9对卵巢癌患者的总生存不利(HR = 1.34;95%置信区间(CI) 1.08 ~ 1.66;P0.01)。MMP-9高表达增加肿瘤分期风险(OR = 3.66;95% CI 1.89 ~ 7.07),但与卵巢癌的肿瘤分级无关(P>0.05)。血清MMP-9诊断卵巢癌的合并分析得出的合并敏感性、特异性和AUC分别为0.72 (95% CI 0.61 ~ 0.81)、0.81 (95% CI 0.77 ~ 0.85)和0.84 (95% CI 0.81 ~ 0.87)。MMP-9高表达可增加肿瘤分期,卵巢癌患者MMP-9高表达与预后不良存在相关性。血清MMP-9对卵巢癌有较好的诊断价值。
Diagnostic and prognostic values of MMP-9 expression in ovarian cancer: A study based on bioinformatics analysis and meta-analysis.
This study aims to explore the expression of matrix metalloproteinase-9 (MMP-9) associated with both diagnostic and prognostic value in ovarian cancer by meta-analysis and bioinformatics analyses. We investigated the prognostic value of MMP-9 expression in ovarian cancer based on The Cancer Genome Atlas. Five databases were used to collect records about MMP-9 expression related to diagnostic and prognostic values in ovarian cancer from inception to June 2022. Using Stata 15.0 software, hazard ratio (HR) and odds ratio (OR) were calculated as the effect index of prognosis. We chose the pooled sensitivity, specificity, and area under the curve (AUC) to judge the diagnostic utility of MMP-9 for ovarian cancer. A total of 23 studies on prognosis, and five studies on diagnosis were entered into the meta-analysis. These suggest that high MMP-9 expression was detrimental to the overall survival of patients with ovarian cancer (HR = 1.34; 95% confidence interval (CI) 1.08∼1.66; P<0.01). High MMP-9 expression increased the risk of tumor stage (OR = 3.66; 95% CI 1.89∼7.07), but was not related to the tumor grade of ovarian cancer (P>0.05). The pooled analysis of serum MMP-9 diagnosing for ovarian cancer gave the pooled sensitivity, specificity, and AUC the values of 0.72 (95% CI 0.61∼0.81), 0.81 (95% CI 0.77∼0.85), and 0.84 (95% CI 0.81∼0.87), respectively. High MMP-9 expression can increase the tumor stage, and a correlation exists between high MMP-9 expression and poor prognosis in patients with ovarian cancer. Also, serum MMP-9 has a good diagnostic value for ovarian cancer.
期刊介绍:
IJBM is an international, online only, peer-reviewed Journal, which publishes original research and critical reviews primarily focused on cancer biomarkers. IJBM targets advanced topics regarding the application of biomarkers in oncology and is dedicated to solid tumors in adult subjects. The clinical scenarios of interests are screening and early diagnosis of cancer, prognostic assessment, prediction of the response to and monitoring of treatment.