International Journal of Biological Markers最新文献

{"title":"Alterations of commensal microbiota are associated with pancreatic cancer.","authors":"Tian Chen, Xuejiao Li, Gaoming Li, Yun Liu, Xiaochun Huang, Wei Ma, Chao Qian, Jie Guo, Shuo Wang, Qin Qin, Shanrong Liu","doi":"10.1177/03936155231166721","DOIUrl":"10.1177/03936155231166721","url":null,"abstract":"<p><strong>Background: </strong>Dysbiosis commonly occurs in pancreatic cancer, but its specific characteristics and interactions with pancreatic cancer remain obscure.</p><p><strong>Materials and methods: </strong>The 16S rRNA sequencing method was used to analyze multisite (oral and gut) microbiota characteristics of pancreatic cancer, chronic pancreatitis, and healthy controls. Differential analysis was used to identify the pancreatic cancer-associated genera and pathways. A random forest algorithm was adopted to establish the diagnostic models for pancreatic cancer.</p><p><strong>Results: </strong>The chronic pancreatitis group exhibited the lowest microbial diversity, while no significant difference was found between the pancreatic cancer group and healthy controls group. Diagnostic models based on the characteristics of the oral (area under the curve (AUC) 0.916, 95% confidence interval (CI) 0.832-1) or gut (AUC 0.856; 95% CI 0.74, 0.972) microbiota effectively discriminate the pancreatic cancer samples in this study, suggesting saliva as a superior sample type in terms of detection efficiency and clinical compliance. Oral pathogenic genera (<i>Granulicatella</i>, <i>Peptostreptococcus</i>, <i>Alloprevotella</i>, <i>Veillonella</i>, etc.) and gut opportunistic genera (<i>Prevotella</i>, <i>Bifidobacterium</i>, <i>Escherichia/Shigella</i>, <i>Peptostreptococcus</i>, <i>Actinomyces</i>, etc.), were significantly enriched in pancreatic cancer. The 16S function prediction analysis revealed that inflammation, immune suppression, and barrier damage pathways were involved in the course of pancreatic cancer.</p><p><strong>Conclusion: </strong>This study comprehensively described the microbiota characteristics of pancreatic cancer and suggested potential microbial markers as non-invasive tools for pancreatic cancer diagnosis.</p>","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 2","pages":"89-98"},"PeriodicalIF":2.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9674648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnosis of malignant pleural effusion with combinations of multiple tumor markers: A comparison study of five machine learning models.","authors":"Yixi Zhang,&nbsp;Jingyuan Wang,&nbsp;Baosheng Liang,&nbsp;Hanyu Wu,&nbsp;Yangyu Chen","doi":"10.1177/03936155231158125","DOIUrl":"https://doi.org/10.1177/03936155231158125","url":null,"abstract":"<p><strong>Background: </strong>To evaluate the diagnostic value of combinations of tumor markers carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 125, CA153, and CA19-9 in identifying malignant pleural effusion (MPE) from non-malignant pleural effusion (non-MPE) using machine learning, and compare the performance of popular machine learning methods.</p><p><strong>Methods: </strong>A total of 319 samples were collected from patients with pleural effusion in Beijing and Wuhan, China, from January 2018 to June 2020. Five machine learning methods including Logistic regression, extreme gradient boosting (XGBoost), Bayesian additive regression tree, random forest, and support vector machine were applied to evaluate the diagnostic performance. Sensitivity, specificity, Youden's index, and the area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of different diagnostic models.</p><p><strong>Results: </strong>For diagnostic models with a single tumor marker, the model using CEA, constructed by XGBoost, performed best (AUC = 0.895, sensitivity = 0.80), and the model with CA153, also by XGBoost, showed the largest specificity 0.98. Among all combinations of tumor markers, the combination of CEA and CA153 achieved the best performance (AUC = 0.921, sensitivity = 0.85) in identifying MPE under the diagnostic model constructed by XGBoost.</p><p><strong>Conclusions: </strong>Diagnostic models for MPE with a combination of multiple tumor markers outperformed the models with a single tumor marker, particularly in sensitivity. Using machine learning methods, especially XGBoost, could comprehensively improve the diagnostic accuracy of MPE.</p>","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 2","pages":"139-146"},"PeriodicalIF":2.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9670205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of secretory DKK3 on circulating CD56^bright natural killer cells in patients with liver cancer.","authors":"Da-Hua Liu,&nbsp;Gui-Min Wen,&nbsp;Chang-Liang Song,&nbsp;Pu Xia","doi":"10.1177/03936155231169796","DOIUrl":"https://doi.org/10.1177/03936155231169796","url":null,"abstract":"<p><strong>Background: </strong>Liver cancer seriously threatens human health. Natural killer (NK) cells are an important part of the innate immune system and have strong anti-tumor ability. Immunotherapy based on NK cells has become a hot topic in the treatment of liver cancer.</p><p><strong>Methods: </strong>In this study, we checked the serum DKK3 (sDKK3) and circulating CD56^bright NK cells using ELISA and flow cytometry, respectively, in the blood of liver cancer patients. The effect on recombinant human DKK3 (rhDKK3) on CD56^bright NK cells was analyzed in vitro.</p><p><strong>Results: </strong>We found low levels of sDKK3 in liver cancer patients and a negative correlation between sDKK3 and circulating CD56^bright NK cells. In addition, we found that DKK3 induced the differentiation and improved the cytotoxicity of CD56^bright NK cells for the first time. It could be used as an agonist for NK cell-based immunotherapy.</p><p><strong>Conclusions: </strong>Improving the clinical efficacy of NK cells through DKK3 will become a new strategy for cancer immunotherapy.</p>","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 2","pages":"99-104"},"PeriodicalIF":2.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9724639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gleason Score-related MT1L as biomarker for prognosis in prostate adenocarcinoma and contribute to tumor progression in vitro.","authors":"Lei Liu,&nbsp;Yaping Li,&nbsp;Shiying Tang,&nbsp;Bin Yang,&nbsp;Qiming Zhang,&nbsp;Ruotao Xiao,&nbsp;Xiaofei Hou,&nbsp;Cheng Liu,&nbsp;Lulin Ma","doi":"10.1177/03936155231156458","DOIUrl":"https://doi.org/10.1177/03936155231156458","url":null,"abstract":"<p><strong>Background: </strong>The Gleason Score is well correlated with biological behavior and prognosis in prostate adenocarcinoma (PRAD). This study was derived to determine the clinical significance and function of Gleason-Score-related genes in PRAD.</p><p><strong>Methods: </strong>RNA-sequencing profiles and clinical data were extracted from the The Cancer Genome Atlas PRAD database. The Gleason-Score-related genes were screened out by the Jonckheere-Terpstra rank-based test. The \"limma\" R package was performed for differentially expressed genes. Next, a Kaplan-Meier survival analysis was performed. Correlation MT1L expression levels with tumor stage, non-tumor tissue stage, radiation therapy, and residual tumor were analyzed. Further, MT1L expression was detected in PRAD cell lines by reverse transcription-quantitative polymerase chain reaction assay. Overexpression of MT1L was constructed and used for cell count kit-8, flow cytometric assay, transwell assay, and wound-healing assay.</p><p><strong>Results: </strong>Survival analysis showed 15 Gleason-Score-related genes as prognostic biomarkers in PRAD. The high-frequency deletion of MT1L was verified in PRAD. Furthermore, MT1L expression was decreased in PRAD cell lines than RWPE-1 cells, and overexpression of MT1L repressed cell proliferation and migration, and induced apoptosis in PC-3 cells.</p><p><strong>Conclusion: </strong>Gleason-Score-related MT1L may serve as a biomarker of poor prognostic biomarker in PRAD. In addition, MT1L plays a tumor suppressor in PRAD progression, which is beneficial for PRAD diagnosis and treatment research.</p>","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 2","pages":"114-123"},"PeriodicalIF":2.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9725159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ensuring efficient development of personalized medicine by addressing regulatory needs: What role can research infrastructures play?","authors":"Francesca Capone,&nbsp;David Morrow,&nbsp;Franca Moretti","doi":"10.1177/03936155231179981","DOIUrl":"https://doi.org/10.1177/03936155231179981","url":null,"abstract":"<p><p>Personalized Medicine is a novel medical practice that uses an individual's genetic profile to guide decisions made regarding the prevention, diagnosis, and treatment of disease. Knowledge of a patient's genetic profile is crucial to support doctors in selecting the proper therapy and administer it using the correct dose or regimen. Personalized Medicine is a great opportunity to turn the \"one size fits all\" approach to diagnostics, therapy, and prevention, into an individualized approach. In this paper we analyze the most recent achievements and regulatory challenges in Personalized Medicine and the role that research infrastructures can play in advancing its development.</p>","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 2","pages":"77-80"},"PeriodicalIF":2.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9664044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prognostic and clinicopathologic significance of PLIN2 in cancers: A systematic review with meta-analysis.","authors":"Ming-Lin Li, Han-Yong Luo, Zi-Wei Quan, Le-Tian Huang, Jia-He Wang","doi":"10.1177/03936155221147536","DOIUrl":"10.1177/03936155221147536","url":null,"abstract":"<p><p>The relationship between PLIN2 expression and prognosis, and clinicopathological significance of various cancers has been extensively studied, but the results are not completely consistent. This review followed the guidelines for systematic reviews of prognostic factors studies and was reported under the Preferred Reporting Program for Systematic Reviews and Meta-Analysis (PRISMA). We searched PubMed, Embase, Cochrane Library, Web of Science, and Google Academia for relevant articles up to September 2, 2022, and calculated the pooled hazard ratios (HR) with 95% confidence intervals (CI) to determine the association between PLIN2 expression and the prognosis of various cancers. The meta-analysis ultimately included 17 studies. The quality of all included cohort studies was evaluated using the Quality in Prognosis Studies (QUIPS) tool, and an adaptation of Grading of Recommendations Assessment, Development and Evaluation (GRADE) method was used to assess the certainty of the results. High expression of PLIN2 was associated with poorer overall survival (HR  =  1.65; 95% CI  =  1.14, 2.38; <i>P</i>  =  0.008), metastasis-free survival (HR  =  1.48; 95% CI  =  1.12, 1.94; <i>P</i>  =  0.005), progression-free survival (HR  =  2.11; 95% CI  =  1.55, 2.87; <i>P</i> < 0.0005) and recurrence-free survival/relapse-free survival (HR  =  2.21; 95% CI  =  1.64, 2.98; <i>P</i> < 0.0005) in cancers. The clinicopathological parameters of digestive system malignancies suggested that high expression of PLIN2 was notably associated with distant metastasis ( + ) (odds ratio (OR)  =   3.37; 95% CI  =  1.31, 8.67; <i>P</i>  =  0.012), lymph node metastasis ( + ) (OR  =  1.61; 95% CI  =  1.01, 2.54; <i>P</i>  =  0.004), and tumor stage (III-IV) (OR  =   1.96; 95% CI  =   1.24, 3.09; <i>P</i>  =  0.006). In summary, overexpression of PLIN2 is significantly associated with a poor prognosis in various human cancers, especially in respiratory and digestive malignancies. Thus, PLIN2 expression may be a potential prognostic biomarker in cancer patients.</p>","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 1","pages":"3-14"},"PeriodicalIF":2.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9230897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Programmed death-ligand 1 expression in diffuse large B-cell lymphoma is associated with poor prognosis.","authors":"Esraa Al-Khateeb,&nbsp;Manal A Abbas,&nbsp;Majd B Khader,&nbsp;Maher A Sughayer","doi":"10.1177/03936155221149749","DOIUrl":"https://doi.org/10.1177/03936155221149749","url":null,"abstract":"<p><strong>Background: </strong>Programmed death-ligand 1 (PD-L1) expression in some tumors has prognostic implications. This work aims at investigating PD-L1 expression in diffuse large B-cell lymphoma (DLBCL) and to study its association with clinicopathological variables.</p><p><strong>Methods: </strong>The study consisted of 75 DLBCL patients who were cared for at the King Hussein Cancer Center during the period 2015-2018. The expression of PD-L1 in tumor tissue was assessed by immunohistochemistry using the anti-human PD-L1 (Clone 22C3) monoclonal antibody. The correlation between gender, age, clinical stage, pre-treatment-LDH level, tumor location, response to therapy, overall and event-free survival with PD-L1 expression was studied.</p><p><strong>Results: </strong>Six patients were excluded from further analysis as they were in relapse at the time of tissue sampling. The tumor proportion score (TPS) was ≥1% in 16/69 (23.2%) of DLBCL cases while the combined positive score (CPS) at a cut-off of ≥20 was observed in 23/69 (33.3%) cases. No significant difference in PD-L1 expression was found between germinal center B-cell-like (GCB) and non-GCB subtypes. Similarly, no differences in PD-L1 expression (at CPS ≥20 and TPS ≥1) were found between different genders, age groups, clinical stages, tumor location, and patient response to therapy. However, base-line lactate dehydrogenase was significantly elevated in patients with PD-L1 CPS ≥20. The overall survival was not significantly different between PD-L1-positive and -negative groups. On the other hand, the median event-free survival was higher in either of the PD-L1 TPS or CPS negative groups at 107months each versus 54 months in the PD-L1 positive group of either category.</p><p><strong>Conclusions: </strong>PD-L1 expression can predict event-free survival in DLBCL cases and therefore poor prognosis.</p>","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 1","pages":"53-60"},"PeriodicalIF":2.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9237414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rosella Silvestrini, Ph.D., a pioneer in the field of translational research in oncology, passed on January 5, 2023, at the age of 92.","authors":"","doi":"10.1177/03936155231160685","DOIUrl":"https://doi.org/10.1177/03936155231160685","url":null,"abstract":"Born in 1930 in Faenza, Italy, Silvestrini graduated with highest honors from the University of Milan in 1952 with a Master of Science degree in biology, and acquired a teaching position in Normal and Pathological Immunohistochemistry in 1964. In the early days of her career, Rosella Silvestrini joined Farmitalia, the largest pharmaceutical company in Italy in the 1970s. Successively, from 1963, she spent much of her career at Milan’s Istituto Nazionale Tumori (National Cancer Institute), initially as a researcher of the National Research Council and later as Director of one of the five Divisions of Experimental Oncology. In 1997 she joined the Istituto Oncologico Romagnolo (Romagna Oncologic Institute) as a scientific consultant coordinator of the research laboratories. During her professional activity, she acted as an advisor in various scientific institutions, and has held positions in the Italian Ministry of University and Research and in the Ministry of Health (in commissions for national research and for oncology plans), and in the National Research Council Committees in which she collaborated in planning the three subsequent special Italian projects focused on oncology. Rosella Silvestrini started her distinguished career in the Farmitalia’s team of Aurelio Di Marco, where she contributed to the discovery and characterization of daunomycin, an antibiotic active against leukemia from which adriamycin was subsequently derived. These studies were conducted in close collaboration with the team of clinicians at the Istituto Nazionale Tumori of Milan, with the close and fruitful collaboration that made possible the development of effective treatments that significantly changed the natural history of solid and systemic malignancies, since then recognized and codified by the international scientific community. The strong collaboration with clinicians that characterized the beginning of Sivestrini’s activity primed and characterized the continuation of her career. Silvestrini led several groundbreaking studies on the biologic factors underlying cancer development, invasiveness, and progression and on determinants of sensitivity/ resistance to clinical treatments, to identify prognostic and predictive markers, and on the action mechanisms of chemical, physical and biological agents in experimental models to define optimal treatment schedules. She was one of the first investigators to report a link between tumor cell proliferation and breast cancer prognosis: in this context and with the support of various Italian cancer institutes, she contributed to the activation around 1990 prospective studies to evaluate the clinical utility of determining proliferation indices to identify patients with stage I tumors at high risk of disease recurrence who could benefit from adjuvant treatments. Furthermore, according to one key scientific question concerning the use of robust and reliable biomarkers in clinical trials, which should be measurable with little or ","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 1","pages":"72-73"},"PeriodicalIF":2.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9239384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plasma metabolomics for the assessment of the progression of non-small cell lung cancer.","authors":"Yingtian Zhang,&nbsp;Yaping Cheng,&nbsp;Liqiang Qin,&nbsp;Yuanliang Liu,&nbsp;Sijia Huang,&nbsp;Liya Dai,&nbsp;Jialong Tao,&nbsp;Jie Pan,&nbsp;Cunjin Su,&nbsp;Yusong Zhang","doi":"10.1177/03936155221137359","DOIUrl":"https://doi.org/10.1177/03936155221137359","url":null,"abstract":"<p><strong>Objectives: </strong>Non-small cell lung cancer (NSCLC) is a leading type of lung cancer with a high mortality rate worldwide. Although many procedures for the diagnosis and prognosis assessment of lung cancer exist, they are often laborious, expensive, and invasive. This study aimed to develop an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS)-based analysis method for the plasma biomarkers of NSCLC with the potential to indicate the stages and progression of this malignancy conveniently and reliably.</p><p><strong>Methods: </strong>A total of 53 patients with NSCLC in early stages (I-III) and advanced stage (IV) were classified into the early and advanced groups based on the tumor node metastasis staging system. A comprehensive metabolomic analysis of plasma from patients with NSCLC was performed via UPLC-MS/MS. Principal component analysis and partial least squares-discriminant analysis were conducted for statistical analysis. Potential biomarkers were evaluated and screened through receiver operating characteristic analyses and correlation analysis. Main differential metabolic pathways were also identified by utilizing metaboanalyst.</p><p><strong>Results: </strong>A total of 129 differential metabolites were detected in accordance with the criteria of VIP ≥ 1 and a <i>P</i>-value of ≤ 0.05. The receiver operating characteristic curves indicated that 11 of these metabolites have the potential to be promising markers of disease progression. Apparent correlated metabolites were also filtered out. Furthermore, the 11 most predominant metabolic pathways with alterations involved in NSCLC were identified.</p><p><strong>Conclusion: </strong>Our study focused on the plasma metabolomic changes in patients with NSCLC. These changes may be used for the prediction of the stage and progression of NSCLC. Moreover, we discussed the metabolic pathways wherein the altered metabolites were mainly enriched.</p>","PeriodicalId":50334,"journal":{"name":"International Journal of Biological Markers","volume":"38 1","pages":"37-45"},"PeriodicalIF":2.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9590728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic and prognostic values of MMP-9 expression in ovarian cancer: A study based on bioinformatics analysis and meta-analysis.","authors":"Changyu Liu,&nbsp;Ying Shen,&nbsp;Qiyan Tan","doi":"10.1177/03936155221140421","DOIUrl":"https://doi.org/10.1177/03936155221140421","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":2.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9291327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}