Wang Yi, Wen Yuting, Wang Jiayin, Lai Xin, Xu Ying, Zhang Xuanping, Zhu Xiaoyan, Ruan Chenglin, Huang Yao
School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Department of Pathology, Xi'an Ninth Hospital Affiliated to Medical College of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Front Microbiol. 2022 Nov 4;13:945463. doi: 10.3389/fmicb.2022.945463. eCollection 2022.
To systematically evaluate the significance of (Fn) levels the clinicopathological impacts of cancer.
Literature from Pubmed, Embase, and Web of Science was retrieved to collect all English literatures on the correlation between Fn and cancer, and the quality of literatures collected was assessed based on the Newcastle-Ottawa Quality Assessment Scale. The heterogeneity and sensitivity were detected by Stata 14.0 software, and the correlation between Fn and cancer clinicopathological as the effect variables was assessed according to the odds ratio (OR) and 95% confidence interval (CI). The forest plot was drawn.
A total of 19 articles meeting the inclusion criteria were selected. The incidence of Fn prevalence varied considerably (range: 6.1 to 83.3%) and was greater than 10% in 13 of 19 studies. Compared with those with no/low Fn levels, the high levels of Fn was positively associated with vascular invasion, nerve invasion, depth of invasion, and distant metastasis [vascular invasion: OR = 1.66, 95%CI(1.07, 2.57), = 21.9%, fixed effect model; nerve invasion: OR = 1.36, 95%CI(1.00, 1.84), = 43.1%, fixed effect model; infiltration depth: OR = 1.94, 95%CI(1.20, 3.15), = 67.2%, random effect model; distant metastasis: OR = 1.80, 95%CI(1.23, 2.64), = 3.4%, fixed effect model]. Patients with MLH1 methylation always present a higher Fn levels than those without methylation [OR = 2.53, 95%CI(1.42, 4.53), = 0.01, = 57.5%, random effect model]. Further, Fn was associatedwith the molecular characteristics of cancers [MSI-H Vs. MSS/MSI-low: OR = 2.92, 95%CI(1.61, 5.32), = 0.01, = 63.2%, random effect model; High Vs. Low/Negative CIMP: OR = 2.23, 95%CI(1.64, 3.03), = 0.01, = 64.2%, random effect model; KRAS mutation Vs. wild-type: OR = 1.24, 95%CI(1.04, 1.48), = 0.02, = 27.0%, fixed effect model; Present Vs. Abscent BRAF mutations: OR = 1.88, 95%CI(1.44, 2.45), = 0.01, = 24.2%, fixed effect model]. The cancer patients with high levels of Fn often have worse RFS than those with no/low Fn levels[OR = 1.14, 95%CI(0.61, 1.68), = 0.01, = 80.7%, random effect model].
This review and meta-analysis showed that Fn could be used to predict unfavorable prognosis and function as potential prognostic biomarkers in colorectal cancer (CRC). Our data may have implications for targeting Fn to develop strategies for cancer prevention and treatment.
系统评价(Fn)水平对癌症临床病理影响的意义。
检索来自PubMed、Embase和Web of Science的文献,收集所有关于Fn与癌症相关性的英文文献,并根据纽卡斯尔-渥太华质量评估量表对收集的文献质量进行评估。使用Stata 14.0软件检测异质性和敏感性,并根据优势比(OR)和95%置信区间(CI)评估Fn与癌症临床病理之间的相关性作为效应变量。绘制森林图。
共选择了19篇符合纳入标准的文章。Fn患病率差异很大(范围:6.1%至83.3%),19项研究中有13项大于10%。与Fn水平低/无的患者相比,Fn水平高与血管侵犯、神经侵犯、浸润深度和远处转移呈正相关[血管侵犯:OR = 1.66,95%CI(1.07,2.57),I² = 21.9%,固定效应模型;神经侵犯:OR = 1.36,95%CI(1.00,1.84),I² = 43.1%,固定效应模型;浸润深度:OR = 1.94,95%CI(1.20,3.15),I² = 67.2%,随机效应模型;远处转移:OR = 1.80,95%CI(1.23,2.64),I² = 3.4%,固定效应模型]。MLH1甲基化的患者Fn水平总是高于未甲基化的患者[OR = 2.53,95%CI(1.42,4.53),P = 0.01,I² = 57.5%,随机效应模型]。此外,Fn与癌症的分子特征相关[微卫星高度不稳定(MSI-H)与微卫星稳定/微卫星低度不稳定(MSS/MSI-Low):OR = 2.92,95%CI(1.61,5.32),P = 0.01,I² = 63.2%,随机效应模型;高甲基化与低/阴性CIMP:OR = 2.23,95%CI(1.64,3.03),P = 0.01,I² = 64.2%,随机效应模型;KRAS突变与野生型:OR = 1.24,95%CI(1.04,1.48),P = 0.02,I² = 27.0%,固定效应模型;存在与不存在BRAF突变:OR = 1.88,95%CI(1.44,2.45),P = 0.01,I² = 24.2%,固定效应模型]。Fn水平高的癌症患者无病生存期(RFS)通常比Fn水平低/无的患者差[OR = 1.14,95%CI(0.61,1.68),P = 0.01,I² = 80.7%,随机效应模型]。
本综述和荟萃分析表明,Fn可用于预测结直肠癌(CRC)的不良预后,并作为潜在的预后生物标志物。我们的数据可能对针对Fn制定癌症预防和治疗策略具有启示意义。