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联合生物标志物面板可提高卵巢癌检测的灵敏度和特异性。

A combined biomarker panel shows improved sensitivity and specificity for detection of ovarian cancer.

机构信息

Guangxi Medical University Cancer Hospital, Nanning, China.

Wuming Hospital of Guangxi Medical University, Nanning, China.

出版信息

J Clin Lab Anal. 2022 Feb;36(2):e24232. doi: 10.1002/jcla.24232. Epub 2022 Jan 7.

DOI:10.1002/jcla.24232
PMID:34995016
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8842139/
Abstract

BACKGROUND

Combined biomarkers can improve the sensitivity and specificity of ovarian cancer (OC) diagnosis and effectively predict patient prognosis. This study explored the diagnostic and prognostic values of serum CCL18 and CXCL1 antigens combined with C1D, FXR1, ZNF573, and TM4SF1 autoantibodies in OC.

METHODS

CCL18 and CXCL1 monoclonal antibodies and C1D, FXR1, ZNF573, and TM4SF1 antigens were coated with microspheres. Logistic regression was used to construct a serum antigen-antibody combined detection model; receiver-operating characteristic curve (ROC) was used to evaluate the diagnostic efficacy of the model; and the Kaplan-Meier method and Cox regression models were used for survival analysis to evaluate the prognosis of OC. Data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects and online survival analysis tools were used to evaluate prognostic genes for OC. The CIBERSORT immune score was used to explore the factors influencing prognosis and their relationship with tumor-infiltrating immune cells.

RESULTS

The levels of each index in the blood samples of patients with OC were higher than those of the other groups. The combined detection model has higher specificity and sensitivity in the diagnosis of OC, and its diagnostic efficiency is better than that of CA125 alone and diagnosing other malignant tumors. CCL18 and TM4SF1 may be factors affecting the prognosis of OC, and CCL18 may be related to immune-infiltrating cells.

CONCLUSIONS

The serum antigen-antibody combined detection model established in this study has high sensitivity and specificity for the diagnosis of OC.

摘要

背景

联合生物标志物可以提高卵巢癌（OC）诊断的灵敏度和特异性，并有效地预测患者预后。本研究探讨了血清 CCL18 和 CXCL1 抗原与 C1D、FXR1、ZNF573 和 TM4SF1 自身抗体联合在 OC 中的诊断和预后价值。

方法

用微球包被 CCL18 和 CXCL1 单克隆抗体及 C1D、FXR1、ZNF573 和 TM4SF1 抗原。采用逻辑回归构建血清抗原-抗体联合检测模型；用受试者工作特征曲线（ROC）评估模型的诊断效能；Kaplan-Meier 法和 Cox 回归模型进行生存分析，评估 OC 的预后。利用癌症基因组图谱（TCGA）和基因型组织表达（GTEx）项目及在线生存分析工具评估 OC 的预后相关基因。利用 CIBERSORT 免疫评分探索影响预后的因素及其与肿瘤浸润免疫细胞的关系。

结果

OC 患者血液样本中各指标水平均高于其他组。联合检测模型对 OC 的诊断具有更高的特异性和灵敏度，其诊断效率优于 CA125 单独诊断和诊断其他恶性肿瘤。CCL18 和 TM4SF1 可能是影响 OC 预后的因素，CCL18 可能与免疫浸润细胞有关。

结论

本研究建立的血清抗原-抗体联合检测模型对 OC 的诊断具有较高的灵敏度和特异性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/84a6430dd47b/JCLA-36-e24232-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/eca84a814629/JCLA-36-e24232-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/86584424edb3/JCLA-36-e24232-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/9564f10359e9/JCLA-36-e24232-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/bd3d479d50b0/JCLA-36-e24232-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/a487104eda5b/JCLA-36-e24232-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/bd516438d24f/JCLA-36-e24232-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/84a6430dd47b/JCLA-36-e24232-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/eca84a814629/JCLA-36-e24232-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/86584424edb3/JCLA-36-e24232-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/9564f10359e9/JCLA-36-e24232-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/bd3d479d50b0/JCLA-36-e24232-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/a487104eda5b/JCLA-36-e24232-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/bd516438d24f/JCLA-36-e24232-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2871/8842139/84a6430dd47b/JCLA-36-e24232-g005.jpg

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