结合甲基化 RNF180 和 SFRP2 血浆生物标记物进行胃癌无创诊断

IF 5 2区医学 Q2 Medicine

Translational Oncology Pub Date : 2024-11-13 DOI:10.1016/j.tranon.2024.102190

Zhihao Dai , Jin Jiang , Qianping Chen , Minghua Bai , Quanquan Sun , Yanru Feng , Dong Liu , Dong Wang , Tong Zhang , Liang Han , Litheng Ng , Jun Zheng , Hao Zou , Wei Mao , Ji Zhu

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引用次数: 0

摘要

简介胃癌（GC）是一种常见的恶性肿瘤，早期诊断可显著提高患者的生存率。本研究旨在探讨环指蛋白180（RNF180）和分泌型脆裂蛋白2（SFRP2）在胃癌中的诊断价值：将165名健康人、34名胃癌前病变患者和104名确诊GC患者分为训练集和验证集；在血液样本的循环DNA中检测甲基化的RNF180和SFRP2。建立并验证了六个模型，包括基于逻辑回归、Naive Bayes、K-近邻算法、glmnet、神经网络和随机森林（RF）的模型。确定了曲线下面积（AUC）、灵敏度、特异性、阳性预测值和阴性预测值：在训练集中，含有 RNF180 和 SFRP2（R + S）的 RF 模型诊断 GC 的 AUC 为 0.839（95 % CI：0.727-0.951），灵敏度为 60.3%，特异度为 85.5%。带有 R + S+ 肿瘤标记物的 RF 模型的 AUC 为 0.849（95 % CI：0.717-0.981），灵敏度为 62.8 %，特异性为 87.1 %。在验证集中，带有 R + S 的 RF 模型的 AUC 为 0.844（95 % CI：0.774-0.923），灵敏度为 87.8 %，特异度为 69.2 %。R+S+肿瘤标记物的RF模型的AUC为0.858（95% CI：0.781-0.939），灵敏度为85.4%，特异度为76.9%：我们的研究结果表明，在使用RF模型时，RNF180和SFRP2可作为GC的诊断生物标志物。

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Combining methylated RNF180 and SFRP2 plasma biomarkers for noninvasive diagnosis of gastric cancer

Introduction

Gastric cancer (GC) is a common malignant tumor, and early diagnosis significantly improves patient survival rates. This study aimed to investigate the diagnostic value of ring finger protein 180 (RNF180) and secreted frizzled protein 2 (SFRP2) in GC.

Materials & Methods

A total of 165 healthy individuals, 34 patients with precancerous gastric lesions, and 104 patients with confirmed GC were divided into training and validation sets; methylated RNF180 and SFRP2 were detected in circulating DNA from blood samples. Six models, including those based on logistic regression, Naive Bayes, K-nearest neighbor algorithm, glmnet, neural network, and random forest (RF) were built and validated. Area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value were determined.

Results

In the training set, the RF model with RNF180 and SFRP2 (R + S) had an AUC of 0.839 (95 % CI: 0.727–0.951), sensitivity of 60.3 %, and specificity of 85.5 % for diagnosing GC. The RF model with R + S+ Tumor markers had an AUC of 0.849 (95 % CI: 0.717–0.981), sensitivity of 62.8 %, and specificity of 87.1 %. In the validation set, the RF model with R + S had an AUC of 0.844 (95 % CI: 0.774–0.923), sensitivity of 87.8 %, and specificity of 69.2 %. The RF model with R + S + Tumor markers had an AUC of 0.858 (95 % CI: 0.781–0.939), sensitivity of 85.4 %, and specificity of 76.9 %.

Conclusion

Our results suggest that RNF180 and SFRP2 could serve as diagnostic biomarkers for GC when using the RF model.

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来源期刊

Translational Oncology ONCOLOGY-

CiteScore

8.40

自引率

2.00%

发文量

314

审稿时长

54 days

期刊介绍： Translational Oncology publishes the results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of oncology patients. Translational Oncology will publish laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer. Peer reviewed manuscript types include Original Reports, Reviews and Editorials.