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高通量和多阶段鉴定自身抗体在早期乳腺癌及亚型诊断中的应用。

High-throughput and multi-phases identification of autoantibodies in diagnosing early-stage breast cancer and subtypes.

机构信息

Department of Clinical Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

出版信息

Cancer Sci. 2022 Feb;113(2):770-783. doi: 10.1111/cas.15227. Epub 2021 Dec 9.

Abstract

Autoantibodies (AAbs) targeted tumor-associated antigens (TAAs) have the potential for early detection of breast cancer. Here, 574 early-stage breast cancer (ES-BC) patients containing 4 subtypes (Luminal A, Luminal B, HER2+, TN), 126 benign breast disease (BBD) patients, and 199 normal healthy controls (NHC) were separated into three-phases to discover, verify, and validate AAbs. In discovery phase using high-throughput protein microarray, 37 AAbs with sensitivity of 31.25%-86.25% and specificity over 73% in ES-BC, and 40 AAbs with different positive rates between subtypes were identified as candidates. In verification phase, 18 AAbs were significantly increased compared with the Control (BBD and NHC) in focused array. Ten out of 18 AAbs exhibited a significant difference between subtypes (P < .05). In ELISA validation phase, 5 novel AAbs (anti-KJ901215, -FAM49B, -HYI, -GARS, -CRLF3) exhibited significantly higher levels in ES-BC compared with BBD/NHC (P < .05). The sensitivities of individual AAb and a 5-AAbs panel were 20.41%-28.57% and 38.78%, whereas the specificities were over 90% and 85.94%. Simultaneously, 4 AAbs except anti-GARS differed significantly between TN and non-TN subtype (P < .05). We constructed 3 random forest classifier models based on AAbs to discriminant ES-BC from Control or BBD, and to discern TN subtype, which yielded an area under the curve of 0.870, 0.860, and 0.875, respectively. Biological interaction analysis revealed 4 TAAs, except for KJ901215, that were associated with well known proteins of BC. This study discovered and stepwise validated 5 novel AAbs with the potential to diagnose ES-BC and discern TN subtype, indicating easy-to-detect and minimally invasive diagnostic value of serum AAbs ahead of biopsy for future application.

摘要

自身抗体(AAbs)针对肿瘤相关抗原(TAAs)具有早期检测乳腺癌的潜力。在这里,将 574 例早期乳腺癌(ES-BC)患者(包含 4 种亚型:Luminal A、Luminal B、HER2+、TN)、126 例良性乳腺疾病(BBD)患者和 199 例正常健康对照(NHC)分为三个阶段来发现、验证和验证 AAbs。在使用高通量蛋白质微阵列的发现阶段,鉴定出 37 种 AAbs,其在 ES-BC 中的敏感性为 31.25%-86.25%,特异性超过 73%,并且在亚型之间具有不同的阳性率的 40 种 AAbs 被鉴定为候选物。在验证阶段,在聚焦阵列中,与对照(BBD 和 NHC)相比,18 种 AAbs 显著增加。在 18 种 AAbs 中有 10 种在亚型之间存在显著差异(P<.05)。在 ELISA 验证阶段,与 BBD/NHC 相比,5 种新型 AAbs(抗-KJ901215、-FAM49B、-HYI、-GARS、-CRLF3)在 ES-BC 中表现出明显更高的水平(P<.05)。单个 AAb 和 5-AAbs 面板的灵敏度分别为 20.41%-28.57%和 38.78%,特异性均超过 90%和 85.94%。同时,除抗-GARS 外,4 种 AAbs 在 TN 和非-TN 亚型之间存在显著差异(P<.05)。我们基于 AAbs 构建了 3 个随机森林分类器模型,用于将 ES-BC 与对照或 BBD 区分开,并辨别 TN 亚型,其曲线下面积分别为 0.870、0.860 和 0.875。生物相互作用分析显示,除 KJ901215 外,4 个 TAAs 与 BC 的已知蛋白相关。本研究发现并逐步验证了 5 种具有诊断 ES-BC 和辨别 TN 亚型潜力的新型 AAbs,表明在活检之前进行血清 AAbs 检测具有易于检测和微创的诊断价值,为未来的应用提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f47/8819333/33a029b7fcb1/CAS-113-770-g004.jpg

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