Classifying patients for breast cancer by detection of autoantibodies against a panel of conformation-carrying antigens.
Classifying patients for breast cancer by detection of autoantibodies against a panel of conformation-carrying antigens.
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DOI：
10.1158/1940-6207.capr-13-0416
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发表时间：
2014-05
期刊：
影响因子：
--
通讯作者：
Egland KA
中科院分区：
文献类型：
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作者：
Evans RL;Pottala JV;Egland KA
乳腺癌（BCa）患者会引发针对癌蛋白的自身抗体反应，这反映并放大了与肿瘤发生相关的细胞变化。检测血浆中的自身抗体可以为早期检测BCa提供微创机制。为了鉴定引起体液应答的癌症蛋白，我们产生了富含编码膜和分泌蛋白的BCa基因的cDNA文库，与细胞内蛋白相比，所述膜和分泌蛋白更可能诱导抗体应答。为了产生被患者抗体有效识别的携带构象的抗原，建立了真核表达策略。使用ELISA测量来自200名BCa患者和200名年龄匹配的健康对照的血浆针对设计为具有构象表位的20种不同抗原的自身抗体活性。使用条件逻辑回归模型来选择针对20种不同抗原的自身抗体应答的组合，以将BCa患者与健康对照分类。最佳组合包括ANGPTL 4、DKK 1、GAL 1、MUC 1、GFRA 1、GRN和LRRC 15;然而，针对GFRA 1、GRN和LRRC 15的自身抗体应答与BCa呈负相关。当将针对7种抗原的自身抗体应答添加到基础模型中时，包括年龄、BMI、种族和当前吸烟状态，该测定具有以下诊断能力：c-stat（95% CI），0.82（0.78至0.86）;灵敏度，73%;特异性，76%; PLR（95% CI），3.04（2.34至3.94）。该模型在风险十分位数之间进行校准（Hosmer-Lemeshow，p = 0.13），并且在BCa的特定亚型中表现良好，包括雌激素受体阳性、HER-2阳性、侵袭性、原位和肿瘤大小>1 cm。
Breast cancer (BCa) patients elicit an autoantibody response against cancer proteins, which reflects and amplifies the cellular changes associated with tumorigenesis. Detection of autoantibodies in plasma may provide a minimally invasive mechanism for early detection of BCa. To identify cancer proteins that elicit a humoral response, we generated a cDNA library enriched for BCa genes that encode membrane and secreted proteins, which are more likely to induce an antibody response compared to intracellular proteins. To generate conformation-carrying antigens that are efficiently recognized by patients’ antibodies, a eukaryotic expression strategy was established. Plasma from 200 BCa patients and 200 age-matched healthy controls were measured for autoantibody activity against 20 different antigens designed to have conformational epitopes using ELISA. A conditional logistic regression model was used to select a combination of autoantibody responses against the 20 different antigens to classify BCa patients from healthy controls. The best combination included ANGPTL4, DKK1, GAL1, MUC1, GFRA1, GRN and LRRC15; however, autoantibody responses against GFRA1, GRN and LRRC15 were inversely correlated with BCa. When the autoantibody responses against the 7 antigens were added to the base model, including age, BMI, race and current smoking status, the assay had the following diagnostic capabilities: c-stat (95% CI), 0.82 (0.78 to 0.86); sensitivity, 73%; specificity, 76%; and PLR (95% CI), 3.04 (2.34 to 3.94). The model was calibrated across risk deciles (Hosmer-Lemeshow, p = 0.13) and performed well in specific subtypes of BCa including estrogen receptor positive, HER-2 positive, invasive, in situ and tumor sizes >1 cm.