Over the past decade, extracellular vesicles (EVs) have emerged as a promising source of cancer-derived RNAs for liquid biopsies. However, blood contains a pool of heterogeneous EVs released by a variety of cell types, making the identification of cancer RNA biomarkers challenging. Here, we performed deep sequencing of plasma EV RNA cargo in 32 patients with locally advanced breast cancer (BC) at diagnosis and 7 days after breast surgery and in 30 cancer-free healthy controls (HCs). To identify BC-derived RNA biomarkers, we searched for RNAs that had higher levels in BC EVs at the time of diagnosis compared with HCs and decreased after surgery. Data analysis showed that the fractions of miRNAs, snRNAs, snoRNAs, and tRFs were increased, but the fraction of lncRNAs was decreased in BC EVs as compared to HCs. BC-derived biomarker candidates were identified across various RNA biotypes. Considered individually, they had very high specificity but moderate sensitivity for the detection of BC, whereas a biomarker model composed of eight RNAs: SNORD3H, SNORD1C, SNORA74D, miR-224-5p, piR-32949, lnc-IFT-122-2, lnc-C9orf50-4, and lnc-FAM122C-3 was able to distinguish BC from HC EVs with an AUC of 0.902 (95% CI = 0.872–0.931,p= 3.4 × 10−9) in leave-one-out cross-validation. Furthermore, a number of RNA biomarkers were correlated with the ER and HER2 expression and additional biomarker models were created to predict hormone receptor and HER2 status. Overall, this study demonstrated that the RNA composition of plasma EVs is altered in BC patients and that they contain cancer-derived RNA biomarkers that can be used for BC detection and monitoring using liquid biopsies.
过去十年间，细胞外囊泡已成为液体活检中癌症来源RNA的重要来源。然而，血液中存在多种细胞释放的异质性囊泡群体，使得癌症RNA生物标志物的鉴定面临挑战。本研究对32例局部晚期乳腺癌患者（诊断时及术后7天）和30例无癌健康对照者的血浆细胞外囊泡RNA进行深度测序。为识别乳腺癌来源的RNA生物标志物，我们筛选在诊断时乳腺癌患者囊泡中表达水平高于健康对照、且术后表达下降的RNA分子。数据分析显示，与健康对照相比，乳腺癌患者囊泡中miRNA、snRNA、snoRNA和tRF的比例升高，而lncRNA比例降低。在不同RNA生物型中均鉴定出潜在的乳腺癌来源生物标志物。单个标志物对乳腺癌检测具有极高特异性但敏感性中等，而由八种RNA（SNORD3H、SNORD1C、SNORA74D、miR-224-5p、piR-32949、lnc-IFT-122-2、lnc-C9orf50-4和lnc-FAM122C-3）构建的生物标志物模型，在留一法交叉验证中能有效区分乳腺癌与健康对照囊泡（AUC=0.902，95% CI=0.872–0.931，p=3.4×10−9）。此外，部分RNA生物标志物与ER、HER2表达水平相关，并构建了预测激素受体和HER2状态的生物标志物模型。本研究证实乳腺癌患者血浆细胞外囊泡的RNA组成发生改变，其中包含的癌症来源RNA生物标志物可用于液体活检中的乳腺癌检测与监测。
肿瘤(癌症)患者之家