Novel visualized quantitative epigenetic imprinted gene biomarkers diagnose the malignancy of ten cancer types
Novel visualized quantitative epigenetic imprinted gene biomarkers diagnose the malignancy of ten cancer types
复制标题
新型可视化定量表观遗传印迹基因生物标志物诊断十种癌症类型的恶性程度
DOI：
10.1186/s13148-020-00861-1
复制
发表时间：
2020-05-24
影响因子：
5.7
通讯作者：
Bai, Chunxue
中科院分区：
文献类型：
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作者：
Shen, Rulong;Cheng, Tong;Bai, Chunxue
背景表观遗传改变涉及大多数癌症，但其在癌症诊断中的应用仍然有限。需要更实用和直观的方法来使用高度敏感的生物标志物检测临床样本中的异常表达。在这项研究中，我们开发了一种新方法来识别、可视化和量化与癌症状态相关的印记基因组的双等位基因和多等位基因表达。我们评估了使用印迹基因组测量的正常和异常表达，以制定诊断模型，该模型可以准确地区分十种癌症类型中每种癌组织的正常和良性病例的印迹差异。结果定量显色印迹基因原位杂交（QCIGISH）方法是根据 1013 个病例研究开发的，该方法提供非编码 RNA 等位基因表达的可视化和定量分析，识别出鸟嘌呤核苷酸结合蛋白，五个测试的印记基因中的α刺激复合基因座（GNAS）、生长因子受体结合蛋白（GRB10）和小核核糖核蛋白多肽N（SNRPN）作为有效的表观遗传生物标志物，用于十种癌症类型的早期检测。为癌症诊断开发的二元算法表明，印迹基因组的双等位基因表达 (BAE)、多等位基因表达 (MAE) 和总表达 (TE) 测量值升高与细胞癌变相关，制定的诊断模型在不同癌症类型中实现了一致的高灵敏度 (91–98%) 和特异性 (86–98%)。结论 QCIGISH 方法提供了一种创新的方法来直观评估和定量分析单个细胞的癌症潜在扩展从增生、不典型增生直至原位癌和侵袭，有效补充了早期癌症检测的标准临床细胞学和组织病理学诊断。此外，根据印迹基因组 GNAS、GRB10 和 SNRPN 的 BAE、MAE 和 TE 测量开发的诊断模型可以提供重要的预测信息，可用于早期癌症检测和个性化癌症管理。
BackgroundEpigenetic alterations are involved in most cancers, but its application in cancer diagnosis is still limited. More practical and intuitive methods to detect the aberrant expressions from clinical samples using highly sensitive biomarkers are needed. In this study, we developed a novel approach in identifying, visualizing, and quantifying the biallelic and multiallelic expressions of an imprinted gene panel associated with cancer status. We evaluated the normal and aberrant expressions measured using the imprinted gene panel to formulate diagnostic models which could accurately distinguish the imprinting differences of normal and benign cases from cancerous tissues for each of the ten cancer types.ResultsThe Quantitative Chromogenic Imprinted Gene In Situ Hybridization (QCIGISH) method developed from a 1013-case study which provides a visual and quantitative analysis of non-coding RNA allelic expressions identified the guanine nucleotide-binding protein, alpha-stimulating complex locus (GNAS), growth factor receptor-bound protein (GRB10), and small nuclear ribonucleoprotein polypeptide N (SNRPN) out of five tested imprinted genes as efficient epigenetic biomarkers for the early-stage detection of ten cancer types. A binary algorithm developed for cancer diagnosis showed that elevated biallelic expression (BAE), multiallelic expression (MAE), and total expression (TE) measurements for the imprinted gene panel were associated with cell carcinogenesis, with the formulated diagnostic models achieving consistently high sensitivities (91–98%) and specificities (86–98%) across the different cancer types.ConclusionsThe QCIGISH method provides an innovative way to visually assess and quantitatively analyze individual cells for cancer potential extending from hyperplasia and dysplasia until carcinoma in situ and invasion, which effectively supplements standard clinical cytologic and histopathologic diagnosis for early cancer detection. In addition, the diagnostic models developed from the BAE, MAE, and TE measurements of the imprinted gene panelGNAS,GRB10, andSNRPNcould provide important predictive information which are useful in early-stage cancer detection and personalized cancer management.