Department of Chemistry, University of Kansas, Lawrence, Kansas.
Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana.
Cancer Res Commun. 2024 Jan 31;4(1):253-263. doi: 10.1158/2767-9764.CRC-23-0327.
The biomarker CA125, a peptide epitope located in several tandem repeats of the mucin MUC16, is the gold standard for monitoring regression and recurrence of high-grade serous ovarian cancer in response to therapy. However, the CA125 epitope along with several structural features of the MUC16 molecule are ill defined. One central aspect still unresolved is the number of tandem repeats in MUC16 and how many of these repeats contain the CA125 epitope. Studies from the early 2000s assembled short DNA reads to estimate that MUC16 contained 63 repeats.Here, we conduct Nanopore long-read sequencing of MUC16 transcripts from three primary ovarian tumors and established cell lines (OVCAR3, OVCAR5, and Kuramochi) for a more exhaustive and accurate estimation and sequencing of the MUC16 tandem repeats.The consensus sequence derived from these six sources was confirmed by proteomics validation and agrees with recent additions to the NCBI database. We propose a model of MUC16 containing 19-not 63-tandem repeats. In addition, we predict the structure of the tandem repeat domain using the deep learning algorithm, AlphaFold.The predicted structure displays an SEA domain and unstructured linker region rich in proline, serine, and threonine residues in all 19 tandem repeats. These studies now pave the way for a detailed characterization of the CA125 epitope. Sequencing and modeling of the MUC16 tandem repeats along with their glycoproteomic characterization, currently underway in our laboratories, will help identify novel epitopes in the MUC16 molecule that improve on the sensitivity and clinical utility of the current CA125 assay.
Despite its crucial role in clinical management of ovarian cancer, the exact molecular sequence and structure of the biomarker, CA125, are not defined. Here, we combine long-read sequencing, mass spectrometry, and in silico modeling to provide the foundational dataset for a more complete characterization of the CA125 epitope.
生物标志物 CA125 是位于黏蛋白 MUC16 的几个串联重复中的肽表位,是监测高级别浆液性卵巢癌对治疗的反应性消退和复发的金标准。然而,CA125 表位以及 MUC16 分子的几个结构特征尚不清楚。一个尚未解决的核心问题是 MUC16 中的串联重复数以及这些重复中有多少包含 CA125 表位。21 世纪初的研究组装了短 DNA 读段来估计 MUC16 包含 63 个重复。在这里,我们对来自三个原发性卵巢肿瘤和建立的细胞系(OVCAR3、OVCAR5 和 Kuramochi)的 MUC16 转录本进行了 Nanopore 长读测序,以便更全面和准确地估计和测序 MUC16 串联重复。从这六个来源推导的共识序列通过蛋白质组学验证得到了证实,并与 NCBI 数据库的最新补充内容一致。我们提出了一个包含 19 个而不是 63 个串联重复的 MUC16 模型。此外,我们使用深度学习算法 AlphaFold 预测了串联重复结构域的结构。预测的结构在所有 19 个串联重复中显示了 SEA 结构域和富含脯氨酸、丝氨酸和苏氨酸残基的无结构连接区。这些研究为 CA125 表位的详细特征描述铺平了道路。我们实验室目前正在进行 MUC16 串联重复的测序和建模以及它们的糖基蛋白组学特征分析,这将有助于识别 MUC16 分子中的新型表位,从而提高当前 CA125 检测的敏感性和临床实用性。
尽管 CA125 在卵巢癌的临床管理中起着至关重要的作用,但生物标志物 CA125 的确切分子序列和结构尚不清楚。在这里,我们结合长读测序、质谱和计算机建模,为更完整地描述 CA125 表位提供了基础数据集。