HMPA：从发现到功能见解的非规范肽组的开创性框架
HMPA: a pioneering framework for the noncanonical peptidome from discovery to functional insights
影响因子:7.70000
分区:生物学2区 / 数学与计算生物学1区 生化研究方法2区
发表日期:2024 Sep 23
作者:
Xinwan Su, Chengyu Shi, Fangzhou Liu, Manman Tan, Ying Wang, Linyu Zhu, Yu Chen, Meng Yu, Xinyi Wang, Jian Liu, Yang Liu, Weiqiang Lin, Zhaoyuan Fang, Qiang Sun, Tianhua Zhou, Aifu Lin
摘要
肽组学的进步揭示了许多具有编码潜力的小型开放式阅读框架，并揭示了其中一些微肽与人类癌症密切相关。但是，从序列到结构和功能的系统分析和集成在很大程度上还没有开发。在这里，作为解决方案，我们构建了一个工作流，用于收集和分析蛋白质组学数据，转录组数据和临床结果，以使用大型同类群的公开可用数据集，以用于癌症相关的微肽。我们最初通过从8种癌症类型的3753个样品中重新分析蛋白质组学数据来鉴定了19个586新的微肽。对这些微肽的进一步定量分析以及相关的临床数据发现了3065例在癌症中失调的，其中370个与预后相关。此外，我们采用了一个深度学习框架来构建菌根 - 蛋白质相互作用网络进行进一步的生物信息学分析，并揭示了小肽与生物活性分子一起参与多种生物学过程。综上所述，我们的Atlas为对菌皮的高通量预测和功能探索提供了基准，从而为其在癌症中的生物学机制提供了新的见解。 HMPA可在http://hmpa.zju.edu.cn上免费获得。
Abstract
Advancements in peptidomics have revealed numerous small open reading frames with coding potential and revealed that some of these micropeptides are closely related to human cancer. However, the systematic analysis and integration from sequence to structure and function remains largely undeveloped. Here, as a solution, we built a workflow for the collection and analysis of proteomic data, transcriptomic data, and clinical outcomes for cancer-associated micropeptides using publicly available datasets from large cohorts. We initially identified 19 586 novel micropeptides by reanalyzing proteomic profile data from 3753 samples across 8 cancer types. Further quantitative analysis of these micropeptides, along with associated clinical data, identified 3065 that were dysregulated in cancer, with 370 of them showing a strong association with prognosis. Moreover, we employed a deep learning framework to construct a micropeptide-protein interaction network for further bioinformatics analysis, revealing that micropeptides are involved in multiple biological processes as bioactive molecules. Taken together, our atlas provides a benchmark for high-throughput prediction and functional exploration of micropeptides, providing new insights into their biological mechanisms in cancer. The HMPA is freely available at http://hmpa.zju.edu.cn.