基于结构的激酶突变临床NGS解读工具数据表

数据集获取（Figshare）

• 源站标题：Data Sheet 2_A structure-based tool to interpret the significance of kinase mutations in clinical next generation sequencing in cancer.pdf
• DOI：10.3389/fonc.2025.1599389.s001
• 发布日期：2025-08-04
• 文件数：1 个
• 文件总体积：62.83 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_2_A_structure-based_tool_to_interpret_the_significance_of_kinase_mutations_in_clinical_next_generation_sequencing_in_cancer_pdf/29818073

命令行下载

curl -L -o "Data Sheet 2_A structure-based tool to interpret the significance of kinase mutations in clinical next generation sequencing in cancer.pdf" "https://ndownloader.figshare.com/files/56878340"

文件清单

• Data Sheet 2_A structure-based tool to interpret the significance of kinase mutations in clinical next generation sequencing in cancer.pdf（62.83 KB）

文件总体积 62.83 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

IntroductionClinical workflows to analyze variants of unknown significance (VUSs) found in clinical next generation sequencing (NGS) are labor intensive, requiring manual analysis of published data for each variant. There is a strong need for tools and resources that provide a consistent way to analyze variants. With the explosion of clinical NGS data and the concurrent availability of protein structures through the Protein Data Bank and protein models through programs such as AlphaFold, there exists an unprecedented opportunity to use structural information to help standardize NGS analysis with the overall goal of advancing personalized cancer therapy.
MethodsUsing the Catalogue of Somatic Mutations in Cancer (COSMIC), the largest curated database of clinical cancer mutations, we mapped thousands of missense mutations in the kinase and juxtamembrane (JM) domains of 48 receptor tyrosine kinases (RTKs) onto structurally aligned kinase structures, then clustered known activating mutations along with VUSs based on proximity in three-dimensional structure. Using cell-based models we demonstrate that our resource can be used to aid in identification of activating mutations while providing insight into mechanisms of kinase activation and regulation.
ResultsWe provide a database of structurally aligned and functionally annotated mutations that can be used as a tool to evaluate kinase VUSs based on their structural alignment with known activating mutations. The tool can be accessed through a user-friendly website in which one can input a kinase mutation of interest, and the system will output a list of structurally analogous mutations in other kinases, as well as their functional annotations.
DiscussionThough our tool is not expected to be used as an isolated source for variant functional prediction, we expect our database will be a valuable addition to the current tools and resources used to analyze clinical NGS, with important clinical implications to guide recommendations for personalized cancer therapy.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fonc.2025.1599389.s001（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_2_A_structure-based_tool_to_interpret_the_significance_of_kinase_mutations_in_clinical_next_generation_sequencing_in_cancer_pdf/29818073）。