表皮生长因子受体酪氨酸激酶定义I期肺腺癌关键预后基因

数据集获取（Figshare）

• 源站标题：Epidermal Growth Factor Receptor Tyrosine Kinase Defines Critical Prognostic Genes of Stage I Lung Adenocarcinoma
• DOI：10.1371/journal.pone.0043923
• 发布日期：2012-09-19
• 文件数：14 个
• 文件总体积：8.42 MB
• 源站页面：https://plos.figshare.com/articles/dataset/Epidermal_Growth_Factor_Receptor_Tyrosine_Kinase_Defines_Critical_Prognostic_Genes_of_Stage_I_Lung_Adenocarcinoma/120206

命令行下载

curl -L -o "Figure_S1.jpeg" "https://ndownloader.figshare.com/files/305218"
curl -L -o "Figure_S2.jpeg" "https://ndownloader.figshare.com/files/305352"
curl -L -o "Figure_S3.jpeg" "https://ndownloader.figshare.com/files/305480"
curl -L -o "Figure_S4.jpeg" "https://ndownloader.figshare.com/files/305653"
curl -L -o "Figure_S5.jpeg" "https://ndownloader.figshare.com/files/305800"
curl -L -o "Figure_S6.jpeg" "https://ndownloader.figshare.com/files/305972"
curl -L -o "Table_S1.xls" "https://ndownloader.figshare.com/files/306102"
curl -L -o "Table_S2.xls" "https://ndownloader.figshare.com/files/306123"

文件清单

• Figure_S1.jpeg（1.06 MB）
• Figure_S2.jpeg（2.47 MB）
• Figure_S3.jpeg（924.08 KB）
• Figure_S4.jpeg（740.40 KB）
• Figure_S5.jpeg（1.46 MB）
• Figure_S6.jpeg（1.11 MB）
• Table_S1.xls（197.12 KB）
• Table_S2.xls（32.77 KB）
• Table_S3.xls（56.83 KB）
• Table_S4.xls（27.65 KB）
• Table_S5.xls（25.09 KB）
• Table_S6.txt（11.40 KB）
• Table_S7.xls（30.72 KB）
• Information_S1.doc（269.31 KB）

文件总体积 8.42 MB（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

Purpose
To identify stage I lung adenocarcinoma patients with a poor prognosis who will benefit from adjuvant therapy.
Patients and Methods
Whole gene expression profiles were obtained at 19 time points over a 48-hour time course from human primary lung epithelial cells that were stimulated with epidermal growth factor (EGF) in the presence or absence of a clinically used EGF receptor tyrosine kinase (RTK)-specific inhibitor, gefitinib. The data were subjected to a mathematical simulation using the State Space Model (SSM). “Gefitinib-sensitive” genes, the expressional dynamics of which were altered by addition of gefitinib, were identified. A risk scoring model was constructed to classify high- or low-risk patients based on expression signatures of 139 gefitinib-sensitive genes in lung cancer using a training data set of 253 lung adenocarcinomas of North American cohort. The predictive ability of the risk scoring model was examined in independent cohorts of surgical specimens of lung cancer.
Results
The risk scoring model enabled the identification of high-risk stage IA and IB cases in another North American cohort for overall survival (OS) with a hazard ratio (HR) of 7.16 (P = 0.029) and 3.26 (P = 0.0072), respectively. It also enabled the identification of high-risk stage I cases without bronchioalveolar carcinoma (BAC) histology in a Japanese cohort for OS and recurrence-free survival (RFS) with HRs of 8.79 (P = 0.001) and 3.72 (P = 0.0049), respectively.
Conclusion
The set of 139 gefitinib-sensitive genes includes many genes known to be involved in biological aspects of cancer phenotypes, but not known to be involved in EGF signaling. The present result strongly re-emphasizes that EGF signaling status in cancer cells underlies an aggressive phenotype of cancer cells, which is useful for the selection of early-stage lung adenocarcinoma patients with a poor prognosis.
Trial Registration
The Gene Expression Omnibus (GEO) GSE31210

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0043923（source: https://plos.figshare.com/articles/dataset/Epidermal_Growth_Factor_Receptor_Tyrosine_Kinase_Defines_Critical_Prognostic_Genes_of_Stage_I_Lung_Adenocarcinoma/120206）。