表15_临床嗜酸性粒细胞相关基因可作为膀胱尿路上皮癌的可靠预测因子.DOC

数据集获取（Figshare）

• 源站标题：Table15_Clinical Eosinophil-Associated Genes can Serve as a Reliable Predictor of Bladder Urothelial Cancer.DOC
• DOI：10.3389/fmolb.2022.963455.s007
• 发布日期：2022-07-22
• 文件数：1 个
• 文件总体积：3.03 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table15_Clinical_Eosinophil-Associated_Genes_can_Serve_as_a_Reliable_Predictor_of_Bladder_Urothelial_Cancer_DOC/20355039

命令行下载

curl -L -o "Table15_Clinical Eosinophil-Associated Genes can Serve as a Reliable Predictor of Bladder Urothelial Cancer.DOC" "https://ndownloader.figshare.com/files/36384942"

文件清单

• Table15_Clinical Eosinophil-Associated Genes can Serve as a Reliable Predictor of Bladder Urothelial Cancer.DOC（3.03 KB）

文件总体积 3.03 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

Background: Numerous studies have shown that infiltrating eosinophils play a key role in the tumor progression of bladder urothelial carcinoma (BLCA). However, the roles of eosinophils and associated hub genes in clinical outcomes and immunotherapy are not well known.
Methods: BLCA patient data were extracted from the TCGA database. The tumor immune microenvironment (TIME) was revealed by the CIBERSORT algorithm. Candidate modules and hub genes associated with eosinophils were identified by weighted gene co-expression network analysis (WGCNA). The external GEO database was applied to validate the above results. TIME-related genes with prognostic significance were screened by univariate Cox regression analysis, lasso regression, and multivariate Cox regression analysis. The patient’s risk score (RS) was calculated and divided subjects into high-risk group (HRG) and low-risk group (LRG). The nomogram was developed based on the risk signature. Models were validated via receiver operating characteristic (ROC) curves and calibration curves. Differences between HRG and LRG in clinical features and tumor mutational burden (TMB) were compared. The Immune Phenomenon Score (IPS) was calculated to estimate the immunotherapeutic significance of RS. Half-maximal inhibitory concentrations (IC50s) of chemotherapeutic drugs were predicted by the pRRophetic algorithm.
Results: 313 eosinophil-related genes were identified by WGCNA. Subsequently, a risk signature containing 9 eosinophil-related genes (AGXT, B3GALT2, CCDC62, CLEC1B, CLEC2D, CYP19A1, DNM3, SLC5A9, SLC26A8) was finally developed via multiplex analysis and screening. Age (p Conclusions: In conclusion, the eosinophil-based RS can be used as a reliable clinical predictor and provide insights into the precise treatment of BLCA.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fmolb.2022.963455.s007（source: https://frontiersin.figshare.com/articles/dataset/Table15_Clinical_Eosinophil-Associated_Genes_can_Serve_as_a_Reliable_Predictor_of_Bladder_Urothelial_Cancer_DOC/20355039）。