表2：基于细胞衰老相关基因的肝细胞癌预后及治疗分层模型数据

数据集获取（Figshare）

• 源站标题：Table2_A cellular senescence-related genes model allows for prognosis and treatment stratification of hepatocellular carcinoma: A bioinformatics analysis and experimental verification.XLS
• DOI：10.3389/fgene.2022.1099148.s002
• 发布日期：2023-01-12
• 文件数：1 个
• 文件总体积：28.16 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table2_A_cellular_senescence-related_genes_model_allows_for_prognosis_and_treatment_stratification_of_hepatocellular_carcinoma_A_bioinformatics_analysis_and_experimental_verification_XLS/21875928

命令行下载

curl -L -o "Table2_A cellular senescence-related genes model allows for prognosis and treatment stratification of hepatocellular carcinoma: A bioinformatics analy.XLS" "https://ndownloader.figshare.com/files/38810343"

文件清单

• Table2_A cellular senescence-related genes model allows for prognosis and treatment stratification of hepatocellular carcinoma: A bioinformatics analy.XLS（28.16 KB）

文件总体积 28.16 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

Introduction: Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with low 5-year survival rate. Cellular senescence, characterized by permanent and irreversible cell proliferation arrest, plays an important role in tumorigenesis and development. This study aims to develop a cellular senescence-based stratified model, and a multivariable-based nomogram for guiding clinical therapy for HCC.
Materials and methods: The mRNAs expression data of HCC patients and cellular senescence-related genes were obtained from TCGA and CellAge database, respectively. Through multiple analysis, a four cellular senescence-related genes-based prognostic stratified model was constructed and its predictive performance was validated through various methods. Then, a nomogram based on the model was constructed and HCC patients stratified by the model were analyzed for tumor mutation burden, tumor microenvironment, immune infiltration, drug sensitivity and immune checkpoint. Functional enrichment analysis was performed to explore potential biological pathways. Finally, we verified this model by siRNA transfection, scratch assay and Transwell Assay.
Results: We established an cellular senescence-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of HCC patients in the ICGC database. The low and high risk score HCC patients stratified by the model showed different tumor mutation burden, tumor microenvironment, immune infiltration, drug sensitivity and immune checkpoint expressions. Functional enrichment analysis suggested several biological pathways related to the process and prognosis of HCC. Scratch assay and transwell assay indicated the promotion effects of the four cellular senescence-related genes (EZH2, G6PD, CBX8, and NDRG1) on the migraiton and invasion of HCC.
Conclusion: We established a cellular senescence-based stratified model, and a multivariable-based nomogram, which could predict the survival of HCC patients and guide clinical treatment.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fgene.2022.1099148.s002（source: https://frontiersin.figshare.com/articles/dataset/Table2_A_cellular_senescence-related_genes_model_allows_for_prognosis_and_treatment_stratification_of_hepatocellular_carcinoma_A_bioinformatics_analysis_and_experimental_verification_XLS/21875928）。