乳腺癌糖代谢相关基因特征数据集

数据集获取（Figshare）

• 源站标题：Table 3_v1_Characterization of glucose metabolism in breast cancer to guide clinical therapy.xls
• DOI：10.3389/fsurg.2022.973410.s004
• 发布日期：2022-09-19
• 文件数：1 个
• 文件总体积：2.49 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_3_v1_Characterization_of_glucose_metabolism_in_breast_cancer_to_guide_clinical_therapy_xls/21153943

命令行下载

curl -L -o "Table 3_v1_Characterization of glucose metabolism in breast cancer to guide clinical therapy.xls" "https://ndownloader.figshare.com/files/37509529"

文件清单

• Table 3_v1_Characterization of glucose metabolism in breast cancer to guide clinical therapy.xls（2.49 KB）

文件总体积 2.49 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

BackgroundBreast cancer (BRCA) ranks as a leading cause of cancer death in women worldwide. Glucose metabolism is a noticeable characteristic of the occurrence of malignant tumors. In this study, we aimed to construct a novel glycometabolism-related gene (GRG) signature to predict overall survival (OS), immune infiltration and therapeutic response in BRCA patients.
Materials and methodsThe mRNA sequencing and corresponding clinical data of BRCA patients were obtained from public cohorts. Lasso regression was applied to establish a GRG signature. The immune infiltration was evaluated with the ESTIMATE and CIBERSORT algorithms. The drug sensitivity was estimated using the value of IC50, and further forecasted the therapeutic response of each patient. The candidate target was selected in Cytoscape. A nomogram was constructed via the R package of “rms”.
ResultsWe constructed a six-GRG signature based on CACNA1H, CHPF, IRS2, NT5E, SDC1 and ATP6AP1, and the high-risk patients were correlated with poorer OS (P = 2.515 × 10−7). M2 macrophage infiltration was considerably superior in high-risk patients, and CD8+ T cell infiltration was significantly higher in low-risk patients. Additionally, the high-risk group was more sensitive to Lapatinib. Fortunately, SDC1 was recognized as candidate target and patients had a better OS in the low-SDC1 group. A nomogram integrating the GRG signature was developed, and calibration curves were consistent between the actual and predicted OS.
ConclusionsWe identified a novel GRG signature complementing the present understanding of the targeted therapy and immune biomarker in breast cancer. The GRGs may provide fresh insights for individualized management of BRCA patients.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fsurg.2022.973410.s004（source: https://frontiersin.figshare.com/articles/dataset/Table_3_v1_Characterization_of_glucose_metabolism_in_breast_cancer_to_guide_clinical_therapy_xls/21153943）。