去泛素化酶OTUD1通过去稳定RAD23B/XPC调控非小细胞肺癌顺铂化疗敏感性

数据集获取

源站：https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE295626

标准获取流程：

1. 访问源站链接，注册/登录账号；
2. 进入数据集详情页，按页面指引申请权限或直接下载；
3. 部分平台提供 SDK，例如：
   • OpenDataLab: pip install openxlab 后 openxlab.dataset.get(...)
   • ModelScope: pip install modelscope 后 modelscope download
   • 天池: 登录后页面提供直链下载
     以源站「数据下载/使用文档」页面为准。

数据说明

Lung cancer, especially the subgroup non-small cell lung cancer (NSCLC), continues to be one of the most commonly diagnosed cancers and the leading cause of cancer-related deaths worldwide. Cisplatin has long been a cornerstone of chemotherapy and has improved the prognosis for NSCLC patients. However, its overall efficacy remains unsatisfactory, and patients ultimately develop drug resistance. Uncovering the underlying mechanism and identifying potential target to enhance cisplatin chemosensitivity is urgent. In this study, we uncovered that OTU deubiquitinase 1 (OTUD1) plays an important role in orchestrating cisplatin chemosensitivity of NSCLC. We found that promoter methylation resulted in downregulation of OTUD1 and the downregulated OTUD1 significantly associates with cisplatin resistance and poor prognosis in NSCLC. Overexpression of OTUD1 enhances cisplatin sensitivity in vitro and in vivo. Mechanistically, OTUD1 promoted the degradation of RAD23B-XPC complex, which is the critical factor for nucleotide excision repair to remove cisplatin-induced DNA adducts, leading to cisplatin-induced cell death. OTUD1 cleaves the K63-linked ubiquitin chain of RAD23B and XPC, and enhances PRKN mediated K48-linked ubiquitination of RAD23B-XPC and the subsequent proteasomal degradation. The findings of this study highlighted that OTUD1 could be a potential therapeutic target for NSCLC.

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。