RAS(ON)抑制剂双药联合解除致癌RAS信号使免疫难治性KRASG12C突变NSCLC对免疫检查点阻断敏感

数据集获取

源站：https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE315010

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

To address RAS pathway hyperactivation and targeted therapy resistance in KRASG12C-mutant NSCLC, we evaluated the potential of the RAS(ON) G12C-selective covalent inhibitor elironrasib and the RAS(ON) multi-selective inhibitor daraxonrasib combination to maximize RAS pathway suppression and forestall pathway reactivation in a series of preclinical models. We demonstrate that the RAS(ON) inhibitor doublet induces profound and sustained tumor regressions and overcomes the increased RAS pathway oncogenic flux that underlies resistance to inactive state–selective KRASG12C inhibitors in NSCLC. Additionally, in immune-competent preclinical models, the RAS(ON) inhibitor doublet enhances tumor immune recognition by boosting antigen presentation and remodeling the suppressive tumor microenvironment, thus promoting immune-dependent complete regressions and sensitization of an immuno-refractory model to checkpoint blockade. Collectively these findings provide a preclinical rationale for the evaluation of a targeted RAS(ON) inhibitor doublet therapy regimen in combination with immune checkpoint blockade in patients with KRASG12C-mutant 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。