GSE274809：Caspase 8缺失驱动神经元祖细胞样重编程与小细胞肺癌进展

数据集获取

源站：https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274809

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

Mimicry of neuronal features is emerging as malignant regulator of cancer growth and metastasis. Neuroendocrine (NE) cancers including small cell lung cancers (SCLC) have been shown to share expression profiles marking various stages of neuronal differentiation. Yet, how these state changes are caused and malignant consequences thereof have remained unexplored.Here, we devise a novel mouse model of SCLC recapitulating low expression of caspase 8 as seen in humans and uncover that this allows for epigenetic reprogramming towards a more aggressive and metastasising stem-cell like neuronal state, resembling neuronal intermediate progenitor cells (nIPCs). Notably, transcriptional signatures of this cellular state are enriched in relapsed and metastatic human SCLC. Mechanistically, caspase 8 loss within the pre-tumoral niche promoted immunosuppression and metastasis via induction of immunogenic cell death. Inactivation of the necroptosis executioner Mixed lineage kinase domain-like protein (MLKL) neutralised caspase 8 loss-induced immunosuppression, metastasis and diminished the stem-cell like state providing genetic evidence for a role of necroptosis in promoting these effects. Collectively our data uncover an unexpected role for low expression of caspase 8 in directing neuronal-like reprogramming towards an immunosuppressive and highly metastatic state in SCLC.

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。