肺表面活性蛋白D通过降低IL-4/STAT6信号减少肺癌进展

数据集获取

源站：https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE249805

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

Pulmonary surfactant protein D (SP-D) is an endogenous innate immune factor known to be involved in several immune related diseases and has also been linked to lung adenocarcinoma cell growth. By analyzing single-cell, bulk, and spatial transcriptomics of human clinical samples, we have demonstrated significantly reduced expression in lung cancer cells compared to healthy cells, along with a distinct localization of SP-D expression in stromal areas adjacent to the tumor cells and at the periphery. Interestingly, a near-complete loss of SP-D expression was observed in metastatic tissue, suggesting its association with a more aggressive and metastatic phenotype. In this context, we show that SP-D re-expression in A549 adenocarcinoma cell line significantly decreased tumor growth and spontaneous metastasis formation in vivo and furthermore, that intranasal administration of recombinant SP-D signicantly reduced lung tumor burden. Mechanistically, we demonstrated that SP-D supresses interleukin 4 (IL4)/IL13 signaling pathways. Intriguingly, our data revealed that recombinant SP-D binds directly to the IL4 receptor, leading to the effective inhibition of the IL4 signaling pathway. Collectively, these findings demonstrate that SP-D acts as a tumor supressor inhibiting both tumor growth and metastatic progression potentially through blokage of the IL4/STAT6 signaling pathway. This provides a rationale of SP-D as a promising therapeutic agent for modulating crucial signaling pathways involved in cancer development and progression.

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。