人类癌症中HGF/MET通路异常的诊断、预后和预测生物标志物

数据集获取（Figshare）

• 源站标题：HGF/MET pathway aberrations as diagnostic, prognostic, and predictive biomarkers in human cancers
• DOI：10.6084/m9.figshare.9810677.v1
• 发布日期：2019-09-12
• 文件数：3 个
• 文件总体积：226.04 KB
• 源站页面：https://tandf.figshare.com/articles/dataset/HGF_MET_pathway_aberrations_as_diagnostic_prognostic_and_predictive_biomarkers_in_human_cancers/9810677

命令行下载

curl -L -o "ilab_a_1653821_sm2106.jpg" "https://ndownloader.figshare.com/files/17602583"
curl -L -o "ilab_a_1653821_sm2105.jpg" "https://ndownloader.figshare.com/files/17602586"
curl -L -o "ilab_a_1653821_sm2104.docx" "https://ndownloader.figshare.com/files/17602589"

文件清单

• ilab_a_1653821_sm2106.jpg（82.68 KB）
• ilab_a_1653821_sm2105.jpg（104.19 KB）
• ilab_a_1653821_sm2104.docx（39.17 KB）

文件总体积 226.04 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

Cancer is a major cause of death worldwide. MET tyrosine kinase receptor [MET, c-MET, hepatocyte growth factor (HGF) receptor] pathway activation is associated with the appearance of several hallmarks of cancer. The HGF/MET pathway has emerged as an important actionable target across many solid tumors; therefore, biomarker discovery becomes essential in order to guide clinical intervention and patient stratification with the aim of moving towards personalized medicine. The focus of this review is on how the aberrant activation of the HGF/MET pathway in tumor tissue or the circulation can provide diagnostic and prognostic biomarkers and predictive biomarkers of drug response. Many meta-analyses have shown that aberrant activation of the MET pathway in tumor tissue, including MET gene overexpression, gene amplification, exon 14 skipping and other activating mutations, is almost invariably associated with shorter survival and poor prognosis. Most meta-analyses have been performed in non-small cell lung cancer (NSCLC), breast, head and neck cancers as well as colorectal, gastric, pancreatic and other gastrointestinal cancers. Furthermore, several studies have shown the predictive value of MET biomarkers in the identification of patients who gain the most benefit from HGF/MET targeted therapies administered as single or combination therapies. The highest predictive values have been observed for response to foretinib and savolitinib in renal cancer, as well as tivantinib in NSCLC and colorectal cancer. However, some studies, especially those based on MET expression, have failed to show much value in these stratifications. This may be rooted in lack of standardization of methodologies, in particular in scoring systems applied in immunohistochemistry determinations or absence of oncogenic addiction of cancer cells to the MET pathway, despite detection of overexpression. Measurements of amplification and mutation aberrations are less likely to suffer from these pitfalls. Increased levels of MET soluble ectodomain (sMET) in circulation have also been associated with poor prognosis; however, the evidence is not as strong as it is with tissue-based biomarkers. As a diagnost

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.9810677.v1（source: https://tandf.figshare.com/articles/dataset/HGF_MET_pathway_aberrations_as_diagnostic_prognostic_and_predictive_biomarkers_in_human_cancers/9810677）。