生殖细胞肿瘤相关体细胞型恶性肿瘤突变负担、DNA甲基化景观及蛋白质组特征数据集
利用多组学方法分析生殖细胞肿瘤相关体细胞型恶性肿瘤的突变、甲基化和蛋白质组特征,探索组织起源、耐药机制及潜在靶点。

基本信息
资源简介
生殖细胞肿瘤相关体细胞型恶性肿瘤突变负担、DNA甲基化景观及蛋白质组特征数据集
【数据集背景】
本数据集源站标题为《Characterizing the mutational burden, DNA methylation landscape and proteome of germ cell tumor-related somatic-type malignancies to identify the tissue-of-origin, mechanisms of therapy resistance and druggable targets》。项目资助方:Wilhelm Sander Stiftung to F. B.。源站首次发布:2023-09-19。
【数据内容】
源站原始描述:Abstract Background: Germ cell tumors (GCT) might undergo transformation into a somatic-type malignancy (STM), resulting in a cell fate switch to tumors usually found in somatic tissues, such as rhabdomyosarcomas or adenocarcinomas. STM is associated with a poor prognosis, but the molecular and epigenetic mechanisms triggering STM are still enigmatic, the tissue-of-origin is under debate and biomarkers are lacking. Methods: To address these questions, we characterized a unique cohort of STM tiss…
【数据结构与技术规格】
文件数 11 个,合计 32.83 MB。数据集 DOI:10.6084/m9.figshare.24160911.v2。
【主题与分类】
源站学科分类:Cancer cell biology、Cancer diagnosis、Cancer genetics、Cancer therapy (excl. chemotherapy and radiation therapy)、Molecular targets、Predictive and prognostic markers。主题标签:Germ cell tumors、Testis cancer、Somatic-type malignancy、Yolk-sac tumor、Teratoma、Epigenetics、Molecular biology、Cancer、Tumor、Therapy。
【适用方向】
多模态数据适合跨模态对齐、融合建模与联合表征学习方向的研究。
【获取与许可】
源站页面:https://figshare.com/articles/dataset/Characterizing_the_mutational_burden_DNA_methylation_landscape_and_proteome_of_germ_cell_tumor-related_somatic-type_malignancies_to_identify_the_tissue-of-origin_mechanisms_of_therapy_resistance_and_druggable_targets/24160911
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Nettersheim, Daniel (2023). Characterizing the mutational burden, DNA methylation landscape and proteome of germ cell tumor-related somatic-type malignancies to identify the tissue-of-origin, mechanisms of therapy resistance and druggable targets. figshare. Dataset
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:Characterizing the mutational burden, DNA methylation landscape and proteome of germ cell tumor-related somatic-type malignancies to identify the tissue-of-origin, mechanisms of therapy resistance and druggable targets
- DOI:10.6084/m9.figshare.24160911.v2
- 发布日期:2023-09-19
- 文件数:11 个
- 文件总体积:32.83 MB
- 源站页面:https://figshare.com/articles/dataset/Characterizing_the_mutational_burden_DNA_methylation_landscape_and_proteome_of_germ_cell_tumor-related_somatic-type_malignancies_to_identify_the_tissue-of-origin_mechanisms_of_therapy_resistance_and_druggable_targets/24160911
命令行下载
curl -L -o "Characterizing the mutational burden, DNA methylation landscape, and proteome of germ cell tumor-related somatictype malignancies to identify the tissue-of-origin, mechanisms of therapy resistance, and druggable targets.pdf" "https://ndownloader.figshare.com/files/42392493"
curl -L -o "Fig. 1.tiff" "https://ndownloader.figshare.com/files/42392496"
curl -L -o "Fig. 2.tiff" "https://ndownloader.figshare.com/files/42392499"
curl -L -o "Fig. 3.tiff" "https://ndownloader.figshare.com/files/42392502"
curl -L -o "Fig. 4.tiff" "https://ndownloader.figshare.com/files/42392505"
curl -L -o "Fig. 5.tiff" "https://ndownloader.figshare.com/files/42392508"
curl -L -o "Fig. S1.tiff" "https://ndownloader.figshare.com/files/42392511"
curl -L -o "Fig. S2.tiff" "https://ndownloader.figshare.com/files/42392520"
文件清单
Characterizing the mutational burden, DNA methylation landscape, and proteome of germ cell tumor-related somatictype malignancies to identify the tissue-of-origin, mechanisms of therapy resistance, and druggable targets.pdf(2.40 MB)Fig. 1.tiff(6.21 MB)Fig. 2.tiff(2.67 MB)Fig. 3.tiff(2.16 MB)Fig. 4.tiff(2.27 MB)Fig. 5.tiff(733.39 KB)Fig. S1.tiff(5.66 MB)Fig. S2.tiff(1.21 MB)Fig. S3.tiff(6.30 MB)Fig. S4.tiff(3.19 MB)Table S1.xlsx(11.41 KB)
文件总体积 32.83 MB(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
Abstract
Background:
Germ cell tumors (GCT) might undergo transformation into a somatic-type malignancy (STM), resulting in a cell fate switch to tumors usually found in somatic tissues, such as rhabdomyosarcomas or adenocarcinomas. STM is associated with a poor prognosis, but the molecular and epigenetic mechanisms triggering STM are still enigmatic, the tissue-of-origin is under debate and biomarkers are lacking.
Methods:
To address these questions, we characterized a unique cohort of STM tissues on mutational, epigenetic and protein level using modern and high-throughput methods like TSO assays, 850k DNA methylation arrays and mass spectrometry.
Results and Conclusions:
For the first time, we show that based on DNA methylation and proteome data carcinoma-related STM more closely resemble yolk-sac tumors, while sarcoma-related STM resemble teratoma. STM harbor mutations in FGF signaling factors (FGF6/23, FGFR1/4)highlighting the corresponding pathway as a therapeutic target. Furthermore, STM utilize signaling pathways, like AKT, FGF, MAPK, and WNT to mediate molecular functions coping with oxidative stress, toxin transport, DNA helicase activity, apoptosis and the cell cycle. Collectively, these data might explain the high therapy resistance of STM. Finally, we identified putative novel biomarkers secreted by STM, like EFEMP1, MIF, and DNA methylation at specific CpG dinucleotides.
https://www.nature.com/articles/s41416-023-02425-5
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.6084/m9.figshare.24160911.v2(source: https://figshare.com/articles/dataset/Characterizing_the_mutational_burden_DNA_methylation_landscape_and_proteome_of_germ_cell_tumor-related_somatic-type_malignancies_to_identify_the_tissue-of-origin_mechanisms_of_therapy_resistance_and_druggable_targets/24160911)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
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