中国人群错配修复缺陷尿路上皮癌真实世界研究数据集

中国人群dMMR尿路上皮癌真实世界数据集,包含临床病理、分子图谱和免疫治疗生物标志物信息。

NIAID Data Ecosystem
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多模态urothelial carcinomamismatch repairLynch syndromePD-1/PD-L1immunotherapy
Table_1_Clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in Chinese population with mismatch repair deficient urothelial carcinoma: a real-world study.docx

基本信息

模态
多模态
大小
0.000018196 GB
许可
CC BY 4.0
创建/更新时间
2026-10-08
版本
v1

资源简介

中国人群错配修复缺陷尿路上皮癌真实世界研究数据集

【一句话概览】

本数据集是 figshare 公开的多模态数据集,收录 1 个文件、合计 18.20 KB,主题涵盖 urothelial carcinoma、mismatch repair、Lynch syndrome、PD-1/PD-L1、immunotherapy,可用于跨模态对齐与融合建模研究,CC BY 4.0 许可开放获取。

【数据集背景】

本数据集源站标题为《Table_1_Clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in Chinese population with mismatch repair deficient urothelial carcinoma: a real-world study.docx》。配套论文《Comparative Effectiveness of Immune Checkpoint Inhibitors vs Chemotherapy in Patients With Metastatic Colorectal Cancer With Measures of Microsatellite Instability, Mismatch Repair, or Tumor Mutational Burden》发表于 JAMA Network Open(2023),DOI:10.1001/jamanetworkopen.2022.52244。源站首次发布:2023-11-06。

【数据内容】

源站原始描述:Urothelial carcinoma (UC) with deficient mismatch repair (dMMR) is a specific subtype of UC characterized by the loss of mismatch repair (MMR) proteins and its association with Lynch syndrome (LS). However, comprehensive real-world data on the incidence, clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in the Chinese patients with dMMR UC remains unknown. We analyzed 374 patients with bladder urothelial carcino…

【数据结构与技术规格】

文件数 1 个,合计 18.20 KB。Table_1_Clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in Chin.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,18.20 KB。数据集 DOI:10.3389/fimmu.2023.1269097.s003。

【主题与分类】

源站学科分类:Transplantation Immunology、Tumour Immunology、Immunology not elsewhere classified、Immunology、Veterinary Immunology、Animal Immunology。主题标签:urothelial carcinoma、mismatch repair、Lynch syndrome、PD-1/PD-L1、immunotherapy。

【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://frontiersin.figshare.com/articles/dataset/Table_1_Clinicopathological_characteristics_molecular_landscape_and_biomarker_landscape_for_predicting_the_efficacy_of_PD-1_PD-L1_inhibitors_in_Chinese_population_with_mismatch_repair_deficient_urothelial_carcinoma_a_real-world_study_docx/24502945

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Ma, Yu-Ting; Hua, Fang; Zhong, Xiu-Ming; Xue, Ying-Jie; Li, Jia; Nie, Yi-Cong; et al. (2023). Table_1_Clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in Chinese population with mismatch repair deficient urothelial…

官方服务

专家保障全链路合规授权与标注交付

陕川双基地 × 超十家三甲医院直连

从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

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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)

命令行下载

curl -L -o "Table_1_Clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in Chin.docx" "https://ndownloader.figshare.com/files/43046920"

文件清单

  • Table_1_Clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in Chin.docx(18.20 KB)

文件总体积 18.20 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

Urothelial carcinoma (UC) with deficient mismatch repair (dMMR) is a specific subtype of UC characterized by the loss of mismatch repair (MMR) proteins and its association with Lynch syndrome (LS). However, comprehensive real-world data on the incidence, clinicopathological characteristics, molecular landscape, and biomarker landscape for predicting the efficacy of PD-1/PD-L1 inhibitors in the Chinese patients with dMMR UC remains unknown. We analyzed 374 patients with bladder urothelial carcinoma (BUC) and 232 patients with upper tract urothelial carcinoma (UTUC) using tissue microarrays, immunohistochemistry, and targeted next-generation sequencing. Results showed the incidence of dMMR UC was higher in the upper urinary tract than in the bladder. Genomic analysis identified frequent mutations in KMT2D and KMT2C genes and LS was confirmed in 53.8% of dMMR UC cases. dMMR UC cases displayed microsatellite instability-high (MSI-H) (PCR method) in 91.7% and tumor mutational burden-high (TMB-H) in 40% of cases. The density of intratumoral CD8+ T cells correlated with better overall survival in dMMR UC patients. Positive PD-L1 expression was found in 20% cases, but some patients positively responded to immunotherapy despite negative PD-L1 expression. Our findings provide valuable insights into the characteristics of dMMR UC in the Chinese population and highlights the relevance of genetic testing and immunotherapy biomarkers for treatment decisions.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fimmu.2023.1269097.s003(source: https://frontiersin.figshare.com/articles/dataset/Table_1_Clinicopathological_characteristics_molecular_landscape_and_biomarker_landscape_for_predicting_the_efficacy_of_PD-1_PD-L1_inhibitors_in_Chinese_population_with_mismatch_repair_deficient_urothelial_carcinoma_a_real-world_study_docx/24502945)。

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。

⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。

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