分子血管生成拟态相关特征预测膀胱癌临床结局和治疗反应的数据表13

数据集获取（Figshare）

• 源站标题：DataSheet13_Molecular vasculogenic mimicry–Related signatures predict clinical outcomes and therapeutic responses in bladder cancer: Results from real-world cohorts.PDF
• DOI：10.3389/fphar.2023.1163115.s005
• 发布日期：2023-04-24
• 文件数：1 个
• 文件总体积：1.75 MB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/DataSheet13_Molecular_vasculogenic_mimicry_Related_signatures_predict_clinical_outcomes_and_therapeutic_responses_in_bladder_cancer_Results_from_real-world_cohorts_PDF/22681399

命令行下载

curl -L -o "DataSheet13_Molecular vasculogenic mimicry–Related signatures predict clinical outcomes and therapeutic responses in bladder cancer: Results from real.PDF" "https://ndownloader.figshare.com/files/40267195"

文件清单

• DataSheet13_Molecular vasculogenic mimicry–Related signatures predict clinical outcomes and therapeutic responses in bladder cancer: Results from real.PDF（1.75 MB）

文件总体积 1.75 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

Bladder cancer (BLCA) is a heterogeneous disease, and there are many classical molecular subtypes that reflect tumor immune microenvironment (TME) heterogeneity but their clinical utility is limited and correct individual treatment and prognosis cannot be predicted based on them. To find reliable and effective biomarkers and tools for predicting patients’ clinical responses to several therapies, we developed a new systemic indicator of molecular vasculogenic mimicry (VM)–related genes mediated by molecular subtypes based on the Xiangya cohort and additional external BLCA cohorts using a random forest algorithm. A correlation was then done between the VM_Score and classical molecular subtypes, clinical outcomes, immunophenotypes, and treatment options for BLCA. With the VM_Score, it is possible to predict classical molecular subtypes, immunophenotypes, prognosis, and therapeutic potential of BLCA with high accuracy. The VM_Scores of high levels indicate a more anticancer immune response but a worse prognosis due to a more basal and inflammatory phenotype. The VM_Score was also found associated with low sensitivity to antiangiogenic and targeted therapies targeting the FGFR3, β-catenin, and PPAR-γ pathways but with high sensitivity to cancer immunotherapy, neoadjuvant chemotherapy, and radiotherapy. A number of aspects of BLCA biology were reflected in the VM_Score, providing new insights into precision medicine. Additionally, the VM_Score may be used as an indicator of pan-cancer immunotherapy response and prognosis.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fphar.2023.1163115.s005（source: https://frontiersin.figshare.com/articles/dataset/DataSheet13_Molecular_vasculogenic_mimicry_Related_signatures_predict_clinical_outcomes_and_therapeutic_responses_in_bladder_cancer_Results_from_real-world_cohorts_PDF/22681399）。