PTPN2作为胰腺腺癌预后预测因子的数据表

胰腺腺癌中PTPN2预后相关分析数据表格,包含表达、预后及免疫浸润等结果。

NIAID Data Ecosystem
浏览 7
表格pancreatic cancerPTPN family genesPTPN2prognosisJAK-STAT
Table_3_PTPN2, A Key Predictor of Prognosis for Pancreatic Adenocarcinoma, Significantly Regulates Cell Cycles, Apoptosis, and Metastasis.xlsx

基本信息

模态
表格
大小
0.000082844 GB
许可
CC BY 4.0
创建/更新时间
2026-10-08
版本
v1

资源简介

PTPN2作为胰腺腺癌预后预测因子的数据表

【一句话概览】

本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 82.84 KB,主题涵盖 pancreatic cancer、PTPN family genes、PTPN2、prognosis、JAK-STAT,可用于统计建模、特征工程与队列分析,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_3_PTPN2, A Key Predictor of Prognosis for Pancreatic Adenocarcinoma, Significantly Regulates Cell Cycles, Apoptosis, and Metastasis.xlsx》。配套论文《Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma》发表于 CA: A Cancer Journal for Clinicians(2020),DOI:10.3322/caac.21626。源站首次发布:2022-01-27。

【数据内容】

源站原始描述:ObjectiveThis study conducted a comprehensive analysis of the members of the PTPN family and emphasized the key role of PTPN2 as a potential therapeutic target and diagnostic biomarker in improving the survival rate of PAAD. MethodOncomine was used to analyze the pan-cancer expression of the PTPN gene family. The Cancer Genome Atlas (TCGA) data as well as Genotype-Tissue Expression (GTEx) data were downloaded to analyze the expression and prognosis of PTPNs. The diagnosis of PTPNs was evaluated…

【数据结构与技术规格】

文件数 1 个,合计 82.84 KB。Table_3_PTPN2, A Key Predictor of Prognosis for Pancreatic Adenocarcinoma, Significantly Regulates Cell Cycles, Apoptosis, and Metastasis.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,82.84 KB。数据集 DOI:10.3389/fimmu.2022.805311.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:pancreatic cancer、PTPN family genes、PTPN2、prognosis、JAK-STAT。

【适用方向】

结构化表格数据可直接用于统计建模、特征工程与队列分析。

【获取与许可】

源站页面:https://frontiersin.figshare.com/articles/dataset/Table_3_PTPN2_A_Key_Predictor_of_Prognosis_for_Pancreatic_Adenocarcinoma_Significantly_Regulates_Cell_Cycles_Apoptosis_and_Metastasis_xlsx/19075652

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

规范引用:Kuang, Wenbin; Wang, Xiao; Ding, Jiayu; Li, Jiaxing; Ji, Minghui; Chen, Weijiao; et al. (2022). Table_3_PTPN2, A Key Predictor of Prognosis for Pancreatic Adenocarcinoma, Significantly Regulates Cell Cycles, Apoptosis, and Metastasis.xlsx. Frontiers. Dataset

【使用注意】

· 源站最后修改于 2023-06-15,引用时请注意版本时效。

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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。

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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_3_PTPN2, A Key Predictor of Prognosis for Pancreatic Adenocarcinoma, Significantly Regulates Cell Cycles, Apoptosis, and Metastasis.xlsx" "https://ndownloader.figshare.com/files/33902348"

文件清单

  • Table_3_PTPN2, A Key Predictor of Prognosis for Pancreatic Adenocarcinoma, Significantly Regulates Cell Cycles, Apoptosis, and Metastasis.xlsx(82.84 KB)

文件总体积 82.84 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

ObjectiveThis study conducted a comprehensive analysis of the members of the PTPN family and emphasized the key role of PTPN2 as a potential therapeutic target and diagnostic biomarker in improving the survival rate of PAAD.
MethodOncomine was used to analyze the pan-cancer expression of the PTPN gene family. The Cancer Genome Atlas (TCGA) data as well as Genotype-Tissue Expression (GTEx) data were downloaded to analyze the expression and prognosis of PTPNs. The diagnosis of PTPNs was evaluated by the experimental ROC curve. The protein-protein interaction (PPI) network was constructed by combining STRING and Cytoscape. The genes of 50 proteins most closely related to PTPN2 were screened and analyzed by GO and KEGG enrichment. The differentially expressed genes of PTPN2 were found by RNA sequencing, and GSEA enrichment analysis was carried out to find the downstream pathways and targets, which were verified by online tools and experiments. Finally, the relationship between PTPN2 and immune cell infiltration in PAAD, and the relationship with immune score and immune checkpoint were studied.
ResultThe expression patterns and the prognostic value of multiple PTPNs in PAAD have been reported through bioinformatic analyzes. Among these members, PTPN2 is the most important prognostic signature that regulates the progression of PAAD by activating JAK-STAT signaling pathway. Comparison of two PAAD cell lines with normal pancreatic epithelial cell lines revealed that PTPN2 expression was up-regulated as a key regulator of PAAD, which was associated with poor prognosis. Knockdown of PTPN2 caused a profound decrease in PAAD cell growth, migration, invasion, and induced PAAD cell cycle and apoptosis. In addition, we conducted a series of enrichment analyses to investigate the PTPN2-binding proteins and the PTPN2 expression-correlated genes. We suggest that STAT1 and EGFR are the key factors to regulate PTPN2, which are involved in the progression of PAAD. Meanwhile, the silencing of PTPN2 induced the repression of STAT1 and EGFR expression.
ConclusionThese findings provide a comprehensive analysis of the PTPN family members, and for PAAD, they also demonstrate that PTPN2 is

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fimmu.2022.805311.s003(source: https://frontiersin.figshare.com/articles/dataset/Table_3_PTPN2_A_Key_Predictor_of_Prognosis_for_Pancreatic_Adenocarcinoma_Significantly_Regulates_Cell_Cycles_Apoptosis_and_Metastasis_xlsx/19075652)。

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