结肠腺癌TP53突变预后策略数据集
基于多个队列的转录组数据构建了TP53突变结肠腺癌的16基因预后特征,用于风险分层和精准治疗指导。

基本信息
资源简介
结肠腺癌TP53突变预后策略数据集
【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 75.23 KB,主题涵盖 prognosis、molecular signature、colon cancer、TP53 mutant、precision treatment planning,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《Datasheet1_A novel strategy for precise prognosis management and treatment option in colon adenocarcinoma with TP53 mutations.pdf》。源站首次发布:2023-02-09。
【数据内容】
源站原始描述:BackgroundTP53 is one of the most frequent mutated genes in colon cancer. Although colon cancer with TP53 mutations has a high risk of metastasis and worse prognosis generally, it showed high heterogeneity clinically. MethodsA total of 1,412 colon adenocarcinoma (COAD) samples were obtained from two RNA-seq cohorts and three microarray cohorts, including the TCGA-COAD (N = 408), the CPTAC-COAD (N = 106), GSE39582 (N = 541), GSE17536 (N = 171) and GSE41258 (N = 186). The LASSO-Cox method was used…
中文译文(机器翻译,仅供快速理解,请以原文为准):背景:TP53是结肠癌中最常见的突变基因之一。尽管TP53突变的结肠癌通常具有高转移风险和较差预后,但其临床表现具有高度异质性。 方法:从两个RNA测序队列和三个微阵列队列中共获取1,412例结肠腺癌(COAD)样本,包括TCGA-COAD(N=408)、CPTAC-COAD(N=106)、GSE39582(N=541)、GSE17536(N=171)和GSE41258(N=186)。采用LASSO-Cox方法基于表达数据建立预后特征模型。根据风险评分中位数将患者分为高风险组和低风险组。在多个队列中验证了该预后特征的效能,包括TP53突变型和TP53野生型。利用从CCLE数据库获取的TP53突变型COAD细胞系表达数据及从GDSC数据库获取的相应药物敏感性数据,探索潜在治疗靶点和药物。 结果:在TP53突变型COAD中建立了一个16基因预后特征模型。在所有TP53突变型数据集中,高风险组的生存时间显著劣于低风险组,而该预后特征模型未能正确区分TP53野生型COAD的预后。此外,风险评分是TP53突变型COAD预后的独立不良因素,基于风险评分的列线图在TP53突变型COAD中也显示出良好的预测效能。此外,我们确定SGPP1、RHOQ和PDGFRB为TP53突变型COAD的潜在靶点,并表明高风险患者可能从IGFR-3801、Staurosporine和Sabutoclax中获益。 结论:建立了一个高效的新型预后特征模型,特别适用于TP53突变的COAD患者。此外,我们为高风险的TP53突变型COAD确定了新的治疗靶点和潜在敏感药物。我们的发现不仅为预后管理提供了新策略,也为TP53突变型COAD的药物应用和精准治疗提供了新线索。
【数据结构与技术规格】
文件数 1 个,合计 75.23 KB。Datasheet1_A novel strategy for precise prognosis management and treatment option in colon adenocarcinoma with TP53 mutations.pdf:application/pdf,75.23 KB。数据集 DOI:10.3389/fsurg.2023.1079129.s001。
【主题与分类】
源站学科分类:Surgery、Oral and Maxillofacial Surgery、Medical Biochemistry: Proteins and Peptides (incl. Medical Proteomics)。主题标签:prognosis、molecular signature、colon cancer、TP53 mutant、precision treatment planning。
【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/Datasheet1_A_novel_strategy_for_precise_prognosis_management_and_treatment_option_in_colon_adenocarcinoma_with_TP53_mutations_pdf/22057634
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Niu, Lei; Liu, Langbiao; Cai, Jun (2023). Datasheet1_A novel strategy for precise prognosis management and treatment option in colon adenocarcinoma with TP53 mutations.pdf. Frontiers. Dataset
【使用注意】
· 源站最后修改于 2023-06-21,引用时请注意版本时效。
下载信息
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使用方式
数据集获取(Figshare)
- 源站标题:Datasheet1_A novel strategy for precise prognosis management and treatment option in colon adenocarcinoma with TP53 mutations.pdf
- DOI:10.3389/fsurg.2023.1079129.s001
- 发布日期:2023-02-09
- 文件数:1 个
- 文件总体积:75.23 KB
- 源站页面:https://frontiersin.figshare.com/articles/dataset/Datasheet1_A_novel_strategy_for_precise_prognosis_management_and_treatment_option_in_colon_adenocarcinoma_with_TP53_mutations_pdf/22057634
命令行下载
curl -L -o "Datasheet1_A novel strategy for precise prognosis management and treatment option in colon adenocarcinoma with TP53 mutations.pdf" "https://ndownloader.figshare.com/files/39162116"
文件清单
Datasheet1_A novel strategy for precise prognosis management and treatment option in colon adenocarcinoma with TP53 mutations.pdf(75.23 KB)
文件总体积 75.23 KB(源站 API 实测)。
数据说明
BackgroundTP53 is one of the most frequent mutated genes in colon cancer. Although colon cancer with TP53 mutations has a high risk of metastasis and worse prognosis generally, it showed high heterogeneity clinically.
MethodsA total of 1,412 colon adenocarcinoma (COAD) samples were obtained from two RNA-seq cohorts and three microarray cohorts, including the TCGA-COAD (N = 408), the CPTAC-COAD (N = 106), GSE39582 (N = 541), GSE17536 (N = 171) and GSE41258 (N = 186). The LASSO-Cox method was used to establish the prognostic signature based on the expression data. The patients were divided into high-risk and low-risk groups based on the median risk score. The efficiency of the prognostic signature was validated in various cohorts, including TP53-mutant and TP53 wild-type. The exploration of potential therapeutic targets and agents was performed by using the expression data of TP53-mutant COAD cell lines obtained from the CCLE database and the corresponding drug sensitivity data obtained from the GDSC database.
ResultsA 16-gene prognostic signature was established in TP53-mutant COAD. The high-risk group had significantly inferior survival time compared to the low-risk group in all TP53-mutant datasets, while the prognostic signature failed to classify the prognosis of COAD with TP53 wild-type properly. Besides, the risk score was the independent poor factor for the prognosis in TP53-mutant COAD and the nomogram based on the risk score was also shown good predictive efficiency in TP53-mutant COAD. Moreover, we identified SGPP1, RHOQ, and PDGFRB as potential targets for TP53-mutant COAD, and illuminated that the high-risk patients might benefit from IGFR-3801, Staurosporine, and Sabutoclax.
ConclusionA novel prognostic signature with great efficiency was established especially for COAD patients with TP53 mutations. Besides, we identified novel therapeutic targets and potential sensitive agents for TP53-mutant COAD with high risk. Our findings provided not only a new strategy for prognosis management but also new clues for drug application and precision treatment in COAD with TP53 mutations.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.3389/fsurg.2023.1079129.s001(source: https://frontiersin.figshare.com/articles/dataset/Datasheet1_A_novel_strategy_for_precise_prognosis_management_and_treatment_option_in_colon_adenocarcinoma_with_TP53_mutations_pdf/22057634)。
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