铂类/紫杉醇治疗上皮性卵巢癌反应相关的基因表达谱综合分析

数据集获取（Figshare）

• 源站标题：Integrated Analysis of Gene Expression Profiles Associated with Response of Platinum/Paclitaxel-Based Treatment in Epithelial Ovarian Cancer
• DOI：10.1371/journal.pone.0052745
• 发布日期：2012-12-27
• 文件数：16 个
• 文件总体积：5.57 MB
• 源站页面：https://plos.figshare.com/articles/dataset/Integrated_Analysis_of_Gene_Expression_Profiles_Associated_with_Response_of_Platinum_Paclitaxel_Based_Treatment_in_Epithelial_Ovarian_Cancer__/115206

命令行下载

curl -L -o "Table_S1.xlsx" "https://ndownloader.figshare.com/files/279943"
curl -L -o "Table_S2.xlsx" "https://ndownloader.figshare.com/files/279968"
curl -L -o "Table_S3.xlsx" "https://ndownloader.figshare.com/files/279986"
curl -L -o "Table_S4.xlsx" "https://ndownloader.figshare.com/files/280002"
curl -L -o "Table_S5.xlsx" "https://ndownloader.figshare.com/files/280020"
curl -L -o "Table_S6.xlsx" "https://ndownloader.figshare.com/files/280080"
curl -L -o "Table_S7.xlsx" "https://ndownloader.figshare.com/files/280101"
curl -L -o "Table_S8.xlsx" "https://ndownloader.figshare.com/files/280118"

文件清单

• Table_S1.xlsx（27.19 KB）
• Table_S2.xlsx（10.62 KB）
• Table_S3.xlsx（15.43 KB）
• Table_S4.xlsx（15.83 KB）
• Table_S5.xlsx（330.03 KB）
• Table_S6.xlsx（22.91 KB）
• Table_S7.xlsx（9.72 KB）
• Table_S8.xlsx（187.86 KB）
• Table_S9.xlsx（32.70 KB）
• Figure_S1.tif（261.14 KB）
• Figure_S2.tif（326.34 KB）
• Figure_S3.tif（1.05 MB）
• Figure_S4.tif（950.09 KB）
• Figure_S5.tif（1.01 MB）
• Figure_S6.tif（750.11 KB）
• Figure_S7.tif（570.80 KB）

文件总体积 5.57 MB（源站 API 实测）。

数据说明

Purpose
This study aims to explore gene expression signatures and serum biomarkers to predict intrinsic chemoresistance in epithelial ovarian cancer (EOC).
Patients and Methods
Gene expression profiling data of 322 high-grade EOC cases between 2009 and 2010 in The Cancer Genome Atlas project (TCGA) were used to develop and validate gene expression signatures that could discriminate different responses to first-line platinum/paclitaxel-based treatments. A gene regulation network was then built to further identify hub genes responsible for differential gene expression between the complete response (CR) group and the progressive disease (PD) group. Further, to find more robust serum biomarkers for clinical application, we integrated our gene signatures and gene signatures reported previously to identify secretory protein-encoding genes by searching the DAVID database. In the end, gene-drug interaction network was constructed by searching Comparative Toxicogenomics Database (CTD) and literature.
Results
A 349-gene predictive model and an 18-gene model independent of key clinical features with high accuracy were developed for prediction of chemoresistance in EOC. Among them, ten important hub genes and six critical signaling pathways were identified to have important implications in chemotherapeutic response. Further, ten potential serum biomarkers were identified for predicting chemoresistance in EOC. Finally, we suggested some drugs for individualized treatment.
Conclusion
We have developed the predictive models and serum biomarkers for platinum/paclitaxel response and established the new approach to discover potential serum biomarkers from gene expression profiles. The potential drugs that target hub genes are also suggested.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0052745（source: https://plos.figshare.com/articles/dataset/Integrated_Analysis_of_Gene_Expression_Profiles_Associated_with_Response_of_Platinum_Paclitaxel_Based_Treatment_in_Epithelial_Ovarian_Cancer__/115206）。