胃癌液-液相分离基因签名分析数据集（Table 2）

数据集获取（Figshare）

• 源站标题：Table 2_Liquid-liquid phase separation in gastric cancer: identifying novel biomarkers and therapeutic targets through gene signature analysis.doc
• DOI：10.3389/fimmu.2025.1620390.s006
• 发布日期：2025-09-01
• 文件数：1 个
• 文件总体积：20.48 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_2_Liquid-liquid_phase_separation_in_gastric_cancer_identifying_novel_biomarkers_and_therapeutic_targets_through_gene_signature_analysis_doc/30020917

命令行下载

curl -L -o "Table 2_Liquid-liquid phase separation in gastric cancer: identifying novel biomarkers and therapeutic targets through gene signature analysis.doc" "https://ndownloader.figshare.com/files/57553207"

文件清单

• Table 2_Liquid-liquid phase separation in gastric cancer: identifying novel biomarkers and therapeutic targets through gene signature analysis.doc（20.48 KB）

文件总体积 20.48 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

Background and objectiveLiquid-liquid phase separation (LLPS) plays an important role in the development of many tumors, including gastric cancer, but its prognostic value is unclear. The aim of this study was to explore the prognostic significance of LLPS-related genes in gastric cancer to provide a basis for improving the accuracy of prognostic prediction and finding potential therapeutic targets in gastric cancer.
MethodsClinical and transcriptomic data of gastric cancer were downloaded from TCGA and GEO databases, and LLPS-related genes were extracted from PhaSepDB. Unsupervised clustering was used to identify molecular subtypes based on LLPS gene expression. LLPS gene features were constructed and validated by LASSO Cox regression, and their staging prediction value was also evaluated by machine learning methods. Key genes were validated by qRT-PCR, Western blot, immunofluorescence, and functional experiments (shRNA knockdown, CCK-8, clone formation, and scratch assay).
ResultsTwenty LLPS-associated genes showed significant mRNA expression, copy number variation, somatic mutation, and interaction network alterations in gastric cancer tissues. Two LLPS molecular isoforms with different survival outcomes and immune microenvironment characteristics were identified. A four-gene LLPS prognostic signature consisting of DACT1, EZH2, PAK2, and PSPC1 was constructed, and the high-risk group had a poorer prognosis and was prone to drug resistance. Machine learning analysis further confirmed the predictive value of this gene signature. Functional experiments showed that knockdown of PSPC1 significantly inhibited the proliferation (inhibition rate >50%, P This study revealed the important role of LLPS in gastric cancer, and the constructed four-gene LLPS signature is expected to be a novel biomarker for prognostic assessment and treatment of gastric cancer. PSPC1 plays a key role in gastric cancer progression, and has the value of a potential therapeutic target.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fimmu.2025.1620390.s006（source: https://frontiersin.figshare.com/articles/dataset/Table_2_Liquid-liquid_phase_separation_in_gastric_cancer_identifying_novel_biomarkers_and_therapeutic_targets_through_gene_signature_analysis_doc/30020917）。