PDAC Multi-omics Data: USP54 Prognostic Role in Tumor-Immune Microenvironment

A multi-omics dataset from a study identifying the deubiquitinase USP54 as a prognostic factor in pancreatic ductal adenocarcinoma (PDAC). The data includes bulk transcriptomics, single-cell RNA sequencing, and spatial transcriptomic profiling, analyzed with machine learning methods like Coxnet and Fuzzy SVM. The dataset was authored by Zibo Yuan and last updated on March 18, 2026.

Use Cases

• Prognostic modeling for pancreatic cancer based on deubiquitinase activity and transcriptomic data.
• Analyzing cell-cell communication networks within the tumor immune microenvironment based on inferred ligand-receptor pairs.
• Spatial deconvolution analysis to validate co-localization of gene expression and signaling pathways within tumor niches.
• Single-cell trajectory analysis to study gene upregulation in malignant ductal cells.

Strengths

• Integrates multiple data modalities: bulk transcriptomics, single-cell RNA-seq, and spatial transcriptomics.
• Analysis includes in vitro and in vivo experimental validation using BxPC-3 and PANC-1 cell lines.
• Dataset is licensed under CC-BY-4.0, allowing for open sharing and reuse.

Limitations

• Row count and column-level documentation are unknown, limiting suitability assessment.
• The primary data file is a 8.0 MB DOCX, which may contain processed results rather than raw data tables.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Data generated from an integrative multi-omics study combining transcriptomic profiling, machine learning, and experimental assays.

Freshness

Last updated 2026-03-18 06:56:41; freshness should be verified.