DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets.

Area of Science:

• Cancer Biology
• Bioinformatics
• Genomics

Background:

• High-throughput omics analyses are crucial for cancer research.
• Integrating multi-omics data remains a significant challenge, often requiring extensive time and expertise.

Purpose of the Study:

• To develop an accessible R Shiny framework, DRPPM-EASY, for integrative multi-omics analysis.
• To demonstrate the utility of DRPPM-EASY in identifying molecular signatures and disruptions in cancer cell lines.

Main Methods:

• Development of DRPPM-EASY, an R Shiny framework for integrative multi-omics analysis.
• Application of the framework to RNA-seq and proteomic data from USP7 knockdown in T-cell acute lymphoblastic leukemia (T-ALL) cell lines.
• Creation of DRPPM-EASY-CCLE, a Shiny extension utilizing the Cancer Cell Line Encyclopedia (CCLE) for phenotype-based querying.

Main Results:

• Identification of an upregulated TAL1-associated proliferative signature in T-ALL cells post-USP7 knockdown.
• Concurrent analysis of transcriptome and proteome revealed disruption of protein degradation machinery and spliceosome.
• Verification of TP53-associated DNA damage signature in TP53-mutated ovarian cancer cells using DRPPM-EASY-CCLE.

Conclusions:

• DR PPM-EASY provides an open-source, user-friendly platform for multi-omics data exploration and discovery in cancer research.
• The framework facilitates the integration of transcriptomic and proteomic data, enabling identification of key biological insights.
• DR PPM-EASY-CCLE enhances data accessibility by integrating meta-information for phenotype-driven analysis.