Development and implementation of the SUM breast cancer cell line functional genomics knowledge base

Area of Science:

• Oncology
• Genomics
• Bioinformatics

Background:

• The SUM panel of human breast cancer cell lines is widely used globally.
• Extensive omics datasets exist for these cell lines.
• Genome-scale shRNA essentiality screens provide functional insights.

Purpose of the Study:

• To create a centralized knowledge base for SUM breast cancer cell lines.
• To enable data mining and functionalization of genomic data.
• To provide insights into breast cancer cell line biology.

Main Methods:

• Development of the SUM Breast Cancer Cell Line Knowledge Base (SLKBase).
• Integration of omics data (genomics, gene expression, protein/phospho-protein expression).
• Inclusion of genome-scale shRNA essentiality screening data.
• Expansion to include genomic data for 27 additional breast cancer cell lines.

Main Results:

• The SLKBase offers cell line derivation information and maintenance protocols.
• Data mining tools facilitate identification of oncogene signatures and pathway enrichment (KEGG).
• Analysis of protein and phospho-protein expression is available.
• Tools for gene searching and identifying functional-druggable signatures are provided.

Conclusions:

• The SLKBase provides deep insights into human breast cancer cell line biology.
• It enables orthogonal analysis of descriptive genomic data.
• The resource supports strategies for reverse engineering of individual breast cancer cell lines.
• Facilitates the development of novel therapeutic strategies.