ACTuDB, a new database for the integrated analysis of array-CGH and clinical data for tumors

Area of Science:

• Genomics
• Bioinformatics
• Cancer Research

Background:

• Tumor genome structure is increasingly investigated using microarray techniques like array comparative genomic hybridization (array-CGH) and single nucleotide polymorphism (SNP) arrays.
• Integrating and comparing existing copy number data is crucial for validation and retrospective analyses in cancer research.
• A homogeneous data preparation and a unified bioinformatics environment are needed to effectively exploit the growing volume of tumor genomic data.

Purpose of the Study:

• To address the need for an integrative tool for tumor DNA copy number data.
• To construct a database, ACTuDB, for array-CGH and other DNA copy number data from tumors.
• To integrate associated clinical, transcriptome, and loss of heterozygosity data when available.

Main Methods:

• Development of ACTuDB, a database for array-CGH and DNA copy number data.
• Integration of approximately 1500 genomic profiles for various tumor types and cell lines.
• Processing of CGH array data using ad hoc algorithms for probe mapping, breakpoint detection, gain/loss status assignment, and visualization.

Main Results:

• ACTuDB currently contains ~1500 genomic profiles for tumors and cell lines across multiple cancer types.
• The database includes data for bladder, brain, breast, colon, liver, lymphoma, neuroblastoma, mouth, and pancreas.
• Associated clinical, transcriptome, and loss of heterozygosity data are integrated where available, alongside replication timing data.

Conclusions:

• ACTuDB provides a unified platform for accessing and analyzing tumor DNA copy number data.
• The database facilitates genomic profiling of tumors, a rapidly advancing field in cancer research.
• ACTuDB is accessible via a user-friendly interface, encouraging data submission from research groups.