CNAdbCC

CNAdbCC catalogs copy number aberrations (CNAs) in cervical cancer to support identification of recurrent somatic amplifications, deletions, and candidate driver genes.

Key Features:

• Extensive Dataset: Integrates approximately 974 cervical cancer samples with raw data sourced from GEO and TCGA.
• High-Resolution Analysis: Leverages high-resolution genomic arrays to detect focal CNAs.
• Driver Gene Identification: Applies GISTIC2.0 to identify recurrent amplification and deletion regions and highlight potential driver genes such as PIK3CA, ERBB2, EP300, and FBXW7.
• Data Mining and Visualization: Provides capabilities for data mining and visualization of CNA patterns.
• Chromothripsis Annotation: Supports exploration of chromothripsis events with an estimated incidence of 6.06% in cervical cancer.

Scientific Applications:

• Molecular Understanding: Cataloging CNAs aids identification of tumor suppressor genes and oncogenes in cervical cancer.
• Diagnostic Indicator: Provides insights into somatic CNAs that are pivotal in cervical cancer pathology.
• Therapeutic Discovery: Enables exploration of therapeutic candidates by examining specific genomic alteration patterns.
• Chromothripsis Research: Facilitates study of chromothripsis events in cervical cancer (estimated incidence 6.06%).

Methodology:

Data from ~974 samples were collected from GEO and TCGA and analyzed using high-resolution genomic arrays; recurrent focal CNAs and candidate driver genes were identified with GISTIC2.0; the database implementation used PHP with custom Perl and R scripts.