NBBC: a non-B DNA burden explorer in cancer
Qi Xu1,2, Jeanne Kowalski1
1Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.
Abstract:
Alternate (non-B) DNA-forming structures, such as Z-DNA, G-quadruplex, triplex have demonstrated a potential role in cancer etiology. It has been found that non-B DNA-forming sequences can stimulate genetic instability in human cancer genomes, implicating them in the development of cancer and other genetic diseases. While there exist several non-B prediction tools and databases, they lack the ability to both analyze and visualize non-B data within a cancer context. Herein, we introduce NBBC, a non-B DNA burden explorer in cancer, that offers analyses and visualizations for non-B DNA forming motifs. To do so, we introduce 'non-B burden' as a metric to summarize the prevalence of non-B DNA motifs at the gene-, signature- and genomic site-levels. Using our non-B burden metric, we developed two analyses modules within a cancer context to assist in exploring both gene- and motif-level non-B type heterogeneity among gene signatures. NBBC is designed to serve as a new analysis and visualization platform for the exploration of non-B DNA, guided by non-B burden as a novel marker.
Insights
Non-B DNA structures, like Z-DNA, are implicated in cancer development. A new tool, NBBC (non-B DNA burden explorer in cancer), analyzes and visualizes these DNA structures within a cancer context.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Research
Background:
- Non-B DNA structures (Z-DNA, G-quadruplex, triplex) are implicated in cancer etiology.
- These structures can stimulate genetic instability in human cancer genomes.
- Existing tools lack cancer-specific analysis and visualization for non-B DNA data.
Purpose of the Study:
- Introduce NBBC (non-B DNA burden explorer in cancer), a novel platform for analyzing and visualizing non-B DNA motifs.
- Develop a 'non-B burden' metric to quantify the prevalence of non-B DNA motifs.
- Facilitate exploration of non-B DNA heterogeneity in cancer.
Main Methods:
- Developed the 'non-B burden' metric to summarize non-B DNA motif prevalence at gene, signature, and genomic levels.
- Created two analysis modules within NBBC for exploring gene- and motif-level non-B DNA heterogeneity.
- Integrated visualization capabilities for non-B DNA data within a cancer context.
Main Results:
- Established 'non-B burden' as a metric for quantifying non-B DNA motif prevalence.
- Enabled analysis of non-B DNA heterogeneity across genes and motifs within cancer gene signatures.
- Provided a new platform for visualizing non-B DNA data in relation to cancer.
Conclusions:
- NBBC offers a novel analysis and visualization platform for non-B DNA exploration in cancer.
- The 'non-B burden' metric serves as a key marker for understanding non-B DNA's role in cancer.
- NBBC aids in exploring non-B DNA's contribution to genetic instability and cancer development.
