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CaGe: A Web-Based Cancer Gene Annotation System for Cancer Genomics.

Park YK, Kang TW, Baek SJ, Kim KI, Kim SY, Lee D, Kim YS - Genomics Inform (2012)

Bottom Line: High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes.The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions.We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.

View Article: PubMed Central - PubMed

Affiliation: Medical Genomics Research Center, KRIBB, Daejeon 305-806, Korea. ; Department of Bio and Brain Engineering, KAIST, Daejeon 305-701, Korea.

ABSTRACT
High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes. The main hurdle in cancer genomics is to identify the real causative mutations or genes out of many candidates from an HGT-based cancer genomic analysis. One useful approach is to refer to known cancer genes and associated information. The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. Some cancer gene or mutation databases exist for this purpose, but few specialized tools exist for an automated analysis of a long gene list from an HGT-based cancer genomic analysis. This report presents a new web-accessible bioinformatic tool, called CaGe, a cancer genome annotation system for the assessment of candidates of cancer genes from HGT-based cancer genomics. The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions. With this tool, researchers can classify their candidate genes from cancer genome studies into either previously reported or novel categories of cancer genes and gain insight into underlying carcinogenic mechanisms through a pathway analysis. We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.

No MeSH data available.


Related in: MedlinePlus

Cancer gene annotation page of CaGe web interface.
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Figure 2: Cancer gene annotation page of CaGe web interface.

Mentions: The goal of this study was to provide researchers with a tool for classifying their candidate genes from HGT-based cancer genome studies into previously reported or novel categories of cancer genes, while providing insight into underlying carcinogenic mechanisms through a pathway analysis. To implement the cancer gene annotation function of CaGe, we constructed reported cancer gene and cancer annotation databases from public cancer genomic databases and cancer pathway-gene databases by pathway analysis with reported cancer gene sets and canonical pathways. We also constructed a gene ID database to allow various input formats for the input of gene lists and a gene functional annotation database to provide users with functional clues for the annotated candidate genes. Then, we developed a core retrieval program and web interfaces for the main functions, which include cancer gene annotation, cancer pathway annotation, cancer gene browsing, and cancer pathway browsing. The workflow for the database construction and data processing in CaGe is summarized in Fig. 1, and the cancer gene annotation page of the CaGe web interface is shown in Fig. 2.


CaGe: A Web-Based Cancer Gene Annotation System for Cancer Genomics.

Park YK, Kang TW, Baek SJ, Kim KI, Kim SY, Lee D, Kim YS - Genomics Inform (2012)

Cancer gene annotation page of CaGe web interface.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3475486&req=5

Figure 2: Cancer gene annotation page of CaGe web interface.
Mentions: The goal of this study was to provide researchers with a tool for classifying their candidate genes from HGT-based cancer genome studies into previously reported or novel categories of cancer genes, while providing insight into underlying carcinogenic mechanisms through a pathway analysis. To implement the cancer gene annotation function of CaGe, we constructed reported cancer gene and cancer annotation databases from public cancer genomic databases and cancer pathway-gene databases by pathway analysis with reported cancer gene sets and canonical pathways. We also constructed a gene ID database to allow various input formats for the input of gene lists and a gene functional annotation database to provide users with functional clues for the annotated candidate genes. Then, we developed a core retrieval program and web interfaces for the main functions, which include cancer gene annotation, cancer pathway annotation, cancer gene browsing, and cancer pathway browsing. The workflow for the database construction and data processing in CaGe is summarized in Fig. 1, and the cancer gene annotation page of the CaGe web interface is shown in Fig. 2.

Bottom Line: High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes.The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions.We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.

View Article: PubMed Central - PubMed

Affiliation: Medical Genomics Research Center, KRIBB, Daejeon 305-806, Korea. ; Department of Bio and Brain Engineering, KAIST, Daejeon 305-701, Korea.

ABSTRACT
High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes. The main hurdle in cancer genomics is to identify the real causative mutations or genes out of many candidates from an HGT-based cancer genomic analysis. One useful approach is to refer to known cancer genes and associated information. The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. Some cancer gene or mutation databases exist for this purpose, but few specialized tools exist for an automated analysis of a long gene list from an HGT-based cancer genomic analysis. This report presents a new web-accessible bioinformatic tool, called CaGe, a cancer genome annotation system for the assessment of candidates of cancer genes from HGT-based cancer genomics. The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions. With this tool, researchers can classify their candidate genes from cancer genome studies into either previously reported or novel categories of cancer genes and gain insight into underlying carcinogenic mechanisms through a pathway analysis. We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.

No MeSH data available.


Related in: MedlinePlus