Abstract B10: CGNT: A database of cancer genes explored in a nontumoral context

• Published in: Clinical cancer research Vol. 24; no. 1_Supplement; p. B10
• Main Authors: Buzatto, Vanessa C., Miller, Thiago A., Ohara, Daniel T., Ivanio, Francisco, Camargo, Anamaria A., Galante, Pedro A.F.
• Format: Journal Article
• Language: English
• Published: 01.01.2018
• ISSN: 1078-0432; 1557-3265
• DOI: 10.1158/1557-3265.TCM17-B10

Abstract The new DNA and RNA sequencing platforms and the capability of analyzing tumor genomes allowed the identification of novel genes related to the process of human tumors appearance and maintenance, in addition to known cancer genes such as TP53, ERBB2, KRAS, APC, RB and PTEN. These genes, when mutated, can function as oncogenes and trigger the tumorigenesis or lose their tumor-supression role. Cancer is a heterogeneous disease both in the aspect of aberrant mutations and in the cellular microenvironment, since that environment can help to transform the healthy cell. Although we already know many of the somatic mutations and aberrant expression profiles of cancer genes, little is known about these genes in the context of normality, as we still do not have a complete database that display such information. For example, we do not know in which tissues many of the cancer genes are expressed in a constitutive way. The most reliable catalogues of known cancer genes, such as TCGA (The Cancer Genome Atlas), ICGC (International Cancer Genome Consortium), and COSMIC (Catalogue of Somatic Mutations in Cancer), brought to light the genomic abnormalities with clinical relevance in different tumor types. The mode of action, the pathways involved, and the pattern of expression of some cancer genes, like TP53, are well known, but for a variety of genes we still do not know its behavior in the transition between normal and tumor conditions. In some cases (ALK gene, ERBB2 gene, for example) the differences in expression levels are related to the pathologic stage of the disease and we can conclude that the gene contributes to the tumorigenesis process and to the more aggressive case of the cancer. For this reason, it is important to know what is normal, to detect the dangerous abnormal. Furthermore, the pattern and levels of gene expression, the polymorphisms found, the structural variants, and the genomic pathway could be useful as tumor markers, helping to get early diagnosis and even supporting the choice of the better procedure or treatment. From this, we hypothesize that collecting and organizing information from cancer-related genes in a normal environment may be of great value. The main goal of this study is to obtain, organize, and make available genetic and genomic data of the cancer-related genes (cancer genes) in normal (nontumoral) conditions to explore the molecular basis involved in the regulation of those genes, the possible candidate mutations related to cancer development, and new biomarkers. Firstly, to define what a cancer gene is, we evaluated the most important cancer gene lists from the literature. We made an extensive analysis for these sets of genes, compiling several evidences from the literature of each gene's involvement in tumorigenesis or classification as oncogene and/or tumor suppressor gene. Further, for a final set of 386 cancer genes, we have developed a publicly available database CGNT (Cancer Genes in Non-tumoral Tissues; publicly available at https://www.bioinfo.mochsl.org.br/cgnt) with a WEB interface, where users can retrieve expression profiles in 16 normal tissues, SNPs (single nucleotide polymorphisms), and Indels (Insertions and Deletions); a summary of gene activity with the genomic context, that is, the gene coordinates; external links to other cancer databases, which (until now) are KEGG (Kyoto Encyclopedia of Genes and Genomes); PubMed, that links the gene to the articles related to cancer and NCBI, linking to the NCBI Gene page; and the oncogene/tumor-suppressor classification. We believe that CGNT is a very useful tool for the scientific community in the aspects of analysis and identification of possible molecular markers from different tissues for a variety of tumors. Citation Format: Vanessa C. Buzatto, Thiago A. Miller, Daniel T. Ohara, Francisco Ivanio, Anamaria A. Camargo, Pedro A.F. Galante. CGNT: A database of cancer genes explored in a nontumoral context [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr B10.