Identification of altered genes in gallbladder cancer as potential driver mutations for diagnostic and prognostic purposes: a computational approach
Autor
D'Afonseca, Vívian
Arencibia-Rodríguez, Ariel
Echeverría-Vega, Alex
Cerpa, Leslie
Cayún, Juan P.
Varela, Nelson M.
Salazar, Marcela
Quiñones, Luis A.
Fecha
2020Resumen
Prognostic markers for cancer can assist in the evaluation of survival probability of patients and help clinicians to assess the available treatment modalities. Gallbladder cancer (GBC) is a rare tumor that causes 165 087 deaths in the world annually. It is the most common cancer of the biliary tract and has a particularly high incidence in Chile, Japan, and northern India. Currently, there is no accurate diagnosis test or effective molecular markers for GBC identification. Several studies have focused on the discovery of genetic alterations in important genes associated with GBC to propose novel diagnosis pathways and to create prognostic profiles. To achieve this, we performed data-mining of GBC in public repositories, harboring 133 samples of GBC, allowing us to describe relevant somatic mutations in important genes and to propose a genetic alteration atlas for GBC. In our results, we reported the 14 most altered genes in GBC: arid1a, arid2, atm, ctnnb1, erbb2, erbb3, kmt2c, kmt2d, kras, pik3ca, smad4, tert, tp53, and znf521 in samples from Japan, the United States, Chile, and China. Missense mutations are common among these genes. The annotations of many mutations revealed their importance in cancer development. The observed annotations mentioned that several mutations found in this repository are probably oncogenic, with a putative loss-of-function. In addition, they are hotspot mutations and are probably linked to poor prognosis in other cancers. We identified another 11 genes, which presented a copy number alteration in gallbladder database samples, which are ccnd1, ccnd3, ccne1, cdk12, cdkn2a, cdkn2b, erbb2, erbb3, kras, mdm2, and myc. The findings reported here can help to detect GBC cancer through the development of systems based on genetic alterations, for example, the development of a mutation panel specifically for GBC diagnosis, as well as the creation of prognostic profiles to accomplish the development of GBC and its prevalence.
Fuente
Cancer Informatics, 19, 1-14Link de Acceso
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doi.org/10.1177/1176935120922154Colecciones
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