Gastric cancer is one of the leading causes of cancer mortality in the world. Its development
is associated with factors related to lifestyle and genetic alterations that can modify genes
and important biosynthetic and metabolic pathways that help maintaining cellular and tissue
integrity. One of the main cancer research objectives is identify genes and mutations that
may be used as genetic markers and potential therapeutic targets. Studies with genes related
to the pathway of steroid hormones proteins have already identified polymorphisms that may
be related to the risk of cancer. Because it is an important route for physiological and
pathological processes identification of genetic polymorphisms in this and cholesterol
biosynthesis pathway may contribute to the understanding of gastric carcinogenesis.
Therefore, we performed a comprehensive bioinformatics analysis of transcriptome datasets
from gastric tissues with and without cancer, in order to identify SNPs in genes associated
to enzymes of biosynthetic pathways of steroid hormones, cholesterol and progesterone
receptor that may be related to gastric cancer. The analysis was performed using the Galaxy
Platform, the Bowtie alignment tool and the Provean software for functional analysis of
variations. Deleterious mutations have been identified in CYP51A1, DHCR24 and SQLE
genes in the steroid hormone biosynthesis pathway, and in CYP3A5, HSD17B12, UGT1A1,
UGT1A5, UGT1A6 and AKR1C3 genes in the cholesterol biosynthetic pathway. The
CYP3A5 gene had the highest number of deleterious SNPs. These results indicate a possible
participation of genes analyzed in the molecular mechanisms involved in the development
of gastric cancer.
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