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Multi-Omic Meta-Analysis of Transcriptomes and the Bibliome Uncovers Novel Hypoxia-Inducible Genes.

ABSTRACT: Hypoxia is a condition in which cells, tissues, or organisms are deprived of sufficient oxygen supply. Aerobic organisms have a hypoxic response system, represented by hypoxia-inducible factor 1-α (HIF1A), to adapt to this condition. Due to publication bias, there has been little focus on genes other than well-known signature hypoxia-inducible genes. Therefore, in this study, we performed a meta-analysis to identify novel hypoxia-inducible genes. We searched publicly available transcriptome databases to obtain hypoxia-related experimental data, retrieved the metadata, and manually curated it. We selected the genes that are differentially expressed by hypoxic stimulation, and evaluated their relevance in hypoxia by performing enrichment analyses. Next, we performed a bibliometric analysis using gene2pubmed data to examine genes that have not been well studied in relation to hypoxia. Gene2pubmed data provides information about the relationship between genes and publications. We calculated and evaluated the number of reports and similarity coefficients of each gene to HIF1A, which is a representative gene in hypoxia studies. In this data-driven study, we report that several genes that were not known to be associated with hypoxia, including the G protein-coupled receptor 146 gene, are upregulated by hypoxic stimulation.

SUBMITTER: Ono Y

PROVIDER: S-EPMC8160971 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe results from the published studies on the association between hypoxia-inducible factor -1alpha (HIF-1alpha) polymorphisms and cancer risk are conflicting. In this meta-analysis, we aimed to investigate the association between HIF-1alpha 1772 C/T and 1790 G/A polymorphisms and cancer.MethodsThe meta-analysis for 1772 C/T polymorphism included 4131 cancer cases and 5387 controls, and for 1790 G/A polymorphism included 2058 cancer cases and 3026 controls. Allelic and genotypic comparisons between cases and controls were evaluated. Subgroup analyses by cancer types, ethnicity, and gender were also performed. We included prostate cancer in male subgroup, and female specific cancers in female subgroup.ResultsFor the 1772 C/T polymorphism, the analysis showed that the T allele and genotype TT were significantly associated with higher cancer risk: odds ratio (OR) = 1.29 [95% confidence interval (CI, 1.01, 1.65)], P = 0.04, P(heterogeneity) < 0.00001, and OR = 2.18 [95% CI (1.32, 3.62)], P = 0.003, P(heterogeneity) = 0.02, respectively. The effect of the genotype TT on cancer especially exists in Caucasians and female subjects: OR = 2.40 [95% CI (1.26, 4.59)], P = 0.008, P(heterogeneity) = 0.02, and OR = 3.60 [95% CI (1.17, 11.11)], P = 0.03, P(heterogeneity) = 0.02, respectively. For the 1790 G/A polymorphism, the pooled ORs for allelic frequency comparison and dominant model comparison suggested a significant association of 1790 G/A polymorphism with a decreased breast cancer risk: OR = 0.28 [95% CI (0.08, 0.90)], P = 0.03, P(heterogeneity) = 0.45, and OR = 0.29 [95% CI (0.09, 0.97)], P = 0.04, P(heterogeneity) = 0.41, respectively. The frequency of the HIF-1alpha 1790 A allele was very low and only two studies were included in the breast cancer subgroup.ConclusionsOur meta-analysis suggests that the HIF-1alpha 1772 C/T polymorphism is significantly associated with higher cancer risk, and 1790 G/A polymorphism is significantly associated with decreased breast cancer risk. The effect of the 1772 C/T polymorphism on cancer especially exists in Caucasians and female subjects. Only female specific cancers were included in female subgroup, which indicates that the 1772 C/T polymorphism is significantly associated with an increased risk for female specific cancers. The association between the 1790 G/A polymorphism and lower breast cancer risk could be due to chance.

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Multi-Omic Meta-Analysis of Transcriptomes and the Bibliome Uncovers Novel Hypoxia-Inducible Genes.

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