A meta-analysis of the C1420T polymorphism in cytosolic serine hydroxymethyltransferase (SHMT1) among Caucasian colorectal cancer populations

Gene-environment interactions and colorectal cancer risk: An umbrella review of systematic reviews and meta-analyses of observational studies

The cause of colorectal cancer (CRC) is multifactorial, involving both genetic variants and environmental risk factors. We systematically searched the MEDLINE, EMBASE, China National Knowledge Infrastructure (CNKI) and Wanfang databases from inception to December 2016, to identify systematic reviews and meta-analyses of observational studies that investigated gene-environment (G×E) interactions in CRC risk. Then, we critically evaluated the cumulative evidence for the G×E interactions using an extension of the Human Genome Epidemiology Network's Venice criteria. Overall, 15 articles reporting systematic reviews of observational studies on 89 G×E interactions, 20 articles reporting meta-analyses of candidate gene- or single-nucleotide polymorphism-based studies on 521 G×E interactions, and 8 articles reporting 33 genome-wide G×E interaction analyses were identified. On the basis of prior and observed scores, only the interaction between rs6983267 (8q24) and aspirin use was found to have a moderate overall credibility score as well as main genetic and environmental effects. Though 5 other interactions were also found to have moderate evidence, these interaction effects were tenuous due to the lack of main genetic effects and/or environmental effects. We did not find highly convincing evidence for any interactions, but several associations were found to have moderate strength of evidence. Our conclusions are based on application of the Venice criteria which were designed to provide a conservative assessment of G×E interactions and thus do not include an evaluation of biological plausibility of an observed joint effect.

Serine hydroxymethyl transferase 1 stimulates pro-oncogenic cytokine expression through sialic acid to promote ovarian cancer tumor growth and progression

High-grade serous (HGS) ovarian cancer accounts for 90% of all ovarian cancer-related deaths. However, factors that drive HGS ovarian cancer tumor growth have not been fully elucidated. In particular, comprehensive analysis of the metabolic requirements of ovarian cancer tumor growth has not been performed. By analyzing The Cancer Genome Atlas mRNA expression data for HGS ovarian cancer patient samples, we observed that six enzymes of the folic acid metabolic pathway were overexpressed in HGS ovarian cancer samples compared with normal ovary samples. Systematic knockdown of all six genes using short hairpin RNAs (shRNAs) and follow-up functional studies demonstrated that serine hydroxymethyl transferase 1 (SHMT1) was necessary for ovarian cancer tumor growth and cell migration in culture and tumor formation in mice. SHMT1 promoter analysis identified transcription factor Wilms tumor 1 (WT1) binding sites, and WT1 knockdown resulted in reduced SHMT1 transcription in ovarian cancer cells. Unbiased large-scale metabolomic analysis and transcriptome-wide mRNA expression profiling identified reduced levels of several metabolites of the amino sugar and nucleotide sugar metabolic pathways, including sialic acid N-acetylneuraminic acid (Neu5Ac), and downregulation of pro-oncogenic cytokines interleukin-6 and 8 (IL-6 and IL-8) as unexpected outcomes of SHMT1 loss. Overexpression of either IL-6 or IL-8 partially rescued SHMT1 loss-induced tumor growth inhibition and migration. Supplementation of culture medium with Neu5Ac stimulated expression of IL-6 and IL-8 and rescued the tumor growth and migratory phenotypes of ovarian cancer cells expressing SHMT1 shRNAs. In agreement with the ovarian tumor-promoting role of Neu5Ac, treatment with Neu5Ac-targeting glycomimetic P-3Fax-Neu5Ac blocked ovarian cancer growth and migration. Collectively, these results demonstrate that SHMT1 controls the expression of pro-oncogenic inflammatory cytokines by regulating sialic acid Neu5Ac to promote ovarian cancer tumor growth and migration. Thus, targeting of SHMT1 and Neu5Ac represents a precision therapy opportunity for effective HGS ovarian cancer treatment.

Approaches for the identification of genetic modifiers of nutrient dependent phenotypes: examples from folate

By combining the sciences of nutrition, bioinformatics, genomics, population genetics, and epidemiology, nutrigenomics is improving our understanding of how diet and nutrient intake can interact with or modify gene expression and disease risk. In this review, we explore various approaches to examine gene–nutrient interactions and the modifying role of nutrient consumption, as they relate to nutrient status and disease risk in human populations. Two common approaches include the use of SNPs in candidate genes to identify their association with nutritional status or disease outcomes, or genome-wide association studies to identify genetic polymorphisms associated with a given phenotype. Here, we examine the results of various gene–nutrient interaction studies, the association of genetic polymorphisms with disease expression, and the identification of nutritional factors that modify gene-dependent disease phenotypes. We have focused on specific examples from investigations of the interactions of folate, B-vitamin consumption, and polymorphisms in the genes of B-vitamin dependent enzymes and their association with disease risk, followed by an examination of the strengths and limitations of the methods employed. We also present suggestions for future studies, including an approach from an on-going large scale study, to examine the interaction of nutrient intake and genotypic variation and their impact on nutritional status.

Methionine synthase A2756G polymorphism and breast cancer risk: an up-to-date meta-analysis

The methionine synthase (MTR) gene polymorphism A2756G has been linked to the risk of developing breast cancer, but the available results were inconsistent and underpowered. To derive a more precise estimation of the association between A2756G and breast cancer risk, an updated meta-analysis of 16 available studies with 9866 cases and 11,702 controls estimating the association between MTR A2756G and breast cancer risk was conducted. The quality of these studies was generally good except 2 studies with a lowest score 4 according to the Newcastle-Ottawa Scale (NOS). The results suggested that there is no significant association between A2756G and breast cancer risk in overall results. In the stratified analysis by ethnicity, source of controls (population or hospital-based), Hardy-Weinberg equilibrium (HWE) in controls, sample size (≥1000 and <1000 subjects), and menopausal status, the 2756G allele was associated with a decreased risk in Caucasians, PB (population-based) subgroup, and large studies. But the associations disappeared after removing the studies not in HWE. On the contrary, an increased risk was found in small studies. In conclusion, the findings suggest that MTR A2756G polymorphism is not associated with altered susceptibility to breast cancer, while the observed decreased risk in Caucasians, PB subgroup, and large studies and increased risk in small studies may be due to selection bias or other unknown factors.