ArticlePloS one2011
Genetic variants in TGF-β pathway are associated with ovarian cancer risk.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.
- Analyzing association of the XRCC3 gene polymorphism with ovarian cancer risk.BioMed research international · 2014Pooled it
- Analyze association of the progesterone receptor gene polymorphism PROGINS with ovarian cancer risk.Molecular biology reports · 2013Pooled it
- The GADD45A (1506T>C) Polymorphism Is Associated with Ovarian Cancer Susceptibility and Prognosis.PloS one · 2015Trial
- Identification of High-Order Single-Nucleotide Polymorphism Barcodes in Breast Cancer Using a Hybrid Taguchi-Genetic Algorithm: Case-Control Study.JMIR medical informatics · 2020Article
- Article
- Single nucleotide polymorphism of transforming growth factor-β1 and interleukin-6 as risk factors for ovarian cancer.Central-European journal of immunology · 2020Article
- Assessing the Effect of SNPs on Litter Traits in Pigs.Scientifica · 2020Article
- Analysis of the association between the XRCC2 rs3218536 polymorphism and ovarian cancer risk.Archives of medical science : AMS · 2020Article
- A 19‑miRNA Support Vector Machine classifier and a 6‑miRNA risk score system designed for ovarian cancer patients.Oncology reports · 2019Article
- Genetic variants in telomere-maintenance genes are associated with ovarian cancer risk and outcome.Journal of cellular and molecular medicine · 2017Article
- The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach.International journal of genomics · 2017Article
- Genetic Polymorphisms of TGFB1, TGFBR1, SNAI1 and TWIST1 Are Associated with Endometrial Cancer Susceptibility in Chinese Han Women.PloS one · 2016Article
- Using distance covariance for improved variable selection with application to learning genetic risk models.Statistics in medicine · 2015Article
- Double-bottom chaotic map particle swarm optimization based on chi-square test to determine gene-gene interactions.BioMed research international · 2014Article
- Article
- Genetic variants in the fibroblast growth factor pathway as potential markers of ovarian cancer risk, therapeutic response, and clinical outcome.Clinical chemistry · 2014Article
- Article
- SNPs in the TGF-β signaling pathway are associated with increased risk of brain metastasis in patients with non-small-cell lung cancer.PloS one · 2012Article
- Article
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
The transforming growth factor-β (TGF-β) signaling pathway is involved in a diverse array of cellular processes responsible for tumorigenesis. In this case-control study, we applied a pathway-based approach to evaluate single-nucleotide polymorphisms (SNPs) in the TGF-β signaling pathway as predictors of ovarian cancer risk. We systematically genotyped 218 SNPs from 21 genes in the TGF-β signaling pathway in 417 ovarian cancer cases and 417 matched control subjects. We analyzed the associations of these SNPs with ovarian cancer risk, performed haplotype analysis and identified potential cumulative effects of genetic variants. We also performed analysis to identify higher-order gene-gene interactions influencing ovarian cancer risk. Individual SNP analysis showed that the most significant SNP was SMAD6: rs4147407, with an adjusted odds ratio (OR) of 1.60 (95% confidence interval [CI], 1.14-2.24, P = 0.0066). Cumulative genotype analysis of 13 SNPs with significant main effects exhibited a clear dose-response trend of escalating risk with increasing number of unfavorable genotypes. In gene-based analysis, SMAD6 was identified as the most significant gene associated with ovarian cancer risk. Haplotype analysis further revealed that two haplotype blocks within SMAD6 were significantly associated with decreased ovarian cancer risk, as compared to the most common haplotype. Gene-gene interaction analysis further categorized the study population into subgroups with different ovarian cancer risk. Our findings suggest that genetic variants in the TGF-β signaling pathway are associated with ovarian cancer risk and may facilitate the identification of high-risk subgroups in the general population.
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