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单核苷酸多态性与乳腺癌预后的关系及发病机制。

Relationships between SNPs and prognosis of breast cancer and pathogenic mechanism.

机构信息

Department of Breast Surgery, Affiliated Tumor Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou, China.

Department of Oncology, Affiliated Tumor Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou, China.

出版信息

Mol Genet Genomic Med. 2019 Sep;7(9):e871. doi: 10.1002/mgg3.871. Epub 2019 Jul 17.

Abstract

BACKGROUND

Association between several single-nucleotide polymorphisms (SNPs) and breast cancer risk has been identified through genome-wide association studies (GWAS), but little is known about their significance in patients' prognosis. We screened SNPs which were related to the prognosis of breast cancer in Henan Han population, analyzed relevant genes by bioinformatics in database, and further constructed the genetic regulatory network involved in the pathogenesis of breast cancer.

METHODS

We evaluated five SNPs in 232 cases of breast cancer at the Affiliated Tumor Hospital of Zhengzhou University. Relationships between five SNPs, clinical prognostic indicators, and disease-free survival (DFS) were evaluated by Kaplan-Meier analysis and Cox proportional hazards model. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of genes and Genome (KEGG) analysis were carried out to preliminarily establish genetic regulation network model of breast cancer. Bayesian algorithm was used to optimize the model.

RESULTS

The multivariate Cox proportional hazards model confirmed that SNP rs3803662 (TOX3/TNRC9) had correlation with DFS independently. In the multivariate Cox proportional hazards model, compared with GA/AA, GG increased the recurrent risk of breast cancer (p = .021, hazard ratio [HR] = 2.914). GO analysis showed that the function of TOX3/TNRC9 included biological_process, molecular_function, and cellular_component. According to KEGG signaling pathway database, the map of breast cancer-related gene regulatory network was obtained. IGF-IGF1R-PI3K-Akt-mTOR-S6K was the best possible pathway for the differentiation of breast cancer cells in this network and ER-TOX3/TNRC9 was the best possible pathway for the survival of tumor cells in this network by Bayesian theorem optimization.

CONCLUSIONS

SNP rs3803662 (TOX3/TNRC9) is an independent prognostic factor for breast cancer in Henan Han Population. ER-TOX3/TNRC9 is the best possible pathway involved in the pathogenesis of breast cancer.

摘要

背景

通过全基因组关联研究(GWAS)已经确定了几种单核苷酸多态性(SNP)与乳腺癌风险之间的关联,但对于它们在患者预后中的意义知之甚少。我们筛选了与河南汉族人群乳腺癌预后相关的 SNP,在数据库中通过生物信息学分析相关基因,并进一步构建了涉及乳腺癌发病机制的遗传调控网络。

方法

我们评估了郑州大学附属肿瘤医院 232 例乳腺癌患者的 5 个 SNP。通过 Kaplan-Meier 分析和 Cox 比例风险模型评估 5 个 SNP 与临床预后指标和无病生存(DFS)的关系。进行基因本体论(GO)功能注释和京都基因与基因组百科全书(KEGG)分析,初步建立乳腺癌遗传调控网络模型。采用贝叶斯算法对模型进行优化。

结果

多变量 Cox 比例风险模型证实,SNP rs3803662(TOX3/TNRC9)与 DFS 独立相关。在多变量 Cox 比例风险模型中,与 GA/AA 相比,GG 增加了乳腺癌的复发风险(p=0.021,风险比[HR]=2.914)。GO 分析表明,TOX3/TNRC9 的功能包括生物学过程、分子功能和细胞成分。根据 KEGG 信号通路数据库,获得了乳腺癌相关基因调控网络的图谱。IGF-IGF1R-PI3K-Akt-mTOR-S6K 是该网络中乳腺癌细胞分化的最佳可能途径,ER-TOX3/TNRC9 是该网络中肿瘤细胞存活的最佳可能途径,通过贝叶斯定理优化得到。

结论

SNP rs3803662(TOX3/TNRC9)是河南汉族人群乳腺癌的独立预后因素。ER-TOX3/TNRC9 是参与乳腺癌发病机制的最佳可能途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/076a/6732281/0482a53fa6ec/MGG3-7-e871-g001.jpg

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