Research Paper Volume 13, Issue 5 pp 7465—7480
SNPs within microRNA binding sites and the prognosis of breast cancer
- 1 Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, People’s Republic of China
- 2 Department of Infection Control, Tianjin Huanhu Hospital, Tianjin 300350, People’s Republic of China
- 3 Department of Epidemiology and Biostatistics, West China School of Public Health, Sichuan University, Sichuan 610041, People’s Republic of China
- 4 Department of Cancer Biobank, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, National Clinical Research Centre of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, People’s Republic of China
Received: October 31, 2020 Accepted: December 29, 2020 Published: February 26, 2021
https://doi.org/10.18632/aging.202612How to Cite
Copyright: © 2021 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Single nucleotide polymorphisms (SNPs) within microRNA binding sites can affect the binding of microRNA to mRNA and regulate gene expression, thereby contributing to cancer prognosis. Here we performed a two-stage study of 2647 breast cancer patients to explore the association between SNPs within microRNA binding sites and breast cancer prognosis. In stage I, we genotyped 192 SNPs within microRNA binding sites using the Illumina Goldengate platform. In stage II, we validated SNPs associated with breast cancer prognosis in another dataset using the TaqMan platform. We identified 8 SNPs significantly associated with breast cancer prognosis in stage I (P<0.05), and only rs10878441 was statistically significant in stage II (AA vs CC, HR=2.21, 95% CI: 1.11-4.42, P=0.024). We combined the data from stage I and stage II, and found that, compared with rs10878441 AA genotype, CC genotype was associated with poor survival of breast cancer (HR=2.19, 95% CI: 1.30-3.70, P=0.003). Stratified analyses demonstrated that rs10878441 was related to breast cancer prognosis in grade II and lymph node-negative patients (P<0.05). The Leucine-rich repeat kinase 2 (LRRK2) rs10878441 CC genotype is associated with poor prognosis of breast cancer in a Chinese population and may be used as a potential prognostic biomarker for breast cancer.
• The LRRK2 rs10878441 CC genotype is associated with poor prognosis of breast cancer in a Chinese population.
• Stratified analyses demonstrated that rs10878441 was related to breast cancer prognosis in grade II patients and lymph node-negative patients.
Abbreviations
SNP: single nucleotide polymorphisms; 3’UTR: 3’untranslated region; MAF: minor genotype frequency; OS: overall survival; DFS: disease-free survival; HR: hazard ratio; CI: confidence interval; BMI: body mass index; BBD: benign breast disease; ER: estrogen receptor; PR: progestogen receptor; HER2: human epidermal growth factor receptor 2; non-IDC: non-invasive ductal carcinoma; IDC: invasive ductal carcinoma; RAD51: RAD51 recombinase; ITGB4: Integrin subunit beta 4; RYR3: Ryanodine receptor 3; SET8: KMT5A, Lysine methyltransferase 5A; NMT1: N-Myristoyltransferase 1; KIF13B: Kinesin family member 13B; PREPL: Prolyl endopeptidase like; MKNK1: MAPK interacting serine/threonine kinase 1; LRRK2: Leucine-rich repeat kinase 2; GREM1: Gremlin 1; ST8SIA4: ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 4; KRAS: Kirsten rat sarcoma viral oncogene; HIF1α: Hypoxia inducible factor1α.