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HU Di, SHUI Yifang, MIAO Keke, LI Mengquan. Mendelian Randomized Study of Protective Effect of Statins on Breast Cancer[J]. Cancer Research on Prevention and Treatment, 2025, 52(2): 165-171. DOI: 10.3971/j.issn.1000-8578.2025.24.0654
Citation: HU Di, SHUI Yifang, MIAO Keke, LI Mengquan. Mendelian Randomized Study of Protective Effect of Statins on Breast Cancer[J]. Cancer Research on Prevention and Treatment, 2025, 52(2): 165-171. DOI: 10.3971/j.issn.1000-8578.2025.24.0654

Mendelian Randomized Study of Protective Effect of Statins on Breast Cancer

Funding: Henan Provincial Medical Science and Technology Tackling Program Project (No. LHGJ20220436)
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  • Received Date: July 07, 2024
  • Revised Date: September 25, 2024
  • Accepted Date: November 17, 2024
  • Available Online: December 04, 2024
  • Objective 

    To genetically investigate the protective effects of statins on breast cancer.

    Methods 

    Instrumental variables for the statin target gene HMGCR and five other cholesterol-regulated genes (LDLR, PCSK9, ABCG8, APOB, and NPC1L1) were obtained from previous expression quantitative trait locus (eQTL) studies. Cholesterol-regulated genes predicted by these instrumental variables served as the exposure factors. Mendelian randomization based on pooled data (SMR) was conducted to explore the genetic effects of exposure factors on the incidence risk of all breast cancers, ER+ breast cancer, and ER-breast cancer. Instrumental variables for total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) were derived from a previous human genome-wide association study and restricted to be chromosomally located within 100 kb of the above cholesterol regulatory genes; the instrumental variables could predict TC, LDL-C, or non-HDL-C levels under the regulation of the abovementioned cholesterol-associated genes which were used as exposure factors. Two-sample Mendelian randomization (IVW, MR-PRESSO, and MR-Egger) was used to explore the genetic effects of exposure factors on the risk of all breast cancers, ER+ breast cancer, and ER− breast cancer.

    Results 

    SMR analysis reported that elevated HMGCR expression was significantly associated with the increased incidence risk of all breast cancers and ER+ breast cancer (P=0.044 and P=0.039, respectively) but not with the change in incidence risk of ER− breast cancer (P=0.190); the other five regulatory genes were not significantly correlated with the change in incidence risk of all breast cancers, ER+ breast cancer, and ER− breast cancer (all P>0.05). IVW analysis reported that under the regulation of HMGCR, elevated levels of peripheral TC, LDL-C, and non-HDL-C significantly increased the incidence risk of all breast cancers (P=1.160e-05, P=1.248e-05, and P=1.869e-05) and the incidence risk of ER+ breast cancer (P=3.181e-04, P=2.231e-04, and P=3.520e-04), but they were not associated with a change in the incidence risk of ER− breast cancer (P=0.062, P=0.133, and P=0.055). The results of MR-PRESSO and MR-Egger analyses supported the IVW results.

    Conclusion 

    Statins could reduce the incidence risk of ER+ breast cancer at the genetic level, but there is no such protective effects on ER− breast cancer.

  • Competing interests: The authors declare that they have no competing interests.

  • [1]
    Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263. doi: 10.3322/caac.21834
    [2]
    胡志强, 游伟程, 潘凯枫, 等. 中、美两国癌症流行特征分析——《2023美国癌症统计报告》解读[J]. 科技导报, 2023, 41(18): 18-28. [Hu ZQ, You WC, Pan KF, et al. Epidemiological characteristics of cancers in China and America: Interpretation of the report of American cancer statistics, 2023[J]. Ke Ji Dao Bao, 2023, 41(18): 18-28.]

    Hu ZQ, You WC, Pan KF, et al. Epidemiological characteristics of cancers in China and America: Interpretation of the report of American cancer statistics, 2023[J]. Ke Ji Dao Bao, 2023, 41(18): 18-28.
    [3]
    Lei S, Zheng R, Zhang S, et al. Breast cancer incidence and mortality in women in China: temporal trends and projections to 2030[J]. Cancer Biol Med, 2021, 18(3): 900-909. doi: 10.20892/j.issn.2095-3941.2020.0523
    [4]
    Waks AG, Winer EP. Breast Cancer Treatment: A Review[J]. JAMA, 2019, 321(3): 288-300. doi: 10.1001/jama.2018.19323
    [5]
    Narii N, Zha L, Komatsu M, et al. Cholesterol and breast cancer risk: a cohort study using health insurance claims and health checkup databases[J]. Breast Cancer Res Treat, 2023, 199(2): 315-322. doi: 10.1007/s10549-023-06917-z
    [6]
    Wang Y, Liu F, Sun L, et al. Association between human blood metabolome and the risk of breast cancer[J]. Breast Cancer Res, 2023, 25(1): 9. doi: 10.1186/s13058-023-01609-4
    [7]
    Ben Hassen C, Goupille C, Vigor C, et al. Is cholesterol a risk factor for breast cancer incidence and outcome?[J]. J Steroid Biochem Mol Biol, 2023, 232: 106346. doi: 10.1016/j.jsbmb.2023.106346
    [8]
    Ricco N, Kron SJ. Statins in Cancer Prevention and Therapy[J]. Cancers (Basel), 2023, 15(15): 3948. doi: 10.3390/cancers15153948
    [9]
    Zhao G, Ji Y, Ye Q, et al. Effect of statins use on risk and prognosis of breast cancer: a meta-analysis[J]. Anticancer Drugs, 2022, 33(1): e507-e518. doi: 10.1097/CAD.0000000000001151
    [10]
    Abdul-Rahman T, Bukhari SMA, Herrera EC, et al. Lipid Lowering Therapy: An Era Beyond Statins[J]. Curr Probl Cardiol, 2022, 47(12): 101342. doi: 10.1016/j.cpcardiol.2022.101342
    [11]
    Miziak P, Baran M, Błaszczak E, et al. Estrogen Receptor Signaling in Breast Cancer[J]. Cancers (Basel), 2023, 15(19): 4689. doi: 10.3390/cancers15194689
    [12]
    Võsa U, Claringbould A, Westra HJ, et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression[J]. Nat Genet, 2021, 53(9): 1300-1310. doi: 10.1038/s41588-021-00913-z
    [13]
    GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues[J]. Science, 2020, 369(6509): 1318-1330.
    [14]
    Graham SE, Clarke SL, Wu KH, et al. The power of genetic diversity in genome-wide association studies of lipids[J]. Nature, 2021, 600(7890): 675-679. doi: 10.1038/s41586-021-04064-3
    [15]
    Michailidou K, Lindström S, Dennis J, et al. Association analysis identifies 65 new breast cancer risk loci[J]. Nature, 2017, 551(7678): 92-94. doi: 10.1038/nature24284
    [16]
    Zhu Z, Zhang F, Hu H, et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets[J]. Nat Genet, 2016, 48(5): 481-487. doi: 10.1038/ng.3538
    [17]
    刘佳, 周星彤, 孙强. 多灶性/多中心性乳腺癌研究进展[J]. 协和医学杂志, 2024, 15(3): 632-641. [Liu J, Zhou XT, Sun Q. Research Progress of Multifocal/Multicentric Breast Cancer[J]. Xie He Yi Xue Za Zhi, 2024, 15(3): 632-641.] doi: 10.12290/xhyxzz.2023-0562

    Liu J, Zhou XT, Sun Q. Research Progress of Multifocal/Multicentric Breast Cancer[J]. Xie He Yi Xue Za Zhi, 2024, 15(3): 632-641. doi: 10.12290/xhyxzz.2023-0562
    [18]
    何国珍, 刘晓, 员晓云, 等. 中医药防治乳腺癌相关信号通路的研究进展[J/OL]. 中华中医药学刊: 1-19 [2024-05-06]. http://kns.cnki.net/kcms/detail/21.1546.R.20240506.1130.002.html. [He GZ, Liu X, Yun XY, et al. Research progress of signaling pathways related to the prevention and treatment of breast cancer by traditional Chinese medicine[J/OL]. Zhonghua Zhong Yi Yao Xue Kan: 1-19 [2024-05-06]. http://kns.cnki.net/kcms/detail/21.1546.R.20240506.1130.002.html.]

    He GZ, Liu X, Yun XY, et al. Research progress of signaling pathways related to the prevention and treatment of breast cancer by traditional Chinese medicine[J/OL]. Zhonghua Zhong Yi Yao Xue Kan: 1-19 [2024-05-06]. http://kns.cnki.net/kcms/detail/21.1546.R.20240506.1130.002.html.
    [19]
    Murto MO, Simolin N, Arponen O, et al. Statin Use, Cholesterol Level, and Mortality Among Females With Breast Cancer[J]. JAMA Netw Open, 2023, 6(11): e2343861. doi: 10.1001/jamanetworkopen.2023.43861
    [20]
    Watson R, Tulk A, Erdrich J. The Link Between Statins and Breast Cancer in Mouse Models: A Systematic Review[J]. Cureus, 2022, 14(11): e31893.
    [21]
    O'Grady S, Crown J, Duffy MJ. Statins inhibit proliferation and induce apoptosis in triple-negative breast cancer cells[J]. Med Oncol, 2022, 39(10): 142. doi: 10.1007/s12032-022-01733-9
    [22]
    Bjarnadottir O, Romero Q, Bendahl PO, et al. Targeting HMG-CoA reductase with statins in a window-of-opportunity breast cancer trial[J]. Breast Cancer Res Treat, 2013, 138(2): 499-508. doi: 10.1007/s10549-013-2473-6
    [23]
    Goda AE, Elsisi AE, Sokkar SS, et al. Enhanced in vivo targeting of estrogen receptor alpha signaling in murine mammary adenocarcinoma by nilotinib/rosuvastatin novel combination[J] Toxicol Appl Pharmacol, 2020, 404: 115185.
    [24]
    Kamal A, Boerner J, Assad H, et al. The Effect of Statins on Markers of Breast Cancer Proliferation and Apoptosis in Women with In Situ or Early-Stage Invasive Breast Cancer[J]. Int J Mol Sci, 2024, 25(17): 9587. doi: 10.3390/ijms25179587
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