Skip to main content

Advertisement

SpringerLink
Log in

Circulating lipids, lipid-lowering drug targets, and breast cancer risk: Comprehensive evidence from Mendelian randomization and summary data-based Mendelian randomization

  • Original Paper
  • Published:
Cancer Causes & Control Aims and scope Submit manuscript

Abstract

Background

Breast cancer (BC) is the most common and fatal cancer among women, yet the causal relationship between circulating lipids, lipid-lowering drugs, and BC remains unclear.

Methods

Mendelian randomization (MR) and summary data-based MR (SMR) analysis are used to explore the causal relationship between plasma lipids, lipid-lowering drug targets, and BC.

Results

The result of MR suggested that per mg/dL higher levels of LDL-C (OR = 1.045, FDR = 0.023), HDL-C (OR = 1.079, FDR = 0.003), TC (OR = 1.043, FDR = 0.026), and APOA-I (OR = 1.085, FDR = 2.64E-04) were associated with increased BC risk, while TG was associated with reduced BC risk (OR = 0.926, FDR = 0.003). Per mg/dL higher levels of HDL-C (OR = 1.080, FDR = 0.011) and APOA-I (OR = 1.083, FDR = 0.002) were associated with increased ER+BC risk, while TG was associated with reduced ER+BC risk (OR = 0.909, FDR = 0.002). For every per 1 mg/dL decrease in LDL, HMGCR (OR: 0.839; FDR = 0.016), NPC1L1 (OR: 0.702; FDR = 0.004), and PCSK9 (OR: 0.916; FDR = 0.026) inhibition were associated with reduced BC risk, whereas CETP inhibition (OR: 1.194; FDR = 0.026) was associated with increased BC risk. For every per 1 mg/dL decrease in LDL, HMGCR (OR: 0.822; FDR = 0.023), NPC1L1 (OR: 0.633; FDR = 2.37E-03), and APOB inhibition (OR: 0.816; FDR = 1.98E-03) were associated with decreased ER−BC risk, while CETP inhibition (OR: 1.465; FDR = 0.011) was associated with increased ER−BC risk. SMR analysis indicated that HMGCR was associated with increased BC risk (OR: 1.112; p = 0.044).

Conclusion

Lipids are associated with the BC risk, and lipid-lowering drugs targets HMGCR, NPC1L1, PCSK9, and APOB may be effective strategies for preventing BC. However, lipid-lowering drugs target CETP may potentially increase BC risk.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

The data for this research is sourced from public databases, and the download links are presented in Supplementary Table 1.

References

  1. Tabassum S, Ghosh MK (2023) DEAD-box RNA helicases with special reference to p68: unwinding their biology, versatility, and therapeutic opportunity in cancer. Genes Dis 10(4):1220–1241

    Article  CAS  PubMed  Google Scholar 

  2. Sung H et al (2021) Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71(3):209–249

    Article  PubMed  Google Scholar 

  3. Burstein HJ et al (2021) Customizing local and systemic therapies for women with early breast cancer: the St. Gallen International Consensus Guidelines for treatment of early breast cancer 2021. Ann Oncol 32(10):1216–1235

    Article  CAS  PubMed  Google Scholar 

  4. Kitahara CM et al (2011) Total cholesterol and cancer risk in a large prospective study in Korea. J Clin Oncol 29(12):1592–1598

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Amerizadeh A et al (2022) An updated systematic review and meta-analysis on association of serum lipid profile with risk of breast cancer incidence. Int J Prev Med 13:142

    PubMed  PubMed Central  Google Scholar 

  6. Martin LJ et al (2015) Serum lipids, lipoproteins, and risk of breast cancer: a nested case-control study using multiple time points. J Natl Cancer Inst. https://doi.org/10.1093/jnci/djv032

    Article  PubMed  PubMed Central  Google Scholar 

  7. Kumar V et al (2015) A comparitive study to evaluate the role of serum lipid levels in aetiology of carcinoma breast. J Clin Diagn Res 9(2):Pc01-3

    PubMed  PubMed Central  Google Scholar 

  8. Dos Rodrigues Santos C et al (2014) Plasma level of LDL-cholesterol at diagnosis is a predictor factor of breast tumor progression. BMC Cancer 14:132

    Article  Google Scholar 

  9. Ni H, Liu H, Gao R (2015) Serum lipids and breast cancer risk: a meta-analysis of prospective cohort studies. PLoS ONE 10(11):e0142669

    Article  PubMed  PubMed Central  Google Scholar 

  10. Llanos AA et al (2012) Cholesterol, lipoproteins, and breast cancer risk in African American women. Ethn Dis 22(3):281–287

    PubMed  Google Scholar 

  11. His M et al (2014) Prospective associations between serum biomarkers of lipid metabolism and overall, breast and prostate cancer risk. Eur J Epidemiol 29(2):119–132

    Article  CAS  PubMed  Google Scholar 

  12. Chandler PD et al (2016) Lipid biomarkers and long-term risk of cancer in the Women’s Health Study. Am J Clin Nutr 103(6):1397–1407

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Borgquist S et al (2016) Apolipoproteins, lipids and risk of cancer. Int J Cancer 138(11):2648–2656

    Article  CAS  PubMed  Google Scholar 

  14. Cauley JA et al (2003) Lipid-lowering drug use and breast cancer in older women: a prospective study. J Womens Health (Larchmt) 12(8):749–756

    Article  PubMed  Google Scholar 

  15. Beckwitt CH et al (2018) Statin drugs to reduce breast cancer recurrence and mortality. Breast Cancer Res 20(1):144

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. McDougall JA et al (2013) Long-term statin use and risk of ductal and lobular breast cancer among women 55 to 74 years of age. Cancer Epidemiol Biomarkers Prev 22(9):1529–1537

    Article  PubMed  PubMed Central  Google Scholar 

  17. Alikhani N et al (2013) Mammary tumor growth and pulmonary metastasis are enhanced in a hyperlipidemic mouse model. Oncogene 32(8):961–967

    Article  MathSciNet  CAS  PubMed  Google Scholar 

  18. Cannon CP et al (2015) Ezetimibe added to statin therapy after acute coronary syndromes. N Engl J Med 372(25):2387–2397

    Article  CAS  PubMed  Google Scholar 

  19. Huang J et al (2023) Impacts of ezetimibe on risks of various types of cancers: a meta-analysis and systematic review. Eur J Cancer Prev 32(1):89–97

    Article  PubMed  Google Scholar 

  20. Ference BA et al (2019) Mendelian randomization study of ACLY and cardiovascular disease. N Engl J Med 380(11):1033–1042

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Chauquet S et al (2021) Association of antihypertensive drug target genes with psychiatric disorders: A mendelian randomization study. JAMA Psychiat 78(6):623–631

    Article  Google Scholar 

  22. Bi Y et al (2023) Lipids, lipid-modifying drug target genes and migraine: a Mendelian randomization study. J Headache Pain 24(1):112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Bakker MK et al (2023) Anti-epileptic drug target perturbation and intracranial aneurysm risk: Mendelian randomization and colocalization study. Stroke 54(1):208–216

    Article  CAS  PubMed  Google Scholar 

  24. Nowak C, Ärnlöv J (2018) A Mendelian randomization study of the effects of blood lipids on breast cancer risk. Nat Commun 9(1):3957

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  25. Johnson KE et al (2020) The relationship between circulating lipids and breast cancer risk: a Mendelian randomization study. PLoS Med 17(9):e1003302

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Sun L et al (2022) Associations of genetically proxied inhibition of HMG-CoA reductase, NPC1L1, and PCSK9 with breast cancer and prostate cancer. Breast Cancer Res 24(1):12

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Liu X et al (2023) Association between trans fatty acids and COVID-19: a multivariate Mendelian randomization study. J Med Virol 95(2):e28455

    Article  CAS  PubMed  Google Scholar 

  28. Michailidou K et al (2017) Association analysis identifies 65 new breast cancer risk loci. Nature 551(7678):92–94

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  29. Papadimitriou N et al (2020) Physical activity and risks of breast and colorectal cancer: a Mendelian randomisation analysis. Nat Commun 11(1):597

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. Bowden J et al (2016) Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-egger regression: the role of the I2 statistic. Int J Epidemiol 45(6):1961–1974

    PubMed  PubMed Central  Google Scholar 

  31. Zhu Z et al (2016) Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet 48(5):481–487

    Article  CAS  PubMed  Google Scholar 

  32. Touvier M et al (2015) Cholesterol and breast cancer risk: a systematic review and meta-analysis of prospective studies. Br J Nutr 114(3):347–357

    Article  CAS  PubMed  Google Scholar 

  33. Narii N et al (2023) Cholesterol and breast cancer risk: a cohort study using health insurance claims and health checkup databases. Breast Cancer Res Treat 199(2):315–322

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wu J et al (2021) Association between serum lipids and breast cancer risk in premenopausal women: systematic review and meta-analysis. J Int Med Res 49(11):3000605211061033

    Article  ADS  CAS  PubMed  Google Scholar 

  35. Chowdhury FA et al (2021) Association of hyperlipidemia with breast cancer in Bangladeshi women. Lipids Health Dis 20(1):52

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Chang SJ et al (2007) The association between lipid profiles and breast cancer among Taiwanese women. Clin Chem Lab Med 45(9):1219–1223

    Article  CAS  PubMed  Google Scholar 

  37. Borgquist S et al (2008) HMG-CoA reductase expression in breast cancer is associated with a less aggressive phenotype and influenced by anthropometric factors. Int J Cancer 123(5):1146–1153

    Article  CAS  PubMed  Google Scholar 

  38. Singh R et al (2015) MicroRNA-195 inhibits proliferation, invasion and metastasis in breast cancer cells by targeting FASN, HMGCR, ACACA and CYP27B1. Sci Rep 5:17454

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  39. Bjarnadottir O et al (2020) Statin use, HMGCR expression, and breast cancer survival - The Malmö Diet and Cancer Study. Sci Rep 10(1):558

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  40. Virani SS et al (2023) 2023 AHA/ACC/ACCP/ASPC/NLA/PCNA guideline for the management of patients with chronic coronary disease: a report of the American heart association/American college of cardiology joint committee on clinical practice guidelines. J Am Coll Cardiol 82(9):833–955

    Article  PubMed  Google Scholar 

  41. Anothaisintawee T et al (2016) Effect of lipophilic and hydrophilic statins on breast cancer risk in Thai women: a cross-sectional study. J Cancer 7(9):1163–1168

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Zhang R et al (2022) The role of NPC1L1 in cancer. Front Pharmacol 13:956619

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Kwon RJ et al (2021) Expression and prognostic significance of Niemann-Pick C1-Like 1 in colorectal cancer: a retrospective cohort study. Lipids Health Dis 20(1):104

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. He J et al (2015) NPC1L1 knockout protects against colitis-associated tumorigenesis in mice. BMC Cancer 15:189

    Article  PubMed  PubMed Central  Google Scholar 

  45. Guillaumond F et al (2015) Cholesterol uptake disruption, in association with chemotherapy, is a promising combined metabolic therapy for pancreatic adenocarcinoma. Proc Natl Acad Sci U S A 112(8):2473–2478

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  46. Nicolle R et al (2017) Pancreatic adenocarcinoma therapeutic targets revealed by tumor-stroma cross-talk analyses in patient-derived xenografts. Cell Rep 21(9):2458–2470

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Luo J, Yang H, Song BL (2020) Mechanisms and regulation of cholesterol homeostasis. Nat Rev Mol Cell Biol 21(4):225–245

    Article  CAS  PubMed  Google Scholar 

  48. Wong Chong E et al (2022) Circulating levels of PCSK9, ANGPTL3 and Lp(a) in stage III breast cancers. BMC Cancer 22(1):1049

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Llaverias G et al (2011) Role of cholesterol in the development and progression of breast cancer. Am J Pathol 178(1):402–412

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Abdelwahed KS et al (2020) Pseurotin A as a novel suppressor of hormone dependent breast cancer progression and recurrence by inhibiting PCSK9 secretion and interaction with LDL receptor. Pharmacol Res 158:104847

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Deng S, Liu J, Niu C (2022) HDL and cholesterol ester transfer protein (CETP). Adv Exp Med Biol 1377:13–26

    Article  CAS  PubMed  Google Scholar 

  52. Tchoua U et al (2008) The effect of cholesteryl ester transfer protein overexpression and inhibition on reverse cholesterol transport. Cardiovasc Res 77(4):732–739

    Article  CAS  PubMed  Google Scholar 

  53. Esau L et al (2016) Identification of CETP as a molecular target for estrogen positive breast cancer cell death by cholesterol depleting agents. Genes Cancer 7(9–10):309–322

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Author information

Authors and Affiliations

  1. Department of Oncology, The First Affiliated Hospital of Harbin Medical University, Harbin, China

    Zhongxu Zhang & Daxin Zhang

Authors
  1. Zhongxu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daxin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Zhongxu Zhang and Daxin Zhang. The first draft of the manuscript was written by Zhongxu Zhang and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Daxin Zhang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical approval

The data for this research are sourced from public databases and ethical approval was obtained during the initial recruitment, therefore no additional ethical approval is required.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (XLSX 252 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Z., Zhang, D. Circulating lipids, lipid-lowering drug targets, and breast cancer risk: Comprehensive evidence from Mendelian randomization and summary data-based Mendelian randomization. Cancer Causes Control (2024). https://doi.org/10.1007/s10552-024-01857-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10552-024-01857-5

Keywords

Search

Navigation