A Causal Relationship Between Genetically Proxied Inhibition of HMGCR, NPC1L1, and PCSK9 and Cancers

Abstract

Cancer remains a significant global health burden, ranking as the second leading cause of death despite considerable medical advances. Increasing evidence links cholesterol metabolism, particularly low-density lipoprotein cholesterol (LDL-C), to cancer risk. Epidemiological studies suggest that elevated LDL-C levels are associated with multiple cancers, including breast, colorectal, and pancreatic cancers [1]. These observations suggest that LDL-C-lowering therapies may have anticancer effects. Although preclinical studies show that statins can inhibit tumor growth and metastasis, the effects of different lipid-lowering agents on cancer risk remain unclear. To investigate this, we conducted a Mendelian randomization (MR) study leveraging genetically proxied LDL-C-lowering drug targets, including HMG-CoA reductase (HMGCR), proprotein convertase subtilisin/kexin type 9 (PCSK9), and Niemann-Pick C1-like 1 (NPC1L1) inhibitors. We examined the associations between these drug targets and 16 different cancer types, as well as overall cancer risk (Figure 1A).

Figure 1B presented the outcomes of MR analyses investigating the causal effects of genetically proxied lipid-lowering drug targets on 17 different types of cancer, alongside pleiotropy assessments. Funnel plots were used to evaluate heterogeneity. A rigorous instrument selection process yielded between 3 and 60 single nucleotide polymorphisms (SNPs) per target, with all F-statistics > 10, mitigating the risk of weak instrument bias. As for the PCSK9 inhibition (PCSK9i), the fixed-effect inverse-variance weighted (IVW) method clearly demonstrated a protective effect on breast cancer (OR: 0.9124, p = 0.0071, 95%CI: 0.8455–0.9792), which this result was corroborated by the weighted median and the weighted mode method. In addition, it also identified PCSK9i had an obvious protective effect on thyroid cancer (OR: 0.3272, p = 0.0397, 95%CI: 0.0370–0.5915) and brain cancer (OR: 0.9985, p = 1.8786E-07, 95%CI: 0.9980–0.9991), only in the IVW method. More importantly, the PCSK9i retained a strong protective association with overall cancer (OR: 0.9883, p = 5.8596E-11, 95%CI: 0.9848–0.9918). However, PCSK9i showed significant associations with higher risk of oesophageal cancer (OR: 1.0009, p = 0.0028, 95%CI: 1.0003–1.0014) and lung cancer (OR: 1.0328, p = 0.0020, 95%CI: 1.0054–1.2782). Additionally, genetically predicted HMGCR inhibition (HMGCRi) had a positive correlation effect on the risk of breast cancer (OR: 0.8266, p = 0.0001, 95%CI: 0.7300–0.9232), ER+ breast cancer (OR: 0.8281, p = 0.0013, 95%CI: 0.7130–0.9431), serous ovarian cancer (OR: 0.7564, p = 0.0213, 95%CI: 0.5187–0.9941), overall ovarian cancer (OR: 0.5954, p = 2.25081E-05, 95%CI: 0.3555–0.8352), kidney cancer (OR: 0.9883, p = 5.85958E-11, 95% CI: 0.9848–0.9918), brain cancer (OR: 0.9982, p = 0.0168, 95%CI: 0.9967–0.9997) and overall cancer (OR: 0.9877, p = 0.0164, 95%CI: 0.9775–0.9978), respectively. While HMGCRi was associated with a higher risk of developing gastric cancer (OR: 1.7295, p = 0.0002, 95%CI: 1.4374–2.0215). In addition, the MR analysis results offer support for the notion that a reduction in LDL-C levels, mediated by the NPC1L1 gene, lowered the risk of breast cancer (OR: 0.7214, p = 0.0045, 95%CI: 0.4958–0.9470), ER+ breast cancer (OR: 0.6575, p = 0.0022, 95%CI: 0.3889–0.9262), ER- breast cancer (OR: 0.6775, p = 0.0022, 95%CI: 0.3889–0.9265), respectively. However, genetically predicted NPC1L1 inhibition (NPC1L1i) was associated with a higher risk of developing bladder cancer (OR: 1.0058, p = 0.0142, 95%CI: 1.0012–1.0104) and oesophageal cancer (OR: 1.0059, p = 0.0010, 95%CI: 1.0024–1.0094). The above positive results are summarized in Figure 1B.

To ensure robustness, we applied Bonferroni correction, confirming that PCSK9i significantly reduced breast cancer (p = 1.88E-07) and overall cancer risk (p = 5.86E-11), while HMGCRi had a strong protective effect against breast, ovarian, and kidney cancers but increased the risk of gastric cancer. Sensitivity analyses (Cochrane's Q test, MR-Egger regression, and MR-PRESSO) indicated no heterogeneity or horizontal pleiotropy, reinforcing the reliability of our findings (Supporting Information S1: Table S1). We further conducted in vitro experiments using PCSK inhibitor PCSK9-IN-11 (compound 5r) and HMGCR inhibitor simvastatin to assess their effects on cell proliferation and apoptosis in breast and ovarian cancer cell lines. Western blot analysis revealed upregulation of Bax and cleaved caspase-3 and downregulation of Bcl-2, confirming their proapoptotic effects (Figure 1C). Both compounds significantly reduced cell proliferation after 48 h of treatment, supporting their potential anticancer properties (Figure 1D).

Our study leverages large-scale GWAS datasets, providing robust causal evidence. Unlike randomized controlled trials (RCTs), MR avoids short-term exposure biases and confounding. Additionally, our findings challenge the assumption that all lipid-lowering therapies are protective against cancer, revealing drug-specific effects. PCSK9 regulates LDL receptor (LDLR) expression, increasing LDL clearance. LDLR is involved in cell proliferation, apoptosis, and angiogenesis, processes critical for tumor growth [2]. High cholesterol levels and PCSK9 overexpression have been reported in breast cancer, suggesting that PCSK9 inhibition may be particularly effective in hormone-dependent tumors. Moreover, PCSK9 inhibition has been linked to improved responses to immune checkpoint therapy. Emerging evidence suggests that PCSK9 may also contribute to tumor progression via non-lipid pathways, particularly through PD-L1-related immune regulation and IL-6-mediated inflammation [3]. The potential involvement of PCSK9 in immune and inflammatory pathways warrants further investigation. HMGCRi (statins) act by disrupting isoprenoid synthesis, affecting Ras and Rho GTPase signaling, essential for cancer cell survival. Statins upregulate proapoptotic proteins (caspase-3, Bax) and downregulate Bcl-2, reinforcing their anticancer potential [4]. However, the association between HMGCRi and increased gastric cancer risk remains debated. This discrepancy may stem from compensatory cholesterol synthesis in extrahepatic tissues or differential effects between lipophilic and hydrophilic statins. In addition, NPC1L1i affect the Akt pathway, impacting apoptosis and proliferation, and may inhibit tumor angiogenesis, as suggested by in vivo studies [5].

However, our study has some limitations. Firstly, cancer types such as hematologic malignancies were not analyzed. Secondly, our data set primarily includes individuals of European ancestry, necessitating further validation in diverse populations. Finally, our study lacks colocalization analyses. Although we conducted multiple sensitivity analyses to assess horizontal pleiotropy and heterogeneity, these approaches cannot fully determine whether the genetic variants used as instruments influence both LDL-C levels and cancer risk through the same causal variant. Future research incorporating colocalization frameworks, especially when integrating eQTL or epigenomic datasets, will be essential to confirm shared causal variants and better delineate the true therapeutic relevance of lipid-lowering drug targets in cancer prevention.

In conclusion, our findings suggest that genetically predicted PCSK9i significantly lowers the risk of breast cancer, thyroid cancer, brain cancer, and overall cancer risk, while simultaneously increasing the risk of lung and esophageal cancer. NPC1L1i appears protective against breast cancer but may increase bladder and esophageal cancer risk. HMGCRi may reduce breast, ovarian, kidney, and brain cancer risk but may elevate gastric cancer risk. Given these findings, future RCTs are warranted to validate the precise role of lipid-lowering therapies in cancer prevention and treatment.

Xin Wang: data curation (lead), formal analysis (lead), methodology (equal), resources (equal), software (equal), writing – original draft (equal). Yiyao Zeng: data curation (equal), formal analysis (equal), investigation (equal), writing – original draft (equal). Zihan Xu: data curation (equal), formal analysis (equal), funding acquisition (equal), writing – original draft (equal). Xiangyue Meng: investigation (equal), methodology (equal), validation (equal), writing – review & editing (equal). Jie Chen: resources (equal), funding acquisition (equal), writing – review & editing (equal). All authors have read and approved the final manuscript.

This study was approved by the Ethics Committee of West China Hospital (Sichuan, China) and The Fourth Affiliated Hospital of Soochow University (No. 202403A0388).

The authors declare no conflicts of interest.