Lipids, cholesterols, statins and liver cancer: a Mendelian randomization study

The role of statins in the regulation of breast and colorectal cancer and future directions

Statins, widely recognized as a cornerstone in the prevention of cardiovascular diseases, have garnered increasing attention in oncology due to their pleiotropic effects, particularly their potential roles in regulating breast and colorectal cancer. Emerging evidence suggests that statins may exert anticancer effects through multiple mechanisms, including the mitochondrial apoptosis pathway, the LKB1-AMPK-p38MAPK-p53-survivin signaling cascade, inhibition of the mevalonate pathway, modulation of the EGFR/RhoA and IGF-1 signaling pathways, and regulation of the BMP/SMAD4 signaling pathway. However, significant heterogeneity exists in the reported anticancer effects of statins, likely due to variations in statin type (lipophilic vs hydrophilic), dosage, treatment duration, and population-specific characteristics. These factors contribute to inconsistencies in study outcomes. Additionally, while combination therapies incorporating statins with chemotherapy and immunotherapy have demonstrated synergistic effects in certain studies, their clinical utility remains to be fully established. Nevertheless, current evidence suggests that statins may have a potential role in reducing breast and colorectal cancer-related mortality. Future research should prioritize elucidating their precise molecular mechanisms, defining dose-response relationships, developing personalized treatment strategies within the framework of precision medicine, and validating their efficacy through large-scale, long-term prospective studies. These efforts will provide a more robust scientific foundation for the clinical application of statins in oncology. This review systematically explores the role of statins in breast and colorectal cancer regulation, covering clinical evidence, underlying biological mechanisms, pharmacological distinctions, synergistic therapeutic potential, and translational medicine prospects.

Mendelian Randomization Assessment of the Genetic Effects of Lipid-Lowering Drugs on Digestive System Cancers

The relationship between lipid-lowering drugs and the risk of digestive system cancers remains unclear. This study aims to assess the risk association between lipid-lowering drugs and digestive system cancers through mendelian randomization (MR) analysis. We utilized genetic instruments to substitute for the exposure to lipid-lowering drugs, including expression quantitative trait loci (eQTL) for HMGCR, PCSK9, and NPC1L1, as well as genetic variants associated with low-density lipoprotein (LDL) from the Global Lipids Genetics Consortium's genome-wide association study (GWAS) data for target genes. We used MR and SMR methods to assess the risk estimates of lipid-lowering drug target genes on digestive system tumors. The MR analysis indicated a negative association between HMGCR-mediated LDL and hepatocellular carcinoma (OR = 0.06, 95% CI: 0.00-0.81, p = 0.03), and a positive association between NPC1L1-mediated LDL and gastric cancer risk (OR = 15.45, 95% CI: 5.96-40.56, p < 0.01). In the SMR analysis, it was observed that HMGCR expression decreased the risk of hepatocellular carcinoma (OR = 0.11, 95% CI: 0.02-0.68, p = 0.02), while NPC1L1 expression increased the risk of gastric cancer (OR = 1.33, 95% CI: 1.08-1.64, p < 0.01). Our study results suggested a potential risk association between HMGCR inhibitors and NPC1L1 with hepatocellular carcinoma and gastric cancer.

The Lipidomic Profile Discriminates Between MASLD and MetALD

BACKGROUND

The recent consensus statement redefined steatotic liver diseases. Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction and alcohol-related liver disease (MetALD) now represent distinct disease entities. However, biomarkers that differentiate MASLD and MetALD remain largely unknown.

AIMS

To identify lipidomic biomarkers with discriminatory potential for distinguishing MetALD from MASLD.

METHODS

Using the UK Biobank dataset, 40,534 people with available MRI liver scans were analysed. A total of, 11,217 cases with a proton density fat fraction (PDFF) ≥ 5% were identified as having steatotic liver disease. Among these, lipidomic profiles were obtained for 5539 MASLD and 462 MetALD cases. A total of, 250 plasma lipidomic and metabolomic parameters were analysed. Mendelian randomisation (MR) analysis was used to confirm the association between alcohol consumption and the lipidomic biomarkers.

RESULTS

When comparing the top 30 differentially expressed lipidomic biomarkers predicting MetALD compared to MASLD, the majority were related to HDL and were significantly overrepresented at both analysed time points. The top five metabolites were: acetoacetate, 3-hydroxybutyrate, phospholipids in Large HDL, concentration of large HDL particles, free cholesterol in large HDL. The sensitivity analysis comparing alcohol-related liver disease to MASLD revealed similar associations, suggesting that the HDL signature is stable over time. Additionally, MR analysis further confirmed that alcohol consumption was associated with increased levels of HDL-related metabolites.

CONCLUSION

Our findings indicate that HDL-centric lipidomic markers, particularly those within the larger and medium HDL subfraction, may differentiate MetALD from MASLD. Further longitudinal and experimental studies are warranted to validate these findings and assess their clinical implications.

Identification of Causal Plasma Proteins in Hepatocellular Carcinoma via Two-Sample Mendelian Randomization and Integrative Transcriptomic‒Proteomic Analysis

SIGNIFICANCE

In this study, we identified several causal proteins in HCC using UK Biobank Pharma Proteomics Project proteomic data via two-sample MR. We performed colocalization and sensitivity analyses, utilized single-cell RNA sequencing data for validation, and discovered potential drugs through molecular docking.

Insights into drug adverse reactions prediction through Mendelian randomization: a review

Adverse drug reactions pose a significant threat to patient safety and public health and often become apparent only after widespread clinical use. Mendelian randomization (MR) analysis is a valuable tool that can be used to infer causality by using genetic variants as instrumental variables, which can predict the occurrence of adverse drug reactions before they occur. Compared with traditional observational studies, MR Analysis can reduce the potential bias of confounding factors. This article reviews the principles of MR Analysis and its application in the prediction of adverse drug reactions, the challenges and future directions, and summarizes how to harness the power of this innovative epidemiological method to put us at the forefront of improving drug safety assessment and personalized medicine.

Prognostic value of baseline clinicopathological characteristics in first-line chemotherapy ± immunotherapy for extensive-stage small cell lung cancer: a retrospective cohort study

Background

The integration of chemotherapy and immunotherapy as a first-line treatment for extensive-stage small cell lung cancer (ES-SCLC) has been adopted in clinical practice, yet the response to immune checkpoint inhibitors (ICIs) is variable, benefiting only a fraction of patients. The current absence of reliable biomarkers for predicting treatment response and prognosis represents a significant gap in knowledge, hindering the optimization of patient stratification and treatment planning. This retrospective cohort study aims to assess the potential predictive and prognostic significance of clinicopathological baseline features in ES-SCLC patients.

Methods

Our study retrospectively analyzed the data of consecutive patients with ES-SCLC treated with first-line etoposide plus platinum chemotherapy ± immunotherapy at The Affiliated Lihuili Hospital of Ningbo University from April 2017 to April 2023. Data on clinical information, serum laboratory indicators, pathological immunohistochemical markers, and progression-free survival (PFS) times were collected. Univariate and multivariate Cox regression analyses were employed to determine whether these indicators could serve as independent prognostic factors for PFS. Further, potential predictive markers for treatment efficacy were identified using a Cox regression model that incorporated an interaction term between treatment modality and the indicator.

Results

A total of 121 patients with ES-SCLC were enrolled in the study, of whom 62 received chemotherapy alone, and 59 received chemotherapy in combination with immunotherapy. Compared to chemotherapy alone, the addition of immunotherapy to first-line chemotherapy significantly extended the PFS time [P<0.001; hazard ratio (HR) =0.42; 95% confidence interval (CI): 0.28, 0.64] of the ES-SCLC patients. The multivariate analysis revealed that an immunochemotherapy regimen (P<0.001, HR =0.40; 95% CI: 0.24, 0.68), a low-density lipoprotein (LDL) level of >1.8 mmol/L (P=0.02; HR =0.41; 95% CI: 0.20, 0.85) were independent prognostic factors of favorable PFS in the first-line treatment of all ES-SCLC, while a lactate dehydrogenase (LDH) level of >273 U/L (P=0.04; HR =1.78; 95% CI: 1.03, 3.07), a neuron-specific enolase (NSE) concentration of >102.6 ng/mL (P=0.009; HR =6.49; 95% CI: 1.60, 26.32), an apolipoprotein A1 (ApoA1) concentration of >0.9 g/L (P<0.001; HR =4.15; 95% CI: 1.98, 8.71), and an apolipoprotein B (ApoB) concentration of >0.8 g/L (P=0.002; HR =2.24; 95% CI: 1.34, 3.75) were independent prognostic factors of poorer PFS. Further, the interaction effect analysis demonstrated that an LDL level of >1.8 mmol/L and the absence of bone metastasis were potential predictors of an improved response to ICI therapy compared to chemotherapy alone.

Conclusions

This study showed the survival benefit of receiving a chemoimmunotherapy regimen as the first-line treatment in a real-world scenario. It also suggests the prognostic significance of pre-treatment LDL, LDH, NSE, ApoA1, and ApoB with optimal cut-off values in the first-line treatment of all ES-SCLC, and the potential utility of baseline LDL level or the presence of bone metastasis in guiding first-line treatment strategies.

The causal relationship between anti-diabetic drugs and gastrointestinal disorders: a drug-targeted mendelian randomization study

BACKGROUND

The incidence of diabetic gastrointestinal diseases is increasing year by year. This study aimed to investigate the causal relationship between antidiabetic medications and gastrointestinal disorders, with the goal of reducing the incidence of diabetes-related gastrointestinal diseases and exploring the potential repurposing of antidiabetic drugs.

METHODS

We employed a two-sample Mendelian randomization (TSMR) design to investigate the causal association between antidiabetic medications and gastrointestinal disorders, including gastroesophageal reflux disease (GERD), gastric ulcer (GU), chronic gastritis, acute gastritis, Helicobacter pylori infection, gastric cancer (GC), functional dyspepsia (FD), irritable bowel syndrome (IBS), ulcerative colitis (UC), Crohn's disease (CD), diverticulosis, and colorectal cancer (CRC). To identify potential inhibitors of antidiabetic drug targets, we collected single-nucleotide polymorphisms (SNPs) associated with metformin, GLP-1 receptor agonists, SGLT2 inhibitors, DPP-4 inhibitors, insulin, and its analogs, thiazolidinediones, sulfonylureas, and alpha-glucosidase inhibitors from published genome-wide association study statistics. We then conducted a drug-target Mendelian randomization (MR) analysis using inverse variance weighting (IVW) as the primary analytical method to assess the impact of these inhibitors on gastrointestinal disorders. Additionally, diabetes was selected as a positive control.

RESULTS

Sulfonylureas were found to significantly reduce the risk of CD (IVW: OR [95% CI] = 0.986 [0.978, 0.995], p = 1.99 × 10- 3), GERD (IVW: OR [95% CI] = 0.649 [0.452, 0.932], p = 1.90 × 10- 2), and chronic gastritis (IVW: OR [95% CI] = 0.991 [0.982, 0.999], p = 4.50 × 10- 2). However, they were associated with an increased risk of GU development (IVW: OR [95%CI] = 2 0.761 [1.259, 6.057], p = 1 0.12 × 10- 2).

CONCLUSIONS

The results indicated that sulfonylureas had a positive effect on the prevention of CD, GERD, and chronic gastritis but a negative effect on the development of gastric ulcers. However, our research found no causal evidence for the impact of metformin, GLP-1 agonists, SGLT2 inhibitors, DPP 4 inhibitors, insulin and its analogs, thiazolidinediones, or alpha-glucosidase inhibitors on gastrointestinal diseases.

Lipid-lowering medications and risk of malignant melanoma: a Mendelian randomization study

Background

The relationship between blood lipids, lipid-modifying medications, and cancer risk has been under investigation for some time. Recent studies suggest that lipid-lowering medications might influence melanoma outcomes, though findings remain controversial. Our study aims to clarify the potential causal relationship between lipid-lowering drugs commonly used and melanoma incidence through a comprehensive Mendelian randomization (MR) analysis.

Methods

Genetic variations within an LDL-related drug target gene (LDL-cholesterol from a genome-wide association study) served as proxies for exposure to lipid-lowering drugs. We conducted a two-sample Mendelian randomization analysis using inverse variance weighting (IVW), MR-Egger, and weighted median approaches. The MR-PRESSO test and pleiotropy_test were utilized to identify and adjust for horizontal pleiotropy. Stability and reliability of the Mendelian randomization findings were assessed using the leave-one-out method, Cochran's Q test, and funnel plot analysis. Odds ratios (OR) were employed to evaluate the causal relationship between genetic proxies of lipid-lowering drugs and melanoma risk.

Results

IVW analysis revealed that HMGCR gene expression is linked to a decreased risk of melanoma [OR: 0.624(0.439-0.888); p = 0.008]. Conversely, PCSK9 gene expression is tied to an elevated risk of melanoma [OR: 1.233(1.026-1.484); p = 0.025]. No significant association was observed between NPC1L1 and melanoma.

Conclusions

HMGCR inhibitors (statins) may increase melanoma risk, while PCSK9 inhibitors (evolocumab, alirocumab) could potentially decrease melanoma risk.

Causal association between lipid-lowering drugs and cancers: A drug target Mendelian randomization study

Accumulating evidences have indicated that lipid-lowering drugs have effect for the treatment of cancers. However, causal associations between lipid-lowering drugs and the risk of cancers are still unclear. In our study, we utilized single nucleotide polymorphisms of proprotein convertase subtilis kexin 9 (PCSK9) inhibitors and 3-hydroxy-3-methylglutaryl-assisted enzyme A reductase (HMGCR) inhibitors and performed a drug target Mendelian randomization to explore the causal association between lipid-lowering drugs and the risk of cancers. Five regression methods were carried out, including inverse variance weighted (IVW) method, MR Egger, weighted median, simple mode and weighted mode methods, of which IVW method was considered as the main analysis. Our outcome dataset contained the risk of breast cancer (BC), colorectal cancer, endometrial cancer, gastric cancer (GC), hepatocellular carcinoma (HCC), lung cancer, esophageal cancer, prostate cancer (PC), and skin cancer (SC). Our results demonstrated that PCSK9 inhibitors were significant associated with a decreased effect of GC [IVW: OR = 0.482, 95% CI: 0.264-0.879, P = .017]. Besides, genetic inhibitions of HMGCR were significant correlated with an increased effect of BC [IVW: OR = 1.421, 95% CI: 1.056-1.911, P = .020], PC [IVW: OR = 1.617, 95% CI: 1.234-2.120, P = .0005] and SC [IVW: OR = 1.266, 95% CI: 1.022-1.569, P = .031]. For GC [IVW: OR = 0.559, 95% CI: 0.382-0.820, P = .0029] and HCC [IVW: OR = 0.241, 95% CI: 0.085-0.686, P = .0077], HMGCR inhibitors had a protective risk. Our method suggested that PCSK9 inhibitors were significant associated with a protective effect of GC. Genetic inhibitions of HMGCR were significant correlated with an increased effect of BC, PC and SC. Meanwhile, HMGCR inhibitors had a protective risk of GC and HCC. Subsequent studies still needed to assess potential effects between lipid-lowering drugs and the risk of cancers with clinical trials.

Statins and Cancer: A Complex Relationship Worth Exploring

This Special Issue, entitled "Statins and Cancer", aims to demonstrate recent and new advances and future trends in using statins in the field of oncology [...].