microRNAs targeting cellular cholesterol: implications for combating anticancer drug resistance

Correlation between serum lipid levels and endocrine resistance in patients with ER-positive breast cancer

Lipid metabolism may be involved in the development of endocrine drug resistance in ER-positive (ER+) breast cancer (BC). This study aimed to investigate the relationship between serum lipid levels, risk stratification of dyslipidemia, and endocrine resistance. We collected the data from 166 ER + breast cancer patients who received endocrine therapy (ET). 73 of 166 patients (44.0%)developed endocrine resistance. Univariate and multivariate COX regression were conducted to explore the potential factors affecting endocrine resistance in BC. The clinical T stage, mean serum lipid levels in ET progression-free-survival (total cholesterol, triglycerides, low-density lipoprotein cholesterol, apolipoprotein A, and triglycerides/high-density lipoprotein cholesterol) were correlated with endocrine resistance (R = 0.214, P = .006; R = 0.268, P < .001; R = 0.182, P = .019;R = 0.197, P = .011; R = 0.211, P = .006; R = 0.159, P < .041). Clinical stage, triglycerides (TG) in endocrine therapy progression-free-survival (ePFS) and low-density lipoprotein cholesterol (LDL-C) in ePFS were independent predictors of endocrine resistance (P < .05; OR = 1.406, CI 1.108-1.783, P < .05; OR = 1.309, CI 1.026-1.669, P < .05, respectively). Moreover, in clinical stage III, the ePFS was worse in patients with in the high-risk and extremely high-risk group the median ePFS time was 8.0 months (95% CI: 1.140-14.860, P < .05). Clinical stage, TG in ePFS and LDL-C in ePFS may act as a new predictive biomarker for endocrine resistance in BC. The lipid levels of BC patients should be closely monitored throughout the treatment process, and patients with dyslipidemia should receive treatment immediately.

miRNA-128 and miRNA-223 regulate cholesterol-mediated drug resistance in breast cancer

BACKGROUND

Breast cancer is the second most common malignancy worldwide and 70% of all breast cancer cases are estrogen receptor-positive (ER+). Endocrine therapy, Tamoxifen (TAM), is a popular treatment for ER+ breast cancer patients; however, despite its success in reducing breast cancer mortality, cancer drug resistance remains a significant challenge. A major contributor to this resistance is the dysregulation of cholesterol homeostasis, where breast cancer cells have elevated cholesterol levels. MicroRNAs (miRNAs) are master regulators of cholesterol-related and cancer drug resistance pathways, and their aberrant expression often confers resistance. Therefore, we aimed to investigate the roles of miRNA-128 and miRNA-223 in cholesterol-mediated TAM resistance.

METHODS

Three breast cancer cell lines were treated with a combination of 1 μM TAM and 10 μM of a cholesterol depleting agent (Acetyl Plumbagin: AP) following transfection with a miR-128 inhibitor or a miR-223 mimic. Cell viability and cholesterol levels were assessed using an MTT assay and fluorescence staining, respectively. In addition, expression levels of several genes and proteins involved in cancer drug resistance and cholesterol homeostasis were also assessed using RT-qPCR and western blotting.

RESULTS

The combination treatment with altered miRNA expression led to reduced cell viability due to a reduction in free cholesterol and lipid rafts in MCF-7, MDA-MB-231, and long-term estrogen-deprived cells (resistant breast cancer cells). Moreover, reduced miR-128 expression was favoured in all breast cancer cell lines as this alteration lowered the expression of genes involved in cholesterol synthesis and transport, drug resistance, and cell signalling.

CONCLUSIONS

Investigating the gene expression profiles in different breast cancer cell lines was important to elucidate further the molecular mechanisms involved in miRNA-regulated cholesterol homeostasis and cancer drug resistance. Therefore, our findings demonstrated that miR-128 and miR-223 could be potential targets in reducing TAM resistance through the depletion of excess cholesterol.

MiR-122-5p regulates the mevalonate pathway by targeting p53 in non-small cell lung cancer

The 5-year survival rate of non-small cell lung cancer (NSCLC) patients is very low. MicroRNAs (miRNAs) are involved in the occurrence of NSCLC. miR-122-5p interacts with wild-type p53 (wtp53), and wtp53 affects tumor growth by inhibiting the mevalonate (MVA) pathway. Therefore, this study aimed to evaluate the role of these factors in NSCLC. The role of miR-122-5p and p53 was established in samples from NSCLC patients, and human NSCLC cells A549 using the miR-122-5p inhibitor, miR-122-5p mimic, and si-p53. Our results showed that inhibiting miR-122-5p expression led to the activation of p53. This inhibited the progression of the MVA pathway in the NSCLC cells A549, hindered cell proliferation and migration, and promoted apoptosis. miR-122-5p was negatively correlated with p53 expression in p53 wild-type NSCLC patients. The expression of key genes in the MVA pathway in tumors of p53 wild-type NSCLC patients was not always higher than the corresponding normal tissues. The malignancy of NSCLC was positively correlated with the high expression of the key genes in the MVA pathway. Therefore, miR-122-5p regulated NSCLC by targeting p53, providing potential molecular targets for developing targeted drugs.

Network analysis of atherosclerotic genes elucidates druggable targets

Background

Atherosclerosis is one of the major causes of cardiovascular disease. It is characterized by the accumulation of atherosclerotic plaque in arteries under the influence of inflammatory responses, proliferation of smooth muscle cell, accumulation of modified low density lipoprotein. The pathophysiology of atherosclerosis involves the interplay of a number of genes and metabolic pathways. In traditional translation method, only a limited number of genes and pathways can be studied at once. However, the new paradigm of network medicine can be explored to study the interaction of a large array of genes and their functional partners and their connections with the concerned disease pathogenesis. Thus, in our study we employed a branch of network medicine, gene network analysis as a tool to identify the most crucial genes and the miRNAs that regulate these genes at the post transcriptional level responsible for pathogenesis of atherosclerosis.

Result

From NCBI database 988 atherosclerotic genes were retrieved. The protein–protein interaction using STRING database resulted in 22,693 PPI interactions among 872 nodes (genes) at different confidence score. The cluster analysis of the 872 genes using MCODE, a plug-in of Cytoscape software revealed a total of 18 clusters, the topological parameter and gene ontology analysis facilitated in the selection of four influential genes viz., AGT, LPL, ITGB2, IRS1 from cluster 3. Further, the miRNAs (miR-26, miR-27, and miR-29 families) targeting these genes were obtained by employing MIENTURNET webtool.

Conclusion

Gene network analysis assisted in filtering out the 4 probable influential genes and 3 miRNA families in the pathogenesis of atherosclerosis. These genes, miRNAs can be targeted to restrict the occurrence of atherosclerosis. Given the importance of atherosclerosis, any approach in the understanding the genes involved in its pathogenesis can substantially enhance the health care system.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01195-y.

DNA methylation and lipid metabolism: an EWAS of 226 metabolic measures

BACKGROUND

The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances.

RESULTS

We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value < 4.7 × 10-10), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations.

CONCLUSION

Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.