Lipid-lowering drugs affect lung cancer risk via sphingolipid metabolism: a drug-target Mendelian randomization study

Li, Honglin; Zhang, Lei; Yang, Feiran; Feng, Xiaoteng; Fu, Rong; Zhao, Ruohan; Li, Xiurong; Li, Huijie

doi:10.3389/fgene.2023.1269291

Cited by 4 publications

(1 citation statement)

References 70 publications

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“…Li et al discovered the considerable influence of ceramidase on lung cancer risk reduction. 8 Ceramidase also contributes to the sensitivity of radiotherapy and chemotherapy for cancer. 9 Reducing SIP production can suppress NSCLC cell growth by targeting sphingosine kinases (SphKs).…”

Section: Introductionmentioning

confidence: 99%

Single‐cell RNA sequencing reveals aberrant sphingolipid metabolism in non‐small cell lung cancer impacts tumor‐associated macrophages and stimulates angiogenesis via macrophage inhibitory factor signaling

Shen,

Liu,

et al. 2024

Thoracic Cancer

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BackgroundSphingolipids not only serve as structural components for maintaining cell membrane fluidity but also function as bioactive molecules involved in cell signaling and the regulation of various biological processes. Their pivotal role in cancer cell development, encompassing cancer cell proliferation, migration, angiogenesis, and metastasis, has been a focal point for decades. However, the contribution of sphingolipids to the complexity of tumor microenvironment promoting cancer progression has been rarely investigated.MethodsThrough the integration of publicly available bulk RNA‐seq and single‐cell RNA‐seq data, we conducted a comprehensive analysis to compare the transcriptomic features between tumors and adjacent normal tissues, thus elucidating the intricacies of the tumor microenvironment (TME).ResultsDisparities in sphingolipid metabolism (SLM)‐associated genes were observed between normal and cancerous tissues, with the TME characterized by the enrichment of sphingolipid signaling in macrophages. Cellular interaction analysis revealed robust communication between macrophages and cancer cells exhibiting low SLM, identifying the crucial ligand‐receptor pair, macrophage inhibitory factor (MIF)‐CD74. Pseudo‐time analysis unveiled the involvement of SLM in modulating macrophage polarization towards either M1 or M2 phenotypes. Categorizing macrophages into six subclusters based on gene expression patterns and function, the SPP1+ cluster, RGS1+ cluster, and CXCL10+ cluster were likely implicated in sphingolipid‐induced M2 macrophage polarization. Additionally, the CXCL10+, AGER+, and FABP4+ clusters were likely to be involved in angiogenesis through their interaction with endothelial cells.ConclusionBased on multiple scRNA‐seq datasets, we propose that a MIF‐targeted strategy could potentially impede the polarization from M1 to M2 and impair tumor angiogenesis in low‐SLM non‐small cell lung cancer (NSCLC), demonstrating its potent antitumor efficacy.

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Section: Introductionmentioning

confidence: 99%

Single‐cell RNA sequencing reveals aberrant sphingolipid metabolism in non‐small cell lung cancer impacts tumor‐associated macrophages and stimulates angiogenesis via macrophage inhibitory factor signaling

Shen,

Liu,

et al. 2024

Thoracic Cancer

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Bioactive sphingolipids as emerging targets for signal transduction in cancer development

Jia,

Yuan,

Zhang

et al. 2024

Biochimica et Biophysica Acta (BBA) - Reviews on Cancer

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Causal Effects of Genetically Determined Lipidome on Lung Cancer and Its Subtypes: A Mendelian Randomization Study

Luo,

2024

Preprint

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Background Previous observational studies have identified abnormalities in lipid metabolism among lung cancer patients, but the causal relationship between lipidomes and lung cancer risk remains unclear. Herein, we investigate the causal effect of lipidomes on the incidence of lung cancer and its subtypes through two-sample Mendelian randomization (MR) analysis. Methods A genome-wide association study of 179 lipid metabolites was used as the exposure, while lung cancer and its subtypes were the outcomes. All the datasets were obtained from an open database. The inverse variance weighted method was used as the primary analysis, and MR-Egger regression, the weighted median method, and the weighted mode method were employed to test the robustness of the results. MR-Egger intercept and Cochran's Q statistical analysis were used to assess potential pleiotropy and heterogeneity. Leave-one-out sensitivity analysis was also used to test the stability of the findings. Results Forty-two significant lipids were identified as causative exposures for lung cancer. Seventeen lipids affected lung cancer risk in smokers, while only four affected non-smokers. There were two overlapping lipids among the three pathological types of lung cancer. Phosphatidylcholine (O-16:1_18:0) had protective effects on small cell lung cancer (odds ratio (OR) = 0.828, P = 0.038) and lung squamous cell carcinoma (LUSC) (OR = 0.859, P = 0.005). Phosphatidylethanolamine (18:0_18:2) also exhibited protective effects on lung adenocarcinoma (OR = 0.943, P = 0.038) and LUSC (OR = 0.912, P = 0.003). Our results were robust even without a single SNP due to a "leave-one-out" analysis. The MR Egger intercept test indicated that genetic pleiotropy had no effect on the results. No heterogeneity was detected by Cochran's Q test. Conclusion This study unveiled the causal effect of specific lipid species on lung cancer and its subtypes. Smoking patients are more susceptible to abnormal lipid metabolism and are at a higher risk of developing lung cancer. Different lipid species are closely associated with various pathological types of lung cancer. Our study suggests that lipids may be utilized in the early screening, prevention, and treatment of lung cancer.

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Lipid-lowering drugs affect lung cancer risk via sphingolipid metabolism: a drug-target Mendelian randomization study

Cited by 4 publications

References 70 publications

Single‐cell RNA sequencing reveals aberrant sphingolipid metabolism in non‐small cell lung cancer impacts tumor‐associated macrophages and stimulates angiogenesis via macrophage inhibitory factor signaling

Single‐cell RNA sequencing reveals aberrant sphingolipid metabolism in non‐small cell lung cancer impacts tumor‐associated macrophages and stimulates angiogenesis via macrophage inhibitory factor signaling

Bioactive sphingolipids as emerging targets for signal transduction in cancer development

Causal Effects of Genetically Determined Lipidome on Lung Cancer and Its Subtypes: A Mendelian Randomization Study

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