Lung cancer is a malignant tumor with one of the highest morbidity and mortality rates in the world. Approximately 80–85% of lung cancer is diagnosed as non-small lung cancer (NSCLC), and its 5-year survival rate is only 21%. Cisplatin is a commonly used chemotherapy drug for the treatment of NSCLC. Its efficacy is often limited by the development of drug resistance after long-term treatment. Therefore, determining how to overcome cisplatin resistance, enhancing the sensitivity of cancer cells to cisplatin, and developing new therapeutic strategies are urgent clinical problems. Z-ligustilide is the main active ingredient of the Chinese medicine Angelica sinensis, and has anti-tumor activity. In the present study, we investigated the effect of the combination of Z-ligustilide and cisplatin (Z-ligustilide+cisplatin) on the resistance of cisplatin-resistant lung cancer cells and its mechanism of action. We found that Z-ligustilide+cisplatin decreased the cell viability, induced cell cycle arrest, and promoted the cell apoptosis of cisplatin-resistant lung cancer cells. Metabolomics combined with transcriptomics revealed that Z-ligustilide+cisplatin inhibited phospholipid synthesis by upregulating the expression of phospholipid phosphatase 1 (PLPP1). A further study showed that PLPP1 expression was positively correlated with good prognosis, whereas the knockdown of PLPP1 abolished the effects of Z-ligustilide+cisplatin on cell cycle and apoptosis. Specifically, Z-ligustilide+cisplatin inhibited the activation of protein kinase B (AKT) by reducing the levels of phosphatidylinositol 3,4,5-trisphosphate (PIP₃). Z-ligustilide+cisplatin induced cell cycle arrest and promoted the cell apoptosis of cisplatin-resistant lung cancer cells by inhibiting PLPP1-mediated phospholipid synthesis. Our findings demonstrate that the combination of Z-Ligustilide and cisplatin is a promising approach to the chemotherapy of malignant tumors that are resistant to cisplatin.

Hepatocarcinogenesis is frequently accompanied by substantial metabolic reprogramming to maximize the growth and proliferation of cancer cells. In this study, we carried out a comprehensive study of metabolomics and lipidomics profiles combined with gene expression analysis to characterize the metabolic reprogramming in hepatocellular carcinoma (HCC). Compared with adjacent noncancerous liver tissue, the enhanced aerobic glycolysis and de novo lipogenesis (DNL) and the repressed urea cycle were underscored in HCC tissue. Furthermore, multiscale embedded correlation analysis was performed to construct differential correlation networks and reveal pathologically relevant molecule modules. The obtained hub nodes were further screened according to the maximum biochemical diversity and the least intraclass correlation. Finally, a panel of ornithine, FFA 18:1, PC O-32:1 and TG (18:1_17:1_18:2) was generated to achieve the prognostic risk stratification of HCC patients (p < 0.001 by log-rank test). Altogether, our findings suggest that the metabolic dysfunctions of HCC detected via metabolomics and lipidomics would contribute to a better understanding of clinical relevance of hepatic metabolic reprogramming and provide potential sources for the identification of therapeutic targets and the discovery of biomarkers.

The healthy growth of infants during early life is associated with lifelong consequences. Breastfeeding has positive impacts on reducing obesity risk, which is likely due to the varied components of breast milk, such as N-acetylneuraminic acid (Neu5Ac). However, the effect of breast milk Neu5Ac on infant growth has not been well studied. In this study, targeted metabolomic and metagenomic analyses were performed to illustrate the association between breast milk Neu5Ac and infant growth. Results demonstrated that Neu5Ac was significantly abundant in breast milk from infants with low obesity risk in two independent Chinese cohorts. Neu5Ac from breast milk altered infant gut microbiota and bile acid metabolism, resulting in a distinct fecal bile acid profile in the high-Neu5Ac group, which was characterized by reduced levels of primary bile acids and elevated levels of secondary bile acids. Taurodeoxycholic acid 3-sulfate and taurochenodeoxycholic acid 3-sulfate were correlated with high breast milk Neu5Ac and low obesity risk in infants, and their associations with healthy growth were reproduced in mice colonized with infant-derived microbiota. Parabacteroides might be linked to bile acid metabolism and act as a mediator between Neu5Ac and infant growth. These results showed the gut microbiota-dependent crosstalk between breast milk Neu5Ac and infant growth.

Z-ligustilide is a main active ingredient in the volatile oil of Angelica sinensis, a traditional Chinese medicine. Cisplatin is a commonly used chemotherapy drug for the treatment of lung cancer. Efficacy is often limited by the development of drug resistance after long-term treatment. Here, we investigated the effect of the combination of Z-ligustilide and cisplatin (Z-ligustilide+cisplatin) on resistance of cisplatin-resistant lung cancer cells and its action mechanism. Cell viability was analyzed by cell counting kit-8 (CCK-8) assay. Cell cycle and cell apoptosis were examined by flow cytometry assay. mRNA and protein levels of factors related to cell cycle and apoptosis were analyzed by real-time PCR and western blot. Liquid chromatography-mass spectrometry (LC-MS) analysis and RNA sequencing in A549, A549/DDP and A549/DDP cells treated with the Z-ligustilide+cisplatin were performed. The expression of PLPP1 was analyzed by the Cancer Genome Atlas (TCGA). The correlation between PLPP1 and prognosis was evaluated by immunohistochemistry and Kaplan-Meier (KM) plotter analysis. We found that Z-ligustilide+cisplatin could decrease the cell viability of cisplatin-resistant lung cancer cells. Z-ligustilide+cisplatin induced cell cycle arrest, and promoted cell apoptosis of cisplatin-resistant lung cancer cells. Metabolomics combined with transcriptomics revealed that Z-ligustilide+cisplatin inhibited phospholipid synthesis by upregulating the expression of PLPP1. Furthermore, PLPP1 expression was positively correlated with good prognosis. Knockdown of PLPP1 abolished the effects of Z-ligustilide+cisplatin on cell cycle and apoptosis. Z-ligustilide+cisplatin inhibited the activation of AKT by reducing the levels of PIP3 levels. Z-ligustilide+cisplatin induced cell cycle arrest and promoted cell apoptosis of cisplatin-resistant lung cancer cells by inhibiting PLPP1-mediated phospholipid synthesis.

Background/Objectives: Lenvatinib combined with anti-PD-1 therapy has shown promise in the treatment of hepatocellular carcinoma (HCC). The study evaluates changes in gut microbiota (GM) and metabolites during HCC treatment with lenvatinib combined with anti-PD-1. Methods: An HCC mouse model was established via diethylnitrosamine (DEN) injection, and the mice were then treated with lenvatinib, anti-PD-1, or their combination. GM composition and structural changes were assessed by 16S rDNA sequencing, and metabolite abundance by liquid chromatography–mass spectrometry (LC–MS). Results: Significant alterations in GM and metabolites were observed in the HCC group compared to the control group, and compared with the HCC group, both monotherapy and combination therapy resulted in varying degrees of GM and metabolites rebalancing. Specifically, compared to the HCC group, lenvatinib combined with anti-PD-1 therapy decreased the abundance of GM, including p_Patescibacteria, g_Lactobacillus, g_Clostridium_sensu_stricto_1, g_Eubacterium_siraeum_group, and g_Desulfovibrio, while the abundance of g_Prevotella_7 increased. Metabolite changes included increased 4-pyridoxic acid, deoxycholic acid, and taurochenodesoxycholic acid, and decreased myristic acid, oleic acid, riboflavin, and uric acid. Conclusions: HCC induces substantial alterations in the GM and metabolic profile of mice. Lenvatinib combined with anti-PD-1 treatment partially modulates these dysregulations. The relevant GM and metabolites may be associated with the efficacy of combined therapy and could serve as potential markers for further investigation.

Background: Diabetic retinopathy (DR) is one of the most prevalent microvascular complications of diabetes mellitus and a leading cause of visual impairment worldwide. However, clinically available, minimally invasive, and convenient tools for early DR screening and disease stage stratification remain inadequate. This study aimed to identify serum metabolic biomarkers for DR stage discrimination and to characterize metabolic alterations associated with DR onset and progression. Methods: Serum samples from four groups—healthy controls (HC), diabetic patients without retinopathy (NDR), patients with mild nonproliferative DR (NPDR), and patients with moderate-to-advanced DR (MADR)—were analyzed using untargeted metabolomics. Three pairwise comparisons were designed to identify key transition points in DR progression. Candidate biomarkers were screened by identifying differential metabolites and further optimized using logistic regression analysis. Results: Stage-specific metabolic reprogramming occurred during DR progression, and lipid metabolism dysregulation persisted throughout the disease course. The candidate biomarker panels achieved cross-validated area under the curve (AUC) values of 0.918, 0.800, and 0.893 for distinguishing NPDR from HC, NPDR from NDR, and MADR from NDR, respectively, demonstrating stable and robust diagnostic performance. Moreover, the identified biomarkers were significantly correlated with key clinical parameters of DR. Conclusions: This study provides promising blood-based candidate biomarkers and novel metabolic insights for early screening and progression monitoring of DR.