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.

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.

Advances in omics technologies provide unprecedented opportunities for systems biology, yet integrating multi-omics data remains challenging due to its complexity, heterogeneity, and the sparsity of prior knowledge networks. Here, we introduce a multi-omics data integration analysis (MODA) framework that fully incorporates prior knowledge to identify hub molecules and pathways, and elucidate biological mechanisms. By leveraging multiple machine learning approaches, MODA transforms raw omics data into a feature importance matrix that is mapped onto a biological knowledge graph to mitigate omics data noise. Then, it uses graph convolutional networks with attention mechanisms to capture intricate molecular relationships and rank molecules via a feature-selective layer. Ultimately, MODA transcends the limitations of predefined pathway annotations by employing an overlapping community detection algorithm to extract core functional modules that are involved in multiple pivotal disease pathways. Systematic evaluations show that MODA outperforms seven existing multi-omics integration methods in classification performance while maintaining biological interpretability. Moreover, MODA achieves superior stability in pan-cancer datasets. Application to the multi-omics datasets of prostate cancer reveals a key role for carnitine and palmitoylcarnitine, regulated by BBOX1 in the progression of prostate cancer. Population samples and in vitro experiments further validate these findings. With high data utilization efficiency and low computational cost, MODA serves as a robust tool for uncovering novel disease mechanisms and advancing precision medicine.

Cancer stem cells (CSCs) are the initiating cells of tumorigenesis, metastasis, and recurrence and play a crucial role in androgen deprivation therapy resistance, yet how sphingolipid metabolism promotes CSC maintenance remains exclusive. Here, we conducted gene expression profiling of sphere-derived castration-resistant prostate cancer stem cells (PCSCs) and identified enhanced sphingolipid de novo biosynthesis with upregulated DEGS2 expression in PCSCs. Silencing of DEGS2 significantly suppressed prostate cancer stem-like traits, cell growth, clonogenicity, and metastasis, while ectopic overexpression of DEGS2 showed the opposite effects. Mechanistically, DEGS2-synthesized phytoceramide activates PI3K-AKT signaling pathway to promote cancer stem-like characteristics, and activation of AKT reversed DEGS2-depletion-inhibited cancer stem-like properties. Clinically, prostate cancer tissues expressed higher levels of DEGS2 compared with adjacent normal tissue, and DEGS2 expression exhibits strong correlations with SOX2, CD133, and Snail expression in primary prostate carcinomas. Collectively, our data illustrate that DEGS2 dictates prostate cancer stem-like properties via the PI3K-AKT pathway, and disruption of this pathway provides potential therapeutic strategies for prostate cancer.