The expression, immune infiltration, prognosis, and experimental validation of OSBPL family genes in liver cancer

Lianhua Qingwen exerts anti-liver cancer effects and synergistic efficacy with sorafenib through PI3K/AKT pathway: Integrating network pharmacology, molecular docking, and experimental validation

Liver cancer is one of the most lethal malignancies and sorafenib resistance is the main treatment obstacle for patients with advanced liver cancer. Developing drugs that sensitize liver cancer patients to sorafenib is of great importance. Lianhua Qingwen (LHQW), a sort of Traditional Chinese Medicine (TCM) approved by the Chinese Food and Drug Administration (CFDA), is reported to exert synergistic effects with oseltamivir against Influenza virus. However, whether LHQW could exhibit anti-liver cancer effects and enhance the efficacy of sorafenib against liver cancer have not been reported. In the present study, the potential anti-liver cancer effects of LHQW and its synergistic effects with sorafenib were investigated via applying network pharmacology, molecular docking, and in vitro experiments. An "ingredient-compound- target-liver cancer" network was constructed which included 12 ingredients, 164 compounds, and 402 targets. AKT1 was identified as the most hub gene and the PI3K/AKT pathway was revealed as the most enriched pathway. Subsequently, the molecular docking results showed that kaempferol, luteolin, and quercetin were screened as the top 3 compounds which showed the tightest binding to AKT1. Further, the in vitro experiments verified that LHQW significantly inhibited liver cancer cell proliferation and induced apoptosis. Western blot assays confirmed that LHQW could attenuate the PI3K/AKT pathway. Interestingly, LHQW showed a synergistic effect with sorafenib against liver cancer via reducing cell viability, inducing apoptosis, and down- regulating PI3K/AKT pathway. This study broadens the potential application of LHQW and provides insights for liver cancer treatment.

A prognostic metabolism-related gene signature associated with the tumor immune microenvironment in neuroblastoma

Neuroblastoma (NB) is the most prevalent malignant solid tumor in children. Tumor metabolism, including lipid, amino acid, and glucose metabolism, is intricately linked to the genesis and progression of tumors. This study aimed to establish a prognostic gene signature for NB patients, based on metabolism-related genes, and to investigate a treatment approach that could enhance the survival rate of high-risk NB patients. From the NB dataset GSE49710, we identified metabolism-related gene markers utilizing the "limma" R package and univariate Cox analysis combined with least absolute shrinkage and selection operator (LASSO) regression analysis. We explored the correlation between these gene markers and the overall survival of NB patients. Gene set enrichment analysis (GSEA) and single-sample GSEA algorithms were used to assess the differences in metabolism and immune status. Furthermore, we examined the association between metabolic subgroups and drug responsiveness. Concurrently, data downloaded from TARGET and MTAB were used for external verification. Using multicolor immunofluorescence and immunohistochemistry, we investigated the relationship between the lipid metabolism-related gene ELOVL6 with both the International Neuroblastoma Staging System classification of NB and survival rate. Finally, we explored the effect of high ELOVL6 expression on the immune microenvironment in NB using flow cytometry. We identified an eight-gene signature comprising metabolism-related genes in NB: ELOVL6, OSBPL9, RPL27A, HSD17B3, ACHE, AKR1C1, PIK3R1, and EPHX2. This panel effectively predicted disease-free survival, and was validated using an internal dataset from GSE49710 and two external datasets from the TARGET and MTAB databases. Moreover, our findings confirmed that ELOVL6 fosters an immunosuppressive microenvironment and contributes to the malignant progression in NB. The eight-gene signature is significant in predicting the prognosis of NB, effectively classifying patients into high- and low-risk groups. This classification may guide the development of innovative treatment strategies for these patients. Notably, the signature gene ELOVL6 markedly encourages an immunosuppressive microenvironment and malignant progression in NB.