Construction and systematic evaluation of a machine learning-based cuproptosis-related lncRNA score signature to predict the response to immunotherapy in hepatocellular carcinoma.

Introduction: Hepatocellular carcinoma (HCC) is a common malignant cancer with a poor prognosis. Cuproptosis and associated lncRNAs are connected with cancer progression. However, the information on the prognostic value of cuproptosis-related lncRNAs is still limited in HCC. Methods: We isolated the transcriptome and clinical information of HCC from TCGA and ICGC databases. Ten cuproptosis-related genes were obtained and related lncRNAs were correlated by Pearson's correlation. By performing lasso regression, we created a cuproptosis-related lncRNA prognostic model based on the cuproptosis-related lncRNA score (CLS). Comprehensive analyses were performed, including the fields of function, immunity, mutation and clinical application, by various R packages. Results: Ten cuproptosis-related genes were selected, and 13 correlated prognostic lncRNAs were collected for model construction. CLS was positively or negatively correlated with cancer-related pathways. In addition, cell cycle and immune related pathways were enriched. By performing tumor microenvironment (TME) analysis, we determined that T-cells were activated. High CLS had more tumor characteristics and may lead to higher invasiveness and treatment resistance. Three genes (TP53, CSMD1 and RB1) were found in high CLS samples with more mutational frequency. More amplification and deletion were detected in high CLS samples. In clinical application, a CLS-based nomogram was constructed. 5-Fluorouracil, gemcitabine and doxorubicin had better sensitivity in patients with high CLS. However, patients with low CLS had better immunotherapeutic sensitivity. Conclusion: We created a prognostic CLS signature by machine learning, and we comprehensively analyzed the signature in the fields of function, immunity, mutation and clinical application.

PPFIA4 Promotes Proliferation, Migration and Glycolysis of Esophageal Cancer Cells.

PPFIA4 has been reported to be associated with cancer glycolysis, but its role in esophageal cancer (EC) is unclear. OBJECTIVE: To investigate the role of PPFIA4 in EC. METHODS: qRT-PCR and WB were used to detect the expression of PPFIA4 in EC cells and normal cells. PPFIA4 was inhibited to detect changes in the invasion and migration ability of EC cells. WB detected the expression of cell invasion and migration marker proteins MMP-2 and MMP-9, and the kit detected changes in ATP and lactate levels in EC cells. RESULTS: PPFIA4 was highly expressed in EC cells. Inhibition of PPFIA4 inhibited the invasion and migration ability as well as the expression of MMP-2 and MMP-9 in EC cells, and decreased the levels of ATP and lactate in EC cells. CONCLUSION: Inhibition of PPFIA4 inhibited invasion, migration ability and glycolysis of EC cells.

Study on Influencing Factors of Phase Transition Hysteresis in the Phase Change Energy Storage.

Phase change energy storage is a new type of energy storage technology that can improve energy utilization and achieve high efficiency and energy savings. Phase change hysteresis affects the utilization effect of phase change energy storage, and the influencing factors are unknown. In this paper, a low-temperature eutectic phase change material, CaCl2·6H2O-MgCl2·6H2O, was selected as the research object, combined with the mechanism of phase change hysteresis characteristics, using a temperature acquisition instrument to draw the step cooling curve. A differential scanning calorimeter was used to measure the DSC (differential scanning calorimetry) curve, and the hysteresis characteristics of phase transformation were studied by factors, such as heat storage temperature, cooling temperature, and cooling rate. The experimental results show that when heating temperature increases by 30 °C, phase transition hysteresis decreases by about 3 °C. The cooling temperature decreased by 10 °C, and the phase transition hysteresis increased by 2.69 °C. This paper provides a new idea for optimizing the properties of phase change energy storage materials and provides a possibility for realizing the parametric control of phase change hysteresis factors.