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Background. Cholesterol-rich low-density lipoprotein (LDL) particles have been demonstrated to regulate breast cancer cell proliferation and migration, but their biological function and relevant mechanisms in endometrial carcinoma (EC) remain unclear Methods. Serum and tissue samples were collected from EC patients (n = 50) and patients with benign endometrial hyperplasia (n = 50). Ishikawa and RL95-2 cells were stimulated with different concentrations of LDL, followed by treatment with a JAK2 inhibitor (SD-1029). LDL concentrations were determined by ELISA. The in vitro biological behavior of cells was examined using the CCK-8 assay, EdU staining, and Transwell assay. The tumorigenicity of LDL in vivo was examined using a xenograft mouse model. western blotting, immunofluorescence, and immunohistochemistry studies were performed to measure related protein expression. Results. The LDL concentrations and levels of p-JAK2 and p-STAT3 expression were elevated in the clinical samples. Similar trends in expression were detected in EC cells after LDL stimulation. LDL treatment significantly promoted EC cell proliferation, migration, and invasion, and also upregulated p-JAK2 and p-STAT3 expression in a dose-dependent manner. Moreover, SD-1029 dramatically blocked the LDL-mediated effects on EC cells. Intravenous injection of LDLs promoted tumor growth in the xenograft nude mice, and also increased p-JAK2, p-STAT3, and Ki-67 expression, and downregulated caspase-3 expression. Conclusions. These findings indicate that LDLs exert an oncogenic effect in EC cells by activating the JAK/STAT signaling pathway, and also suggest the JAK/STAT pathway as a possible therapeutic target for EC. [ABSTRACT FROM AUTHOR]

In the present study, we aimed to investigate immune-related signatures and immune infiltration in melanoma. The transcriptome profiling and clinical data of melanoma were downloaded from The Cancer Genome Atlas database, and their matched normal samples were obtained from the Genotype-Tissue Expression database. After merging the genome expression data using Perl, the limma package was used for data normalization. We screened the differentially expressed genes (DEGs) and obtained immune signatures associated with melanoma by an immune-related signature list from the InnateDB database. Univariate Cox regression analysis was used to identify potential prognostic immune genes, and LASSO analysis was used to identify the hub genes. Next, based on the results of multivariate Cox regression analysis, we constructed a risk model for melanoma. We investigated the correlation between risk score and clinical characteristics and overall survival (OS) of patients. Based on the TIMER database, the association between selected immune signatures and immune cell distribution was evaluated. Next, the Wilcoxon rank-sum test was performed using CIBERSORT, which confirmed the differential distribution of immune-infiltrating cells between different risk groups. We obtained a list of 91 differentially expressed immune-related signatures. Functional enrichment analysis indicated that these immune-related DEGs participated in several areas of immune-related crosstalk, including cytokine-cytokine receptor interactions, JAK–STAT signaling pathway, chemokine signaling pathway, and Th17 cell differentiation pathway. A risk model was established based on multivariate Cox analysis results, and Kaplan-Meier analysis was performed. The Kruskal-Wallis test suggested that a high risk score indicated a poorer OS and correlated with higher American Joint Committee on Cancer-TNM (AJCC-TNM) stages and advanced pathological stages (P < 0.01). Furthermore, the association between hub immune signatures and immune cell distribution was evaluated in specific tumor samples. The Wilcoxon rank-sum test was used to estimate immune infiltration density in the two groups, and results showed that the high-risk group exhibited a lower infiltration density, and the dominant immune cells included M0 macrophages (P = 0.023) and activated mast cells (P = 0.005). [ABSTRACT FROM AUTHOR]