Background: Hepatocellular carcinoma (HCC) is the leading cause of cancer death. Kinesin family member 2C (KIF2C) has been shown as oncogene in a variety of tumors. However, it's role in HCC remains unclear.Methods: In this study, the expression level of KIF2C in HCC was detected by immunohistochemical staining and RT-PCR, and verified by Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and Oncomine database. A curve was established to evaluate the diagnostic efficiency of KIF2C. The effect of KIF2C on HCC was investigated by flow cytometry, Cell Counting Kit-8, Transwell, and the wound-healing assay. We explored the underlying mechanism through epithelial-to-mesenchymal transition (EMT) and transcriptome sequences analysis.Results: KIF2C was overexpression in HCC tissue and related to neoplasm histologic grade (P<0.001), pathology stage (P=0.001), and a dismal prognosis (overall, recurrence-free, and disease-free survival). The diagnostic efficacy of KIF2C was >90% in diagnosing HCC. The HCC cell function experiments showed that KIF2C promoted HCC cell proliferation, migration, invasion, and an accelerated cell cycle, and inhibited apoptosis. Based on western blot analysis and RT-PCR, we found that KIF2C promoted HCC invasion and metastasis through activation of the EMT. Based on transcriptome sequences, we showed that KIF2C promoted HCC through the Ras/MAPK and PI3K/Akt signaling pathway.Conclusions: KIF2C was found to promote the progression of HCC and is anticipated to serve as a biomarker for HCC diagnosis, prognosis, and targeted therapy.

Background: The tumor microenvironment (TME) has an essential role in tumorigenesis, progression, and therapeutic response in many cancers. Currently, the role of TME in acute myeloid leukemia (AML) is unclear.This study investigated the correlation between immune-related genes and prognosis in AML patients.Methods: Transcriptome RNA-Seq data for 151 AML samples were downloaded from TCGA database (https://portal.gdc.cancer.gov/), and the immune related genes (irgs) were selected from Immport database.Bioinformatics screening was used to identify irgs for AML, and genes with a critical role in the prognosis of AML were selected for further analysis. To confirm the prognostic role of irgs in AML, we undertook protein-protein interaction (PPI) network analysis of the top 30 interacting genes. We then investigated associations between immune cell infiltration and prognosis in AML patients. Immunohistochemistry was used to validate protein expression levels between AML and normal bone marrow samples. Analysis of the drug sensitivity of the selected gene was then performed. Results:The integrin lymphocyte function-associated antigen 1 (CD11A/CD18; ITGAL/ITGB2) was identified as the key immune-related gene that significantly influenced prognosis in AML patients.Overexpression of ITGB2 indicated poor prognosis in AML patients (P=0.007). Risk modeling indicated that a high-risk score led to poor outcomes (P=3.076e−08) in AML patients. The risk model showed accuracy for predicting prognosis in AML patients, with area under curve (AUC) at 1 year, 0.816; AUC at 3 years, 0.82; and AUC at 5 years, 0.875. In addition, we found that ITGB2 had a powerful influence on immune cell infiltration into AML TME. The results of immunohistochemistry showed that AML patients had significantly higher ITGB2 protein expression than normal samples. The AML patients were divided into 2 groups based on ITGB2 risk scores. Drug sensitivity test results indicated that the high-risk group was sensitive to cytarabine, axitinib, bosutinib, and docetaxel, but resistant to cisplatin and bortezomib.Conclusions: In the present study, we found that ITGB2 may be able to serve as a biomarker for assessing prognosis and drug sensitivity in AML patients.

Background: Tumor microenvironment (TME) plays an essential role in lung adenocarcinoma (LUAD) development and metastasis. With the development of TME research, it has been proved that differences in tumor-infiltrating immune cells (TICs) and gene expression profile are related to the prognosis of cancer.The aim of our study was to identify key genes affecting immune state in TME of LUAD. Methods:The RNA-seq data and clinical characteristics of 594 LUAD patients were downloaded from the TCGA database. ImmuneScore, StromalScore and ESTIMATEScore of each LUAD sample were calculated using ESTIMATE algorithm. Based on the median of different scores, LUAD samples were divided into high and low score groups. Differentially expressed genes (DEGs) between groups were obtained, and univariate Cox regression analysis and protein-protein interaction (PPI) network were used to screen the shared DEGs generating in the intersection analysis. Finally, the CIBORSORT algorithm was performed to calculate the relative contents of TICs for each LUAD sample, and the correlation analysis between TICs and key genes was used to determine the influence of key genes to the TME.Results: In the presented study, we found that three different scores were positively correlated with the prognosis of LUAD patients, and correlation analysis showed the different scores were closely related to tumor progression and metastasis. After performing the intersection analysis, a total of 585 up-regulated and 107 down-regulated DEGs between the high and low score groups were obtained, all of which were enriched in immune-related functions. Having used univariate COX regression analysis and PPI network, the key genes, CCR2 and PTPRC, affecting the immune status of TME and the prognosis of LUAD were acquired.Analysis based on the CIBERSORT algorithm suggested that CCR2 and PTPRC were correlated with a variety of TICs, and closely related to the clinical characteristics of the LUAD patients.Conclusions: Our research showed that CCR2 and PTPRC may be potential prognostic markers in LUAD, which may affect the function of γδT cells and other immune cells by participating in the regulation of TME immune state.

Background: It has been reported that atractylodin has a potential antitumor effect. This study aimed to investigate the effects of atractylodin on Huh7 and Hccm hepatocellular carcinoma (HCC) cells and its molecular mechanism.Methods: Huh7 and Hccm cells were cultured in vitro, and their viability was detected by CCK-8 assay and the half inhibitory concentration (IC50) was calculated. The cells were treated with different concentrations of atractylodin, and the migration and invasion ability of cells was detected by scratch assay and Transwell assay. The cell cycle change and apoptosis rate were detected by flow cytometry. IlluminaHiSeq4000 platform was used for transcriptome sequencing, and the results were analyzed for gene differential expression, gene function, and signal pathway enrichment. Morphological changes of cells were detected by transmission electron microscopy, reactive oxygen species (ROS) levels were detected by DCFH-DA probe, and the expressions of ferroptosis related proteins GPX4, ACSL4, FTL, and TFR1 were detected by Western blot. Results:The results showed that atractylodin could inhibit the proliferation, migration, and invasion of Huh7 and Hccm cells, regulate the cell cycle, and induce cell apoptosis and G1 phase cell cycle arrest. In addition, it could significantly induce the increase of intracellular ROS levels, decrease the expression of GPX4 and FTL proteins, and up-regulate the expression of ACSL4 and TFR1 proteins.Conclusions: Atractylodin can inhibit the proliferation, migration, and invasion of Huh7 and Hccm liver cancer cells, and induce cell apoptosis and cell cycle arrest. In addition, our results suggest that atractylodin may induce ferroptosis in HCC cells by inhibiting the expression of GPX4 and FTL proteins, and upregulating the expression of ACSL4 and TFR1 proteins.

Background: Diabetic foot ulcer (DFU) is the main cause of disability in diabetic patients. However, the molecular changes underlying the occurrence and progression of DFU remain unclear. We conducted this study to examine gene alterations in different DFU patients.Methods: GSE143735 and GSE134431 transcriptome data sets were acquired from the Gene Expression Omnibus database, and differential expression analyses of the genes in these data sets were performed.A functional enrichment analysis of the differentially expressed genes (DEGs) was performed using clusterProfiler package in R. To examine the correlations between DEGs and significant immune-related genes, we identified the intersecting ulcer-related DEGs, healing-related DEGs, and immune-related DEGs.Finally, we further investigate the relationship between the selected genes with immune cell regulation via a single-sample gene set enrichment analysis, and the infiltration of 28 immune cells in common diabetes samples, unhealed DFU samples, and healed samples DFU were compared.Results: We found 238 upregulated genes and 207 downregulated genes in the diabetic foot (DF) patients with ulcers compared to the DF patients without ulcers, and 74 upregulated genes and 28 downregulated genes in the healed samples compared to the unhealed samples. To examine the main biological functions, we conducted a functional enrichment analysis. The results showed that the biological functions of functional enrichment analysis included neutrophil degranulation, leukocyte chemotaxis, myeloid leukocyte migration, phagosome, cytokine-cytokine receptor interaction, and the chemokine signaling pathway. Interleukin (IL)-1B was more highly expressed in patients with ulcers and healed DFU patients than those without ulcers and unhealed DFU patients. Finally, the immune cell abundance difference results showed that activated cluster of differentiation (CD) 8 T cells, central memory CD8 T cells, T follicular helper cells, myeloid-derived suppressor cells, natural killer T cells and monocytes were more highly infiltrated in normal diabetes patients and healed DFU patients than unhealed DFU patients. However, no difference was found between DF patients with and without ulcers.Conclusions: IL-1B is an inflammation gene that can be used to assess and regulate DFU progression.