The deregulation of fatty acid metabolism plays a crucial role in cancer. However, the prognostic value of genes involved in the metabolism in hepatocellular carcinoma (HCC) remains largely unknown. We first constructed a multi-fatty acid metabolic gene prognostic model of HCC based on The Cancer Genome Atlas (TCGA) and further validated it using the International Cancer Genome Consortium (ICGC) database. The model was integrated with the clinical parameters, and a nomogram was built and weighted. Moreover, immune cell infiltration of the tumor microenvironment was investigated. A prognostic model was constructed using 6 selected fatty acid metabolism-related genes, and HCC patients were divided into high- and low-risk groups. Receiver operating characteristic curve (ROC) analysis, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE) analysis showed the optimal performance of the model. The concordance index (C-index), ROC curve, calibration plot and decision curve analysis (DCA) all confirmed the satisfactory predictive capacity of the nomogram. The analysis of immune cell infiltration in HCC patients revealed a correlation with different risk levels. Our findings indicate that a prognostic model based on fatty acid metabolism-related genes has superior predictive capacities, which provides the possibility for further improving the individualized treatment of patients with HCC.
Background: Gastric cancer is a highly heterogeneous disease and its traditional histopathological classification is difficult to meet clinical needs. Oxaliplatin is an antitumor drug with high efficiency and low toxicity. Therefore, the insensitivity or secondary drug resistance of oxaliplatin to gastric cancer is vital for tumor progression. The aim of this study was to investigate the sensitivity of gastric cancer cells to oxaliplatin after ARID1A (AT-rich interactive domain1A gene) gene silencing.Methods: MGC-803 and AGS cells were selected as gastric cancer cells for study. ARID1A protein and mRNA expression was detected by Western blot and quantitative reverse-transcription PCR (qRT-PCR).The short hairpin RNA (shRNA) fragment of ARID1A gene silencing was constructed and introduced into gastric cancer cells. The cell proliferation activity was calculated using CCK8 and the IC50 was calculated.The flow cytometry was used to detect the cell cycle and apoptosis rate. The ability of cell invasion was detected by transwell method. Cells were treated with different concentrations of oxaliplatin.Results: The proliferation of gastric cancer cells was promoted by ARID1A gene silencing (P<0.01), the quantity of cells in S phase increased (P<0.05), and the invasive ability increased (P<0.05). After treatment with oxaliplatin at different concentrations, ARID1A gene silencing reduced the inhibition rate of oxaliplatin on gastric cancer cells and apoptosis rate (P<0.05), and increased IC 50 (P<0.01).Conclusions: ARID1A gene silencing, a factor promoting proliferation of gastric cancer cells, would reduce the sensitivity of gastric cancer cells to oxaliplatin, which can provide a basis for the exploration of targeted drugs for individualized treatment of gastric cancer.
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