Alterations in genes involved in glycolysis and hypoxia affect the prognosis of pancreatic cancer.

Purpose: To construct a prognostic model for pancreatic cancer based on glycolytic and hypoxic metabolic subtypes. To analyze the biological characteristics of these subtypes and explore potential therapeutic options. Methods: We obtained mRNA, simple nucleotide variation (SNP), and clinical data for pancreatic cancer from The Cancer Genome Atlas (TCGA). Patients were classified into four metabolic subtypes. We focused on glycolysis and hypoxia subtypes. Single-sample gene set enrichment analysis (ssGSEA) assessed immune cell infiltration. We evaluated the effects of immunotherapy and chemotherapy on these subtypes. Cox regression and random survival forest algorithms were used to build a prognostic model. Validation was performed using data from the International Cancer Genome Consortium (ICGC) and ArrayExpress database. Results: We identified four subtypes. Kaplan-Meier survival analysis showed the glycolytic subtype had the longest survival, while the hypoxic subtype had the shortest. The glycolytic subtype exhibited higher immune cell infiltration. Immunotherapy and chemotherapy appeared more beneficial for the glycolytic subtype. KRAS mutations were more frequent in the hypoxic subtype. Our prognostic model indicated a worse prognosis for high-risk groups, validated by external data. Conclusion: The glycolytic metabolic subtype of pancreatic cancer is associated with longer survival and better response to chemotherapy and immunotherapy compared to the hypoxic subtype.

Ordered spatial configuration protects representations of dissimilar items and reduces the similarity effect in visual working memory.

Although similarity could improve visual working memory (VWM) performance, it remains unclear how the spatial configuration of visual information influences the similarity effect in VWM. We explored this question by manipulating the orderliness of spatial configuration (ordered vs. scrambled) in the simultaneous (Experiment 1) and sequential (Experiment 2) change detection tasks. The results showed that similarity improved VWM performance when memory items were presented simultaneously and sequentially. For the simultaneous memory array containing similar and dissimilar items, the performance of the ordered spatial configuration was better than that of the scrambled spatial configuration when probing dissimilar items, while no such difference was found when probing similar items. Further, the similarity effect value in the scrambled spatial configuration was higher than that in the ordered spatial configuration. For the sequential memory array containing similar and dissimilar items, spatial configuration did not affect the similarity effect in VWM. Taken together, these findings suggest that spatial configuration could modulate the similarity effect when memory items are presented simultaneously, in which the ordered spatial configuration protects representations of dissimilar items and reduces the similarity effect in VWM. Our study provides additional evidence for the role of spatial configuration in the similarity effect in VWM, and supports the hierarchical model.

Development of a Nomogram to Predict Clinically Relevant Postoperative Pancreatic Fistula After Pancreaticoduodenectomy on the Basis of Visceral Fat Area and Magnetic Resonance Imaging.

BACKGROUND: The aim of this study was to develop a nomogram to predict the risk of developing clinically relevant postoperative pancreatic fistula (CR-POPF) after pancreaticoduodenectomy (PD) using preoperative clinical and imaging data. METHODS: The data of 205 patients were retrospectively analyzed, randomly divided into training (n = 125) and testing groups (n = 80). The patients' preoperative laboratory indicators, preoperative clinical baseline data, and preoperative imaging data [enhanced computed tomography (CT), enhanced magnetic resonance imaging (MRI)] were collected. Univariate analyses combined with multivariate logistic regression were used to identify the independent risk factors for CR-POPF. These factors were used to train and validate the model and to develop the risk nomogram. The area under the curve (AUC) was used to measure the predictive ability of the models. The integrated discrimination improvement index (IDI) and decision curve analysis (DCA) were used to assess the clinical feasibility of the nomogram in relation to five other models established in literature. RESULTS: CT visceral fat area (P = 0.014), the pancreatic spleen signal ratio on T1 fat-suppressed MRI sequences (P < 0.001), and CT main pancreatic duct diameter (P = 0.001) were identified as independent prognostic factors and used to develop the model. The final nomogram achieved an AUC of 0.903. The IDI and DCA showed that the nomogram outperformed the other five CR-POPF models in the training and testing cohorts. CONCLUSION: The nomogram achieved a superior predictive ability for CR-POPF following PD than other models described in literature. Clinicians can use this simple model to optimize perioperative planning according to the patient's risk of developing CR-POPF.

Glycolytic and fatty acid oxidation genes affect the treatment and prognosis of liver cancer.

BACKGROUND: Metabolic reprogramming is a feature of tumour cells and is essential to support their rapid proliferation. The glycolytic activity of liver cancer cells is significantly higher than that of normal liver cells, and the rapidly proliferating tumour cells are powered by aerobic glycolysis. Lipid metabolism reprogramming enables tumour cells to meet their needs for highly proliferative growth and is an important driving force for the development of hepatocellular carcinoma (HCC). AIM: To explore the influence of different metabolic subtypes of HCC and analyse their significance in guiding prognosis and treatment based on the molecular mechanism of glycolysis and fatty acid oxidation (FAO). METHODS: By downloading related data from public databases including the Cancer Genome Atlas (TCGA), the Molecular Signatures Database, and International Cancer Genome Consortium, we utilised unsupervised consensus clustering to divide TCGA Liver Hepatocellular Carcinoma samples into four metabolic subgroups and compared single nucleotide polymorphism, copy number variation, tumour microenvironment, and Genomics of Drug Sensitivity in Cancer and Tumour Immune Dysfunction and Exclusion between different metabolites. The differences and causes of survival and the clinical characteristics between them were analysed, and a prognostic model was established based on glycolysis and FAO genes. Combined with the clinical features, a Norman diagram was created to compare the pros and cons of each model. RESULTS: In the four metabolic subgroups, with the increase in glycolytic expression, the median survival of patients showed the worst results, while FAO showed the best. When comparing the follow-up analysis of each group, we considered that the differences between them might be related to reactive oxygen species, somatic copy number variation of key genes, and immune microenvironment. It was also found that the FAO group and the low-risk group had better efficacy and response to immune checkpoint blockade treatment and anti-tumour drugs. CONCLUSION: There are obvious differences in genes, chromosomes, and clinical characteristics between metabolic subgroups. The establishment of a prognostic model could predict patient prognosis and guide clinical treatment.

Identifying glycolysis-related LncRNAs for predicting prognosis in breast cancer patients.

PURPOSE: Functions associated with glycolysis could serve as targets or biomarkers for therapy cancer. Our purpose was to establish a prognostic model that could evaluate the importance of Glycolysis-related lncRNAs in breast cancer. METHODS: Gene expressions were evaluated for breast cancer through The Cancer Genome Atlas (TCGA) database, and we calculated Pearson correlations to discover potential related lncRNAs. Differentially expressed genes were identified via criteria of FDR < 0.05 and |FC|> 2. Total samples were separated into training and validating sets randomly. Univariate Cox regression identified 14 prognostic lncRNAs in training set. A prognostic model was constructed to evaluate the accuracy in predicting prognosis. The univariate and multivariate Cox analysis were performed to verify whether lncRNA signature could be an independent prognostic factor The signature was validated in validating set. Immune infiltration levels were assessed. RESULTS: Eighty-nine differentially expressed lncRNAs were identified from 420 Glycolysis-related lncRNAs. 14 lncRNAs were correlated with prognosis in training set and were selected to establish the prognostic model. Low risk group had better prognosis in both training (p= 9.025 e -10) and validating (p= 4.272 e -3) sets. The univariate and multivariate Cox analysis revealed that risk score of glycolysis-related lncRNAs (P< 0.001) was an independent prognostic factor in both training and validating sets. The neutrophils (p= 4.214 e -13, r=-0.223), CD4+ T cells (p= 1.833 e -20, r=-0.283), CD8+ T cells (p= 7.641 e -12, r=-0.211), B cells (p= 2.502 e -10, r=-0.195) and dendritic cells (p= 5.14 e -18, r=-0.265) were negatively correlated with risk score of prognostic model. The Macrophage (p= 0.016, r= 0.0755) was positively correlated with the risk score. CONCLUSION: Our study indicated that glycolysis-related lncRNAs had a significant role to facilitate the individualized survival prediction in breast cancer patients, which would be a potential therapeutic target.

Cisplatin-resistant HepG2 cell-derived exosomes transfer cisplatin resistance to cisplatin-sensitive cells in HCC.

BACKGROUNDS: Cancer cell resistance to chemotherapy drugs such as Gemcitabine, Oxaliplatin, Cisplatin, Doxorubicin, and 5-fluorouracil account for the main reason of chemotherapy failure for HCC patients, especially for those with advanced HCC or metastasis patients. This emerging resistance limits the effectiveness and clinical application of these chemotherapy drugs. Previous studies reported that drug-resistant tumor cell-derived exosomes could transfer their resistance property to tumor sensitive cells in some cancer, including lung and gastric cancer. This study sought to explore whether HepG2/DDP cell-derived exosomes transmit cisplatin (DDP) resistance to HepG2 and other HCC sensitive cells, and provide considerable guidance for HCC nursing with Cisplatin DDP clinically. METHODS: The HepG2 DDP-resistant cell line (HepG2/DDP) was established, and the exosomes from both HepG2/DDP and HepG2 cells were isolated and named ES-2, ES-1, respectively. HepG2 or SMMC-7721 or Huh7 cells were treated with DDP or DDP + ES-2, and HepG2/DDP cells were treated with ES-1. Then, the activation of drug resistance via HepG2/DDP exosomes transfer to HepG2, SMMC-7721 and Huh7 cells were assessed by cell viability assay and ROS formation. Moreover, the relative expression of P-glycoprotein (P-gp) was measured by western blot analysis. RESULTS: HepG2/DDP cell-derived exosomes were successfully isolated from cisplatin-resistant HepG2 cells, and named ES-2. Cell viability of HepG2 or SMMC-7721 or Huh7 cells treated with DDP + ES-2 was enhanced compared with that of DDP treatment group. Also, the concentration of ROS generated in cells under DDP or DDP + ES-2 treatment was strongly increased compared with that of control, although the concentration of ROS was clearly smaller in DDP + ES-2 treatment group compared with DDP treatment. At the same time, the expression of P-gp was upregulated on the ES-2 surface. CONCLUSION: The results mentioned above clarified that HepG2/DDP cell-derived exosomes conferred cisplatin resistance to HepG2 and other HCC cell lines, and provided a new significance for improving the effectiveness of DDP in treating HCC.