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sun yat-sen university gene expression profile p53-mediated tumour suppression article download pdf activating anti-tumour immunity hepatocellular carcinoma based immune-related high-risk groups pyroptosis-related gene signatures time-dependent roc curves chemokine-mediated signaling pathways pd-l1-mediated gasdermin obtained rna-seq data kaplan–meier os curves hepatocellular carcinoma rongping guo bak/bax-caspase-3-gsdme pathway privacy choices/manage cookies full access renguo guan caspase-3/gsdme signal pathway prognostic nomogram based programmed cell death 10-gene signature utilizing predictive markers low-risk groups based collaborative innovation center programmed cell deaths human leukocyte antigen identify pyroptosis-related genes including chemokine receptor provided theoretical support antigen-presenting cell cox regression method low-risk groups showed search tool high-risk hcc patients independent prognostic factors protein–protein interaction kaplan–meier curves gene expression omnibus kaplan–meier method cancer genome atlas cell cycle arrest cell death patterns regulated cell death cell death differ cell death dis cox regression analysis diverging inflammasome signals related subjects

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• Lymphedema after sentinel lymph node biopsy: who is at Risk?
• The role of pyroptosis in cancer: pro-cancer or pro-“host”?

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         headline:The pyroptosis-related gene signature predicts prognosis and indicates immune activity in hepatocellular carcinoma
         description:Hepatocellular carcinoma (HCC) remains one of the most common malignant tumors with poor survival. Pyroptosis is a kind of programmed cell death that can regulate the proliferation, invasion, and metastasis of tumor cells. However, the expression levels of pyroptosis-related genes (PRGs) in HCC and their relationship with prognosis are still unclear. Our study identified 35 PRGs through bioinformatics analysis that were differentially expressed between tumor samples and nontumor samples. According to these differentially expressed genes, HCC patients could be divided into two groups, cluster 1 and cluster 2. The least absolute shrinkage and selection operator (LASSO) Cox regression method was performed to construct a 10-gene signature that classified HCC patients in the cancer genome atlas (TCGA) database into low-risk and high-risk groups. The results showed that the survival rate of HCC patients in the low-risk group was significantly higher than that in the high-risk group (p < 0.001). The validation cohort, the Gene Expression Omnibus (GEO) cohort, was divided into two risk groups based on the median risk score calculated by the TCGA cohort. The overall survival (OS) of the low-risk group was significantly better than that of the high-risk group (p = 0.007). Univariate and multivariate Cox regression analyses revealed that the risk score was an independent factor in predicting OS in HCC patients. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that immune-related high-risk groups were rich in genes and had reduced immune status. PRGs play a significant role in tumor immunity and have the potential capability to predict the prognosis of HCC patients.
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      headline:The pyroptosis-related gene signature predicts prognosis and indicates immune activity in hepatocellular carcinoma
      description:Hepatocellular carcinoma (HCC) remains one of the most common malignant tumors with poor survival. Pyroptosis is a kind of programmed cell death that can regulate the proliferation, invasion, and metastasis of tumor cells. However, the expression levels of pyroptosis-related genes (PRGs) in HCC and their relationship with prognosis are still unclear. Our study identified 35 PRGs through bioinformatics analysis that were differentially expressed between tumor samples and nontumor samples. According to these differentially expressed genes, HCC patients could be divided into two groups, cluster 1 and cluster 2. The least absolute shrinkage and selection operator (LASSO) Cox regression method was performed to construct a 10-gene signature that classified HCC patients in the cancer genome atlas (TCGA) database into low-risk and high-risk groups. The results showed that the survival rate of HCC patients in the low-risk group was significantly higher than that in the high-risk group (p < 0.001). The validation cohort, the Gene Expression Omnibus (GEO) cohort, was divided into two risk groups based on the median risk score calculated by the TCGA cohort. The overall survival (OS) of the low-risk group was significantly better than that of the high-risk group (p = 0.007). Univariate and multivariate Cox regression analyses revealed that the risk score was an independent factor in predicting OS in HCC patients. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that immune-related high-risk groups were rich in genes and had reduced immune status. PRGs play a significant role in tumor immunity and have the potential capability to predict the prognosis of HCC patients.
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               type:PostalAddress
            type:Organization
            name:State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine
            address:
               name:State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
      name:State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
      name:Department of Dermatovenereology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
      name:Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
      name:State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
      name:Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
      name:State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
      name:State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
      name:Research Unit of Precision Diagnosis and Treatment for Gastrointestinal Cancer, Chinese Academy of Medical Sciences, Guangzhou, China
      name:Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
      name:State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
      name:Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
      name:State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
      name:Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
      name:State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China

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