Background: Cancer stem cells (CSCs) are the tumor cell of origin with self-renewing ability and multidifferentiation potency. CSCs can play vital roles in gastric cancer (GC) metastasis and relapse. However, the genes that regulate the stemness maintenance of CSCs in GC patients remain largely unknown. In the present study, we sought to determine the key genes associated with stemness in GC patients.Methods: mRNA expression-based stemness index (mRNA SI) was analyzed with regard to the differential expression levels between normal and GC tissues, as well as clinical features and survival outcomes. Weighted gene co-expression network analysis (WGCNA) was performed to identify modules of interest and key genes. The differences in mRNA expression of key genes between normal and GC tissues were calculated by "ggpubr" package in R. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis were carried out to annotate the function of key genes. Protein-protein interaction (PPI) and gene co-expression analyses were conducted using STRING and "corrplot" package in R, respectively.Results: mRNA SI score was markedly increased in GC tumor compared to normal tissues. High mRNA SI score was remarkably associated with more advanced tumor stage and higher pathologic grade, but longer survival times. Based on the results of WGCNA, 19 key genes (i.e.,
Background and Aims:The immune system plays vital roles in hepatocellular carcinoma (HCC) initiation and progression. The present study aimed to construct an immunegene related prognostic signature (IRPS) for predicting the prognosis of HCC patients. Methods: Gene expression data were retrieved from The Cancer Genome Atlas database. The IRPS was established via least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. The prognostic values of the IRPS were further validated using the International Cancer Genome Consortium (ICGC) dataset. Results: A total of 62 genes were identified as candidate immune-related prognostic genes. According to the results of Lasso and multivariate Cox regression analysis, we established an IRPS and confirmed its stability and reliability in the ICGC dataset. The IRPS was significantly associated with advanced clinicopathological characteristics. Both Cox regression analyses revealed that the IRPS could be independent risk factors influencing prognosis of HCC patients. The relationships between the IRPS and infiltration of immune cells demonstrated that the IRPS was associated with immune cell infiltration. Furthermore, a nomogram was constructed to estimate the survival probability of HCC patients. Conclusions: The IRPS was effective for predicting prognosis of HCC patients, which might serve as novel prognostic and therapeutic biomarkers for HCC.
Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality. The immune system plays vital roles in HCC initiation and progression. The present study aimed to construct an immune-gene related prognostic signature (IRPS) for predicting the prognosis of HCC patients. Methods: Gene expression data were retrieved from The Cancer Genome Atlas database. Univariate Cox regression analysis was carried out to identify differentially expressed genes that associated with overall survival. The IRPS was established via Lasso and multivariate Cox regression analysis. Both Cox regression analyses were conducted to determine the independent prognostic factors for HCC. Next, the association between the IRPS and clinical-related factors were evaluated. The prognostic values of the IRPS were further validated using the International Cancer Genome Consortium (ICGC) dataset. Gene set enrichment analyses (GSEA) were conducted to understand the biological mechanisms of the IRPS.Results: A total of 62 genes were identified to be candidate immune-related prognostic genes. Transcription factors-immunogenes network was generated to explore the interactions among these candidate genes. According to the results of Lasso and multivariate Cox regression analysis, we established an IRPS and confirmed its stability and reliability in ICGC dataset. The IRPS was significantly associated with advanced clinicopathological characteristics. Both Cox regression analyses revealed that the IRPS could be an independent risk factor influencing the prognosis of HCC patients. The relationships between the IRPS and infiltration immune cells demonstrated that the IRPS was associated with immune cell infiltration. GSEA identified significantly enriched pathways, which might assist in elucidating the biological mechanisms of the IRPS. Furthermore, a nomogram was constructed to estimate the survival probability of HCC patients. Conclusions: The IRPS was effective for predicting prognosis of HCC patients, which might serve as novel prognostic and therapeutic biomarkers for HCC.
Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality. The immune system plays vital roles in HCC initiation and progression. The present study aimed to construct an immune-gene related prognostic signature (IRPS) for predicting the prognosis of HCC patients. Methods: Gene expression data were retrieved from The Cancer Genome Atlas database. Univariate Cox regression analysis was carried out to identify differentially expressed genes that associated with overall survival. The IRPS was established via Lasso and multivariate Cox regression analysis. Both Cox regression analyses were conducted to determine the independent prognostic factors for HCC. Next, the association between the IRPS and clinical-related factors were evaluated. The prognostic values of the IRPS were further validated using the International Cancer Genome Consortium (ICGC) dataset. Gene set enrichment analyses (GSEA) were conducted to understand the biological mechanisms of the IRPS. Results: A total of 62 genes were identified to be candidate immune-related prognostic genes. Transcription factors-immunogenes network was generated to explore the interactions among these candidate genes. According to the results of Lasso and multivariate Cox regression analysis, we established an IRPS and confirmed its stability and reliability in ICGC dataset. The IRPS was significantly associated with advanced clinicopathological characteristics. Both Cox regression analyses revealed that the IRPS could be an independent risk factor influencing the prognosis of HCC patients. The relationships between the IRPS and infiltration immune cells demonstrated that the IRPS was associated with immune cell infiltration. GSEA identified significantly enriched pathways, which might assist in elucidating the biological mechanisms of the IRPS. Furthermore, a nomogram was constructed to estimate the survival probability of HCC patients.Conclusions: The IRPS was effective for predicting prognosis of HCC patients, which might serve as novel prognostic and therapeutic biomarkers for HCC.
Objective: Sijunzi decoction (SJZD) has been used for alleviating peptic ulcer or gastric discomfort, and treating spleen disorders since the Song Dynasty, but its pharmacological effect on human gastric cancer (GC) is still unclear. In this research, a network pharmacology-based strategy was applied to explore active ingredients, potential targets, and molecular mechanisms of SJZD against GC. Methods: The active compounds and potential targets of SJZD, as well as GC-associated gene targets, were retrieved from publicly available databases. Bioinformatics approaches were used to assess the network interaction, functional regulation, and signaling pathways between SJZD ingredients and GC targets. The anticancer effects of SJZD against GC were verified in vivo by a mouse subcutaneous model. Results: The results of network analysis showed that quercetin was the most active ingredient in SJZD. Several prominent target genes of SJZD were identified, such as AKT1 and STAT3. Gene ontology analysis revealed that the core anti-GC targets of SJZD included transcription factor activity and kinase activity. Pathway enrichment analysis indicated that GC patients could be benefited from SJZD treatment via modulation of signaling pathways related to endocrine system, cancer, and infectious disease. Furthermore, in vivo experiments showed that high-dose SJZD could inhibit GC xenograft tumor growth, reduce GC cell proliferation, induce GC cell apoptosis, and decrease the expression of p-AKT1 and p-STAT3. Conclusions: Taken together, our results suggest that SJZD can serve as an effective adjuvant therapeutic agent for GC patients.
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