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BACKGROUND: mRNA vaccines have been investigated in multiple tumors, but limited studies have been conducted on their use for hepatocellular carcinoma (HCC). AIM: To identify candidate mRNA vaccine antigens for HCC and suitable subpopulations for mRNA vaccination. METHODS: Gene expression profiles and clinical information of HCC datasets were obtained from International Cancer Genome Consortium and The Cancer Genome Atlas. Genes with somatic mutations and copy number variations were identified by cBioPortal analysis. The differentially expressed genes with significant prognostic value were identified by Gene Expression Profiling Interactive Analysis 2 website analysis. The Tumor Immune Estimation Resource database was used to assess the correlation between candidate antigens and the abundance of antigen-presenting cells (APCs). Tumor-associated antigens were overexpressed in tumors and associated with prognosis, genomic alterations, and APC infiltration. A consensus cluster analysis was performed with the Consensus Cluster Plus package to identify the immune subtypes. The weighted gene coexpression network analysis (WGCNA) was used to determine the candidate biomarker molecules for appropriate populations for mRNA vaccines. RESULTS: AURKA, CCNB1, CDC25C, CDK1, TRIP13, PES1, MCM3, PPM1G, NEK2, KIF2C, PTTG1, KPNA2, and PRC1 were identified as candidate HCC antigens for mRNA vaccine development. Four immune subtypes (IS1-IS4) and five immune gene modules of HCC were identified that were consistent in both patient cohorts. The immune subtypes showed distinct cellular and clinical characteristics. The IS1 and IS3 immune subtypes were immunologically "cold". The IS2 and IS4 immune subtypes were immunologically "hot", and the immune checkpoint genes and immunogenic cell death genes were upregulated in these subtypes. IS1-related modules were identified with the WGCNA algorithm. Ultimately, five hub genes (RBP4, KNG1, METTL7A, F12, and ABAT) were identified, and they might be potential biomarkers for mRNA vaccines. CONCLUSION: AURKA, CCNB1, CDC25C, CDK1, TRIP13, PES1, MCM3, PPM1G, NEK2, KIF2C, PTTG1, KPNA2, and PRC1 have been identified as candidate HCC antigens for mRNA vaccine development. The IS1 and IS3 immune subtypes are suitable populations for mRNA vaccination. RBP4, KNG1, METTL7A, F12, and ABAT are potential biomarkers for mRNA vaccines.
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Gastric cancer is a global health problem with high mortality. The incidence of gastric cancer has significant regional differences. Helicobacter pylori (H. pylori) infection and its interaction with epigenetics are closely related to the occurrence of gastric cancer. It is of great significance to explore the early diagnosis and effective therapeutic targets of gastric cancer. Emerging evidence indicates that antisense long non-coding RNAs (lncRNAs) are closely associated with various biological and functional aspects of gastric cancer. However, diverse antisense lncRNAs in gastric cancer have not been compiled and discussed. In this review, we summarize the predisposing factors and compile the interaction between H. pylori and epigenetics in gastric cancer. Moreover, we focus on the underlying molecular mechanism and regulatory role of each antisense lncRNA in gastric cancer. In addition, we provide a new insight into the potential diagnosis and treatment of antisense lncRNAs in gastric cancer.
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Helicobacter pylori , ARN Largo no Codificante , Neoplasias Gástricas , Humanos , ARN Largo no Codificante/genética , Neoplasias Gástricas/diagnóstico , Neoplasias Gástricas/genéticaRESUMEN
Gastrointestinal (GI) cancer is a global health problem with wide lesions and numerous cases. The increased morbidity and mortality of GI cancer is a socio-economic challenge for decades to come. Melatonin, a nature indolamine, exerts a crucial role in molecular interactions involved in multiple functional and physiological processes. Increasing evidence indicates that melatonin can modulate GI tract, decrease the occurrence of GI cancer, and enhance the sensitivity to chemoradiotherapy. However, little is known about the exact role of melatonin in anti-carcinogenesis. In this review, we discuss the action of the beneficial effects of melatonin in GI carcinogenesis. Furthermore, we compile the understanding of the role of melatonin in GI cancer, including esophageal cancer (EC), gastric cancer (GC), hepatocellular carcinoma (HCC), colorectal cancer (CRC), and pancreatic cancer (PC). In addition, the potential therapeutic application and clinical evaluation of melatonin in GI cancer are also discussed.
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Background: Liver metastasis of colon cancer is strongly affected by the tumor microenvironment (TME), with interactions between tumor cells and cancer-associated fibroblasts (CAFs) in particular. TGF-ß is well known for its ability to mediate the CAF phenotype, and CXCR4 expression is closely correlated to poor prognosis in CRC. The relationship between these two signaling pathways remains to be delineated in liver metastasis of colon cancer.Methods: Immunohistochemistry was employed to investigate CXCR4 expression in 45 human specimens of primary colorectal cancer (CRC) and liver metastasis. The functions of SDF-1 released by hepatic stellate cells (HSCs) on CXCR4 and TGF-ß1 in CRC cells were investigated in vitro. The effects of CRC on HSCs differentiation into CAFs were confirmed using co-culture technology and expression analysis of CAFs markers by qPCR, western blot and immunofluorescence. The involvement of CXCR4 and TGF-ß1 was verified with addition of CXCR4 inhibitor AMD3100 and TGF-ß1 inhibitor cyclophosphamide (Cy) both in vitro and in vivo.Results: There were more CXCR4-positive cells at the liver metastatic tissues compared to the primary sites. CRC cells activated and transformed HSCs to CAFs after co-cultivating with HSCs. Activated HSCs stimulated TGF-ß1 secretion from CRC cells after co-culture with CRC cells in vitro. Moreover, the expression of CAFs markers was increasing in the activated HSCs. In a mouse hepatic metastasis model, treated with AMD3100 or Cy blocked the metastatic potential of HCT116 cells and the hepatic CAFs differentiation.Conclusions: These results indicated that CXCR4/TGF-ß1 axis plays an important role in CRC liver metastasis through mediating HSCs differentiation into CAFs, providing preclinical evidences that blockade of the axis might be beneficial for anti-metastasis therapy in CRC.
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Fibroblastos Asociados al Cáncer/patología , Diferenciación Celular , Neoplasias Colorrectales/patología , Células Estrelladas Hepáticas/citología , Neoplasias Hepáticas/secundario , Receptores CXCR4/metabolismo , Factor de Crecimiento Transformador beta1/metabolismo , Animales , Apoptosis , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Fibroblastos Asociados al Cáncer/metabolismo , Movimiento Celular , Proliferación Celular , Técnicas de Cocultivo , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/metabolismo , Regulación Neoplásica de la Expresión Génica , Células Estrelladas Hepáticas/metabolismo , Humanos , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/metabolismo , Masculino , Ratones , Ratones Desnudos , Pronóstico , Receptores CXCR4/antagonistas & inhibidores , Receptores CXCR4/genética , Factor de Crecimiento Transformador beta1/antagonistas & inhibidores , Factor de Crecimiento Transformador beta1/genética , Células Tumorales Cultivadas , Microambiente Tumoral , Ensayos Antitumor por Modelo de XenoinjertoRESUMEN
BACKGROUND/AIMS: To study the effect of cytotoxic T-lymphocyte antigen 4 gene haplotypes to susceptibility of esophageal squamous cell carcinoma. METHODOLOGY: A gender- and age-matched case-control design was used in this study. PCR-RFLP method was used to detect the genotype of CTLA4 in 205 patients and 205 control individuals in the Anyang area. Furthermore, haplotypes were calculated by PHASE2.1 software. Finally, the conditional logistic regression analysis was carried out to analyze the relevance between the risk of ESCC and the genotypes or haplotypes of CTLA4 gene. RESULTS: The CTLA4 rs231775 and rs4553808 genotypes in patients with ESCC were significantly different from controls (p=0.004, p=0.023, respectively). The AG and AA genotypes of rs231775 were highly correlated with the risk of ESCC (Adjusted OR=2.280, 95%CI=1.433-3.629, p=0.001; Adjusted OR=2.192, 95%CI=1.229-3.911, p=0.008, respectively), and AG genotype of rs4553808 also increased the susceptibility of ESCC (Adjusted OR=1.848, 95%CI=1.220-2.800, p=0.004). Further study suggested that AAG haplotype may enhance the risk of ESCC (Adjusted OR=5.035, 95%CI=1.599-15.860, p=0.005), but GAA haplotype played a protective role (Adjusted OR=0.413, 95%CI=0.251-0.680, p=0.001). CONCLUSIONS: Our research confirmed that CTLA4 genetic variation was related to ESCC in the Anyang area and GAA haplotype was the protective factor of ESCC.