Dataset Information

Expression pattern of tumour-associated antigens in hepatocellular carcinoma: association with immune infiltration and disease progression.

ABSTRACT:

Background

The distinct expression pattern of tumour-associated antigens (TAAs) might be a critical reason for the inefficacy of immunity-based treatments and heterogeneous postsurgical recovery in patients with solid tumours, including hepatocellular carcinoma (HCC). However, little is known about the clinical value of the coexpression patterns of multiple TAAs.

Methods

We determined the expression of multiple TAAs with identified immunogenicity (GPC3, AFP, SSX-2, NY-ESO-1, EpCAM, midkine) and the density of tumour-infiltrating immune cells by immunohistochemistry in a panel of 362 primary HCC patients. We evaluated the association between the TAAs, immune cell infiltration, clinicopathological parameters, and prognosis.

Results

Patients who coexpressed more TAAs had better prognosis (P<0.00001, overall survival). The integrated pattern of TAA was associated with good differentiation and small tumour size, and with more CD57(+) natural killer and CD20(+) B-cell infiltration (P<0.05). Multivariate Cox proportional hazards analysis identified the TAA index as an independent prognostic indicator (hazard ratio 0.625; 95% confidence interval 0.467-0.837; P=0.002), and could further predict patient prognosis in collaboration with local immune infiltration.

Conclusion

Our results could provide new evidence for the improvement of prognostic molecular signatures in HCC, and a novel rationale for patient enrolment in future immunotherapeutic trials and/or clinical treatments.

SUBMITTER: Liang J

PROVIDER: S-EPMC3749565 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Expression pattern of tumour-associated antigens in hepatocellular carcinoma: association with immune infiltration and disease progression.

Liang J J Ding T T Guo Z-W ZW Yu X-J XJ Hu Y-Z YZ Zheng L L Xu J J

British journal of cancer 20130718 4

<h4>Background</h4>The distinct expression pattern of tumour-associated antigens (TAAs) might be a critical reason for the inefficacy of immunity-based treatments and heterogeneous postsurgical recovery in patients with solid tumours, including hepatocellular carcinoma (HCC). However, little is known about the clinical value of the coexpression patterns of multiple TAAs.<h4>Methods</h4>We determined the expression of multiple TAAs with identified immunogenicity (GPC3, AFP, SSX-2, NY-ESO-1, EpCAM ...[more]

PMID: 23868000

Similar Datasets

Project description:Purpose:Hepatocellular carcinoma (HCC) is one of the most commonly diagnosed digestive cancers and the fourth leading cause of death worldwide. Long noncoding RNAs (lncRNAs) with key roles in HCC development and progression have emerged and are used in the diagnosis and prognostic prediction of HCC. The lncRNA gradually increased during hepatocarcinogenesis (GIHCG) is a novel lncRNA with aberrant expression in many tumors, but its prognostic value and biological role in HCC have not been fully studied. Thus, the aim of this study was to explore the expression pattern and potential biological role of GIHCG in HCC. Patients and Methods:The expression pattern of GIHCG in HCC was analyzed in our HCC cohort and validated in The Cancer Genome Atlas (TCGA) database. To assess the prognostic value of GIHCG, survival analyses and Cox regression analyses were carried out in two HCC cohorts. Functional enrichment analysis was used to predict the gene sets and pathways related to aberrant GIHCG expression. Furthermore, the relationship between GIHCG expression and immune infiltration in HCC was analyzed. Results:GIHCG was highly expressed in HCC tissues compared with normal liver tissues. In addition, high GIHCG expression was significantly correlated with inferior clinicopathological characteristics and shorter survival times. High GIHCG expression was an independent prognostic factor for overall survival and disease-free survival in the HCC cohort in our center and in the TCGA-LIHC cohort. Hallmark terms such as "G2M checkpoint", "MYC targets" and "DNA repair" were enriched in the GIHCG high-expression groups. High GIHCG expression negatively correlated with the infiltration of memory CD4+ and CD8+ T cells, natural killer cells, macrophages, dendritic cells, neutrophils and monocytes. Conclusion:The findings of our study indicate that GIHCG is a biomarker that can be used to predict the prognosis of HCC patients and is correlated with immune cell infiltration in HCC.

Project description:Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, and its prognosis remains unsatisfactory. The identification of new and effective markers is helpful for better predicting the prognosis of patients with HCC and for conducting individualized management. The oncogene Aurora kinase A (AURKA) is involved in a variety of tumors; however, its role in liver cancer is poorly understood. The aim of this study was to establish AURKA-related gene signatures for predicting the prognosis of patients with HCC. Methods: We first analyzed the expression of AURKA in liver cancer and its prognostic significance in different data sets. Subsequently, we selected genes with prognostic value related to AURKA and constructed a gene signature based on them. The predictive ability of the gene signature was tested using the HCC cohort development and verification data sets. A nomogram was constructed by integrating the risk score and clinicopathological characteristics. Finally, the influence of the gene signature on the immune microenvironment in HCC was comprehensively analyzed. Results: We found that AURKA was highly expressed in HCC, and it exhibited prognostic value. We selected eight AURKA-related genes with prognostic value through the protein-protein interaction network and successfully constructed a gene signature. The nine-gene signature could effectively stratify the risk of patients with HCC and demonstrated a good ability in predicting survival. The nomogram showed good discrimination and consistency of risk scores. In addition, the high-risk group showed a higher percentage of immune cell infiltration (i.e., macrophages, myeloid dendritic cells, neutrophils, and CD4+T cells). Moreover, the immune checkpoints SIGLEC15, TIGIT, CD274, HAVCR2, and PDCD1LG2 were also higher in the high-risk group versus the low-risk group. Conclusions: This gene signature may be useful prognostic markers and therapeutic targets in patients with HCC.

Project description:Background: Increasing evidence supports that competing endogenous RNAs (ceRNAs) and tumor immune infiltration act as pivotal players in tumor progression of hepatocellular carcinoma (HCC). Nonetheless, comprehensive analysis focusing on ceRNAs and immune infiltration in HCC is lacking. Methods: RNA and miRNA sequencing information, corresponding clinical annotation, and mutation data of HCC downloaded from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) project were employed to identify significant differentially expressed mRNAs (DEMs), miRNAs (DEMis), and lncRNAs (DELs) to establish a ceRNA regulatory network. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene ontology (GO) enrichment pathways were analyzed to functionally annotate these DEMs. A multigene-based risk signature was developed utilizing least absolute shrinkage and selection operator method (LASSO) algorithm. Moreover, survival analysis and receiver operating characteristic (ROC) analysis were applied for prognostic value validation. Seven algorithms (TIMER, XCELL, MCPcounter, QUANTISEQ, CIBERSORT, EPIC, and CIBERSORT-ABS) were utilized to characterize tumor immune microenvironment (TIME). Finally, the mutation data were analyzed by employing "maftools" package. Results: In total, 136 DELs, 128 DEMis, and 2,028 DEMs were recognized in HCC. A specific lncRNA-miRNA-mRNA network consisting of 3 lncRNAs, 12 miRNAs, and 21 mRNAs was established. A ceRNA-based prognostic signature was established to classify samples into two risk subgroups, which presented excellent prognostic performance. In additional, prognostic risk-clinical nomogram was delineated to assess risk of individual sample quantitatively. Besides, risk score was significantly associated with contexture of TIME and immunotherapeutic targets. Finally, potential interaction between risk score with tumor mutation burden (TMB) was revealed. Conclusion: In this work, comprehensive analyses of ceRNAs coexpression network will facilitate prognostic prediction, delineate complexity of TIME, and contribute insight into precision therapy for HCC.

Dataset Information

Expression pattern of tumour-associated antigens in hepatocellular carcinoma: association with immune infiltration and disease progression.

Background

Methods

Results

Conclusion

Publications

Expression pattern of tumour-associated antigens in hepatocellular carcinoma: association with immune infiltration and disease progression.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure