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pmid:31681571

Multi-omics Analysis of Microenvironment Characteristics and Immune Escape Mechanisms of Hepatocellular Carcinoma.

Wenli Li · Huimei Wang · Zhanzhong Ma · Jian Zhang · Wen Ou-Yang · Yan Qi · Jun Liu

Frontiers in oncology · 2019 doi:10.3389/fonc.2019.01019

Paper

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title
Multi-omics Analysis of Microenvironment Characteristics and Immune Escape Mechanisms of Hepatocellular Carcinoma.
doi
10.3389/fonc.2019.01019
pmid
31681571
authors array · 7 items
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Wenli Li
[1]
Huimei Wang
[2]
Zhanzhong Ma
[3]
Jian Zhang
[4]
Wen Ou-Yang
[5]
Yan Qi
[6]
Jun Liu
journal
Frontiers in oncology
year
2019
abstract
The immune environment in primary tumor has a profound impact on immunotherapy. However, the clinical relevance of immune environment in hepatocellular carcinoma (HCC) is largely unknown. Here, the immune profile and its clinical response in HCC were investigated. The gene expression profiles of 569 HCCs from three cohorts (The Cancer Genome Atlas, TCGA, n = 257; Gene Expression Omnibus, GEO, n = 170; International Cancer Genome Consortium, ICGC, n = 142) were used in the current study. Five gene expression subtypes (C1-C5) responsible for global immune genes were identified in HCCs at stage I/II. It was found that subtype C4 was associated with upregulation and subtype C5 was associated with downregulation of immune profiles in most metagenes. Immune-correlation analysis of the five subtypes demonstrated that C3 and C4 had higher immune score and better prognostic outcome, as compared with other subtypes. Moreover, the mutation frequencies of TP53, CTNNB1, and AXIN1 had significant difference in the five subgroups. Further, the expression of PDCD1, CD274, PDCD1LG2, CTLA4, CD86, and CD80 was higher in subtype C4 in comparison with the other subtypes. The WGCNA of immune-related genes in the five subtypes revealed that blue and turquoise modules were positively correlated with subtype C4 and were associated with 12 common pathways in the KEGG database. These results were validated in external cohorts from the NCI (National Cancer Institute) cohort (GSE14520) and the ICGC (International Cancer Genome Consortium) cohort. In summary, one immune-enhanced subtype and one immune-decreased subtype having different immune and clinical characteristics may provide guidance for developing novel treatment strategies for immune system malfunction-related cancer.
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sections[6] "Identification of HCC Subtypes Based on the Immune Genes" paragraph 2
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The ConsensusClusterPlus package (26) was utilized to perform consistent clustering and screening of molecular subtypes based on immune gene expression profiles.
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Publicly available datasets were analyzed in this study. This data can be found here: TCGA-LIHC, GSE14520, and ICGC-LIRI-JP.
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Transcript data for six modules.
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Gene Co-expression Network Analysis
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Transcript data for six modules.
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77
[2] array · 2 items
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[1]
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[3] array · 2 items
[0]
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[1]
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[4] array · 2 items
[0]
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[1]
31
[5] array · 2 items
[0]
Turquoise
[1]
121
[6] array · 2 items
[0]
Yellow
[1]
42
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section[17]/table-wrap[1]#T1
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Gene Co-expression Network Analysis
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Table 1
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Transcript data for six modules.
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Brown
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Turquoise
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Yellow
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section[17]/table-wrap[1]#T1
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asset:data:geo:GSE14520 not downloaded
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asset:data:geo:GSE14520 licence not read
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student_t_test
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student_t
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evidence object · 3 fields
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Categorical (contingency table) analysis
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method-5
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null
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ConsensusClusterPlus consensus clustering
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missing_operations array · 0 items
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evidence object · 3 fields
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verbatim
quote
The ConsensusClusterPlus package (26) was utilized to perform consistent clustering and screening of molecular subtypes based on immune gene expression profiles.
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method.reader_named_unmapped
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candidate
Automated Assays Laravel application and simulated adapters
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student_t
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: student_t_test.
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capability:computational_analysis
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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GSE14520
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Publicly available datasets were analyzed in this study. This data can be found here: TCGA-LIHC, GSE14520, and ICGC-LIRI-JP.
basis
The paper names GSE14520 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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source:pmid:31681571
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data:geo:GSE14520
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Here, the immune profile and its clinical response in HCC were investigated. The gene expression profiles of 569 HCCs from three cohorts (The Cancer Genome Atlas, TCGA, n = 257; Gene Expression Omnibus, GEO, n = 170; International Cancer Genome Consortium, ICGC, n = 142) were used in the current study. Five gene expression subtypes (C1-C5) responsible for global immune genes were identified in HCCs at stage I/II. It was found that subtype C4 was associated with upregulation and subtype C5 was associated with downregulation of immune profiles in most metagenes. Immune-correlation analysis of the five subtypes demonstrated that C3 and C4 had higher immune score and better prognostic outcome, as compared with other subtypes. Moreover, the mutation frequencies of TP53, CTNNB1, and AXIN1 had significant difference in the five subgroups. Further, the expression of PDCD1, CD274, PDCD1LG2, CTLA4, CD86, and CD80 was higher in subtype C4 in comparison with the other subtypes. The WGCNA of immune-related genes in the five subtypes revealed that blue and turquoise modules were positively correlated with subtype C4 and were associated with 12 common pathways in the KEGG database. These results were validated in external cohorts from the NCI (National Cancer Institute) cohort (GSE14520) and the ICGC (International Cancer Genome Consortium) cohort. 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