An immunogenomic signature for molecular classification in hepatocellular carcinoma

Zhuang, Weiwei; Sun, Hongwei; Zhang, Shanshan; Zhou, Yifei; Weng, Wanqing; Wu, Boda; Ye, Tingbo; Huang, Weiguo; Lin, Zhuo; Shi, Liang; Shi, Ke‐Qing

doi:10.1016/j.omtn.2021.06.024

Cited by 45 publications

(38 citation statements)

References 37 publications

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“…Hepatocellular carcinoma (HCC) is a heterogeneous type of cancer that varies vastly in clinical outcome and response to therapy. Although several studies have identified important molecular classes in HCC, uncertainty remains regarding their associations with outcomes and their complex interaction with liver regenerative processes [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ]. Recently, our lab defined three distinct molecular-based subpopulations of HCC tumors, namely HCC, Blast-Like, and CCA-like, based on gene expression similarity to cholangiocarcinomas and hepatoblast cells [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

DNA Damage Repair Classifier Defines Distinct Groups in Hepatocellular Carcinoma

Smith

Alsten

Walens

et al. 2022

Cancers

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DNA repair pathways have been associated with variability in hepatocellular carcinoma (HCC) clinical outcomes, but the mechanism through which DNA repair varies as a function of liver regeneration and other HCC characteristics is poorly understood. We curated a panel of 199 genes representing 15 DNA repair pathways to identify DNA repair expression classes and evaluate their associations with liver features and clinicopathologic variables in The Cancer Genome Atlas (TCGA) HCC study. We identified two groups in HCC, defined by low or high expression across all DNA repair pathways. The low-repair group had lower grade and retained the expression of classical liver markers, whereas the high-repair group had more clinically aggressive features, increased p53 mutant-like gene expression, and high liver regenerative gene expression. These pronounced features overshadowed the variation in the low-repair subset, but when considered separately, the low-repair samples included three subgroups: L1, L2, and L3. L3 had high DNA repair expression with worse progression-free (HR 1.24, 95% CI 0.81–1.91) and overall (HR 1.63, 95% CI 0.98–2.71) survival. High-repair outcomes were also significantly worse compared with the L1 and L2 groups. HCCs vary in DNA repair expression, and a subset of tumors with high regeneration profoundly disrupts liver biology and poor prognosis.

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Section: Introductionmentioning

confidence: 99%

DNA Damage Repair Classifier Defines Distinct Groups in Hepatocellular Carcinoma

Smith

Alsten

Walens

et al. 2022

Cancers

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“…Together, majority of member genes of CLST are closely related to LILs and functional transition of LILs in liver microenvironment. However, these previous studies are performed based on flow cytometry(FCM), immune fluorescence (IF) and immunohistochemistry (IHC) with a limited subpopulations of LILs and samples size (50) (36) (51) (52)，the crosstalking between CLST with a variety of LILs/immunogenomic pathways are not comprehensively investigated due to the absence of efficient tools for defining further richness of LILs and immunogenomic pathways from high through transcriptomic data until GSEA based algorithms (31,60) and other algorithms including CIBERSORT(61), MCP-counter, TIMER et al were developed (31,60,62,63).Nowadays, GSEA based algorithms have been widely used in tumor (29,31,(64)(65)(66)(67) and non-tumor researches (32,68,69) for immunogenomic signatures/pathways identification. According to the previous studies (31,32,67,69)，we calculated ES of 28 LILs by cell marker gene based ssGSEA algorithm in HBV related diseases.…”

Section: Discussionmentioning

confidence: 99%

“…The orchestra of viral factors ， parenchymal hepatic cells ， tissue-resident lymphocytes and extrahepatic immune cells in liver microenvironment is highly associated with HBV related diseases processes (30).Until now, intrahepatic landscape of immunophenotypes and their diagnosis values remind largely unknown and few studies identified core immune signals during disease progression from initial HBV infection to HBV-HCC by Single-sample gene set enrichment analysis (ssGSEA) widely used in immunogenomic biosignatures identification (3,29,(31)(32)(33). Intrahepatic chemokines play pivotal roles in the initiate recruiting extrahepatic pathogenic T cells (34)(35)(36)(37) (38), ECM deposition are drivers of malignant liver diseases (39,40) , but these genes in liver tissues as a whole and their cross-talking with intrahepatic immune cells across disease stages for candidate biomarkers development，as well as therapeutical targets for immune interruption are still far from being investigated.…”

Section: Introductionmentioning

confidence: 99%

“…Investigating and confirming targets that directly blocking viral replication or indirectly through regressing HBV mediated pathogenesis from more than 20,000 protein coding genes is a huge project, previously. With the development of gene microarray and high-throughput RNA-sequencing, a large amount of high-quality gene expression date were generated (6,(18)(19)(20)(21)(22)(23) and majority of these data uploaded to webaccessible databases give rise to the possibilities to carry out integrated bioinformatics analysis (6,(24)(25)(26)(27)(28)(29).…”

Section: Introductionmentioning

confidence: 99%

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A GSVA based gene set synergizing with CD4+T cell bearing harmful factors yield risk signals in HBV related diseases via amalgamation of artificial intelligence

Huang

Zhao

Zhang

et al. 2022

Preprint

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Genes encoding chemokines and extracellular matrix (ECM) play pivotal roles in chronic HBV infection (CHB), HBV related fibrosis (HBV-LF) and hepatocellular carcinoma (HBV-HCC). The landscape and potential of these genes in prognosis across diseases stages have not been fully and systemically understood. In this study, we defined a LF associated gene set comprised of chemokines and ECM related genes directly induced by initial HBV infection through GSVA algorithm that named as CLST (C stands for CXCL9, CXCL10, CCL19 and CCL20; L for LUM; S for SOX9 and SPP1; T for THBS1, THBS2) and evaluated its biomarker values in CHB and HBV-LF. Enrichment scores (ES) of CLST was subsequently observed synergized with activated CD4+T cells (aCD4) highly related to T helper cell 17 (TH17) associated genes and immune checkpoints and addressed as risk signals due to bearing harmful prognosis factors in tumor tissues of patients with HBV-HCC. Dual higher enrichment score (ES) of CLST and aCD4 in HBV-HCC patients exhibited worse overall survival (OS). Feature genes specific to these two gene sets showed promising clinical relevance in early-stage of HBV-HCC definition and OS prediction incorporating laboratory parameters via artificial intelligence (AI) systems. Finally, a novel mechanistic insight into the issue was proposed that PEG IFN-a as an immunotherapy through modulating CLST signal in treatment responders and these immune signals down-regulation could be beneficial for HBV related diseases control and prevention. Together, our study provides GSVA and AI derived immunogenomic prognosis signatures and clinical utility of these signals will be benefit for HBV related diseases cure.

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“…Disease progression is influenced by immune cell infiltrations in the TME. In several cancers, immune-related indicators correlate better with clinical outcomes, relative to TNM staging [18][19][20]. Therefore, immune scores associated with TME are essential components of the staging system [21].…”

Section: Discussionmentioning

confidence: 99%

Identification of Prognostic Genes and Immune Landscape Signatures Based on Tumor Microenvironment in Lung Adenocarcinoma

et al. 2022

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Background. Lung adenocarcinoma is the most common lung cancer subtype and accounts for the highest proportion of cancer-related deaths. The tumor microenvironment influences prognostic outcomes in lung adenocarcinoma (LUAD). Materials and Methods. We used the ESTIMATE algorithm (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) to investigate the role of microenvironment-related genes and stromal cells in lung adenocarcinoma prognosis. This analysis was done on lung adenocarcinoma cases from The Cancer Genome Atlas (TCGA). The cases were divided into high and low groups on the basis of immune and stromal scores, respectively. Results. There were close correlations between immune scores with prognosis and disease stage. There were 367 differentially expressed genes. Combining the Gene Expression Omnibus (GEO) database, we found 14 prognosis-related genes. Results. Based on the enrichment levels of the immune cell types, we clustered LUAD into Immunity_H and Immunity_L subtypes. Most of these genes were upregulated in Immunity_H subtype. Finally, using the Human Protein Atlas (HPA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, most of the proteins corresponding to prognostic genes were verified to be differentially expressed between the tumor and normal groups. Conclusions. The key genes identified in this study are involved in molecular mechanisms of LUAD.

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An immunogenomic signature for molecular classification in hepatocellular carcinoma

Cited by 45 publications

References 37 publications

DNA Damage Repair Classifier Defines Distinct Groups in Hepatocellular Carcinoma

DNA Damage Repair Classifier Defines Distinct Groups in Hepatocellular Carcinoma

A GSVA based gene set synergizing with CD4+T cell bearing harmful factors yield risk signals in HBV related diseases via amalgamation of artificial intelligence

Identification of Prognostic Genes and Immune Landscape Signatures Based on Tumor Microenvironment in Lung Adenocarcinoma

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