Table 2.
Representative transcriptomic studies in recurrence of hepatocellular carcinoma
|
Ref.
|
Method
|
Sample comparison
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Major findings
|
Featured research domain
|
| Jiang et al[29], 2000 | RT-qPCR | Nontumorous liver vs tumor samples; peripheral blood from HCC patients | MMP9 in tumors was related to recurrence. mRNA of AFP in blood samples was associated with recurrence | Primary cancer cells |
| Morimoto et al[30], 2005 | RT-qPCR | Peripheral blood and bone marrow samples from patients with HCC vs benign diseases | AFP mRNA level in blood, but not bone marrow, could be useful for predicting postoperative tumor recurrence | Primary cancer cells |
| Cheung et al[56], 2005 | Microarray | HCC tumors from patients with post-OP recurrence vs without recurrence | CLDN10, along with the pTNM stage, were independent predictors for HCC recurrence | Primary cancer cells |
| Matoba et al[57], 2005 | Microarray | HCC tumors from patients with vs without post-OP early (< 1 yr) recurrence | HLA-DRA, HLA-DRB1, HLA-DG, and HLA-DQA had significantly lower expression in the early IHR group | Primary cancer cells |
| Iizuka et al[58], 2006 | Microarray | HCC tumors from patients with post-OP IHR vs EHR | 46 cell adhesion-related genes, including ITGA6 and SPP1, had higher expression levels in HCC with early IHR | Primary cancer cells |
| Ho et al[62], 2006 | Microarray | HCC tumors from patients with vs without PVI | Differential expression of 14 genes related to the human melanoma gene family, cell growth, DNA glycosylation, and thrombin inhibitors, can be used to predict recurrence | Primary cancer cells |
| Chen et al[63], 2002 | Microarray | HCC tumor and corresponding nontumorous tissue with vs without PVI | ARHGAP8 and ARHGEF6 were PVI-associated. | Primary cancer cells |
| Okabe et al[64], 2001 | Microarray | HCC tumor from patients with vs without PVI | Upregulation of MMP14 and downregulation of two CYP genes, ADAMTS1, and ITGA7 were associated with PVI | Primary cancer cells |
| Okamoto et al[76], 2006 | Microarray | Multicentric vs single nodular recurrent HCV-related HCC | 36 marker genes were associated with multicentric recurrence and were used to develop a predictive scoring system | Carcinogenic stimulants |
| Mas et al[78], 2007 | Microarray | HCV-related HCC from patients with vs without disease progression | Upregulation of FAIM3 and USP18, and downregulation of TFP1, HIST1H4E, and NRG1 were related to disease-free survival after curative treatment | Carcinogenic stimulants |
| Nagalakshmi et al[80], 2008 | Microarray | MIM vs MAM | HLA-DPA1, HLA-DRA, PRG1, and ANXA1 were associated with a metastatic phenotype (Th2-predominant), for which CSF1 may be responsible | Microenvironment |
| Yoshioka et al[66], 2009 | Microarray | HCC tumors from patients with multiple early (< 2 yr) IHR vs with DFS > 3 yr | Informative gene sets including PPARBP, RREB-1, BCL2, HDAC1, and BIRC5 were yielded and used for a predictive model, which was validated in independent cases | Primary cancer cells |
| Kim et al[74], 2012 | Predictive model construction using microarray database | DGE in 65 genes from pre-existing databases were used for a predictive model for early HCC recurrence and validated in independent HBV-related HCC cohorts | A risk scoring system with 65 differentially expressed genes identified from microarray data successfully predicted overall survival < 3 yr post-OP | Carcinogenic stimulants |
| Kim et al[75], 2014 | Predictive model construction using microarray database | DGE of 233 HIR-related genes from preexisting databases were used for a predictive model for late HCC recurrence and validated in independent HBV-related HCC cohorts | Genes related to STAT3/Notch signaling activation were related to late (> 1 yr) recurrence of HCC. RALGDS, IER3, CEBPD, and SLC2A3 were independent predictors of recurrence. | Carcinogenic stimulants |
| Nakagawa et al[65], 2021 | Predictive model construction using microarray database | Validation of intrahepatic metastasis risk signatures created based on a preexisting microarray database in an independent patient cohort | STC1, FOXK2, MMP1, and LOXL2 that promote either cell cycle advancement or histone modulation could predict the incidence of early recurrence | Primary cancer cells |
| Liu et al[87], 2022 | RNA-seq | HCC tumors from patients with vs without recurrence | Most altered expression genes are related to DNA synthesis (MCM8, MCM6, TOP2A, and CDC7), chromatin segregation (BUB1 and CDC6), and mitosis (NDC80 and PPP2R3C) | Primary cancer cells |
| Ng et al[88], 2021 | RNA-seq | Paired tumor tissues vs nontumorous tissues from HCC patients | GSTA2 expression was associated with early-phase systemic injury and reactive oxygen species levels and could serve as a predictor of recurrence | Primary cancer cells |
| Lachmann et al[90], 2018 | RNA-seq | Paired primary vs recurrent HCC tumor tissues | Mutations of GOLGB1 and SF3B3 are potential key drivers for the aggressive phenotype in recurrent HCC | Primary cancer cells |
| Okrah et al[97], 2018 | RNA-seq | HBV-related HCC tumor vs distant nontumorous liver tissues | More HBV gene integrations correlated with a higher recurrence rate | Carcinogenic stimulants |
| Wang et al[98], 2021 | Validation of RNA-seq database | HCC tumors vs matched cirrhotic tissues; CD8+ CTL-infiltrated vs T cell-excluded tumor tissues | Local tumor immunosuppression coincided with disease progression. Association was found between elevated fibrosis and the T cell-excluded immune phenotype | Microenvironment |
| Ho et al[99], 2021 | Predictive model construction using RNA-seq database | Validation of recurrence-associated lncRNAs identified by regression analysis of TCGA database | 9 immune-related lncRNAs were tightly associated with recurrence | Microenvironment |
| Zheng et al[120], 2018 | scRNA-seq | CSC vs non-CSC populations defined by triple+ or triple− surface expression of CD133, CD24, EpCAM | 286 signature genes linked to triple+ CSC could predict tumor recurrence in 240 HCC cases with multivariable Cox regression survival risk prediction analysis | Primary cancer cells |
| Sun et al[122], 2021 | scRNA-seq | Tumors from primary vs early-relapse HCC patients | Decreased Treg and T cell proliferation with an increased proportion of CD8+- T cells and DC were found in early-relapse tumors compared to primary tumors. CD8+ T cells with overexpression of KLRB1 revealed an innate dysfunctional state with immunosuppressive phenotypes in recurrent tumors | Microenvironment |
| Fu and Lei[123], 2022 | scRNA-seq | Primary vs early-relapsed HCC samples | ScRNA-seq analysis of primary vs relapsed HCC identified 645 genes with DGE across three T cell types. Univariate and multivariate analysis identified 15 prognostic genes (AP000866.1, ATIC, CAPN10, EDC3, EID3, NCKIPSD, OXLD1, PHOSPHO2, POLE2, POLR3G, SEPHS1, SRXN1, TIMM9, ZNF487, and ZSCAN9) | Microenvironment |
AFP: Alpha-fetoprotein; CSC: Cancer stem cell; CTL: Cytotoxic T lymphocyte; CYP: Cytochrome P450; DC: Dendritic cell; DFS: Disease-free survival; DGE: Differential gene expression; EHR: Extrahepatic recurrence; EpCAM: Epithelial cellular adhesion molecule; GSTA2: Glutathione S-transferase A2; HBV: Hepatitis B virus; HCC: Hepatocellular carcinoma; HCV: Hepatitis C virus; HIR: Hepatic injury and regeneration; IHR: Intrahepatic recurrence; lncRNA: Long non-coding RNA; MAM: Metastasis-averse microenvironment; MIM: Metastasis-inclined microenvironment; MMP9: Matrix metalloproteinase 9; post-OP: Postoperative; pTNM: Pathological tumor-node-metastasis; PVI: Portal vein invasion; RNA-seq: RNA-sequencing; RT-qPCR: Real-time quantitative reverse transcription; scRNA-seq: Single-cell RNA sequencing; STAT3: Signal transducer and activator of transcription 3; TCGA: The Cancer Genome Atlas; Th2: T helper 2 cell; Treg: T-regulatory cell.