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. 2018 Aug 15;9:309. doi: 10.3389/fgene.2018.00309

Table 2.

Subclassification of ICCs and their associated genetic alterations.

Classification Technology Subtype I Subtype II References
Class Characters Class Characters
Cells of origin RNA-Seq
WES
Proteomics
C1 class - Mutations in TP53, BAP1, ARID1A, ARID2
- Altered expression of PLK1 and ECT2
C2 class - Obesity
- Bile acid metabolism
- T-cell infiltration
Chaisaingmongkol et al., 2017
Anatomical structure WGS
WES
RNA-Seq
ICC-specific - FGFR2 fusion
- IDH1/2, EPHA2, BAP1 Mutation
ICC and ECC shared - KRAS, SMAD4, ARID1A and GNAS mutation Nakamura et al., 2015
Liver-fluke infection Microarray Liver fluke positive - Xenobiotic metabolism Liver fluke negative - Growth factor signaling Jinawath et al., 2006
WGS
WES
WGS
- TP53, KRAS, SMAD4, MLL3, ROBO2, RNF43, PEG3 and GNAS oncogene - BAP1, IDH1/2 Ong et al., 2012; Chan-On et al., 2013
Epigenomics - High somatic mutations
- TP53, ARID1A and BRCA1/2 mutations
- ERBB2 amplification
- Hypermethylation in promoter CpG islands
- H3K27me3-associated promoter mutations
- Poorer prognosis
- High copy-number alterations
- BAP1 and IDH1/2 mutations
- Altered PD-1/PD-L2 expression
- Alterations and elevated expression of FGFR genes
- Hypermethylation in promotor CpG shore
- Better prognosis
Jusakul et al., 2017
Gene expression and copy number alterations - Microarray
- SNP array
Proliferation class - Oncogenic pathways
- Mutations in KRAS, BRAF and EGFR
- Chr11q13.2 amplification
- Chr14q22.1 deletion
- Moderate/poorly differentiated
- Poorer prognosis
Inflammation class - Inflammatory pathways (Interleukins/chemokines),
- STAT3 activation signaling pathway
- Well differentiated
- Better prognosis
Sia et al., 2013a,b Sia et al., 2017
Prognosis - Microarray Poor prognosis - Mutations in KRAS and BRAF Good prognosis - No KRAS mutation Andersen et al., 2013
Mutations and copy number alterations - WGS
- RNA-seq
M class - Recurrent mutations of KRAS, TP53, IDH1 C class - Recurrent focal copy number alterations including deletions involving CDKN2A, ROBO1/2, RUNX3 and SMAD4 Kim et al., 2016