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Alonso-Peña et al. Cancer Drug Resist 2019;2:680-709  I  http://dx.doi.org/10.20517/cdr.2019.006                                            Page 689

               Table 4. Germline (G) and somatic (S) mutations affecting coding (c) and non-coding (nc) regions in genes coding phase II
               enzymes in primary liver cancer
                                                        Protein   Functional   Clinical
               Gene    Protein  Genetic mutations  G/S Region                            Studies  References
                                                       mutations  consequences consecuences
               DCK    DCK     c.*823C>T      S   nc   3’ UTR      Modifier  ND         TCGA-LIHC    TCGA
                              c.*157G>T      S   nc   3’ UTR      Modifier  ND         TCGA-LIHC    TCGA
               CDA    CDA     c.208G>A       G   c    Ala70Thr    High     Neutropenia   Several types   [87]
                                                                           and decreased   of cancer
                                                                           clearance of
                                                                           gemcitabine
                              c.271A>G       S   c    Met91Val    Moderate  Neutral    TCGA-LIHC   TCGA
                              c.267-1G>A     S   c    Splice acceptor  High  Pathogenic  TCGA-LIHC  TCGA
                              c.157T>C       S   c    Cys53Arg    Moderate  ND         TCGA-LIHC   TCGA
               MET    MET     c.65G>T        S   c    Ser22Ile    Moderate  ND         TCGA-LIHC   TCGA
                              c.3713A>T      S   c    His1238Leu  Moderate  ND         TCGA-LIHC   TCGA
                              c.3767A>T               His1256Leu  Moderate  ND         TCGA-LIHC   TCGA
               SULT1A1 SULT1A1  c.-265_-     S   nc   5’ UTR      Modifier  ND         TCGA-CHOL   TCGA
                              258delGTGAGGGG
                              c.-4-460_-4-   S   nc   Intron      Modifier  ND         TCGA-CHOL   TCGA
                              453delGTGAGGGG
               UGT2B7 UGT2B7  c.311C>A       S   c    Thr104Lys   Moderate  Neutral    TCGA-LIHC   TCGA
                              c.22G>T        S   c    Val8Leu     Moderate  ND         TCGA-LIHC   TCGA
                              c.282_283delTA  S  c    Lys95Glufs*26  High  ND          TCGA-LIHC   TCGA
                              c.589_591delGTT  S  c   Val197del   Moderate  ND         TCGA-LIHC   TCGA
               UGT1A1 UGT1A1  c.725T>A       S   c    Val242Glu   Moderate  ND         TCGA-LIHC   TCGA
               UGT1A3 UGT1A3  c.779A>G       S   c    Asp260Gly   Moderate  ND         TCGA-LIHC   TCGA
                              c.457C>T       S   c    Pro153Ser   Modifier  ND         TCGA-LIHC   TCGA
                              c.867+13031C>T  S  c    Intron      Modifier  ND         TCGA-LIHC   TCGA
                              c.867+17971A>G  S  c    Intron      Moderate  ND         TCGA-LIHC   TCGA
               UGT1A9 UGT1A9  c.668T>A       S   c    Phe223Tyr   Moderate  Neutral    TCGA-LIHC   TCGA
               Data obtained from TCGA database (https://cancergenome.nih.gov/) and referred literature. Functional consequences are based on VEP
               (Variant Effect Predictor; https://www.ensembl.org/vep) impact: High means that the variant is supposed to cause a high disruptive
               impact in the protein, which is likely to cause loss of function; Moderate means that the variant may be not disruptive, but results in a
               decrease effectiveness of the encoded protein; Modifier is usually referred to non-coding variants, whose impact is difficult to determine,
               although they can be involved in transcription or splicing changes. ND: not described; TCGA: the cancer genome atlas; TCGA-LIHC: the
               cancer genome atlas - liver hepatocellular carcinoma; TCGA-CHOL: the cancer genome atlas - cholangiocarcinoma

               (p.Ile359Leu) was expressed in HCC . CYP3A4 is the major enzyme involved in metabolism of drugs,
                                               [79]
               which includes sorafenib, gefitinib and paclitaxel. However, CYP3A4 is usually very poorly expressed in
               tumors and cell lines of different origin . Thus, CYP3A4 activity has been found markedly decreased in
                                                 [88]
               tumors of 96 patients with HBV-positive HCC, as compared with the adjacent non-tumor tissue .
                                                                                                [85]
               Epoxide hydrolase (EH) metabolizes epoxy eicosatrienoinc acids (EETs) and other lipid epoxides and is
               involved in a variety of biological activities, such angiogenesis and cancer metastasis . The microsomal
                                                                                         [89]
               form of EH (mEH) has been characterized and two SNPs in the coding region, c.337T>C (p.Tyr113His) and
               c.416A>G (p.His139Arg) have been identified. Both variants have lower enzyme activity compared to the
               wild-type protein [90,91] . The relationship between these variants and HCC is poorly understood . In a meta-
                                                                                              [92]
               analysis involving 1,696 HCC cases, the His113-mEH allele was significantly associated with increased risk
               of HCC, whereas the Arg139-mEH genotype had no association with HCC development .
                                                                                          [80]
               Dihydropyrimidine dehydrogenase (DPD, gene symbol DPYD), which is highly expressed in human liver,
               is involved in the first step of pyrimidines breakdown. DPD converts thymine to 5,6-dihydrothymine and
               uracil to 5,6-dihydrouracil. Accordingly, this catalytic activity can modify the effectiveness of 5-FU .
                                                                                                        [93]
               Thus, intratumor levels of this drug can vary among patients, despite of receiving the same dose . DPD
                                                                                                   [94]
               polymorphisms play a key role in this differential response . Although more than 200 polymorphisms
                                                                   [86]
               have been identified, in vitro studies have shown that only few of them have a deleterious impact on DPD
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