单核苷酸多态性(SNP)在各种恶性肿瘤中发挥重要作用,但它们在胆管癌(CCA)中的作用仍有待阐明。因此,本系统综述的目的是评估SNP与CCA之间的关联,关注肿瘤发生和预后。使用PubMed进行了系统的文献检索,Embase,WebofScience和Cochrane数据库,用于SNP和CCA之间的关联,包括2000年1月至2022年4月出版的文献。这篇系统综述汇编了32个与CCA风险相关的基因中的43个SNP,基于34项研究的转移性进展和总体预后。对CCA的易感性与炎症相关基因中的SNP有关(PTGS2/COX2,IL6,IFNG/IFN-γ,TNF/TNF-α),DNA修复(ERCC1,MTHFR,MUTYH,XRCC1,OGG1),解毒(NAT1,NAT2和ABCC2),酶(SERPINA1,GSTO1,APOBEC3A,APOBEC3B),RNA(HOTAIR)和膜基蛋白(EGFR,GAB1,KLRK1/NKG2D)。总体肿瘤预后也与8个基因(GNB3,NFE2L2/NRF2,GALNT14,EGFR,XRCC1,EZH2,GNAS,CXCR1)。我们的发现表明,多个SNP在CCA的各个阶段发挥不同的作用,并可能作为生物标志物指导治疗和允许肿瘤风险评估。考虑到SNP检测方法的差异,患者种族和相应的环境因素,需要进行更大规模的多中心调查,以充分确定SNP分析在CCA易感性预测和预后方面的潜力.
Single-nucleotide polymorphisms (SNPs) play an essential role in various malignancies, but their role in cholangiocarcinoma (CCA) remains to be elucidated. Therefore, the purpose of this systematic
review was to evaluate the association between SNPs and CCA, focusing on tumorigenesis and prognosis. A systematic literature search was carried out using PubMed, Embase, Web of Science and the Cochrane database for the association between SNPs and CCA, including literature published between January 2000 and April 2022. This systematic
review compiles 43 SNPs in 32 genes associated with CCA risk, metastatic progression and overall prognosis based on 34 studies. Susceptibility to CCA was associated with SNPs in genes related to inflammation (PTGS2/COX2, IL6, IFNG/IFN-γ, TNF/TNF-α), DNA repair (ERCC1, MTHFR, MUTYH, XRCC1, OGG1), detoxification (NAT1, NAT2 and ABCC2), enzymes (SERPINA1, GSTO1, APOBEC3A, APOBEC3B), RNA (HOTAIR) and membrane-based proteins (EGFR, GAB1, KLRK1/NKG2D). Overall oncological prognosis was also related to SNPs in eight genes (GNB3, NFE2L2/NRF2, GALNT14, EGFR, XRCC1, EZH2, GNAS, CXCR1). Our findings indicate that multiple SNPs play different roles at various stages of CCA and might serve as biomarkers guiding treatment and allowing oncological risk assessment. Considering the differences in SNP detection methods, patient ethnicity and corresponding environmental factors, more large-scale multicentric investigations are needed to fully determine the potential of SNP analysis for CCA susceptibility prediction and prognostication.