背景:结直肠癌(CRC)的耐药性受多种分子因素调节,这可以通过基因调查来确定。关键基因内的单核苷酸多态性(SNP)具有损害化疗剂如5-氟尿嘧啶(5-FU)的功效的潜力。因此,在CRC患者中,与耐药相关的SNP的鉴定可显著促进定制治疗方法的进展和治疗结局的提高.
方法:为了鉴定基于5-FU的化疗应答者或非应答者CRC患者中失调的基因,进行了荟萃分析.接下来,使用STRING数据库分析已鉴定基因的蛋白质-蛋白质相互作用(PPI)网络.选择最重要的模块进行进一步分析。此外,进行了文献综述以鉴定耐药相关基因。进行富集分析以验证主要模块基因和从文献综述中鉴定的基因。研究了SNP与耐药性之间的关系,和错义变异的后果使用silico工具进行评估。
结果:荟萃分析鉴定出796个失调基因。然后,进行PPI分析和富集分析,我们发现了23个与细胞周期通路密切相关的基因。因此,选择这23个基因进行SNP分析.通过使用dbSNP数据库和ANNOVAR,我们成功地检测并标记了这些特定基因中的SNP。此外,在仔细排除等位基因频率低于0.01的SNP后,我们评估了来自HDAC1,MCM2,CDK1,BUB1B,CDC14B,和CCNE1基因使用8种生物信息学工具。因此,这些SNP被多个计算工具鉴定为潜在有害的.具体来说,CDK1(Val124Gly)中的rs199958833被预测为使用的所有工具都有损害。我们的分析强烈表明该特异性SNP可能对CDK1蛋白的稳定性和功能性产生负面影响。
结论:根据我们目前的理解,关于CDK1多态性在CRC耐药情况下的评估尚待进行.在这次调查中,我们发现CDK1基因中的rs199958833变异可能有利于对基于5-FU的化疗耐药。然而,这些发现需要在独立的患者队列中进行验证.
BACKGROUND: Drug resistance in colorectal cancer (CRC) is modulated by multiple molecular factors, which can be ascertained through genetic investigation. Single nucleotide polymorphisms (SNPs) within key genes have the potential to impair the efficacy of chemotherapeutic agents such as 5-fluorouracil (5-FU). Therefore, the identification of SNPs linked to drug resistance can significantly contribute to the advancement of tailored therapeutic approaches and the enhancement of treatment outcomes in patients with CRC.
METHODS: To identify dysregulated genes in 5-FU-based chemotherapy responder or non-responder CRC patients, a meta-analysis was performed. Next, the protein-protein interaction (PPI) network of the identified genes was analyzed using the STRING database. The most significant module was chosen for further analysis. In addition, a literature review was conducted to identify drug resistance-related genes. Enrichment analysis was conducted to validate the main module genes and the genes identified from the literature review. The associations between SNPs and drug resistance were investigated, and the consequences of missense variants were assessed using in silico tools.
RESULTS: The meta-analysis identified 796 dysregulated genes. Then, to conduct PPI analysis and enrichment analysis, we were able to discover 23 genes that are intricately involved in the cell cycle pathway. Consequently, these 23 genes were chosen for SNP analysis. By using the dbSNP database and ANNOVAR, we successfully detected and labeled SNPs in these specific genes. Additionally, after careful exclusion of SNPs with allele frequencies below 0.01, we evaluated 6 SNPs from the HDAC1, MCM2,
CDK1, BUB1B, CDC14B, and CCNE1 genes using 8 bioinformatics tools. Therefore, these SNPs were identified as potentially harmful by multiple computational tools. Specifically, rs199958833 in
CDK1 (Val124Gly) was predicted to be damaging by all tools used. Our analysis strongly indicates that this specific SNP could negatively affect the stability and functionality of the
CDK1 protein.
CONCLUSIONS: Based on our current understanding, the evaluation of
CDK1 polymorphisms in the context of drug resistance in CRC has yet to be undertaken. In this investigation, we showed that rs199958833 variant in the
CDK1 gene may favor resistance to 5-FU-based chemotherapy. However, these findings need validation in an independent cohort of patients.