Discipline of Pharmacology, School of Biomedicine, The University of Adelaide, L2 Helen Mayo South, Adelaide, SA, 5000, Australia.
Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia.
Cancer Chemother Pharmacol. 2023 Jun;91(6):507-521. doi: 10.1007/s00280-023-04538-3. Epub 2023 May 10.
Adverse effects following fluoropyrimidine-based chemotherapy regimens are common. However, there are no current accepted diagnostic markers for prediction prior to treatment, and the underlying mechanisms remain unclear. This study aimed to determine genetic and non-genetic predictors of adverse effects.
Genomic DNA was analyzed for 25 single nucleotide polymorphisms (SNPs). Demographics, comorbidities, cancer and fluoropyrimidine-based chemotherapy regimen types, and adverse effect data were obtained from clinical records for 155 Australian White participants. Associations were determined by bivariate analysis, logistic regression modeling and Bayesian network analysis.
Twelve different adverse effects were observed in the participants, the most common severe adverse effect was diarrhea (12.9%). Bivariate analysis revealed associations between all adverse effects except neutropenia, between genetic and non-genetic predictors, and between 8 genetic and 12 non-genetic predictors with more than 1 adverse effect. Logistic regression modeling of adverse effects revealed a greater/sole role for six genetic predictors in overall gastrointestinal toxicity, nausea and/or vomiting, constipation, and neutropenia, and for nine non-genetic predictors in diarrhea, mucositis, neuropathy, generalized pain, hand-foot syndrome, skin toxicity, cardiotoxicity and fatigue. The Bayesian network analysis revealed less directly associated predictors (one genetic and six non-genetic) with adverse effects and confirmed associations between six adverse effects, eight genetic predictors and nine non-genetic predictors.
This study is the first to link both genetic and non-genetic predictors with adverse effects following fluoropyrimidine-based chemotherapy. Collectively, we report a wealth of information that warrants further investigation to elucidate the clinical significance, especially associations with genetic predictors and adverse effects.
基于氟嘧啶的化疗方案的不良反应很常见。然而,目前尚无治疗前预测的公认诊断标志物,其潜在机制仍不清楚。本研究旨在确定不良影响的遗传和非遗传预测因子。
分析了 25 个单核苷酸多态性(SNP)的基因组 DNA。从临床记录中获得了 155 名澳大利亚白人参与者的人口统计学、合并症、癌症和基于氟嘧啶的化疗方案类型以及不良反应数据。通过双变量分析、逻辑回归模型和贝叶斯网络分析确定相关性。
在参与者中观察到 12 种不同的不良反应,最常见的严重不良反应是腹泻(12.9%)。双变量分析显示,除中性粒细胞减少症外,所有不良反应与遗传和非遗传预测因子之间,以及 8 个遗传和 12 个非遗传预测因子与 1 个以上不良反应之间均存在相关性。不良影响的逻辑回归模型显示,在总体胃肠道毒性、恶心和/或呕吐、便秘和中性粒细胞减少症中,6 个遗传预测因子具有更大/唯一作用,在腹泻、粘膜炎、神经病变、全身疼痛、手足综合征、皮肤毒性、心脏毒性和疲劳中,9 个非遗传预测因子具有更大/唯一作用。贝叶斯网络分析显示,与不良反应的直接相关预测因子(一个遗传和六个非遗传)较少,并确认了六个不良反应、八个遗传预测因子和九个非遗传预测因子之间的关联。
本研究首次将遗传和非遗传预测因子与基于氟嘧啶的化疗后不良反应联系起来。总的来说,我们报告了大量的信息,需要进一步研究阐明其临床意义,特别是与遗传预测因子和不良反应的关联。