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Article

SNPs and blood inflammatory marker featured machine learning for predicting the efficacy of fluorouracil-based chemotherapy in colorectal cancer.

Scientific reports - 12 Nov 2024

Li Jiyifan, Zhang Wenxin, Chen Lu, Mao Xiang, Wang Xinhai, Liu Jiafeng, Huang Yuxin, Qi Huijie, Chen Li, Shi Huanying, Chen Bicui, Zhong Mingkang, Li Qunyi, Wang Tianxiao

Abstract excerpt

Fluorouracil-based chemotherapy responses in colorectal cancer (CRC) patients vary widely, highlighting the role of pharmacogenomics in developing better predictive models. We analyzed 379 CRC patients receiving fluorouracil-based chemotherapy, collecting data on fluorouracil metabolism-related SNPs (TYMS, MTHFR, DPYD, RRM1), blood inflammatory markers, and clinical status. Six machine learning models-K-nearest...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 39532939
DOI: 10.1038/s41598-024-79036-4
PMCID: PMC11557704

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