FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithms.

Journal: Cancer medicine
PMID: 31893575

Abstract

Early identification of metastatic or recurrent colorectal cancer (CRC) patients who will be sensitive to FOLFOX (5-FU, leucovorin and oxaliplatin) therapy is very important. We performed microarray meta-analysis to identify differentially expressed genes (DEGs) between FOLFOX responders and nonresponders in metastatic or recurrent CRC patients, and found that the expression levels of WASHC4, HELZ, ERN1, RPS6KB1, and APPBP2 were downregulated, while the expression levels of IRF7, EML3, LYPLA2, DRAP1, RNH1, PKP3, TSPAN17, LSS, MLKL, PPP1R7, GCDH, C19ORF24, and CCDC124 were upregulated in FOLFOX responders compared with nonresponders. Subsequent functional annotation showed that DEGs were significantly enriched in autophagy, ErbB signaling pathway, mitophagy, endocytosis, FoxO signaling pathway, apoptosis, and antifolate resistance pathways. Based on those candidate genes, several machine learning algorithms were applied to the training set, then performances of models were assessed via the cross validation method. Candidate models with the best tuning parameters were applied to the test set and the final model showed satisfactory performance. In addition, we also reported that MLKL and CCDC124 gene expression were independent prognostic factors for metastatic CRC patients undergoing FOLFOX therapy.

Authors

  • Wei Lu
    Department of Pharmacy, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
  • Dongliang Fu
    Department of Colorectal Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Xiangxing Kong
    Department of Surgical Oncology, The Second Affiliated Hospital of Zhejiang University Medical School, Hangzhou, China.
  • Zhiheng Huang
    Department of Colorectal Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Maxwell Hwang
    Department of Colorectal Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Yingshuang Zhu
    Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Liubo Chen
    Department of Colorectal Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Kai Jiang
    Merchant Marine College, Shanghai Maritime University, Shanghai 201306, China.
  • Xinlin Li
    Department of Colorectal Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Yihua Wu
    Department of Toxicology, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China.
  • Jun Li
    Department of Emergency, Zhuhai Integrated Traditional Chinese and Western Medicine Hospital, Zhuhai, 519020, Guangdong Province, China. quanshabai43@163.com.
  • Ying Yuan
    Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. Electronic address: yuany83@163.com.
  • Kefeng Ding
    Department of Surgical Oncology, The Second Affiliated Hospital of Zhejiang University Medical School, Hangzhou, China.

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