Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy

doi:10.12998/wjcc.v12.i20.4091

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World Journal of Clinical Cases

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2307-8960

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Clin Cases. Jul 16, 2024; 12(20): 4091-4107
Published online Jul 16, 2024. doi: 10.12998/wjcc.v12.i20.4091

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Figure 1 Correlation between neutrophil extracellular traps and chemoimmunotherapy efficacy. A: Portion of high neutrophil extracellular traps (NETs) and low NETs in different efficacy group; B: NET formation in clinical samples. 4',6-diamidino-2-phenylindole (blue); MPO (red); cit-histone 3 (green); C: Levels of NETs positively correlated with the neutrophil-to-lymphocyte ratio; D: Levels of NETs positively correlated with the interleukin-8.

Citation: Li YN, Su JL, Tan SH, Chen XL, Cheng TL, Jiang Z, Luo YZ, Zhang LM. Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy. World J Clin Cases 2024; 12(20): 4091-4107
URL: https://www.wjgnet.com/2307-8960/full/v12/i20/4091.htm
DOI: https://dx.doi.org/10.12998/wjcc.v12.i20.4091