Frontiers in Pharmacology (Oct 2022)

Discovering the potential active ingredients of Qi-Yu-San-Long decoction for anti-oxidation, inhibition of non-small cell lung cancer based on the spectrum-effect relationship combined with chemometric methods

  • Mengwen Huang,
  • Ruijuan Li,
  • Mo Yang,
  • An Zhou,
  • Hong Wu,
  • Zegeng Li,
  • Zegeng Li,
  • Zegeng Li,
  • Huan Wu,
  • Huan Wu

DOI
https://doi.org/10.3389/fphar.2022.989139
Journal volume & issue
Vol. 13

Abstract

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Qi-Yu-San-Long decoction (QYSLD), a traditional Chinese medicine (TCM) prescription, consisting of ten types of herbal medicine which has significant clinical efficacy in the treatment of non-small cell lung cancer (NSCLC). However, the bioactive ingredients of QYSLD remain unclear, due to their “multi-ingredients” and “multi-targets” features. This study aimed to construct a spectrum-effect correlation analysis model and screen the potential active components of QYSLD. A fingerprint method based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) was developed and validated to obtain seventy common peaks of ten batches of QYSLD. The results of methodological evaluation, including precision, repeatability and stability, were less than 8.19%. In terms of linearity, eleven common components did not reach the linear standard (R2 < 0.99), they were removed before spectrum-effect relationship analysis. After treated with ten batches of QYSLD, the results of DPPH and FRAP assays ranged from 1.59 to 5.50 mg mL−1 and 143.83–873.83 μmol L−1, respectively. Meanwhile, the cell viabilities of A549 cells treated with QYSLD samples ranged from 21.73% to 85.71%. The relative healing rates ranged from 21.50% to 44.46%. The number of migrated and invaded cells ranged from 12.00 to 68.67 and 7.67 to 27.00, respectively. Then, the potential active components of QYSLD were screened through spectrum-effect relationship constructed by grey correlation analysis (GRA), partial least squares regression (PLSR) and backpropagation neural network (BP-ANN). The results were as follow: 1) eight ingredients of QYSLD were relevant to DPPH free radical scavenging ability; 2) nine ingredients were relevant to FRAP; 3) six ingredients were relevant to inhibit the proliferation ability of A549 cells; 4) twenty-two ingredients were relevant to inhibit the horizontal migration ability; 5) five ingredients were relevant to inhibit the vertical migration ability; 6) twelve ingredients were relevant to inhibit the invasion ability. Confirmatory experiments showed that compared with the unscreened ingredients, the potential active ingredients screened by the spectrum-effect relationship had better antioxidant and anti-NSCLC effects. In general, this study found the potential active ingredients in QYSLD. Meanwhile, the established method provided a valuable reference model for the potential active ingredients of TCM.

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