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Modular characteristics and the mechanism of Chinese medicine’s treatment of gastric cancer: a data mining and pharmacology-based identification

BACKGROUND: Traditional Chinese medicine (TCM) is increasingly extensively being applied as a complementary and alternative therapy for gastric cancer (GC); however, there is a lack of large-scale evidence-based deep learning for the guidance of its clinical prescription. METHODS: The combinational...

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Autores principales: Xu, Xintian, Chen, Yaling, Zhang, Xingxing, Zhang, Ruijuan, Chen, Xu, Liu, Shenlin, Sun, Qingmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8756228/
https://www.ncbi.nlm.nih.gov/pubmed/35071471
http://dx.doi.org/10.21037/atm-21-6301
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author Xu, Xintian
Chen, Yaling
Zhang, Xingxing
Zhang, Ruijuan
Chen, Xu
Liu, Shenlin
Sun, Qingmin
author_facet Xu, Xintian
Chen, Yaling
Zhang, Xingxing
Zhang, Ruijuan
Chen, Xu
Liu, Shenlin
Sun, Qingmin
author_sort Xu, Xintian
collection PubMed
description BACKGROUND: Traditional Chinese medicine (TCM) is increasingly extensively being applied as a complementary and alternative therapy for gastric cancer (GC); however, there is a lack of large-scale evidence-based deep learning for the guidance of its clinical prescription. METHODS: The combinational search terms of “Gastric cancer and/or gastric malignancy” and “Traditional Chinese Medicine” were used to retrieve clinical study-based herbal prescriptions from public database over the past 3 decades [1990–2020]. Association rules mining (ARM) was used to analyze the prescription patterns of the herbs extracted from the eligible studies. Deep machine learning and computational prediction were conducted to explore candidate prescriptions with general applicability for GC. The action mechanism of the preferred prescription was investigated through network pharmacology, and further validated via in vivo and in vitro experiments. RESULTS: A total of 194 clinical study-based herbal prescriptions with good efficacy for GC were collected. TCM with focus on invigorating the Spleen and tonifying the vital-Qi is a promising adjuvant therapy for GC. The preferred prescription is composed of Atractylodis Macrocephalae Rhizoma, Astragali Radix, Pinelliae Rhizoma, Citri Reticulatae Pericarpium, Herba Hedyotidis Diffusae, Crataegi Fructus, and so on. We screened 74 bioactive compounds and 2,128 predictive targets of the preferred prescription from public databases. Eventually, 135 GC-related genes were identified as the targets of the preferred prescription. The compound-target network revealed that the crucial substances in the preferred prescription are quercetin, kaempferol, baicalein, and nobiletin. Experimentally, the preferred prescription was validated to modulate GC cell survival and inhibit tumor progression mainly via the hTERT/MDM2-p53 signaling pathway in vivo and in vitro. CONCLUSIONS: TCM aimed at invigorating the Spleen and tonifying the vital-Qi is a promising adjuvant therapy for GC, which offers a guidance for worldwide use of TCM in the treatment of GC.
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spelling pubmed-87562282022-01-21 Modular characteristics and the mechanism of Chinese medicine’s treatment of gastric cancer: a data mining and pharmacology-based identification Xu, Xintian Chen, Yaling Zhang, Xingxing Zhang, Ruijuan Chen, Xu Liu, Shenlin Sun, Qingmin Ann Transl Med Original Article BACKGROUND: Traditional Chinese medicine (TCM) is increasingly extensively being applied as a complementary and alternative therapy for gastric cancer (GC); however, there is a lack of large-scale evidence-based deep learning for the guidance of its clinical prescription. METHODS: The combinational search terms of “Gastric cancer and/or gastric malignancy” and “Traditional Chinese Medicine” were used to retrieve clinical study-based herbal prescriptions from public database over the past 3 decades [1990–2020]. Association rules mining (ARM) was used to analyze the prescription patterns of the herbs extracted from the eligible studies. Deep machine learning and computational prediction were conducted to explore candidate prescriptions with general applicability for GC. The action mechanism of the preferred prescription was investigated through network pharmacology, and further validated via in vivo and in vitro experiments. RESULTS: A total of 194 clinical study-based herbal prescriptions with good efficacy for GC were collected. TCM with focus on invigorating the Spleen and tonifying the vital-Qi is a promising adjuvant therapy for GC. The preferred prescription is composed of Atractylodis Macrocephalae Rhizoma, Astragali Radix, Pinelliae Rhizoma, Citri Reticulatae Pericarpium, Herba Hedyotidis Diffusae, Crataegi Fructus, and so on. We screened 74 bioactive compounds and 2,128 predictive targets of the preferred prescription from public databases. Eventually, 135 GC-related genes were identified as the targets of the preferred prescription. The compound-target network revealed that the crucial substances in the preferred prescription are quercetin, kaempferol, baicalein, and nobiletin. Experimentally, the preferred prescription was validated to modulate GC cell survival and inhibit tumor progression mainly via the hTERT/MDM2-p53 signaling pathway in vivo and in vitro. CONCLUSIONS: TCM aimed at invigorating the Spleen and tonifying the vital-Qi is a promising adjuvant therapy for GC, which offers a guidance for worldwide use of TCM in the treatment of GC. AME Publishing Company 2021-12 /pmc/articles/PMC8756228/ /pubmed/35071471 http://dx.doi.org/10.21037/atm-21-6301 Text en 2021 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Xu, Xintian
Chen, Yaling
Zhang, Xingxing
Zhang, Ruijuan
Chen, Xu
Liu, Shenlin
Sun, Qingmin
Modular characteristics and the mechanism of Chinese medicine’s treatment of gastric cancer: a data mining and pharmacology-based identification
title Modular characteristics and the mechanism of Chinese medicine’s treatment of gastric cancer: a data mining and pharmacology-based identification
title_full Modular characteristics and the mechanism of Chinese medicine’s treatment of gastric cancer: a data mining and pharmacology-based identification
title_fullStr Modular characteristics and the mechanism of Chinese medicine’s treatment of gastric cancer: a data mining and pharmacology-based identification
title_full_unstemmed Modular characteristics and the mechanism of Chinese medicine’s treatment of gastric cancer: a data mining and pharmacology-based identification
title_short Modular characteristics and the mechanism of Chinese medicine’s treatment of gastric cancer: a data mining and pharmacology-based identification
title_sort modular characteristics and the mechanism of chinese medicine’s treatment of gastric cancer: a data mining and pharmacology-based identification
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8756228/
https://www.ncbi.nlm.nih.gov/pubmed/35071471
http://dx.doi.org/10.21037/atm-21-6301
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