Evidence map›Paper›PMID 33558586›Full record

ReviewScientific reports2021

In silico identification of natural products from Traditional Chinese Medicine for cancer immunotherapy.

Chuipu Cai, Qihui Wu, Honghai Hong, Liying He, Zhihong Liu, Yong Gu, Shijie Zhang, Qi Wang, Xiude Fan, Jiansong Fang

Open access · goldAbstract readReview
In one paragraph

Review in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.9field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 38 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Mini reviews in medicinal chemistry · 2024
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  7. Network-based drug repurposing for potential stroke therapy.Computational and structural biotechnology journal · 2023
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  8. Review
  9. Article
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  11. DPHB, a diarylheptane fromFrontiers in pharmacology · 2022
    Article
  12. Article
  13. Frontiers in pharmacology · 2021
    Article
  14. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 2 countries.

Chuipu Cai *Department of Computer Science, Key Laboratory of Intelligent Manufacturing Technology of Ministry of Education, Shantou University, Shantou, 515000, China.
Qihui Wu *Clinical Research Center, Hainan Provincial Hospital of Traditional Chinese Medicine, Haikou, 570100, China.
Honghai Hong *Department of Clinical Laboratory, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Liying HeScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
Zhihong LiuGuangdong Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, 510000, China.
Yong GuClinical Research Center, Hainan Provincial Hospital of Traditional Chinese Medicine, Haikou, 570100, China.
Shijie ZhangScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
Qi WangScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.
Xiude FanLerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA. FANX@ccf.org.
Jiansong FangScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China. fangjs@gzucm.edu.cn.
Guangzhou University of Chinese Medicine · CNHainan Provincial Hospital of Traditional Chinese Medicine · CNCleveland Clinic Lerner College of Medicine · USInstitute of Microbiology · CNThird Affiliated Hospital of Guangzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in immunotherapy have revolutionized treatments in many types of cancer. Traditional Chinese Medicine (TCM), which has a long history of clinical adjuvant application against cancer, is emerging as an important medical resource for developing innovative cancer treatments, including immunotherapy. In this study, we developed a quantitative and systems pharmacology-based framework to identify TCM-derived natural products for cancer immunotherapy. Specifically, we integrated 381 cancer immune response-related genes and a compound-target interaction network connecting 3273 proteins and 766 natural products from 66 cancer-related herbs based on literature-mining. Via systems pharmacology-based prediction, we uncovered 182 TCM-derived natural products having potential anti-tumor immune responses effect. Importantly, 32 of the 49 most promising natural products (success rate = 65.31%) are validated by multiple evidence, including published experimental data from clinical studies, in vitro and in vivo assays. We further identified the mechanism-of-action of TCM in cancer immunotherapy using network-based functional enrichment analysis. We showcased that three typical natural products (baicalin, wogonin, and oroxylin A) in Huangqin (Scutellaria baicalensis Georgi) potentially overcome resistance of known oncology agents by regulating tumor immunosuppressive microenvironments. In summary, this study offers a novel and effective systems pharmacology infrastructure for potential cancer immunotherapeutic development by exploiting the medical wealth of natural products in TCM.

Indexed as

Computer SimulationImmunotherapyMedicine, Chinese TraditionalAntineoplastic Agents, PhytogenicDrugs, Chinese HerbalHumansNeoplasmsAntineoplastic Agents, PhytogenicDrugs, Chinese Herbal

Identifiers

PMID33558586
PMCPMC7870934
OpenAlexW3128287526

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.