Evidence map›Paper›PMID 31408580›Full record

ArticleMolecular oncology2019

Prioritization of candidate cancer drugs based on a drug functional similarity network constructed by integrating pathway activities and drug activities.

Jieyi Di, Baotong Zheng, Qingfei Kong, Ying Jiang, Siyao Liu, Yang Yang, Xudong Han, Yuqi Sheng, Yunpeng Zhang, Liang Cheng and 1 more

Abstract read
In one paragraph

Article in Molecular oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. DrugRepoBank: a comprehensive database and discovery platform for accelerating drug repositioning.Database : the journal of biological databases and curation · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Guiding Drug Repositioning for Cancers Based on Drug Similarity Networks.International journal of molecular sciences · 2023
    Article
  8. Article
  9. Article
  10. Informatics on Drug Repurposing for Breast Cancer.Drug design, development and therapy · 2023
    Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Artificial Intelligence for Precision Oncology.Advances in experimental medicine and biology · 2022
    Review
  17. Lung Cancer Stage Prediction Using Multi-Omics Data.Computational and mathematical methods in medicine · 2022
    Article
  18. Article
  19. Article
  20. Article
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

11 authors.

Jieyi DiCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Baotong ZhengCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Qingfei KongDepartment of Neurobiology, Harbin Medical University, China.
Ying JiangCollege of Basic Medical Science, Heilongjiang University of Chinese Medicine, Harbin, China.
Siyao LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Yang YangCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Xudong HanCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Yuqi ShengCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Yunpeng ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Liang ChengCollege of Bioinformatics Science and Technology, Harbin Medical University, China.
Junwei HanCollege of Bioinformatics Science and Technology, Harbin Medical University, China.ORCID 0000-0002-3276-0819

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the speed, efficiency, relative risk, and lower costs compared to traditional drug discovery, the prioritization of candidate drugs for repurposing against cancers of interest has attracted the attention of experts in recent years. Herein, we present a powerful computational approach, termed prioritization of candidate drugs (PriorCD), for the prioritization of candidate cancer drugs based on a global network propagation algorithm and a drug-drug functional similarity network constructed by integrating pathway activity profiles and drug activity profiles. This provides a new approach to drug repurposing by first considering the drug functional similarities at the pathway level. The performance of PriorCD in drug repurposing was evaluated by using drug datasets of breast cancer and ovarian cancer. Cross-validation tests on the drugs approved for the treatment of these cancers indicated that our approach can achieve area under receiver-operating characteristic curve (AUROC) values greater than 0.82. Furthermore, literature searches validated our results, and comparison with other classical gene-based repurposing methods indicated that our pathway-level PriorCD is comparatively more effective at prioritizing candidate drugs with similar therapeutic effects. We hope that our study will be of benefit to the field of drug discovery. In order to expand the usage of PriorCD, a freely available R-based package, PriorCD, has been developed to prioritize candidate anticancer drugs for drug repurposing.

Indexed as

AlgorithmsAntineoplastic AgentsBreast NeoplasmsComputational BiologyDrug DiscoveryDrug RepositioningFemaleHumansMicroRNAsNeoplasmsOvarian NeoplasmsRNA, MessengerROC CurveSoftwareAntineoplastic AgentsMicroRNAsRNA, Messengerdrug activitiesdrug functional similarity networkdrug repurposingpathway activities

Identifiers

PMID31408580
PMCPMC6763777

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.