Evidence map›Paper›PMID 31852840›Full record

ArticleAging2019

System level characterization of small molecule drugs and their affected long noncoding RNAs.

Haixiu Yang, Yanan Jiang, Yunpeng Zhang, Yanjun Xu, Chunlong Zhang, Junwei Han, Fei Su, Xiaoqi Liu, Kai Mi, Bing Liu and 1 more

Open access · greenAbstract read
In one paragraph

Article in Aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 35% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Interplay between LncRNAs and microRNAs in Breast Cancer.International journal of molecular sciences · 2023
    Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. 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

11 authors at 1 institution in 1 country.

Haixiu YangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yanan JiangTranslational Medicine Research and Cooperation Center of Northern China, Heilongjiang Academy of Medical Sciences, Harbin 150081, Heilongjiang, China.
Yunpeng ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yanjun XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Chunlong ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Junwei HanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Fei SuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Xiaoqi LiuDepartment of Orthopedic Surgery, The Second Affiliated Hospital, Harbin Medical University, Harbin 150001, China.
Kai MiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Bing LiuTranslational Medicine Research and Cooperation Center of Northern China, Heilongjiang Academy of Medical Sciences, Harbin 150081, Heilongjiang, China.
Desi ShangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long noncoding RNAs (lncRNAs) have multiple regulatory roles and are involved in many human diseases. A potential therapeutic strategy based on targeting lncRNAs was recently developed. To gain insight into the global relationship between small molecule drugs and their affected lncRNAs, we constructed a small molecule lncRNA network consisting of 1206 nodes (1033 drugs and 173 lncRNAs) and 4770 drug-lncRNA associations using LNCmap, which reannotated the microarray data from the Connectivity Map (CMap) database. Based on network biology, we found that the connected drug pairs tended to share the same targets, indications, and side effects. In addition, the connected drug pairs tended to have a similar structure. By inferring the functions of lncRNAs through their co-expressing mRNAs, we found that lncRNA functions related to the modular interface were associated with the mode of action or side effects of the corresponding connected drugs, suggesting that lncRNAs may directly/indirectly participate in specific biological processes after drug administration. Finally, we investigated the tissue-specificity of drug-affected lncRNAs and found that some kinds of drugs tended to have a broader influence (e.g. antineoplastic and immunomodulating drugs), whereas some tissue-specific lncRNAs (nervous system) tended to be affected by multiple types of drugs.

Indexed as

Gene Regulatory NetworksPharmaceutical PreparationsGene Expression ProfilingGene Expression RegulationHumansRNA, Long NoncodingRNA, MessengerPharmaceutical PreparationsRNA, Long NoncodingRNA, Messengerlong noncoding RNAsnetworkpharmacological analysissmall molecule drugstissue-specificity

Identifiers

PMID31852840
PMCPMC6949102
OpenAlexW2996301489

What OpenQuestion 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 OpenQuestion graph.