Evidence map›Paper›PMID 25652794›Full record

ArticleBMC genomics2015

Integrating transcriptomics and proteomics to show that tanshinone IIA suppresses cell growth by blocking glucose metabolism in gastric cancer cells.

Li-Ling Lin, Chieh-Ren Hsia, Chia-Lang Hsu, Hsuan-Cheng Huang, Hsueh-Fen Juan

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.

  1. Pooled it
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  10. Frontiers in pharmacology · 2022
    Review
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  15. Article
  16. Multi-omics Integration Analysis Robustly Predicts High-Grade Patient Survival and Identifies CPT1B Effect on Fatty Acid Metabolism in Bladder Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019
    Article
  17. Article
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  19. Article
  20. The Use of Omic Technologies Applied to Traditional Chinese Medicine Research.Evidence-based complementary and alternative medicine : eCAM · 2017
    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

5 authors at 2 institutions in 1 country.

Li-Ling LinDepartment of Life Science, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 106, Taiwan. f94b43019@ntu.edu.tw.
Chieh-Ren HsiaDepartment of Life Science, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 106, Taiwan. chiehren@gmail.com.
Chia-Lang HsuDepartment of Life Science, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 106, Taiwan. auymle@gmail.com.
Hsuan-Cheng HuangInstitute of Biomedical Informatics and Center for Systems and Synthetic Biology, National Yang-Ming University, No.155, Sec.2, Linong Street, Taipei, 112, Taiwan. hsuancheng@ym.edu.tw.
Hsueh-Fen JuanDepartment of Life Science, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 106, Taiwan. yukijuan@ntu.edu.tw.
National Taiwan University · TWNational Yang Ming Chiao Tung University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTanshinone IIA (TIIA) is a diterpene quinone extracted from the plant Danshen (Salvia miltiorrhiza) used in traditional Chinese herbal medicine. It has been reported to have anti-tumor potential against several kinds of cancer, including gastric cancer. In most solid tumors, a metabolic switch to glucose is a hallmark of cancer cells, which do this to provide nutrients for cell proliferation. However, the mechanism associated with glucose metabolism by which TIIA acts on gastric cancer cells remains to be elucidated.

resultsWe found that TIIA treatment is able to significantly inhibit cell growth and the proliferation of gastric cancer in a dose-dependent manner. Using next-generation sequencing-based RNA-seq transcriptomics and quantitative proteomics-isobaric tags for relative and absolute quantification (iTRAQ), we characterized the mechanism of TIIA regulation in gastric cancer cell line AGS. In total, 16,603 unique transcripts and 102 proteins were identified. After enrichment analysis, we found that TIIA regulated genes are involved in carbohydrate metabolism, the cell cycle, apoptosis, DNA damage and cytoskeleton reorganization. Our proteomics data revealed the downregulation of intracellular ATP levels, glucose-6-phosphate isomerase and L-lactate dehydrogenase B chains by TIIA, which might work with disorders of glucose metabolism and extracellular lactate levels to suppress cell proliferation. The up-regulation of p53 and down-regulation of AKT was shown in TIIA- treated cells, which indicates the transformation of oncogenes. Severe DNA damage, cell cycle arrest at the G2/M transition and apoptosis with cytoskeleton reorganization were detected in TIIA-treated gastric cancer cells.

conclusionsCombining transcriptomics and proteomics results, we propose that TIIA treatment could lead cell stresses, including nutrient deficiency and DNA damage, by inhibiting the glucose metabolism of cancer cells. This study provides an insight into how the TIIA regulatory metabolism in gastric cancer cells suppresses cell growth, and may help improve the development of cancer therapy.

Indexed as

ProteomicsAbietanesCell Line, TumorCell ProliferationDrugs, Chinese HerbalGene Expression Regulation, NeoplasticGlucoseHumansNeoplasm ProteinsStomach NeoplasmsTranscriptomeAbietanesDrugs, Chinese HerbalGlucoseNeoplasm Proteinstanshinone

Identifiers

PMID25652794
PMCPMC4328042
OpenAlexW2048193771

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.