Evidence map›Paper›PMID 27631970›Full record

ArticlePloS one2016

Radiation Changes the Metabolic Profiling of Melanoma Cell Line B16.

Lige Wu, Zixi Hu, Yingying Huang, Yating Yu, Wei Liang, Qinghui Zheng, Xianing Huang, Yong Huang, Xiaoling Lu, Yongxiang Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Review
  2. Increased [Npj imaging · 2024
    Article
  3. Review
  4. One extraction tool forJournal of pharmaceutical analysis · 2021
    Article
  5. Review
  6. Review
  7. Article
  8. 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

10 authors.

Lige WuNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.ORCID http://orcid.org/0000-0002-9388-6706
Zixi HuNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
Yingying HuangNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
Yating YuNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
Wei LiangNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
Qinghui ZhengNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
Xianing HuangNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
Yong HuangNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
Xiaoling LuNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
Yongxiang ZhaoNational Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiation therapy can be an effective way to kill cancer cells using ionizing radiation, but some tumors are resistant to radiation therapy and the underlying mechanism still remains elusive. It is therefore necessary to establish an appropriate working model to study and monitor radiation-mediated cancer therapy. In response to cellular stress, the metabolome is the integrated profiling of changes in all metabolites in cells, which can be used to investigate radiation tolerance mechanisms and identify targets for cancer radiation sensibilization. In this study, using 1H nuclear magnetic resonance for untargeted metabolic profiling in radiation-tolerant mouse melanoma cell line B16, we comprehensively investigated changes in metabolites and metabolic network in B16 cells in response to radiation. Principal component analysis and partial least squares discriminant analysis indicated the difference in cellular metabolites between the untreated cells and X-ray radiated cells. In radiated cells, the content of alanine, glutamate, glycine and choline was increased, while the content of leucine, lactate, creatine and creatine phosphate was decreased. Enrichment analysis of metabolic pathway showed that the changes in metabolites were related to multiple metabolic pathways including the metabolism of glycine, arginine, taurine, glycolysis, and gluconeogenesis. Taken together, with cellular metabolome study followed by bioinformatic analysis to profile specific metabolic pathways in response to radiation, we deepened our understanding of radiation-resistant mechanisms and radiation sensibilization in cancer, which may further provide a theoretical and practical basis for personalized cancer therapy.

Indexed as

AnimalsCell Line, TumorMelanoma, ExperimentalMetabolomeMicePrincipal Component Analysis

Identifiers

PMID27631970
PMCPMC5025142

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.