↓ Skip to main content

A metabolomic approach to identifying platinum resistance in ovarian cancer

Overview of attention for article published in Journal of Ovarian Research, March 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#39 of 707)
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
1 news outlet
twitter
2 X users
peer_reviews
1 peer review site

Citations

dimensions_citation
62 Dimensions

Readers on

mendeley
77 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A metabolomic approach to identifying platinum resistance in ovarian cancer
Published in
Journal of Ovarian Research, March 2015
DOI 10.1186/s13048-015-0140-8
Pubmed ID
Authors

Laila M Poisson, Adnan Munkarah, Hala Madi, Indrani Datta, Sharon Hensley-Alford, Calvin Tebbe, Thomas Buekers, Shailendra Giri, Ramandeep Rattan

Abstract

Acquisition of metabolic alterations has been shown to be essential for the unremitting growth of cancer, yet the relation of such alterations to chemosensitivity has not been investigated. In the present study our aim was to identify the metabolic alterations that are specifically associated with platinum resistance in ovarian cancer. A global metabolic analysis of the A2780 platinum-sensitive and its platinum-resistant derivative C200 ovarian cancer cell line was performed utilizing ultra-high performance liquid chromatography/mass spectroscopy and gas chromatography/mass spectroscopy. Per-metabolite comparisons were made between cell lines and an interpretive analysis was carried out using the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic library and the Ingenuity exogenous molecule library. We observed 288 identified metabolites, of which 179 were found to be significantly different (t-test p < 0.05) between A2780 and C200 cells. Of these, 70 had increased and 109 had decreased levels in platinum resistant C200 cells. The top altered KEGG pathways based on number or impact of alterations involved the cysteine and methionine metabolism. An Ingenuity Pathway Analysis also revealed that the methionine degradation super-pathway and cysteine biosynthesis are the top two canonical pathways affected. The highest scoring network of altered metabolites was related to carbohydrate metabolism, energy production, and small molecule biochemistry. Compilation of KEGG analysis and the common network molecules revealed methionine and associated pathways of glutathione synthesis and polyamine biosynthesis to be most significantly altered. Our findings disclose that the chemoresistant C200 ovarian cancer cells have distinct metabolic alterations that may contribute to its platinum resistance. This distinct metabolic profile of platinum resistance is a first step towards biomarker development for the detection of chemoresistant disease and metabolism-based drug targets specific for chemoresistant tumors.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 1%
Unknown 76 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 21%
Student > Master 14 18%
Researcher 11 14%
Student > Bachelor 9 12%
Student > Doctoral Student 4 5%
Other 7 9%
Unknown 16 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 22%
Medicine and Dentistry 15 19%
Agricultural and Biological Sciences 12 16%
Pharmacology, Toxicology and Pharmaceutical Science 3 4%
Chemistry 3 4%
Other 7 9%
Unknown 20 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 December 2023.
All research outputs
#2,741,155
of 24,953,268 outputs
Outputs from Journal of Ovarian Research
#39
of 707 outputs
Outputs of similar age
#34,378
of 268,871 outputs
Outputs of similar age from Journal of Ovarian Research
#2
of 10 outputs
Altmetric has tracked 24,953,268 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 707 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 268,871 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.