↓ Skip to main content

Metabolic profiling of triple-negative breast cancer cells reveals metabolic vulnerabilities

Overview of attention for article published in Cancer & Metabolism, August 2017
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#4 of 206)
  • High Attention Score compared to outputs of the same age (95th percentile)

Mentioned by

news
7 news outlets
blogs
1 blog
facebook
1 Facebook page

Citations

dimensions_citation
121 Dimensions

Readers on

mendeley
199 Mendeley
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
Metabolic profiling of triple-negative breast cancer cells reveals metabolic vulnerabilities
Published in
Cancer & Metabolism, August 2017
DOI 10.1186/s40170-017-0168-x
Pubmed ID
Authors

Nathan J. Lanning, Joshua P. Castle, Simar J. Singh, Andre N. Leon, Elizabeth A. Tovar, Amandeep Sanghera, Jeffrey P. MacKeigan, Fabian V. Filipp, Carrie R. Graveel

Abstract

Among breast cancers, the triple-negative breast cancer (TNBC) subtype has the worst prognosis with no approved targeted therapies and only standard chemotherapy as the backbone of systemic therapy. Unique metabolic changes in cancer progression provide innovative therapeutic opportunities. The receptor tyrosine kinases (RTKs) epidermal growth factor receptor (EGFR), and MET receptor are highly expressed in TNBC, making both promising therapeutic targets. RTK signaling profoundly alters cellular metabolism by increasing glucose consumption and subsequently diverting glucose carbon sources into metabolic pathways necessary to support the tumorigenesis. Therefore, detailed metabolic profiles of TNBC subtypes and their response to tyrosine kinase inhibitors may identify therapeutic sensitivities. We quantified the metabolic profiles of TNBC cell lines representing multiple TNBC subtypes using gas chromatography mass spectrometry. In addition, we subjected MDA-MB-231, MDA-MB-468, Hs578T, and HCC70 cell lines to metabolic flux analysis of basal and maximal glycolytic and mitochondrial oxidative rates. Metabolic pool size and flux measurements were performed in the presence and absence of the MET inhibitor, INC280/capmatinib, and the EGFR inhibitor, erlotinib. Further, the sensitivities of these cells to modulators of core metabolic pathways were determined. In addition, we annotated a rate-limiting metabolic enzymes library and performed a siRNA screen in combination with MET or EGFR inhibitors to validate synergistic effects. TNBC cell line models displayed significant metabolic heterogeneity with respect to basal and maximal metabolic rates and responses to RTK and metabolic pathway inhibitors. Comprehensive systems biology analysis of metabolic perturbations, combined siRNA and tyrosine kinase inhibitor screens identified a core set of TCA cycle and fatty acid pathways whose perturbation sensitizes TNBC cells to small molecule targeting of receptor tyrosine kinases. Similar to the genomic heterogeneity observed in TNBC, our results reveal metabolic heterogeneity among TNBC subtypes and demonstrate that understanding metabolic profiles and drug responses may prove valuable in targeting TNBC subtypes and identifying therapeutic susceptibilities in TNBC patients. Perturbation of metabolic pathways sensitizes TNBC to inhibition of receptor tyrosine kinases. Such metabolic vulnerabilities offer promise for effective therapeutic targeting for TNBC patients.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 199 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 199 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 23%
Researcher 27 14%
Student > Bachelor 25 13%
Student > Master 22 11%
Student > Doctoral Student 9 5%
Other 20 10%
Unknown 51 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 72 36%
Agricultural and Biological Sciences 21 11%
Pharmacology, Toxicology and Pharmaceutical Science 15 8%
Chemistry 9 5%
Medicine and Dentistry 8 4%
Other 12 6%
Unknown 62 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 65. 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 03 October 2018.
All research outputs
#563,205
of 23,001,641 outputs
Outputs from Cancer & Metabolism
#4
of 206 outputs
Outputs of similar age
#13,193
of 317,366 outputs
Outputs of similar age from Cancer & Metabolism
#1
of 3 outputs
Altmetric has tracked 23,001,641 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 206 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has done particularly well, scoring higher than 98% 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 317,366 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them