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Metabolism in Cancer

Overview of attention for book
Attention for Chapter 9: Quantitative Analysis of Cancer Metabolism: From pSIRM to MFA.
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Chapter title
Quantitative Analysis of Cancer Metabolism: From pSIRM to MFA.
Chapter number 9
Book title
Metabolism in Cancer
Published in
Recent results in cancer research Fortschritte der Krebsforschung Progrès dans les recherches sur le cancer, August 2016
DOI 10.1007/978-3-319-42118-6_9
Pubmed ID
Book ISBNs
978-3-31-942116-2, 978-3-31-942118-6

Christin Zasada, Stefan Kempa, Zasada, Christin, Kempa, Stefan


Thorsten Cramer, Clemens A. Schmitt


Metabolic reprogramming is a required step during oncogenesis and essential for cellular proliferation. It is triggered by activation of oncogenes and loss of tumor suppressor genes. Beside the combinatorial events leading to cancer, common changes within the central metabolism are reported. Increase of glycolysis and subsequent lactic acid formation has been a focus of cancer metabolism research for almost a century. With the improvements of bioanalytical techniques within the last decades, a more detailed analysis of metabolism is possible and recent studies demonstrate a wide range of metabolic rearrangements in various cancer types. However, a systematic and mechanistic understanding is missing thus far. Therefore, analytical and computational tools have to be developed allowing for a dynamic and quantitative analysis of cancer metabolism. In this chapter, we outline the application of pulsed stable isotope resolved metabolomics (pSIRM) and describe the interface toward computational analysis of metabolism.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 31%
Student > Bachelor 2 15%
Other 2 15%
Student > Master 1 8%
Unknown 4 31%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 31%
Biochemistry, Genetics and Molecular Biology 2 15%
Mathematics 1 8%
Chemistry 1 8%
Unknown 5 38%