Cancer heterogeneity is not compatible with one unique cancer cell metabolic map

Abstract

The Warburg effect and its accompanying metabolic features (anaplerosis, cataplerosis) are presented in textbooks and reviews as a hallmark (general characteristic): the metabolic map of cancer. On the other hand, research articles on specific tumors since a few years emphasize various biological features of different cancers, different cells in a cancer and the dynamic heterogeneity of these cells. We have analysed the research literature of the subject and show the generality of a dynamic, evolving biological and metabolic, spatial and temporal heterogeneity of individual cancers. We conclude that there is no one metabolic map of cancer but several and describe the two extremes of a panel from the hypoxic to the normoxic state. The implications for the significance of general ‘omic' studies, and on therapeutic conclusions drawn from them and for the diagnostic use of fractional biopsies is discussed.

Glutamine Metabolism in Cancer: Understanding the Heterogeneity

“…It is now clear that there is a not a single ‘metabolic map’ or ‘metabolic switch’ describing cancer cell metabolism [74], and the fate of glutamine varies with a range of parameters, including the tissue of origin of a cancer, the genetic aberrations which drive it, the tumor microenvironment, and possibly diet and host metabolism. The collective effect of these variables is striking, such that the metabolic phenotypes of cancer cells range from those that are highly dependent on catabolism of exogenous glutamine, to those that accumulate glutamine via de novo synthesis and are self-sufficient for glutamine requirements.…”

Integrated omics and gene expression analysis identifies the loss of metabolite–metabolite correlations in small cell lung cancer

“…Metabolism is highly conserved to the specific taxa. 20 , 21 It was reported that cancer metabolome profiles are mainly associated with the malignancy. 22 Compared with NSLCC, SCLC is more malignant with shorter doubling time, higher growth fraction, and earlier development of metastases.…”

Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor

“…Increasing evidence suggests that individual cells in a population can be metabolically very different (Nikolic et al, 2013;van Heerden et al, 2014;Solopova et al, 2014;Kotte et al, 2015;Takhaveev & Heinemann, 2018). Metabolic heterogeneity has been found, for instance, not only in microbial cultures used for biotechnological processes (Xiao et al, 2016), but also in cells of human tumors (Strickaert et al, 2017). Because metabolic heterogeneity is connected with productivity and yield losses in biotechnological production processes (Xiao et al, 2016), and in cancer with limited therapeutic successes (Robertson-Tessi et al, 2015), it is key to identify metabolic subpopulations and to understand their emergence.…”