cells
Review
Mapping the Metabolic Networks of Tumor Cells and
Cancer-Associated Fibroblasts
Jessica Karta
1
, Ysaline Bossicard
1
, Konstantinos Kotzamanis
1
, Helmut Dolznig
2
and Elisabeth Letellier
1,
*
Citation: Karta, J.; Bossicard, Y.;
Kotzamanis, K.; Dolznig, H.; Letellier,
E. Mapping the Metabolic Networks of
Tumor Cells and Cancer-Associated
Fibroblasts. Cells 2021, 10, 304.
https://doi.org/10.3390/cells10020304
Academic Editor: Maria Letizia Taddei
Received: 16 December 2020
Accepted: 26 January 2021
Published: 2 February 2021
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1
Molecular Disease Mechanisms Group, Department of Life Sciences and Medicine, Faculty of Science,
Technology and Medicine, University of Luxembourg, 6 avenue du Swing, L-4367 Belval, Luxembourg;
jessica.karta@uni.lu (J.K.); ysaline.bossicard@uni.lu (Y.B.); Kostas.Kotzamanis@uni.lu (K.K.)
2
Tumor Stroma Interaction Group, Institute of Medical Genetics, Medical University of Vienna,
Währinger Strasse 10, 1090 Vienna, Austria; helmut.dolznig@meduniwien.ac.at
* Correspondence: elisabeth.letellier@uni.lu; Tel.: +352-466-644-6954
Abstract: Metabolism is considered to be the core of all cellular activity. Thus, extensive studies of
metabolic processes are ongoing in various fields of biology, including cancer research. Cancer cells
are known to adapt their metabolism to sustain high proliferation rates and survive in unfavorable
environments with low oxygen and nutrient concentrations. Hence, targeting cancer cell metabolism
is a promising therapeutic strategy in cancer research. However, cancers consist not only of genetically
altered tumor cells but are interwoven with endothelial cells, immune cells and fibroblasts, which
together with the extracellular matrix (ECM) constitute the tumor microenvironment (TME). Cancer-
associated fibroblasts (CAFs), which are linked to poor prognosis in different cancer types, are one
important component of the TME. CAFs play a significant role in reprogramming the metabolic
landscape of tumor cells, but how, and in what manner, this interaction takes place remains rather
unclear. This review aims to highlight the metabolic landscape of tumor cells and CAFs, including
their recently identified subtypes, in different tumor types. In addition, we discuss various in vitro
and in vivo metabolic techniques as well as different in silico computational tools that can be used to
identify and characterize CAF–tumor cell interactions. Finally, we provide our view on how mapping
the complex metabolic networks of stromal-tumor metabolism will help in finding novel metabolic
targets for cancer treatment.
Keywords: cancer; cancer-associated fibroblasts (CAFs); CAF-tumor cross-talk; tumor metabolism;
metabolomics’ measurement techniques; in silico modeling; personalized metabolic drugs
1. Introduction
1.1. CAFs as the Epitome of Tumor Metabolism
Max Borst first noted the importance of the tumor microenvironment (TME) on cancer
progression in 1902 [1]. Today, it is well acknowledged that the tumor mass includes not
only a highly heterogenous cancer cell population but also various types of resident and
infiltrating host cells. Cancer-associated fibroblasts (CAFs) are a major component of the
TME. CAFs are fibroblasts that display an activated phenotype: they tend to be larger than
their normal counterparts, are spindle-shaped and show the presence of stress fibers. This
phenotype is transiently observed in normal fibroblasts during wound healing. In contrast,
CAFs seem to be constantly activated and unable to revert to a quiescent phenotype [2].
This observation contributed to Harold Dvorak’s definition of cancer as “the wound that
does not heal” [3]. Additionally, the CAF genome was reported to be subject to epigenetic
reprogramming whereas most studies have not found mutations in CAFs [4].
CAFs communicate with cancer cells in various ways in supporting tumorigenesis.
These include signaling molecules, secretion of growth factors, interleukins and metabolite
exchanges [5]. CAFs secrete extracellular matrix components such as collagen and laminins,
and produce a plethora of cytokines and chemokines (e.g., interferon-γ, stromal cell-derived
Cells 2021, 10, 304. https://doi.org/10.3390/cells10020304 https://www.mdpi.com/journal/cells