The origin of symmetry in the metabolism of cancer – From systems biology to translational medicine
Doctoral thesis, 2015

Why do not we have a cure for cancer yet? Cancer is the malady of the century, the most intensely studied disease of all time. The question is puzzling. It assumes that cancer is a single entity that we can target and eradicate. On the contrary, the current theory on the origin of cancer dictates that each patient bears a cancer that is an exquisite experiment of nature, in which a unique constellation of genetic aberrations confers the cell with malignant traits that enable it to proliferate and survive until death of the host. Nevertheless, the question is legitimate. Cancer is also a single entity because, in spite of the heterogeneity of origins, every individual cancer in its evolution ought to converge in the acquisition of the same malignant traits, e.g. abnormal proliferation and ability to metastasize. I define this phenomenon of convergent evolution as the symmetry of cancer and each of these traits as symmetric, reminiscent of the fact that as diverse as two individual cancers can be in its origin, they can be repositioned along the trait to be identical. This thesis is dedicated to understanding the origin of symmetry of cancer through systems biology. In particular, I focused my interest in a specific malignant trait, the reprogramming of cell metabolism. Metabolic reprogramming in cancer is associated with deregulation of anabolism and energy metabolism to foster rapid cell proliferation and plastic adaptation to enable cell survival. Human metabolism is a complex system, which consists of thousands of biochemical reactions that transform nutrients into energy, building blocks for cell growth (like membrane phospholipids), macromolecules with specialized functions (like hormones), and in general support life by maintaining whole body homeostasis. I sought to explore whether the transformation to cancer entailed some symmetric patterns of regulation of metabolism. In order to undertake an unbiased view of this complex system, I adopted a systems level perspective, in which genome-scale changes of gene and protein expression (so-called omics) attributable to cancer were bridged with the network of reactions that form the backbone of human metabolism. The results were two-fold. First, any cancer seemed to acquire a symmetric overexpression of nucleotide metabolism, regardless from where it originated (Paper I). However, the comparison was performed against the matched healthy tissues of origin, mostly composed of quiescent cells. Therefore we ascribed this symmetry to an adaptation to a metabolic requirement of cellular proliferation. In order to discern what regulatory patterns in metabolism are not adaptive but oncogenic, meaning an obligate metabolic reprogramming to foster evolution, we characterized those gene expression changes occurring in presence of an oncogenic mutation, again irrespective of the tissue of origin or other confounding factor (Paper II). This analysis revealed that oncogenic mutations independently converge on the deregulation of a sub-network revolving around the metabolism of arachidonic acid and xenobiotics mediated by glutathione and oxygen, which we termed AraX. Deregulation of AraX can be associated with a successful engagement of the immune system in tumor evolution, suggesting that the symmetry of cancer metabolism may exclusively rely on reprogramming fluxes to support pro-tumorigenic inflammation. Second, the symmetry of cancer metabolism broke with the most common form of kidney cancer, clear cell renal cell carcinoma (ccRCC). We reported that a ccRCC-specific set of genetic aberrations is associated with the emergence of a uniquely compromised metabolic network (Paper I). These outstanding features of ccRCC metabolism provided an opportunity for translational medicine. We proved that it is possible to exploit ccRCC defective network to predict computationally metabolic liabilities that induce selective cell death in ccRCC (Paper III). Moreover, these changes in metabolic regulation unique to ccRCC can be distilled, through an algorithm of our creation, Kiwi (Paper V), in a coordinated regulation of glycosaminoglycan biosynthesis (GAGs) (Paper IV). This is mirrored by an altered profile of GAGs in kidney-proximal fluids, urine and blood, that we prove bearing a strong, accurate, and robust diagnostic value in metastatic ccRCC. The case of ccRCC and potential role of inflammation in AraX may raise more doubt than support on the existence of symmetry in the metabolic reprogramming in any cancer cell (Paper VI). Perhaps researchers are simply observing an enhanced plasticity in the adaptation to ever-changing conditions that is induced by mutations, but which is not symmetric under any specific trait and as such not essential to cancer. Yet, I argue that the quest for searching the symmetry in cancer should not be abandoned. This quest is in my opinion of paramount importance to unlock the discovery of a cure for cancer.


systems biology

biological networks

convergent evolution




KC (Kemihuset, Kemigården 4)
Opponent: Sara-Maria Fendt, VIB Vesalius Research Center, KU Leuven


Francesco Gatto

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Flux balance analysis predicts essential genes in clear cell renal cell carcinoma metabolism

Scientific Reports,; Vol. 5(2015)p. Art. no. 10738-

Journal article

Chromosome 3p loss of heterozygosity is associated with a unique metabolic network in clear cell renal carcinoma

Proceedings of the National Academy of Sciences of the United States of America,; Vol. 111(2014)p. E866-E875

Journal article


C3SE (Chalmers Centre for Computational Science and Engineering)

Areas of Advance

Life Science Engineering (2010-2018)

Subject Categories

Bioinformatics and Systems Biology



Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 3906

KC (Kemihuset, Kemigården 4)

Opponent: Sara-Maria Fendt, VIB Vesalius Research Center, KU Leuven

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