Nature or nurture? Environmental impact on metabolic dependencies of cancer
Cancer is not a single disease, but a collection of over 400 different neoplastic malignancies. Mostly classified via their genetic diversity (cancer cells have heavily mutated genomes) or by the host tissue (lung, pancreas, breast etc…) affected, the diversity makes it impossible to find a single cure for cancer.
Similar to how a single vaccine cannot prevent all sorts of different viral infections, but only the one it’s aimed for, scientists needed to first discover what defines the different cancers and what distinguishes them from each other. A hopeless task only a decade and a half ago.
Luckily, advances in sequencing technologies and computation have brought this goal into reach. Today, tens of thousands of cancer genomes have been sequenced in a collaborative effort all around the world in the hope of personalized medical treatment. The idea is simple, if we develop a treatment for each form of cancer, then we only need to take a patient sample, sequence it, and adjust treatment correspondingly. While this sounds laborious and complicated, it is feasible and in large part automatable, which usually drives prices down.
If a treatment for most cancer types can be found, that is. I have mentioned before that any shared trade within cancer cells has enormous consequences for therapy, in the context of a study that found many different cancer types abusing the same stress response proteins to cope with genetic mutations.
However, diversity in cancer cells is not only caused by their genetic mutations and tissue origin, but also by their 3D environment, as recently shown by a study spearheaded by Massachusetts Institute of Technology in Cambridge, US.
In an effort to investigate discrepancies between cancer cell-culture systems and patient tumor data (cancer biologists have a poor record of transferring knowledge gains from the lab to patients & therapy), Davidson et al. set out to take a look at two of the oldest and best understood metabolic pathways important for cancer, glycolysis and the TCA cycle.
Usually, glycolysis converts sugar to pyruvate, a metabolite that supports energy generation via a set of chemical reactions (TCA cycle) in the mitochondria. This process is called oxidative phosphorylation, because it requires oxygen for energy (ATP) production. However, cancer cells are known to reprogram glycolysis to convert pyruvate to lactate instead of passing it on to the mitochondria, a biological phenomenon called the “Warburg effect”. A cell is a complex and dynamic system, everything is connected and controlled by each other, so changes to pyruvate utilization has profound effect on the cell. For example, the Warburg effect causes a increased reliance on glucose for energy production, thus glucose uptake is increased. Furthermore, glucose uptake and turnover rates are coupled to cell proliferation (since it makes sense for a cell to proliferate if there is plenty of nutrients around). Additionally, proliferation requires biosynthesis of large biomolecules, many of them are dependent on glycolysis too. The list goes on and on…
And here is the problem: We know all those metabolic dependencies from studies in cell culture systems, in fact we got so precise with our models that they accurately show how even small differences can have huge effects and cause a complete change in metabolism. So how do we know we are not a dog chasing its own tail, investigating changes we introduced by our own investigation or model system?
In their study, Davidson and colleagues could show that a long-held notion about TCA cycle shutoff is not necessarily a given in cancer cells, in fact, some cells seem to even rely heavily on this particular pathway. The reason why the Warburg effect in cell culture systems was so decidedly characterized by pyruvate to lactate conversion was in part caused by the environment of the cell culture, namely glutamine in the nutritional culture medium.
Cancer cells (in cell culture models) did not need to feed pyruvate into the TCA cycle, because they were running on abundantly available glutamine.
However, glutamine in the body is not as available, so depending on the environment of the cancer cells in question, some would rely on glucose → pyruvate → TCA cycle for survival. This has also been playing a big part in cancer resistance to treatment or relapse after treatment, as metabolic flexibility has been previously underappreciated.
This study highlights the importance of model selection to identify metabolic cancer targets. Cell-culture conditions are nonphysiological with respect to nutrients, oxygen, and tolerance for excretion of toxic metabolites such as ammonia. Cell culture also selects for the most rapidly proliferating cells, and many tumor cells cannot be cultured in vitro. The fact that transplanted tumors exhibit a phenotype more similar to tumors arising in the lung that are never exposed to cell culture suggests that environment has a greater impact on how nutrients are utilized than genetic or epigenetic selection associated with cell-line formation. — Davidson SM et al., Cell, 2016
Looking at the broader picture, Davidson et al. findings shed more light on different ways how cancer cells reach their observed diversity, which is not only through genetic or tissue-specific means, but also caused by the environment.
Every gain in knowledge about cancer comes with a bit of frustration on how we will ever solve this complexity puzzle.
Yet, to leave on a more positive note, if we know how cancer is affected by its environment, we might just find more options to attack and vulnerabilities to uncover.
Source: Davidson SM et al., Cell, 2016
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