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Paul J Cancer Metastasis Treat 2020;6:29 I http://dx.doi.org/10.20517/2394-4722.2020.63 Page 23 of 31

NOVEL THERAPEUTIC APPROACHES USING THE CANCER SYSTEM MODEL
Mark Vincent classified cancer treatments in two fundamentally different approaches: a “causality-
inhibition” strategy, targeted towards the cancer cause, which at present is still a “moon shot”, remote from
our current cancer treatment practices, and, an ”acausal” approach that target a specific cancer marker
or signature [234] . At present, many aspects of cancer, in general, and, by large, the metastatic process
are still incompletely charted territories, and, therefore, most our current cancer treatments are not
directed towards the specific cause that triggeres the cancer process. In the near future, hopefully, once
the mechanisms of the different cancer cellular programs are better described, we will be able to design
effective causality-inhibition therapies.

For example, the immunomodulatory function of exosomes may be exploited for therapeutic effect. In 2008,
a Chinese group from Guangxi University [235] reported the results of a Phase I study in which 40 patients
with advanced colorectal cancer received four weekly intravenous injections of ascites derived exosomes
plus or minus GM-CSF. Stable disease and a minor response were observed in two of the patients treated.
More recently, another Chinese group [236] , suggested that miRNA depleted pancreatic cancer exosomes
might enhance the killing capacity of dendritic or cytokine-induced killer cells, and activate the immune
system against pancreatic cancer. The exosomes packaging is closely regulated, and, different clones even
from the same tumor may secret exosomes carrying a different cargo with different properties [237] .

DISMANTELLING CANCER NETWORKS AT THE ORGANISM LEVEL
Networks, composed of various nodes and edges may be described at different levels in an organism. In a
cell, nodes may be amino acids of cancer-related proteins, where edges are their distances in the 3D protein
structure or nodes may represent protein/RNA molecules or DNA-segments, where edges are their physical
or signaling contacts. In metabolic networks, nodes are metabolites and edges are the enzymes, which
catalyze the reactions to convert them to each other. At the tissular levels, nodes can be the cancer cells and
the stromal cells and the edges the different molecules through which they communicate. At the level of
the whole organism, nodes may represent the different components of the cancer system and the different
components of the normal body systems [Figure 2] and, the edges, cellular, exosomal or proteic signals
exchanged between them. Cancer is a robust system that is able to maintain stable functioning despite
various perturbations. The essential robustness of cancer is maintained through heterogeneous redundancy,
i.e., the cancer tissue contains a heterogeneous distribution of genetically different cancer cells maintained
by genetic instability [238] . Communication is crucial for the development of the cancer system. In order to
be able to dismantle such a complex multi-layered network as cancer, novel targeted multi-scale approaches
[239]
are needed that target simultaneously key elements of the cellular, tissular and systemic cancer networks .
Targeting the master genetic regulators or the hubs at the cellular level led to promising results [28,240] . Also, a
therapeutic approach based on game theory targeting the collaboration between cancer cells at the tissular
level was recently proposed by Archetti and Pienta [241] . It is conceivable that using similar mathematical
tools, treatments targeting specific CISPN elements at the organismic level can be designed. Evaluating
the cancer system vulnerabilities through analysis of network topology and, especially, network dynamics
can predict novel anti-cancer drug targets [242] . In general, therapeutic approaches targeting levels above the
cellular level may be less affected by cancer genetic instability and heterogeneity than treatments targeting
the cancer cells themselves. A suggestive example is the improvement in the long term survival associated
with check-point inhibitors that target cancer tissue as opposed to cancer cells [243-245] as opposed to the
almost universal development of acquired resistence associated to the use of tyrosine kinase inhibitors that
target specific intra-cellular cancer networks [246] . An attractive top-down regulator of cancer is the nervous
system and novel therapies could be designed stimulating or inhibiting some of its components [198] . As a
proof of principle, amplyfing a single gene in the hypothalamus of obese mice through gene transfer of
BDNF inhibited breast cancer progression and metastasis [247] .