Signal transducer and activator of transcription (STAT)
proteins are powerful controllers of gene expression. Recent work has involved
them in Prostate Cancer along with the many other targets which have been
identified. We examine this specific gene and its recently identified significance.
The specific STAT is STAT3. Previously it has been linked to aggressive
cancers. In fact attempts have been made to therapeutically target this
pathway. The authors in a recent paper however contend that it is just the
opposite. Namely STAT3 actually prevent metastatic behavior.
This discussion is a critical one as we examine further the
targeting of genes and their behavior. The STAT3 issue seems to state that on
one hand over-expression is bad, yet then on the other hand over-expression is
good. This highlights the issue of cross talk between paths as well as the yet
to be fully understood dynamics of pathways. Add to this is the fact that STAT3
is driven by IL-6 and this links in the immune system as well.
We begin the discussion with information in a Press Release
in Science Daily which reports[1]:
A gene that is responsible for cancer growth plays a
totally unexpected role in prostate cancer. The gene Stat3 is controlled by the
immune modulator interleukin 6 and normally supports the growth of cancer
cells. The international research team led by Prof. Lukas Kenner from the
Medical University of Vienna, the Veterinary University of Vienna, and the Ludwig
Boltzmann Institute for Cancer Research (LBI-CR) discovered a missing link for
an essential role of Stat3 and IL-6 signalling in prostate cancer progression.
Interleukin 6
(IL-6) is an important cytokine that controls the cell survival and tumor growth.
Hyperactive IL-6 may support cancer growth, particularly as it controls STAT3,
which was shown to have an oncogenic role in most tumours. Many therapies are
therefore designed to suppress IL-6 or STAT3. But the situation is different in
prostate cancer. Lukas Kenner's research group has shown that, contrary to
expectations; active STAT3 suppresses cell growth in prostate tumours. It
activates the gene p14ARF, which blocks cell division and thus
inhibits tumour growth.
IL-6 is one of many interleukin cytokines, activating immune
cells and leading to their proliferation. In a classic model for STAT3, it is
activated by IL-6 and then it progresses via phosphorlyation to act as a
promoter or enhancer for a multiplicity of genes whose expression leads to cancerous
growth. However there is an alternative pathway, the ARF-MDM2-p53 pathway the
controls and may mitigate some of these processes. This paper focuses on this
crossover effect.
The article continues:
For this reason, STAT3 and p14ARF are ideally
suited to act as biomarkers for the prognosis of this disease. If these two
factors are missing in tissue samples, the risk is massively increased that the
tumour grows and forms metastases.
According to Lukas Kenner, this is important, as the
predictive power of these proteins as biomarkers is twice as good as the
previous gold standard. As only about 10 % of patients with prostate cancer die
from the disease, this can help to prevent unnecessary therapeutic
interventions with severe side effects such as incontinence and impotence. A
non-invasive nuclear medical test based on these findings might soon be able to
replace the painful removal of tissue samples to be examined.
The reversed role of interleukin 6 as an inhibitor of
prostate cancer has an additional significance. Blockade of interleukin 6 is
used to treat other diseases, such as rheumatoid arthritis. According to
Kenner, this means that therapies that block the IL-6 pathway may enhance the
growth of prostate cancer.
Thus, the drug that is used to treat inflammatory disease
may exacerbate malignancies. "Applying IL-6/Stat3 blockers to clinical
practice might be dangerous for patients with cancerous lesions, further
studies are mandatory to assess the possibility of increased cancer risk right
now," says coauthor of this study, Helmut Dolznig, also from the Medical
University of Vienna. The study was financed mainly by the LBI-CR and the FWF.
These results have just been published in the distinguished scientific journal
Nature Communications.
The following is a generalized paradigmatic summary of
Pencik et al. Namely; they observed that IL6 controls STAT3 which in turn
controls the ARF-MDM2-p53 pathway, which is critical in the overall control of
PCa metastasis.
Now it should also be noted that the above is not the
complete presentation. For example in this pathway p53 actually drives MDM2.
There are other linkages that should be considered as well. We shall discuss
some of these later.
Now from the paper in question, namely Pencik et al, they
conclude:
We have uncovered a paradigm shift in understanding the
key function of STAT3 in tumorigenicity and metastatic progression in PCa.
Therefore, our results call for cautious use of anti-IL-6- STAT3 signalling
blockers in the treatment of PCa as this may turn low-grade tumours into highly
malignant cancers by loss of senescence controlled by the STAT3–ARF axis. As
IL-6/STAT3 signalling blockers are successful in the treatment of chronic
inflammatory or autoimmune diseases, their influence on PCa development needs to
be carefully evaluated in future studies.
Reactivating the IL-6/STAT3/ARF-dependent senescence
pathway57 might be a promising strategy for PCa therapy via downregulation of
Mdm2 (ref. 58) or p53 induction59. Alternatively, triggering
ARF–p53-independent cellular senescence by a small molecule inhibitor could be
beneficial for PCa patients in whom other therapies have failed.
Namely, they argue that the STAT3 control of the
ARF-MDM2-p53 pathway should not be interfered with. That pathway actually
enables control over metastatic behavior. We will discuss each element in some
detail in what follows.
The classic understanding of STAT3 is that is acts to
promote cancers. The figure below is a modification from Yu et al:
Immune cells in the tumour microenvironment not only fail
to mount an effective anti-tumour immune response, but also interact intimately
with the transformed cells to promote oncogenesis actively. Signal transducer
and activator of transcription 3 (STAT3), which is a point of convergence for
numerous oncogenic signalling pathways, is constitutively activated both in
tumour cells and in immune cells in the tumour microenvironment.
Constitutively activated STAT3 inhibits the expression of
mediators necessary for immune activation against tumour cells. Furthermore,
STAT3 activity promotes the production of immunosuppressive factors that
activate STAT3 in diverse immune-cell subsets, altering gene-expression programmes
and, thereby, restraining anti-tumour immune responses. As such, STAT3
propagates several levels of crosstalk between tumour cells and their
immunological microenvironment, leading to tumour-induced immunosuppression. Consequently,
STAT3 has emerged as a promising target for cancer immunotherapy.
Thus the classic view is that STAT3 is an essential element
in the pathology of tumorogenesis which as we indicated earlier is in contrast
to the recent results. Thus do we block it or allow it? That is the question.
Yu et al conclude:
The ability of STAT3 to broadly and profoundly affect
tumour immunity strongly indicates that constitutively activated STAT3 both in
tumour cells and in tumour stromal immune cells is an attractive target for
cancer immunotherapy. Another unique and appealing aspect of targeting STAT3
for cancer immunotherapy is due to the crucial role of STAT3 in tumour-cell
survival and tumour angiogenesis. Many experiments have shown that tumour
rejection mediated by CD8+ T cells is always preceded by the inhibition of
tumour-induced angiogenesis.
Because targeting STAT3 is expected to decrease the
survival and angiogenic potential both of tumour cells and of the tumour
stroma, targeting STAT3 could facilitate immune-cell-mediated anti-tumour
effects at several levels. Although STAT3 is the first oncogenic target for
cancer immunotherapy, other important onco proteins, such as MAPKs, might have
similar roles. With the emergence of targeted delivery systems, and small molecule
inhibitors or RNAi technology to block STAT3 and other relevant oncogenic
pathways, a new era of molecular targeting for cancer immunotherapy is on the
horizon.
Yu et al are focusing on hematopoietic cells not prostate
cells. There is no reason why one should expect the same effect in different
cells. Yet from a therapeutic perspective if such a drastically different model
is functioning, the results would be problematic at best.
As Niu et al have stated:
Loss of p53 function by mutation is common in cancer.
However, most natural p53 mutations occur at a late stage in tumor development,
and many clinically detectable cancers have reduced p53 expression but no p53
mutations.
It remains to be fully determined what mechanisms disable
p53 during malignant initiation and in cancers without mutations that directly
affect p53.
We show here that oncogenic signaling pathways inhibit
the p53 gene transcription rate through a mechanism involving Stat3, which
binds to the p53 promoter in vitro and in vivo.
Site-specific mutation of a Stat3 DNA-binding site in the
p53 promoter partially abrogates Stat3- induced inhibition. Stat3 activity also
influences p53 response genes and affects UV-induced cell growth arrest in
normal cells. Furthermore, blocking Stat3 in cancer cells up-regulates
expression of p53, leading to p53-mediated tumor cell apoptosis. As a point of
convergence for many oncogenic signaling pathways, Stat3 is constitutively
activated at high frequency in a wide diversity of cancers and is a promising
molecular target for cancer therapy.
Thus, repression of p53 expression by Stat3 is likely to
have an important role in development of tumors, and targeting Stat3 represents
a novel therapeutic approach for p53 reactivation in many cancers lacking p53
mutations.
Thus, Niu et al also present a model for Stat3 inhibiting
p53, again in contrast to the paper in question. Niu et al conclude:
1. Stat3 protein interacts with the p53 promoter.
2. Stat3 inhibits p53 expression at the transcription level.
3. Stat3 binds to the p53 promoter in vitro as determined by EMSA.
4. Interaction between Stat3 protein and the p53 promoter
contributes to Stat3-mediated inhibition.
5. Stat3 activity inhibits the p53-responsive element and UV-induced
p53-mediated growth arrest.
6. Blocking Stat3 activates p53 expression in human cancer cells.
7. Blocking Stat3 induces p53-mediated tumor cell apoptosis and
facilitates UV-induced tumor cell growth inhibition.
The results of these two studies seem fairly conclusive
regarding Stat3. Namely it is oncogenic. But despite the study in question here
seems to reverse that position. We will examine that in some detail.
Let us now review what is understood about the ARF-MDM2-p53
pathway. This will be necessary before linking this pathway to STAT3 and its
functions.
Now this is a classic pathway whose ultimate control
mechanism is p53 expression. p53 is generally understood to be a control gene,
keeping the cell in some homeostasis and preventing malignancy. As we will not
later this may not always be the case but that will not apply to the current
discussion.
The following Figure depicts the process of the three gene
control mechanism. Simply:
1. p53 activates the production of MDM2
2. MDM2 can bind to p53 and result in its dissolution via an
Ubiquination
3. ARF can bind to MDM2 and allow the p53 to survive.
4. The process, albeit a bit complex, reaches a steady state
for all three proteins.
From Sherr and Weber (as modified) we have the following
details as well shown graphically:
Note in the above we have the cyclic MDM2 and p53 control as
well as the cell instigators. Now Van Maerken, T., et al notes the following regarding the
details of this feedback loop:
The p53-MDM2 autoregulatory feedback loop.
(a) The p53 protein induces expression of MDM2, which
negatively regulates the stability and activity of p53, providing a means to
keep p53 levels and activity low in unstressed cells and to switch off p53 at
the end of a stress response.
(b) The p53-mediated expression of MDM2 results from
binding of p53 to response elements in the MDM2 gene and subsequent
transactivation of MDM2. The domain structure of p53 is shown schematically:
i.
TAD, transactivation
domain, amino acids;
ii.
PRD, proline-rich
domain, amino acids; DBD, DNA-binding domain, amino acids;
iii.
TD, tetramerization
domain, amino acids;
iv.
CTD, C-terminal
regulatory domain, amino acids.
(c) The p53-inhibitory activity of MDM2 relies on
multiple mechanisms. Binding of MDM2 to p53 conceals the TAD and consequently
blocks the transcriptional activity of p53. MDM2 also recruits several
corepressor proteins to p53, including HDAC1, CTBP2, YY1, and KAP1.
The E3 ubiquitin ligase activity of MDM2 results in
ubiquitination of lysine residues in the CTD of p53, preventing acetylation of
p53, favoring nuclear export, and promoting proteasomal degradation (see text
for details). Some of these lysine residues can also be neddylated by MDM2,
resulting in inhibition of the transcriptional activity of p53. Finally, MDM2
may also serve as a p53-specific transcriptional silencer by binding and
monoubiquitinating histone proteins in the proximity of p53-responsive
promoters. Nd, NEDD8; Ub, ubiquitin. …
They continue the discussion as follows:
The p14ARF protein is predominantly localized
to the nucleolus, in which it is stabilized by binding to nucleophosmin within
maturing pre-ribosomal particles, pointing to a function in the regulation of
ribosome biogenesis.
Nucleophosmin promotes the processing of ribosomal RNA
precursors and the nuclear export of ribosomal subunits, whereas overexpression
of p14ARF or its murine homolog p19ARF interferes with
transcription and processing of ribosomal RNA, impedes nucleocytoplasmic
shuttling of nucleophosmin, and inhibits ribosome nuclear export. However, the
precise biological function of the nucleophosmin– p14ARF complexes
remains a subject of debate. Stress signals trigger the disruption of the
interaction between p14ARF and nucleophosmin, and induce
translocation of p14ARF to the nucleoplasm.
This redistribution enables p14ARF to interact
with p53-bound MDM2 and to antagonize MDM2 function by inhibiting its E3
ubiquitin ligase activity and by blocking nucleocytoplasmic shuttling of MDM2
and p53, resulting in p53 stabilization. The p53-inhibitory activity of MDM2
may also be neutralized by p14ARF -mediated mobilization of MDM2
into the nucleolus, although this mechanism is not strictly required for the
p53-dependent functions of p14ARF.
This is clearly a highly complex mechanism. They continue:
Furthermore, the p14ARF
protein is capable of inhibiting the activity of another E3 ubiquitin ligase
that targets p53 for degradation, ARF-BP1/Mule, and of counteracting the
p53-antagonizing NF-kappaB pathway. It should be noted that p14ARF also exerts
a potent tumor suppressor activity independently of p53.
Various researchers have tried to model these systems using
different techniques. One technique is the use of Petri Nets[2]. From
CSML we have a Petri Net models describing the details of such a network and
they state[3]:
Proteins p53, MDM2, and p19ARF are proteins
closely related to cancer. The protein p53 is a protein which suppresses the
formation of tumors, and the protein MDM2 promotes the formation of tumors by
decreasing the activity of the protein p53.
Understanding of control mechanism of these proteins
connects to development of an effective medicine for suppressing the tumor. It
is known that protein p53 works as a transcription factor for many genes and
its transcriptional activity is controlled by a complex formed with proteins
MDM2 and p19ARF.
However, it is
still unclear whether protein p53 keeps its transcriptional activity in the
form of the trimer with proteins p53, MDM2 and p19ARF. … a hybrid
functional Petri net (HFPN) model which has been constructed by compiling and
interpreting the information of p53-MDM2 interactions... With our HFPN model,
we have simulated mutual behaviors between genes p53, MDM2, p19ARF,
and their products. Through simulation, we discussed whether the complex
p53-MDM2-p19ARF has transcriptional activity for genes Bax and MDM2
or not.
It is worth examining these structures, namely the Petri
Nets. We leave the examination to the reference. From Moll and Petrenko we have
the following result:
Activation of the p53 protein protects the organism
against the propagation of cells that carry damaged DNA with potentially
oncogenic mutations. MDM2, a p53- specific E3 ubiquitin ligase, is the
principal cellular antagonist of p53, acting to limit the p53 growthsuppressive
function in unstressed cells. In unstressed cells, MDM2 constantly
monoubiquitinates p53 and thus is the critical step in mediating its
degradation by nuclear and cytoplasmic proteasomes.
The interaction between p53 and MDM2 is
conformation-based and is tightly regulated on multiple levels. Disruption of
the p53-MDM2 complex by multiple routes is the pivotal event for p53
activation, leading to p53 induction and its biological response. Because the
p53-MDM2 interaction is structurally and biologically well understood, the
design of small lipophilic molecules that disrupt or prevent it has become an
important target for cancer therapy.
Let us go back and re-examine the functions of STAT3 and
this time in the context of the paper in study. As NCBI states[4]:
The protein encoded by this gene is a member of the STAT
protein family. In response to cytokines and growth factors, STAT family
members are phosphorylated by the receptor associated kinases, and then form
homo- or heterodimers that translocate to the cell nucleus where they act as
transcription activators.
This protein is activated through phosphorylation in
response to various cytokines and growth factors including IFNs, EGF, IL5, IL6,
HGF, LIF and BMP2. This protein mediates the expression of a variety of genes
in response to cell stimuli, and thus plays a key role in many cellular
processes such as cell growth and apoptosis. The small GTPase Rac1 has been
shown to bind and regulate the activity of this protein. PIAS3 protein is a
specific inhibitor of this protein.
As Niu et al have noted:
Loss of p53 function by mutation is common in cancer.
However, most natural p53 mutations occur at a late stage
in tumor development, and many clinically detectable cancers have reduced p53
expression but no p53 mutations. It remains to be fully determined what
mechanisms disable p53 during malignant initiation and in cancers without
mutations that directly affect p53. We show here that oncogenic signaling
pathways inhibit the p53 gene transcription rate through a mechanism involving
Stat3, which binds to the p53 promoter in vitro and in vivo.
Site-specific mutation of a Stat3 DNA-binding site in the
p53 promoter partially abrogates Stat3- induced inhibition. Stat3 activity also
influences p53 response genes and affects UV-induced cell growth arrest in
normal cells. Furthermore, blocking Stat3 in cancer cells up-regulates
expression of p53, leading to p53-mediated tumor cell apoptosis. As a point of
convergence for many oncogenic signaling pathways, Stat3 is constitutively
activated at high frequency in a wide diversity of cancers and is a promising
molecular target for cancer therapy.
Thus, repression of p53 expression by Stat3 is likely to
have an important role in development of tumors, and targeting Stat3 represents
a novel therapeutic approach for p53 reactivation in many cancers lacking p53
mutations.
Namely in many cancers the excess expression of STAT3 leads
to an inactivation of p53 and thus an oncogenic state. The figure below is a
depiction of this process.
However, Pencik, J., have recently noted the following as regards
to PCa.
Prostate cancer (PCa) is the most prevalent cancer in
men. Hyperactive STAT3 is thought to be oncogenic in PCa. However, targeting of
the IL-6/STAT3 axis in PCa patients has failed to provide therapeutic benefit.
Here we show that genetic inactivation of Stat3 or IL-6 signalling in a
Pten-deficient PCa mouse model accelerates cancer progression leading to
metastasis. Mechanistically, we identify p19ARF as a direct Stat3 target.
Loss of Stat3 signalling disrupts the ARF–Mdm2–p53 tumour
suppressor axis bypassing senescence. Strikingly, we also identify STAT3 and
CDKN2A mutations in primary human PCa. STAT3 and CDKN2A deletions co-occurred
with high frequency in PCa metastases. In accordance, loss of STAT3 and p14ARF expression
in patient tumours correlates with increased risk of disease recurrence and metastatic
PCa. Thus, STAT3 and ARF may be prognostic markers to stratify high from low risk
PCa patients. Our findings challenge the current discussion on therapeutic
benefit or risk of IL-6/STAT3 inhibition.
But Pencik et al further note:
PTEN is one of the most frequently deleted or mutated
tumour suppressors in PCa, with an estimated incidence of 70% in metastatic
PCa, causing aberrant activation of the PI3K– AKT–mTOR signalling pathway
We have examined this extensively in our analyses of PCa.
Loss of Pten leads to senescence, which is critically
regulated by the ARF–p53 pathway.
PTEN is a major controller of PI3K and its pathway. Loss of
PTEN is common in most PCa. On the other hand we have the ARF-MDM2-p53 dynamic
which we shall discuss later.
While the tumour
suppressor ARF (p14ARF in humans; p19ARF in mice) is
readily degraded in normal cells, it is stabilized to increase p53 function on
loss of Pten. ARF was shown to augment p53 stability by promoting the
degradation of Mdm2, a negative regulator of p53.
Concomitant inactivation of Pten and p53 leads to bypass
of senescence and as a consequence to a malignant PCa phenotype.
Loss of PTEN and of p53 is potentially a universally
catastrophic event. It is a loss of two of the most significant stabilization
elements in any cell, especially the prostate.
Previous studies report PTEN–STAT3 signalling crosstalk
in malignant glioblastoma, but the detailed molecular mechanisms in cancer
progression and metastasis remain unresolved.
In this study, we show that loss of IL-6/Stat3 signalling
in a Pten-deficient PCa model accelerates cancer progression leading to
metastasis. Loss of IL-6/Stat3 signalling in PCa bypasses senescence via
disrupting the ARF–Mdm2–p53 tumour suppressor axis.
We identify ARF as a novel direct Stat3 target. Notably,
loss of STAT3 and p14ARF expression correlates with increased risk of
recurrence in PCa patients. In addition, STAT3 and p14ARF expression was lost
in metastasis compared with the primary tumours.
This is the nexus between the STAT3 pathway and the
ARF-MDM2-p53 pathways. Namely the authors seem to argue that STAT3 targets ARF
and it is through this “targeting” that the latter pathway becomes defective.
We identified STAT3 and CDKN2A mutations in primary PCa
patients. Furthermore, PCa metastases show a high frequency of STAT3 and CDKN2A
deletions.
We propose STAT3 and ARF as prognostic markers for high
versus low risk PCa patient stratification.
Pencik et al also note the following inference:
Stat3 regulates the ARF–Mdm2–p53pathway. Since loss of
Pten triggers senescence thereby restricting cancer progression and
metastasis11, we next tested whether Stat3 exerts a tumour suppressive function
by activating senescence-inducing programmes in Ptenpc-/-PCa cells at an early
stage of PCa development.
Senescence is generally characterized by upregulation of
p53, cyclin-dependent kinase inhibitor 1 (Cdkn1, p21), promyelocytic leukaemia
protein (PML) and elevated senescence-associated-b-galactosidase activity. Of
note, Ptenpc-/-Stat3-/- tumours lacked p21 expression, displayed reduced
numbers of PML nuclear bodies and decreased SA-b-Gal activity compared with
Ptenpc-/- tumours, suggesting Stat3 as a novel mediator of senescence in
response to loss of Pten.
Again the statement is “suggesting” and there is no
definitive well defined mechanism.
Senescence associated with loss of Pten was shown to be
bypassed by deletion of p53 leading to early lethality11. We show here that
loss of Stat3 and Pten revealed a phenotype strikingly similar to that of p53
and Pten loss11. Intriguingly, Stat3 and Pten deletion resulted in
downregulation of p53 expression in the prostate epithelium, which was
accompanied by the loss of p19ARF
The authors make the following statement:
The p53 expression in the tumour stromal cells
remained unchanged. Since p19ARF is a critical regulator of Mdm2
degradation, our results suggest that the tumour suppressive capacity of Stat3
in senescent tumour cells may rely on the p19ARF–Mdm2–p53 tumour suppressor
axis.
The conclusion is still a bit tentative. Just what the
mechanism is may not be well understood.
Now Yu et al state:
The Janus kinases (JAKs) and signal transducer and
activator of transcription (STAT) proteins, particularly STAT3, are among the
most promising new targets for cancer therapy. In addition to interleukin-6
(IL-6) and its family members, multiple pathways, including G-protein-coupled
receptors (GPCRs), Toll-like receptors (TLRs) and microRNAs were recently
identified to regulate JAK–STAT signalling in cancer.
Well known for its role in tumour cell proliferation,
survival, invasion and immunosuppression, JAK–STAT3 signalling also promotes
cancer through inflammation, obesity, stem cells and the pre-metastatic niche.
In addition to its established role as a transcription factor in cancer, STAT3
regulates mitochondrion functions, as well as gene expression through
epigenetic mechanisms. Newly identified regulators and functions of JAK–STAT3
in tumours are important targets for potential therapeutic strategies in the
treatment of cancer.
Huang, et al state that STAT3 is a preferred target for
cancer therapy. Specifically:
Numerous cytokines, growth factors, and oncogenic
proteins activate signal transducer and activator of transcription 3 (Stat3),
which has been recognized as one of the common pathways in cancer cells. Stat3
signaling affects the expression and function of a variety of genes that are
critical to cell survival, cell proliferation, invasion, angiogenesis, and
immune evasion. Evidently, the Stat3 signaling pathway regulates cancer
metastasis and constitutes a potential preventive and therapeutic target for
cancer metastasis. .
Furthermore Huang et al outline the reasons for this:
Contribution of Stat3 signaling pathway to cancer
metastasis.
Stat3 in the cytoplasm of unstimulated cells becomes
activated by recruitment to phosphotyrosine motifs within complexes of growth
factor receptors (e.g., epidermal growth factor receptor), cytokine receptors
(e.g., IL-6 receptor), or non-receptor tyrosine kinases (e.g., Src and BCR-ABL)
through their SH2 domain. Stat3 is then phosphorylated on a tyrosine residue by
activated tyrosine kinases in receptor complexes.
Phosphorylated Stat3 forms homodimers and heterodimers
and translocates to the nucleus. In the nucleus, Stat3 dimers bind to specific
promoter elements of target genes and regulate gene expression. The Stat3
signaling pathway regulates cancer metastasis by regulating the expression of
genes that are critical to cell survival, cell proliferation, invasion,
angiogenesis, and tumor immune evasion.
It would be useful if somehow these conflicting views could be
brought into alignment. In addition we have the work Marcias, E., et al, who state:
Pathways associated with Stat3 activation. Stat3 is
activated downstream of receptor tyrosine kinases (e.g., EGFR), cytokine
receptors via associated Janus family kinases (JAKs) (e.g., IL-6 receptor), and
nonreceptor-associated tyrosine kinases (e.g., c-src). Tumor promoters such as
TPA and UVB activate Stat3 in keratinocytes primarily via the EGFR.
Activation of PKCs by tumor promoters leads to the
processing of membrane-bound preforms of EGFR ligands such as heparin-binding
EGF (HB-EGF) by matrix metalloproteinases (MMPs). In addition, PKCs associate
with and phosphorylate Stat3 at Ser727, which is necessary for maximal Stat3
transcriptional activity. Furthermore, transcriptional induction of cytokines
and EGF ligands can lead to autocrine stimulation and sustained Stat3
phosphorylation.
After phosphorylation, STAT3 dimerizes and translocates
to the nucleus, where Stat3 dimers directly regulate gene expression of
transcriptional targets including Bcl-xL, cyclin D1, c-myc, Twist and Survivin.
STAT3-mediated regulation of target gene expression is involved in various
cellular functions including cell differentiation, proliferation, survival, and
oncogenesis. Stat3 can also act through noncanonical signaling pathways. In
this regard, unphosphorylated Stat3 (U-Stat3) can drive gene expression of a
subset of genes that are different from p-Stat3 dimers in an NF-κB-dependent
and independent manner.
In addition, p-Stat3 Ser727 can translocate into the
mitochondria and influence mitochondrial respiratory chain activity. These
noncanonical Stat3 signaling pathways have protumorigenic roles in certain
cell/tissue types; however their role in epithelial carcinogenesis has not been
evaluated.
Thus the nature of STAT3 and its importance must be better
investigated.
This paper by Pencik et al presents an interesting challenge
to the ability to identify genetic markers for various cancers. What may at one
time seem to be a problem may later be understood in a more complete fashion to
be a necessary control element. To some degree we have observed this with BRAF
inhibitors in melanoma, which lead to SCC and thus require a MEK inhibitor. In
some sense unless a full dynamic understanding of pathways is established one
may continue to see this “whack a mole” approach to therapeutics.
To reiterate the Pencik et al observations:
1. Co-deletion of Stat3 and Pten triggers PCa: We know that
PTEN loss is found in PCa and we also know that active Stat3 is a significant
factor in many malignancies. Yet the loss of both may appear as being of
significance.
2. Stat3 regulates the ARF–Mdm2–p53pathway: This is the key
observation which they articulate and stress and the main divergence from
standard thought.
3. Loss of IL-6 and Pten leads to cancer and metastasis: We
know that IL-6 drives Stat3 and that loss of IL-6 would most likely lead to a
loss of Stat3 expression. As noted above loss of both Pten and Stat3 would lead
to a malignant state.
4. Loss of STAT3 and ARF in PCa is associated with metastases:
ARF is key to the ARF-MDM2 –p53 pathway. MDM2 inhibits p53. Thus the
association of Stat3 being the “driver” of the ARF process is essential.
We reiterate the p53 processes as shown below. The three
lead to either apoptosis or cell arrest as one would expect. In all cases p53
plays a key role but it is also clear that other proteins are required in some
cases.
Pencik et al finally note:
Interestingly, loss of PTEN expression in primary human
PCa did not correlate with overall survival and could not predict PCa-specific
death. Moreover, heterozygous PTEN deletions far outnumber homozygous deletions
in primary human PCa and we show here that PTEN is mutated or lost only in a
small subset (4.7%) of a large cohort of patients with primary PCa.
However, PTEN is lost in >50% of human PCa metastases
suggesting an important role for PTEN in this process. Finally, we show in our
study that STAT3 is co-deleted with PTEN in 66% of human PCa metastases in two
independent data sets.
Since PTEN is mutated or lost in only a minor fraction of
primary PCa, other aberrations must occur (oncogene induction or loss of tumour
suppressor function) to activate STAT3 and ARF to induce senescence in human
cancers. Indeed, several studies indicate that different aberrations can lead
to induction of senescence in human cancers
From Soissi and Wiman:
The standard classification used to define the various
cancer genes confines tumor protein p53 (TP53) to the role of a tumor
suppressor gene. However, it is now an indisputable fact that many p53 mutants
act as oncogenic proteins.
This statement is based on multiple arguments including
the mutation signature of the TP53 gene in human cancer, the various
gains-of-function (GOFs) of the different p53 mutants and the heterogeneous
phenotypes developed by knock-in mouse strains modeling several human TP53
mutations.
In this review, we will shatter the classical and traditional
image of tumor protein p53 (TP53) as a tumor suppressor gene by emphasizing its
multiple oncogenic properties that make it a potential therapeutic target that
should not be underestimated.
Analysis of the data generated by the various cancer genome
projects highlights the high frequency of TP53 mutations and reveals that
several p53 hotspot mutants are the most common oncoprotein variants expressed
in several types of tumors.
The use of Muller’s classical definition of mutations
based on quantitative and qualitative consequences on the protein product, such
as ‘amorph’, ‘hypomorph’, ‘hypermorph’ ‘neomorph’ or ‘antimorph’, allows a more
meaningful assessment of the consequences of cancer gene modifications, their
potential clinical significance, and clearly demonstrates that the TP53 gene is
an atypical cancer gene.
There is an interesting paper from CSHL on progress on
cancer classification. Linnaeus some 300 years ago came up with a
classification system for various species. Aristotle was driven by his desire
to classify, and ever since we have people trying their best to do that task.
Patients always want to know what they have, and that is a form of
classification.
We classify cancers based upon organs. We may modify it
based on cell types or based on cell markers such as immunological markers. I
remember back in the 60s that Leukemias were simple; acute or chronic, you died
now or later. Now we have a plethora of subtypes and a multiplicity of
therapeutics.
But we also know genomic data. Perhaps then we should
classify cancers based upon genes, not upon organs, binding proteins, or the
like,
As the authors state:
Classification is an everyday instinct as well as a
full-fledged scientific discipline. Throughout the history of medicine, disease
classification is central to how we organize knowledge, obtain diagnosis, and
assign treatment. Here we discuss the classification of cancer, the process of
categorizing cancers based on their observed clinical and biological features.
Traditionally, cancer nomenclature is primarily based on organ location, e.g.,
"lung cancer" designates a tumor originating in lung structures.
Within each organ-specific major type, further subgroups can be defined based
on patient age, cell type, histological grades, and sometimes molecular
markers, e.g., hormonal receptor status in breast cancer, or microsatellite
instability in colorectal cancer. In the past 15+ years, high-throughput
technologies have generated rich new data for somatic variations in DNA, RNA,
protein, or epigenomic features for many cancers. These data, representing
increasingly large tumor collections, have provided not only new insights into
the biological diversity of human cancers, but also exciting opportunities for discovery
of new cancer subtypes.
They continue:
An ever finer classification system has many potential
benefits. It is needed to capture the full spectrum of biological diversity—the
"endless forms" that Darwin spoke of. It could lead to a better
recognition of patient-specific disease mechanisms, and importantly, could
suggest treatment options that are more accurately matched to the patient's
tumor. Precision medicine, at its very foundation, relies on valid and
continuously optimized disease classification that reflects the underlying
mechanisms. However, a fine-grained classification system also has many
potential drawbacks. The newly proposed splits may not be technically robust.
Even when the finer categories are robustly supported by statistical significance
and by replication, they may still lack a clear biological meaning, or have
little impact on treatment options (#3 below) if it turns out that some
subtypes share the same clinical endpoint, or if treatment options are limited.
Indeed, we may find it much more powerful to have a new
Linnaeus type look at classification. Classifying genomically, via genes, RNA,
and epigenetic factors, may help stratify and focus on therapeutics. This
article raises an interesting dialog.
Overall we can make some summary observations:
1. Perhaps one should be cautious as regards to murine and
human models. All too often what we see in mouse models does not pan out in
human. The reasons may very well be the complexity of the signally paths.
2. Signalling paths are complex and dynamic. What may work
at one instant may not at another? The question then is: how critical are
realistic repeatable and predictive models in assisting in both prognostic
evaluation and therapeutic approaches?
3. Cells are not the same everywhere. Thus when we perform a
prostate biopsy we may get one profile but when that cell metastasizes to other
organs we get dramatically different cells. As we have discussed before the
paper by Gundem et al presets a compelling picture of the complexity of gene
expression in PCa. Namely each cell cluster may have complex and disparate
genes expressed. If that is the case then we would also be concerned that we
look at similar expression when performing biopsies.
1. Gundem et al, The evolutionary history of lethal metastatic
prostate cancer, Nature 2015. doi:10.1038/nature14347
2. Hao, Q., W. Cho, Battle Against Cancer: An Everlasting Saga of
p53, Int. J. Mol. Sci. 2014, 15(12), 22109-22127
3. Hart, J., et al, Essential role of Stat3 in PI3K-induced
oncogenic transformation, PNAS,| August 9, 2011,| vol. 108,| no. 32,|
13247–13252 MEDICAL SCIENCES
4. Huang, S., Regulation of Metastases by Signal Transducer and
Activator of Transcription 3 Signaling Pathway: Clinical Implications, Clin
Cancer Res March 1, 2007 13; 1362.
5. Marcias, E., et al, Role of Stat3 in Skin Carcinogenesis:
Insights Gained from Relevant Mouse Models, Journal of Skin Cancer Volume 2013
(2013), Article ID 684050, 10 pages
6. Moll, U., O., Petrenko, The MDM2-p53 Interaction, Molecular
Cancer Research , Vol. 1, 1001–1008, December 2003.
7. Murray-Zmijewski, F., et al A complex barcode underlies the
heterogeneous response of p53 to stress, Nature Reviews Molecular Cell Biology
9, 702-712 (September 2008)
8. Niu, et al, Role of Stat3 in Regulating p53 Expression and
Function, MOLECULAR AND CELLULAR BIOLOGY, Sept. 2005, p. 7432–7440
9. O’Shea, et al, JAKs and STATs in Immunity, Immunodeficiency, and
Cancer, NEJM, 368;2 nejm.org January 10,
2013
10. Pencik, J., et al, STAT3 regulated ARF expression suppresses
prostate cancer metastasis, Nature Communications, 22 Jul 2015.
11. Pestell, R., M., Nevalainen, Prostate Cancer, Humana (Totowa NJ)
2008.
12. Reisig, W., Understanding Petri Nets, Springer (Berlin) 2013.
13. Sherr, C., J. Weber, The ARF/p53 pathway, Current Opinion in
Genetics & Development 2000, 10:94–99
14. Song, J, et al, Cancer classification in the genomic era: five
contemporary problems, http://biorxiv.org/content/early/2015/07/23/023127?rss=1
15. Soussi, T., K. Wiman, TP53: an oncogene in disguise, Cell Death
and Differentiation (2015) 22, 1239–1249
16. Thiagalingam, S., Systems Biology of Cancer, Cambridge (New
York), 2015.
17. Van Maerken , T., et al, Escape from p53-mediated tumor
surveillance in neuroblastoma: switching off the p14ARF-MDM2-p53 axis, Cell
Death and Differentiation (2009) 16, 1563–1572
18. Yu, H., et al, Crosstalk between cancer and immune cells: role
of STAT3 in the tumour microenvironment, NATURE REVIEWS, IMMUNOLOGY, VOLUME 7,
JANUARY 2007, p| 41
19. Yu, H., et al, Revisiting STAT3 signalling in cancer: new and
unexpected biological functions, Nature Reviews Cancer, 14, 736–746, 2014.
Posts
