Prostate cancer has frequently been seen related to
inflammatory processes. The exact connection is yet to be determined. However
recent results have indicated that metformin has shown some effect on PCa and a
recent paper by Danzig et al shows significant effects with metformin and
statins. Both drugs have a certain antiinflammatory role, one in glucose
metabolism management and the other through lipid pathways. In this paper we
examine both the Danzig et al results as well and the details regarding the specific
pathways involved. Specifically the drugs deal with metabolic related pathways,
which is no surprise given the nature of Type 2 Diabetes. However the statin
usage is not directly metabolic but may very well be so. In a recent White Paper we expand upon the results, summarized herein.
Shao et al state[1]:
The widely used anti-diabetic drug metformin has been
shown to exert strong antineoplastic actions in numerous tumor types, including
prostate cancer (PCa). In this study, we show that BI2536, a specific Plk1
inhibitor, acted synergistically with metformin in inhibiting PCa cell
proliferation. Furthermore, we also provide evidence that Plk1 inhibition makes
PCa cells carrying WT p53 much more sensitive to low-dose metformin treatment.
Mechanistically, we found that co-treatment with BI2536 and metformin induced
p53-dependent apoptosis and further activated the p53/Redd-1 pathway.
Moreover, we also show that BI2536 treatment inhibited
metformin-induced glycolysis and glutamine anaplerosis, both of which are
survival responses of cells against mitochondrial poisons. Finally, we
confirmed the cell-based observations using both cultured cell-derived and
patient-derived xenograft studies. Collectively, our findings support another
promising therapeutic strategy by combining two well tolerated drugs against
PCa proliferation and the progression of androgen-dependent PCa to the
castration-resistant stage.
For example in the work of Margel et al they note:
By using fractional polynomials, we verified that the
association between cumulative metformin use after PC diagnosis and PC specific
mortality is linear. Onmultivariable analysis, for each additional 6 months of
metformin use after PC diagnosis, there was a 24% reduction in PC-specific
mortality (adjusted HR [aHR], 0.76; 95% CI, 0.64 to 0.89). Increasing durations
of cumulative use of all other antidiabetic medications was not associated with
PC-specific mortality.
In a similar manner in a study with statins Allott et al
noted[2]:
In this retrospective cohort of men undergoing RP,
post-RP statin use was significantly associated with reduced risk of BCR.
Whether the association between post-RP statin use and BCR differs by race
requires further study. Given these findings, coupled with other studies
suggesting that statins may reduce risk of advanced prostate cancer, randomized
controlled trials are warranted to formally test the hypothesis that statins
slow prostate cancer progression.
Thus it would be reasonable to try an analysis with
metformin and a statin combined. It is this study that we have focused upon as
a vehicle to explore the effects on prostate cells using drugs that have
effects on processes which are fundamentally inflammatory; excess blood glucose
and excess blood lipids. To do this we sue the most recent paper of Danzig et
al where they state:
The combination of statins and metformin in men
undergoing RP for prostate cancer (PCa) may be associated with a lower BCR risk
than would be predicted based on the independent effects of both medications. A
synergism between these two agents is biologically plausible based on our
current understanding of their diverse molecular pathways of action. The
results of future clinical trials involving the use of either medication in men
with PCa should be carefully assessed for confirmatory evidence of such a
relationship.
Thus there may very well be a beneficial result of such an
approach. We briefly examine this and the details beneath in terms of the
cellular pathway dynamics. In this analysis we utilize the Danzig et al paper
and examinie in some details the functions of the specific drugs and their
pathway characteristics. We specifically focus on metabolic pathway elements
such as mTOR, AMPK, and how these are influencing a pathogenic characteristic
leading to PCa.
Our focus is on the results from the Danzig et al paper. It
demonstrates a synergism between metformin and statins in reducing mortality
from both HGPIN and PCa. The issue of concern is; just how do these two
medications function and what if anything can be generalized from this
observation? It is well known that statins have an ameliorative effect on
certain cancers and it is also well known that cancers can be initiated and
exacerbated by inflammatory processes such as Type 2 Diabetes. We examine some
of the basic observations presented in the paper and then proceed to examine
the details of the pathway controls.
From the Dantzig paper we have the following survival across
the four groups:
Note the alleged improvement. Also presented in the paper
are Hazard Ratios. We summarize three key ones below.
First, we summarize the results of Hazard Ratios on several
key factors in the initial stages of presentation. These are all related to
biochemical recurrence, BCR.
Second the Hazard Ratios for race are presented.
Surprisingly Asia is higher than African American.
Third, below is the Hazard Ratio summary for conditions of
the lesion. What is interesting is the importance of pre-operative PSA levels.
Perhaps this is a marker for reflecting on the importance of continuing to
measure PSAs since the higher it is pre-operatively the greater the chance of
post-operative recurrence.
As Danzig et al conclude:
In conclusion, we found that the combination of statins
and metformin in men undergoing RP for PCa may be associated with a lower BCR
risk than would be predicted based on the independent effects of both
medications. A synergism between these two agents is biologically plausible
based on our current understanding of their diverse molecular pathways of
action. The results of future clinical trials involving the use of either
medication in men with PCa should be carefully assessed for confirmatory
evidence of such a relationship. Finally, continued research into the molecular
mechanisms by which these drugs affect cancer behavior will be highly
instructive.
Thus the study presents some significant additional insight
into pathways via the use of these medications. We thus start with pathways and
then consider the effects of the medications.
Now metabolic factors in a cells environment place stress
upon a cell that can result in loss of control as shown above. One metabolic or
environmental factor is inflammation, others such as excess glucose or loss of
glucose control is another. We examine the latter here.
For example, regulating p53 expression is known to be a
major goal. Loss of that regulation is a major concern. One of the major
players in that role is AMPK, AMP kinase. AMPK is a metabolic regulatory gene
product that on the one hand manages cell energy control and on the other hand
can control p53. Thus controlling this element is essential.
This then leads us to other gene products such as mTOR and
essential metabolic gene product as well as LKB1.
Cell metabolism is the
process whereby a cell uses energy that is made available to it to maintain normal
processes and to grow and reproduce as may be required. Normal metabolic
processes in a cell allow for the control of all of the elements in a balanced
manner. Excess glucose as seen in Type 2 Diabetes can result in
quasi-inflammatory states and loss of homeostasis.
Let us focus briefly upon
AMPK, AMP kinase, as an initial point to understand the intra-cellular
metabolic processes. AMPK is a key control element in many intracellular
pathways[3].
From the paper by Mihaylova and Shaw we have[4]:
One of the central regulators of cellular and organismal
metabolism in eukaryotes is AMP-activated protein kinase (AMPK), which is
activated when intracellular ATP production decreases.
AMPK has critical roles in regulating growth and
reprogramming metabolism, and has recently been connected to cellular processes
such as autophagy and cell polarity. Here we review a number of recent
breakthroughs in the mechanistic understanding of AMPK function, focusing on a
number of newly identified downstream effectors of AMPK.
From the work of Shackelford and Shaw we have[5]:
In the past decade, studies of the human tumour
suppressor LKB1 have uncovered a novel signalling pathway that links cell
metabolism to growth control and cell polarity.
LKB1 encodes a serine–threonine kinase that directly
phosphorylates and activates AMPK, a central metabolic sensor. AMPK regulates
lipid, cholesterol and glucose metabolism in specialized metabolic tissues,
such as liver, muscle and adipose tissue. This function has made AMPK a key
therapeutic target in patients with diabetes.
The connection of AMPK with several tumour suppressors
suggests that therapeutic manipulation of this pathway using established
diabetes drugs warrants further investigation in patients with cancer.
In particular Shackelford and Shaw demonstrate the impact of
Metformin on this pathway.
As Mendelsohn et al state:
While growth factor–stimulated signaling cascades promote
cell growth under favorable conditions, cells have sophisticated nutrient
sensing systems that serve to block growth when the internal energy supply is
limiting. These regulators ensure that, during periods of intracellular
nutrient depletion, metabolites are redirected from anabolic pathways and
instead used to fuel catabolic pathways that will provide the energy required
to survive the period of nutrient limitation. The AMP-activated protein kinase
(AMPK) plays a major role coordinating cellular energy status with appropriate
metabolic responses.
AMPK directly senses cellular energy levels in the form
of the AMP/ATP ratio. Falling energy levels increase the cellular AMP/ATP
ratio, priming AMPK for activation by the liver kinase B1 (LKB1). AMPK
phosphorylates multiple targets with the cumulative effect of blocking anabolic
reactions and stimulating energy-generating catabolic pathways.
For example, AMPK phosphorylates and inhibits acetyl-CoA
carboxylase (ACC), with the dual effect of blocking fatty acid synthesis and
activating fatty acid oxidation. AMPK also directly inhibits cell growth, both
by inducing a p53-dependent cell cycle arrest and by blocking mTOR activity at
multiple levels. Through these diverse activities, AMPK functions as a
metabolic checkpoint, ensuring that cell growth is halted until bioenergetic
conditions are favorable for growth.
AMPK is a powerful regulator of cell dynamics. It senses and
manages energy via the ATP control cycle. Its impact on p53 which we have
discussed earlier is also a major factor which may lead to cell oncogenesis.
Thus examining how AMPK reacts to excess glucose and how it can be reset is a
key observation.
mTOR is a control protein that in involved in metabolic
related pathways. mTOR, the mammalian target of rapamycin, is a gene product
(1p36.2) is a protein which acts in a critical manner in interconnecting the
genetic circuits in mammals, and especially man. It fundamentally controls
glucose transport and protein synthesis. The pathway depicted below is a
modification of the graphic from Weinberg (p 785) which shows mTOR in its two
modes, one with Raptor assisting and one with Rictor. The Rictor/mTOR mode
activates the Akt pathway via the placement of a phosphate and this manages the
protein synthesis portion. The inclusion of rapamycin will block the
Raptor/mTOR path and reduce the protein synthesis and cell growth portion. The
inhibitory effect on Akt/PKB by rapamycin is assumed to be the main factor in
its anti-cancer effects.
We depict the mTOR C1 pathway below:
The following chart presents a more complex version of the
mTOR C1 pathway (Raptor). This allows us to best understand the complex
interactions. The mTOR C1 and C2 pathways are depicted in the combined chart
below:
Looking at the complexity of the mTOR pathway it presents an
interesting one for addressing PCa. Kinkaide et al (2008) indicate:
Among the major
signaling networks that have been implicated in advanced prostate cancer are
the AKT/mammalian target of rapamycin (AKT/mTOR) and MAPK pathways. Indeed,
deregulated expression and/or mutations of the phosphate and tensin homolog
tumor suppressor gene (PTEN) occur with high frequency in prostate
cancer, leading to aberrant activation of AKT kinase activity as well as its
downstream effectors, including the mTOR signaling pathway. In addition, many
prostate tumors display deregulated growth factor signaling, which may result
in activation of MAPK kinase 1 (MEK) kinase and ultimately ERK MAP.
Notably, previous
studies have demonstrated that the AKT/mTOR and MAPK signaling pathways are
alternatively and/ or coordinately expressed in advanced prostate cancer and
function cooperatively to promote tumor growth and the emergence of hormone-
refractory disease. These observations formed the basis for our hypothesis that
targeting these signaling pathways combinatorially may be effective for
inhibiting tumorigenicity and androgen independence in prostate cancer.
Kinkaide et al also demonstrate the creation of HGPIN via
their work. This represents another pathway of HGPIN to PCa.
LoPiccolo et al state:
The PI3K/Akt/mTOR
pathway is a prototypic survival pathway that is constitutively activated in
many types of cancer. Mechanisms for pathway activation include loss of tumor
suppressor PTEN function, amplification or mutation of PI3K, amplification or
mutation of Akt, activation of growth factor receptors, and exposure to
carcinogens. Once activated, signaling through Akt can be propagated to a
diverse array of substrates, including mTOR, a key regulator of protein
translation. This pathway is an attractive therapeutic target in cancer because
it serves as a convergence point for many growth stimuli, and through its
downstream substrates, controls cellular processes that contribute to the
initiation and maintenance of cancer. Moreover, activation of the Akt/mTOR
pathway confers resistance to many types of cancer therapy, and is a poor
prognostic factor for many types of cancers.
As we have shown with the more complex Weinberg model, here
mTOR and PTEN play a strong role in the overall control. The authors show the
points of possible control. The complexity of the pathways will be a challenge.
It is less an issue of size complexity than a feedback and instability
complexity. Nelson et al (2007) have demonstrated similar results as well.
Other researchers have also posited other simple models. We
demonstrated the one by Hay as has been stated:
The downstream
effector of PI3K, Akt, is frequently hyperactivated in human cancers. A
critical downstream effector of Akt, which contributes to tumorigenesis, is
mTOR. In the PI3K/Akt/mTOR pathway, Akt is flanked by two tumor suppressors:
PTEN, acting as a brake upstream of Akt, and TSC1/TSC2 heterodimer, acting as a
brake downstream of Akt and upstream of mTOR.
The Baldo et al model is quite similar to the Weinberg model
shown initially. It clearly demonstrates the overall controlling influence of
mTOR. As Baldo et al state:
There is a great body
of evidence supporting consideration of the mTOR signaling system as an
important network in cell regulation, differentiation and survival. mTOR is a
sensor of mitogen, energy and nutritional levels, acting as a “switch” for
cell-cycle progression from phase G1 to phase S.
The antibiotic
Rapamycin, a potent mTOR inhibitor, has been known to the National Cancer
Institute and recognized for its potential anticancer properties since the
1970s. The observation that cell lines from different cancer types exposed to
low doses of Rapamycin underwent cell-cycle arrest in phase G1, provided the
basis for considering mTOR as a target for cancer therapy.
Development of mTOR
inhibitor compounds has proceeded empirically due to the lack of understanding
of the precise molecular targets and the required dose of the new compounds .
The development of Rapamycin analogs (“Rapalogs”),
but also of other, structurally different, mTOR inhibitors, was directed at the selection of
specific cancer type sensitivity and an optimization of pharmaceutical forms.
The mTOR pathway controls cell size and cellular proliferation.…nutrient metabolism, mRNA translation and
cell survival control. Disruption of TOR leads to early embryonic death in
flies and mammalian cells, indicating mTOR plays an important role in
regulating cell survival. … deregulation of several mTOR components leads to
modified cell proliferation patterns and, on the other, that many mTOR
components are deregulated in several human cancers.
… Therefore, inhibition of mTOR leads to slowing or arrest of cells in
the G1 phase. Translational control may have an important role in the
balance of cell survival and death, and hence for apoptosis. Importantly,
components of mTOR are deregulated in some human cancers, for example, breast
and colon. Alteration of PI3-K/Akt is frequently observed in head and neck
cancer .
As Easton and Houghton state:
Proteins regulating
the mammalian target of rapamycin (mTOR), as well as some of the targets of the
mTOR kinase, are overexpressed or mutated in cancer. Rapamycin, the naturally
occurring inhibitor of mTOR, along with a number of recently developed rapamycin
analogs (rapalogs) consisting of synthetically derived compounds containing
minor chemical modifications to the parent structure, inhibit the growth of
cell lines derived from multiple tumor types in vitro, and tumor models in
vivo.
Results from clinical
trials indicate that the rapalogs may be useful for the treatment of subsets of
certain types of cancer. The sporadic responses from the initial clinical
trials, based on the hypothesis of general translation inhibition of cancer
cells are now beginning to be understood owing to a more complete understanding
of the dynamics of mTOR regulation and the function of mTOR in the tumor
microenvironment. This review will summarize the preclinical and clinical data
and recent discoveries of the function of mTOR in cancer and growth regulation.
The other observation here is that we often find multiple
characterizations of the pathways. Namely there is no canonical form, and often
a pathway is depicted to demonstrate a specific protein function. Thus we may
see an emphasis on one set of proteins while others are neglected. As much as
we currently attempt to unify this process we are left somewhat adrift in model
development at this stage. This can be exemplified by now looking at the next
section on LKB1. There we show its control over PTEN whereas in an earlier
model we have it controlling AMPK. In reality there are multiple links as we
have discussed. The literature can be even more confusing on this issue as
well.
As Mendelsohn et al state:
It is now widely accepted that mTORC1 positively controls
an array of cellular processes critical for growth, including protein
synthesis, ribosome biogenesis, and metabolism, and negatively influences
catabolic processes such as autophagy—all of which have roles in cancer pathogenesis.
Elucidating the key downstream targets of mTORC1 driving these events is an
intense area of research.
Originally, much of the study of mTOR relied on
experiments in which rapamycin was used acutely to inhibit mTOR (which we now
know was mTORC1) in cultured cells. This led to extensive characterization of
the best known mTORC1 substrates eiF-4E-binding protein 1(4E-BP1) and S6 kinase
1 (S6K1), both of which regulate protein synthesis.3 In the unphosphorylated
state, 4E-BP1 binds and inhibits the cap-binding protein and translational
regulator eIF4E. When phosphorylated by mTOR, 4E-BP1 is relieved of its
inhibitory duty, promoting eIF4E interaction with the eIF4F complex and the
translation of capped nuclear transcribed mRNA.
Following co-regulatory phosphorylation by mTORC1 and
another kinase called phosphatidylinositol 3-dependent kinase 1 (PDK1), S6K1
positively affects mRNA synthesis at multiple steps including initiation and
elongation by phosphorylating several translational regulators. Although the
preponderance of evidence indicates that S6K1 and 4E-BP1 are directly
phosphorylated by mTOR, an unidentified phosphatase activity may also be
involved in their regulation. For example, the rapamycin-sensitive
phosphorylation site on S6K1 is rapidly dephosphorylated (i.e., within minutes)
of exposure to the drug.
They continue:
Conditions that inhibit growth, such as decreased energy,
low oxygen, and insufficient nutrients, are associated with the harsh
microenvironment of poorly vascularized tumor. The ability of cancer cells to
overcome these adverse conditions would promote tumor growth, putting the
desensitization of mTORC1 signaling in the spotlight as a potential mechanism
cancer cells could exploit to enhance their viability. Whether mutations in the
amino acid– and glucose-sensing pathway that activates mTORC1 exist in cancer
is not known. Mutations in the growth factor inputs to mTORC1 are prominent in
cancer…
Therefore, understanding the contribution and relevance
of mTORC1 signaling in the progression of cancers with aberrant PI3K-AKT
signaling is an important area of research.
LKB1 has been demonstrated to be the underlying control
element in Peutz-Jeghers syndrome, a proliferative melanocytic genetically
dominant disorder. It controls certain pathways and as a result can be
considered as a candidate in the development and progression of melanoma.
Generally LKB1 is a gene whose protein stabilizes the growth and location of
melanocytes. Understanding its impact in Peutz-Jeghers allows one to examine
what happens when its function is suppressed in melanoma. Albeit not an
initiator in the process, its aberration in a melanocyte argues for movement
and loss of control.
In a recent paper by Liu et al the authors examine this premise
and conclude that loss of LKB1 is significant especially in metastatic
evolution. As Liu et al state:
Germline mutations in LKB1 (STK11) are associated with
the Peutz-Jeghers syndrome (PJS), which includes aberrant mucocutaneous
pigmentation, and somatic LKB1 mutations occur in 10% of cutaneous melanoma. By
somatically inactivating Lkb1 with K-Ras activation (±p53 loss) in murine
melanocytes, we observed variably pigmented and highly metastatic melanoma with
100% penetrance. LKB1 deficiency resulted in increased phosphorylation of the
SRC family kinase (SFK) YES, increased expression of WNT target genes, and
expansion of a CD24+ cell population, which showed increased
metastatic behavior in vitro and in vivo relative to isogenic CD24−
cells. These results suggest that LKB1 inactivation in the context of RAS
activation facilitates metastasis by inducing an SFK-dependent expansion of a
prometastatic, CD24+ tumor subpopulation.
Earlier work by Zheng et al noted:
The LKB1-AMPK signaling pathway serves as a critical
cellular sensor coupling energy homeostasis to cell growth, proliferation, and
survival. However, how tumor cells suppress this signaling pathway to gain
growth advantage under conditions of energy stress is largely unknown. Here, we
show that AMPK activation is suppressed in melanoma cells with the B-RAF V600E
mutation and that downregulation of B-RAF signaling activates AMPK. We find
that in these cells LKB1 is phosphorylated by ERK and Rsk, two kinases
downstream of B-RAF, and that this phosphorylation compromises the ability of
LKB1 to bind and activate AMPK. Furthermore, expression of a
phosphorylation-deficient mutant of LKB1 allows activation of AMPK and inhibits
melanoma cell proliferation and anchorage-independent cell growth.
Thus Zheng et al putatively identified these two pathways as
sources for melanoma development. Liu et al appear to have extended this to
metastasis.
The LKB1 gene, also called STK11, which encodes a member of
the serine/threonine kinase, regulates cell polarity and functions as a tumour
suppressor. This is clearly demonstrated in the above. Now recall that mTOR is
a protein kinase and is a key regulator of cell growth[6].
mTOR stimulates mRNA translation thus facilitating the conversion into
proteins. mTOR also facilitates the formation of ribosomes which as an
important condition of cell growth under specific physiological conditions.
Through the effects of mTOR on the ribosome machinery it becomes a significant
factor in increasing translational activity in a cell.
As Marks et al state regarding the above flow we have (p
337):
Activation
and effects of the mTOR protein kinase By inactivating
the GAP TSC2 of the small G-protein Rheb, extracellular signals stimulating the
PI3K-PKB signaling cascade prompt Rheb to activate mTOR. mTOR enhances the
activity of the protein kinase S6K and represses 4E-BP1 and eEF2 activities,
resulting in an increased rate of translation (whether 4E-BP1 and eEF2 kinase
are phosphorylated directly by mTOR, as shown here, or by S6K or by both
kinases is not entirely clear).
mTOR
may also be directly phosphorylated and activated by PKB.
Now Liu et al state regarding this pathway model:
Two independent pathways appear to be critically
important in regulating cell growth in response to nutrient supply and
mitogenic stimulation:
(i) the PKA/PRKAR1A-LKB1 tumour suppressor protein
pathway, acting via AMPK, and
(ii) the PI3K/AKT pathway.
Recent evidence suggests that the tumour suppressor gene
complex, TSC1/TSC2, orchestrates the signal from both pathways to the
downstream target, mTOR, which in turn regulates the ribosomal protein S6 and
4EBP-1, a repressor of the translational initiation factor eIF4E. In this
model, at times of nutrient stress LKB1/AMPK activation of the TSC1/TSC2
complex results in inhibition of mTOR and a decrease in protein synthesis.
Under stimulation of mitogenic pathways, PI3K
phosphorylates PIP2 to PIP3 resulting in recruitment of AKT to the membrane
where it is activated by PDK1. Activated AKT inhibits the TSC1/TSC2 tumour
suppressor complex leading to increased mTOR activity. In the later pathway,
PTEN antagonises PIP3 action through dephosphorylation, and thus provides an
‘‘off’’ switch for regulating mitogenic pathway induced cellular growth and
proliferation.
Cross talk of several other pathways appears to play
important regulatory roles in the lentiginoses syndromes to include the
Ras/MAPK pathway in the regulation of translation, the LKB1 pathway in cellular
polarity, the AKT pathway (as well as the TSC1/TSC2 complex) in the regulation
of the Wnt/GSK3b/b-Cat pathway, and the BMP pathway in the regulation of PTEN
(see text for further discussion). Lastly, both PTEN and mTOR appear to have
negative regulatory effects on VEGF through loss of stabilisation of the
hypoxia inducible transcription factor 1 (HIF1).
When LKB1 is inactivated we have the following changes
observed in a melanocyte. Note the deactivation of normal LKB1 proteins as well
as a PTEN loss of function. We then have the models of Bauer and Stratakis,
which we graphically depicted before and they are compelling and establish a
paradigm which the work of Liu et al can be considered.
Let us go back to LKB1 and its function. From NLM database
we have[7]:
LKB1 is a primary upstream kinase of adenine
monophosphate-activated protein kinase (AMPK),
a necessary element in cell metabolism that is required for
maintaining energy homeostasis. It
is now clear that LKB1 exerts its growth suppressing effects by activating a
group of other ~14 kinases, comprising AMPK
and AMPK-related
kinases.
Activation of AMPK
by LKB1 suppresses growth and proliferation when energy and nutrient levels are
scarce. Activation of AMPK-related kinases by LKB1 plays vital roles
maintaining cell polarity thereby inhibiting inappropriate expansion of tumour
cells. A picture from current research is emerging that loss of LKB1 leads to
disorganization of cell polarity and facilitates tumour growth under
energetically unfavorable conditions. Also it is known as PJS; LKB1; hLKB1.
From the results of Shaw et al we have[8]:
AMP-activated protein kinase (AMPK) is a highly conserved
sensor of cellular energy status found in all eukaryotic cells. AMPK is
activated by stimuli that increase the cellular AMP/ATP ratio. Essential to
activation of AMPK is its phosphorylation at Thr-172 by an upstream kinase,
AMPKK, whose identity in mammalian cells has remained elusive..LKB1-deficient
murine embryonic fibroblasts show nearly complete loss of Thr-172
phosphorylation and downstream AMPK signaling in response to a variety of
stimuli that activate AMPK. Reintroduction of WT, but not kinase-dead, LKB1
into these cells restores AMPK activity. Furthermore, we show that LKB1 plays a
biologically significant role in this pathway, because LKB1-deficient cells are
hypersensitive to apoptosis induced by energy stress.
Shaw et al describe the above as follows:
Model for LKB1 as a sensor of low energy and negative
regulator of tumorigenesis and apoptosis. Under basal conditions, LKB1 serves as a sensor of
low energy, keeping
ATP-consuming processes including protein synthesis in check via AMPK phosphorylation of TSC2. In response to stresses such as low glucose, hypoxia, nutrient deprivation, or mitochondrial poisons,
LKB1 phosphorylates AMPK, which shuts off ATP-consuming processes and up-regulates ATP production to offset the elevated
AMP/ATP ratio. This activity prevents
the cells from going into apoptosis in response to elevated AMP. In LKB1-deficient cells, under some basal conditions, there may be increases in TOR signaling due to the lack of TSC2 phosphorylation by AMPK, resulting in increased growth or tumorigenic potential. In response
to further increases
in intracellular AMP, these cells have no mechanism to offset the elevated AMP and go straight into apoptosis.
We now want to examine some of the details of each of the
two medications and specifically their cellular pathway elements and how
putatively the two medications may function. We begin by returning to Danzig et
al and seeing what they state about the specifics.
For metformin Danzig et al remark:
Metformin has been shown to inhibit mitochondrial
respiration, to induce apoptosis through activation of the AMPK/p53 pathway,
and to trigger a G2-M cell cycle arrest independent of
its effect on p53.
Its AMPK activation results in diminished mTOR and S6K1
activity, impeding translation.
Independent of AMPK, metformin also induces G0/G1 cell
cycle arrest via reduction of cyclin D1 levels and pRb phosphorylation.
Finally, metformin inhibits nuclear factor κB (NFkB) and
Erk 1/2 and reduces levels of c-MYC.
For statins the author’s remark:
Statins, through HMG-CoA reductase inhibition, limit
mevalonate production, which is used in protein prenylation.
This has been shown to induce apoptosis through Ras
inhibition and to reduce invasiveness by preventing intracellular Rho
relocalization.
Another cholesterol-dependent effect is statins’
interference with lipid raft signaling, which reduces activation of the
PI3k/Akt proliferation pathway.
Independent of HMG-CoA reduction, statins can also induce
apoptosis through the MEK/ERK pathway, inhibit cell proliferation through
blockade of the G1-S and G2-M cell cycle transitions, induce apoptosis by
caspase activation and reduce angiogenesis through diminished endothelial
nitric oxide production.
Finally, statins inhibit leukocyte migration and the
resultant inflammation, which has been linked to PCa progression.
The statin effects are significant in overall pathway
modulation.
Metformin is a classic Type 2
Diabetic control medication and has been used extensively with many patients
for several decades. We demonstrate below the areas in which Metformin
exercises its influence.
It reduces, inhibits, and activates a variety of pathway elements
all of which control cell cycles and apoptosis. It controls the metabolic
cycles that relate to the pathway elements we have shown in the previous
sections.
The impact of AMPK and in turn p53 is a significant pathway.
AMPK is as we have seen a significant metabolic player and metformin modulates
it behavior. It manages the Cyclin D1 which controls cell cycle growth. One may
wonder why so effectively in the prostate, however. The mTOR management is via
AMPK as well and then through mTOR C1.
As Mendelsohn et al state:
Metformin belongs to the biguanide class of antidiabetic
drugs and activates the LKB1/AMPK axis (mediating glucose and energy
homeostasis) and inhibits cancer cell viability through the inhibition of mTOR.
Metformin can also downregulate mTOR and subsequent cell growth through
AMPK-independent mechanisms. A recent study using mouse models of lung cancer
to assess the protective effect of metformin suggested two possible mechanisms:
decreased levels of circulating insulin and lowered energy stress leading to
inhibition of mTOR.
Owing to the fact that studies show metformin is
associated with a decreased risk of cancer incidence compared with other
treatments (such as insulin) among diabetic patients, metformin is rightfully
garnering interest for its role in cancer prevention and therapy and supports
further testing in the clinical setting.
The Mendelsohn comment has been demonstrated in Danzig
somewhat.
Statins are used to reduce VDL levels. The typical mechanism
is shown below. The statin blocks the production of intracellular cholesterol
which in turns sets off a cascade that sends out LDL receptors to collect LDL
from the blood thus lowering serum LDL.
Overall this is a simple and straightforward mechanism.
However, just how this affects the PCa process has been postulated in the paper
we have focused on but may be likely to a topic of discussion. Chan et al have discussed
several general mechanisms.
As Chan et al note:
HMG-CoA reductase inhibitors have been shown to
synchronize tumor cells by blocking the transition of G1-S in the cell cycle,
thereby exerting its antiproliferative effect. This effect is reversed with the
addition of mevalonate. In primary cultures of human glioblastoma cells,
inhibition of Ras farnesylation by lovastatin is associated with reduction of
proliferation and migration. However, the inhibition of cell growth by
lovastatin may be independent of Ras function .
These findings suggest that geranyl-geranylated proteins
(but to a much lesser degree, farnesylated proteins such as Ras) are essential
for progression of C6 glioma cells into the S phase of the cell cycle. In
addition, N-Ras mutated, primary AML cells were no more sensitive to
simvastatin than AML cells without the mutation, suggesting that the inhibition
of AML cell proliferation by HMB-CoA reductase inhibitors may be independent of
the Ras signaling pathway.
The results by Danzig et al present an interesting window to
possible control of PCa expansion by using metabolic pathway elements which may
also have been causative factors in its initiation. We examine here several
observations which may expand the work provided therein.
Let us examine a few additional issues:
What impact will methylation have and is it also driven by
similar modalities? We know that methylation is also a factor especially in
inflammation like states. Thus what effect does methylation have in this
specific case?
Does the process activated by metformin and statins affect
all altered prostate cells including stem cells or does it deal solely with the
proliferating cells? Here is the issue regarding changes not only to prostate
cells but to all cells. There is no specificity of these two therapeutics to
prostate cells. The affect cells across the body. Are these effects stabilizing
as they may be to the prostate or are they potentially unstabilizing?
How does this combo deal with other cells? This is a corollary
to the above observation. Namely here we would examine the impacts, beneficial
and harmful, to other cells. These medications are modulating metabolic
processes. These metabolic processes are common across many cell areas. It
would be useful to see what the balanced effect is.
This must be a common combination. If so that a study may
reveal a significant different in end-stage mortality in such a large
population. Namely we know that this
combination is quite common. If so, then a retrospective study may be
beneficial. However, as we have noted before, we do not have either compliance
or detailed measurements regarding lipids or blood sugar (eg HbA1c)
information.
What is the cause of the synergy between the two? As noted
by Danzig et al:
Several potential mechanisms of synergism between the two
medications have been explored in preclinical studies. In one study of fatty
liver pathogenesis, type 2 diabetic mice fed with a high-fat diet developed
increased levels of markers of inflammation and oxidative stress, including
C-reactive protein, interleukin-6 and tumor necrosis factor-α. The
combinatorial use of atorvastatin and metformin attenuated these effects to a
significantly greater degree than either drug alone.
Another study found that the proapoptotic and
anti-survival effects of an AMPK activator similar to metformin on malignant
melanoma cell lines were enhanced by combination with simvastatin or
fluvastatin. As discussed earlier, these two drugs are thought to have a wide
range of effects on both metabolic and pleiotropic pathways.
Therefore, the possible means by which they may interact
intracellularly to impact cancer behavior are plentiful and diverse.
The cause of the synergy is not really understood. Frankly,
even single drug cause is at best generically understood. The range of impact
of statins is not fully grasped and thus it may be the statin which has the
greater effect. At this stage we need added information regarding the nature of
effects.
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Allott, et al, Postoperative
statin use and risk of biochemical recurrence following radical prostatectomy:
results from the Shared Equal Access Regional Cancer Hospital (SEARCH) database,
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Pathway and mTOR inhibitors as Agents for Cancer Therapy, 2008, Curr Can Drug
Targets, pp 647-668.
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Polarization of Single Intestinal Epithelial Cells upon Activation of LKB1 by
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as anticancer agents. Clin Cancer Res 2003; 9: 10–19.\
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Danzig, et al, Synergism
between metformin and statins in modifying the risk of biochemical recurrence
following radical prostatectomy in men with diabetes, Prostate Cancer and
Prostatic Disease (2015) 18, 63–68
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Easton, J., P. Houghton,
mTOR and Cancer Therapy, Oncogene, 2006, pp 6436-6446.
8.
Kinkaide, C., et al,
Targeting Akt/mTOR and ERK MAPK Signalling Inhibits Hormone Refractory Prostate
Cancer in Preclinical Mouse Model, Jrl Clin Inv 2008, 99 3051-3064.
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Alterations in Prostate Basal Cell Lauer and Basement Membrane, Int Jrl Bio
Sci, V 5, 2009, pp 276-285.
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LoPiccolo, J., et al,
Targeting the PI3K/Akt/mTOR Pathway, Drug Res Up, 2008, pp 32-50.
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Margel, D., et al,
Metformin Use and All-Cause and Prostate Cancer Specific Mortality Among Men
With Diabetes, JCO Sep 1, 2013:3069-3075; DOI:10.1200/JCO.2012.46.7043.
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Signal Processing, Garland (New York), 2009
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McGarty, T. P., Obesity and
Type 2 Diabetes: Cause and Effect, DOI: 10.13140/2.1.2118.5929 https://www.researchgate.net/publication/265206539_Obesity_and_Type_2_Diabetes_Cause_and_Effect
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McGarty, T. P., Prostate
Cancer: A Systems Approach, DOI: 10.13140/2.1.2475.2007 https://www.researchgate.net/publication/264960277_Prostate_Cancer_A_Systems_Approach
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Molecular Basis of Cancer, Elsevier (New York) 2014.
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coordinates cell growth, autophagy and metabolism, Nature Cell Biology13,
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Polo-like Kinase 1 (Plk1) Enhances the Antineoplastic Activity of Metformin in
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[3] http://www.cellsignal.com/contents/science-pathway-research-cellular-metabolism/ampk-signaling-pathway/pathways-ampk
This is a useful pathway description worth examining in detail.
[6] See Marks et al pp 335-345.
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