Review Article
Diabetes Mellitus and Reprogrammed Glucose Metabolism in Pancreatic Cancer: Features for Clinical Translation
Daniela Basso*, Andrea Padoan, Paola Fogar, Carlo-Federico Zambon and Mario Plebani
Department of Medicine–DIMED, University of Padova, Italy
*Corresponding author: Daniela Basso, Department of Medicine–DIMED, University of Padova, Via Giustiniani, 235128 Padova, Italy
Published: 20 Oct, 2016
Cite this article as: Basso D, Padoan A, Fogar P, Zambon
C-F, Plebani M. Diabetes Mellitus and
Reprogrammed Glucose Metabolism in
Pancreatic Cancer: Features for Clinical
Translation. Clin Oncol. 2016; 1: 1123.
Abstract
The reprogrammed metabolism of cancer cells underlies the shift of glucose energetics from the highly efficient oxidative phosphorylation to the less efficient aerobic glycolysis, the Warburg effect. This phenomenon, with the activation of the glutamine pathway, advantages survival and proliferation of pancreatic ductal adenocarcinoma (PDAC) cells, which live in an adverse hypoxic and nutrient restricted microenvironment. In PDAC, glucose metabolic alterations occur also at the whole organism, Diabetes Mellitus (DM) being diagnosed in approximately 60% to 80% of patients. The association between PDAC and DM is a dual face phenomenon, DM being both a risk factor for and a consequence of this tumor type. Data from epidemiology indicate that longstanding DM increases PDAC risk 1.5 to 2.0 fold, probably because of the pro-proliferative effects of hyperinsulinemia. By contrast early onset DM, i.e. diabetes diagnosed no more than two years prior to cancer diagnosis, is considered a consequence of PDAC. Secondary DM is due to complex interactions between tumor cells, tumor microenvironment and pancreatic endocrine cells. In this scenario the role of the inflammatory S100A8 calcium binding protein, matrix metalloproteinases, Vanin1 or amylin has been experimentally demonstrated. However, the efforts made to translate in the clinical practice any individual new poteantial biomarker failed, because none reached enough sensitivity and specificity to be considered a reliable biomarker to diagnose PDAC even in high risk subjects as those with new onset DM. Therefore the identification and clinical validation of new biomarkers remains a challenge for future studies.
Introduction
The glucose metabolism alterations present at both the cancer cell site and throughout the
organism level in cancer patients are particularly evident in pancreatic ductal adenocarcinoma
(PDAC), the fourth leading cause of cancer related deaths [1]. Glucose transporter GLUT1
over expression at the cancer cell site favours the uptake of glucose, the main source for cellular
energetics, on which in PET imaging the use of the tracer 18fluorodeoxyglucose is based [2]. In
cancer cells glucose metabolism is reprogrammed and, even in the presence of oxygen, glucose is
mainly processed in the cytosol to pyruvate, which largely escapes from the energy efficient Krebs
cycle in the mitochondria [3]. This phenomenon, first described by Otto Warburg almost 100 years
ago, and now known as Warburg’s effect or “aerobic glycolysis”, is considered one of the emerging
hallmarks of cancer [4]. The clinical manifestation of altered glucose metabolism in the organism
is diabetes mellitus, considered a risk factor for, and a consequence of, PDAC [5]. Although it is
not known whether glucose metabolic alterations in the cancer cell, and in the entire organism,
influence each other, it has been suggested that insulin and insulin-like growth factors play a part in
cancer onset and progression [6,7].
Alterations in glucose metabolism at the cancer cell site
Although first described almost 100 years ago, renewed attention in the Warburg effect over the
last few decades, has led to the definition of two main concepts:
1. Metabolic reprogramming is a feature of cancer cells contributing to proliferation and
metastases [3,8];
2. Drugs targeting cancer metabolism might enhance the efficacy of chemotherapy [9].
In PDAC, cancer cells are dispersed within a hypovascular dense desmoplasia, which contributes
to a hypoxic and nutrient deficient tumoral microenvironment. These features might limit the
access of cancer cells to fuel and nutrients, indispensable for the biosynthesis of amino acids and
nucleotides, required for cell proliferation. By reprogramming their metabolism, PDAC cells are
enabled to support amino acids and nucleotide biosynthesis, thus
deriving advantage from the adverse microenvironment. In cancer
cells glucose uptake and glycolysis are favoured by the over expression
of the glucose transporter GLUT1 and of a series of glycolytic
enzymes, including lactate dehydrogenase (LDH, that converts
pyruvate into lactate), hexokinase 2 (HK2, the first rate limiting
enzyme of glycolysis) and pyruvate kinase M2 (PKM2, the final rate
limiting enzyme of glycolysis) [2]. Even in the presence of oxygen,
only a minimal part of pyruvate enters mitochondrial oxidative
phosphorylation (OXPHOS), mainly being converted to lactate; this
is due, at least in part, to the inactivation of pyruvate dehydrogenase
(PDH, which converts pyruvate into acetyl-CoA for the TCA cycle).
Lactate accumulates in the microenvironment and lowers pH, which
induces the expression of matrix metalloproteinases, mainly MMP-
2 and MMP-9 [3], while inhibiting the immune response [10], thus
favouring the metastatic potential. Aerobic glycolysis is less efficient
than OXPHOS in terms of energy supply: only four rather than
36 ATP moles per mole of glucose are produced. Energy supply
by OXPHOS in cancer cells may be supported by the glutamine
pathway, which also supports the biosynthesis of nucleotides, lipids
and glutathione [11]. The metabolic reprogramming of cancer cells by
means of aerobic glycolysis and glutaminolysis, appears to be closely
correlated with the genetic landscape of cancer cells themselves. KRAS
activating mutations, TP53 loss of function and MYC over expression,
frequently found in PDAC, regulate the Warburg’s effect [2,9]. It
has recently emerged that in tumours metabolic reprogramming is
not restricted to cancer cells: this phenomenon, also known as the
reverse Warburg effect, also involves stromal cells, such as cancer
associated fibroblasts (CAFs). In pseudo-hypoxyc conditions, CAFs
produce HIF-1 alpha, which promotes glycolysis with the production
of lactate that further reduces pH, and glutamate, which might fuel
cancer cells. This metabolic symbiosis also occurs between cancer cells
and cancer stem cells [3], and between cancer cells and immune cells
[12]. Intriguingly, elsewhere we observed a reverse Warburg effect in
myoblasts, the magnitude of lactate production being correlated with
PDAC-associated diabetes mellitus, suggesting that there is a link
between alterations in glucose metabolism at the cancer cell site and
in the whole organism [13].
Table 1
Table 1
PDAC prevalence impacts on the positive (PPV) and negative (NPV) predictive values of biomarkers.
Alterations in Glucose Metabolism in the Whole Organism
Diabetes mellitus as a cause of PDAC – evidence from
epidemiology
The association between diabetes mellitus and PDAC has been
recognised for over 100 years. Diabetes mellitus or reduced glucose
tolerance are diagnosed in the majority of PDAC patients, i.e. 50%
and 30-40% of cases, respectively [14]. This high association rate
was soon to give rise to the question as to whether diabetes mellitus
was the cause or effect of PDAC. Epidemiological and experimental
studies conducted to address this issue have led to the conclusion that
diabetes mellitus is a modest risk factor for PDAC, which is rather a
cause of diabetes mellitus. In 2005 in their meta-analysis, Huxley et
al. [15] analysed 17 case-control and 19 cohort studies and reported
pooled risk estimates for PDAC among diabetics of 1.94 (95% CI:
1.53-2.46) and 1.73 (95% CI: 1.59-1.88), respectively. On considering
studies investigating the association between PDAC and the duration
of pre-existing diabetes mellitus, the authors reported that the shorter
the duration of diabetes, the higher the risk of PDAC, the relative
risk being 2.05 (95% CI: 1.87-2.25) for a duration of four years or
less, 1.54 (95%CI: 1.31-1.81) for a duration above five and equal to
or less than 9 years, and 1.51 (95%CI: 1.16-1.96) for a longstanding
history of diabetes (>=10 years). The magnitude of the overall
increase in PDAC risk among diabetics and its decreasing trend
proportionate to the duration of diabetes has been confirmed in two
large pooled analyses of data from US and European case control
studies [16,17]. The increased PDAC risk associated with diabetes
mellitus appears to be independent from geographic location [18],
the risk estimates reported for eastern Asia being close to those of
Europe and US [adjusted hazard ratio: 1.54 (95% CI 1.39–1.71) in
Taiwan and 2.1 (95% CI 1.3–3.5) in Japan] [19,20]. Epidemiological
studies exploring the inverse relationship between the duration
of diabetes mellitus and PDAC risk agree that early onset diabetes
mellitus is probably a manifestation of PDAC rather than a preexisting
condition, while longstanding diabetes mellitus increases
the risk of PDAC [15,17,18,21,22]. However, consensus has not been
attained concerning the time limit distinguishing early onset from
longstanding diabetes mellitus. This time limit ranges from one to
four years across studies [15,18], although the majority of authors
agree with a duration of less than two years in defining the early
onset form [17,21,22]. The difficulty in defining this temporal limit
might also depend on the following: a) when PDAC develops on a
ground of pre-existing longstanding diabetes mellitus, the tumour
might progressively decompensate metabolic control and, in this
case, the switch time from non-neoplastic to neoplastic diabetes
might be extremely difficult to define; b) PDAC arises from precursor
lesions, such as pancreatic intraepithelial neoplasia (PanIN) or
intraductal papillary mucinous neoplasia (IPMN), its evolution and
progression following a stepwise model similar to that described for
the polyp adenocarcinoma sequence in colon cancer [23]. PDAC cells
accumulate a series of molecular aberrations. Some, namely KRAS,
CDKN2A, TP53 and SMAD4, are highly frequent across tumours
while others are sporadic, thus accounting for the extremely high
molecular heterogeneity of this tumour type [24,25]. The stepwise
accumulation of genetic defects during tumour progression might
underlie a stepwise worsening of tumour-associated diabetes mellitus
the progression of which might follow the evolution of the tumour,
its clinical manifestations occurring and diagnosis being made after
variable periods of mild hyperglycemia. This suggestion is borne out by
findings from the Mayo Clinic demonstrating a progressive increase
in blood glucose starting from 36 months prior to PDAC diagnosis
[26], thus supporting the proposal of screening asymptomatic
individuals using new-onset hyperglycemia and diabetes as a first
filter to detect those at a higher risk of PDAC. However this detection
calls for a reliable biomarker of pancreatic cancer-associated diabetes
mellitus [27].
Longstanding diabetes mellitus preceding PDAC is not a
single entity, but a highly complex and heterogeneous disease. The
heterogeneity is due to differences in comorbidities, medications,
compensation, and in some cases, exposure to diabetogenic and/or
carcinogenetic environmental factors. The metabolic syndrome, the
main comorbidity of diabetes mellitus to have been investigated, is
a complex of inter-related co-existing conditions, mainly insulin
resistance and diabetes, hypertension, dyslipidemia and obesity.
Epidemiological studies exploring the role of diabetes mellitus as a
risk factor for PDAC while taking other components of the metabolic
syndrome into account have confirmed that diabetes mellitus has
an independent role, but have also highlighted an increased body
mass index as a risk factor for PDAC [20,28]. Co-existent metabolic
syndrome components appear to enhance the risk of PDAC [29].
Available treatments for diabetes mellitus mainly include insulin
and oral antidiabetic drugs. Since it targets hepatocytes, adipocytes
and muscle cells, insulin is the main glucose-regulating hormone.
However, in other normal and transformed cell types this drug has
a relevant pro-proliferative and pro-survival effects through direct
or indirect effects, which include enhancing of insulin-like growth
factor I activity [6]. It is therefore more than likely that diabetes
mellitus increases PDAC risk because of hyperinsulinemia due
to insulin resistance and/or insulin therapy. However, although
some epidemiological studies support the assumption that insulin
treatment increases PDAC risk among diabetics two to fivefold
[16,22], other studies do not [30]. In a few epidemiological studies
focusing on patients with type 1 diabetes mellitus, invariably treated
with insulin, PDAC risk (RR: 2.0, 95% CI: 1.37-3.01) was similar to
that of patients with type 2 diabetes mellitus [31], thus suggesting
that insulin treatment in case of endogenous insulin deficiency has a
neutral effect on the risk of PDAC. The protective or carcinogenetic
effects of oral antidiabetics is still widely debated, even if treatment
with metformin appears to slightly decrease, while sulfonylureas
appear to increase, PDAC risk (30). A poor glycemic control in
diabetics might be regarded as a potentially relevant risk factor
for PDAC since chronic hyperglycemia can induce an increased
tumour cell proliferation and migration by enhancing the release of
the chemokine CXCL12 from stromal pancreatic stellate cells [32].
Although the specific aim of these studies was not to investigate
how poor glycemic control impacts on PDAC risk, in a population
of male smokers fasting glucose was shown to correlate with PDAC
risk [33], and in their dose response meta-analysis Liao et al. [34]
found a linear dose-response relation between fasting blood glucose
concentration and the rate of PDAC, every 0.56 mmol/L increase
in fasting blood glucose being associated with a 14% increase in the
rate of pancreatic cancer. Fasting glucose is, however, an imperfect
index of the glycemic control, glycated haemoglobin (HbA1c) being
a much more reliable tracer of long-term glucose exposure. The prediagnostic
levels of HbA1c are also positively correlated with PDAC
risk with a linear trend across increasing quartiles [35]. While in type
1 diabetes mellitus, insulin is lacking as a consequence of beta cell
destruction, in type 2 diabetes mellitus hyperinsulinemia frequently
occurs as a consequence of insulin resistance. Epidemiological studies
have been conducted to investigate whether or not insulin resistance
is the main predisposing factor for PDAC in diabetics. Stolzenberg-
Solomon et al. used the HOMA-IR formula {[fasting insulin (mIU/L)
x fasting glucose (mmol/L)]/22.5} to estimate insulin resistance and
their findings indicate that an increased HOMA-IR is a risk factor
for PDAC, this risk appearing to be greater when insulin resistance
is diagnosed more than ten years before cancer. Wolpin et al. [33]
used plasma proinsulin levels as a marker of peripheral insulin
resistance in their study, which confirmed that insulin resistance
was associated with an almost 2.5-fold increase in the risk of PDAC,
the risk being even greater (3.6-fold) when insulin resistance was
detected more than 10 years before cancer diagnosis [35]. In their
study, Michaud et al. provided further evidence of the role of insulin
resistance in increasing PDAC risk. These Authors found that
elevated post-prandial C-peptide, a fragment enzymatically released
from proinsulin in equimolar concentrations with insulin, enhances
the PDAC risk 4.24-fold [36]. Hyperinsulinemia should therefore be
considered one of the factors involved in PDAC carcinogenesis, in
line with its pro-survival and pro-metastatic effects [6,7,37].
Diabetes mellitus as a consequence of PDAC – clinical
and experimental evidence
The concept that early onset diabetes mellitus is a consequence
of PDAC is supported not only by the epidemiological observations
described in the previous section, but also by the clinical observation
that overt diabetes mellitus or reduced glucose tolerance is found
in more than 60% of patients at PDAC diagnosis [38-40], and that
diabetes mellitus ameliorates after surgical removal of the tumor
[41,42]. This last finding, furthermore, argues against the simple
hypothesis that pancreatic cancer-associated diabetes mellitus is due
to cancer-related islet cells destruction and supports the hypothesis
that PDAC induces diabetes through the release of diabetogenic
molecules, which might cause peripheral insulin resistance and/or
impaired insulin release from beta-cells, both of which have been
found in PDAC patients [43-45]. Another clinical issue concerns the
impact of diabetes mellitus on the prognosis of patients with PDAC.
Fasting glucose levels are positively associated with the overall cancerrelated
mortality [46], and survival after surgical removal of PDAC
was shown to be significantly affected by uncontrolled longstanding
severe hyperglycemia [47].
PDAC-associated diabetes mellitus and islet cell
dysfunction
Several research groups, ours included, have thrown light on
the pathophysiological mechanisms underlying PDAC-associated
diabetes mellitus, which is due to a complex interplay between tumor
and stromal-derived molecules, pancreatic endocrine cells and insulin
targeted peripheral tissues/organs. The key player molecules in this
process appear to be matrix metalloproteinases and the calcium
binding protein, S100A8, a 10 kDa protein belonging to the family of
S100 Ca2+ binding EF hand type proteins [48], which form homo- and
hetero-complexes, S100A9 being the main binding partner of S100A8.
The resulting S100A8/A9 heterodimer, also known as calprotectin,
is normally produced and released by polymorphonuclear and
mononuclear cells. The extracellular S100A8/A9 complex acts as a
ligand for different receptors, including RAGE and TLR4. In PDAC,
high S100A8 expression is found in the stromal compartment when
tumor cells express the tumor suppressor gene SMAD4, while, when
SMAD4 is lost, S100A8 is no longer expressed by stromal cells, but
by cancer cells [49]. This inverse relationship between SMAD4 and
S100A8 expression is further supported by findings made “in vitro”:
when pancreatic cancer cells without SMAD4 expression, but with
S100A8 expression are forced to express SMAD4 by transfection, they
lose their ability to express S100A8 [50]. The numerous biological
effects of S100A8 in PDAC include epithelial to mesenchymal
transition and the SMAD4-dependent inhibition, or activation, of
pro-survival and pro-metastatic intracellular signalling pathways
such as NF-κB, AKT and mTOR [51]. But S100A8 can also induce the
expression of MMP8 and of MMP9 by inflammatory mononuclear
cells [40]. Intriguingly, S100A8 is a substrate for metalloproteinases,
which catalyse the release of the N-terminal 14 aminoacid peptide
from the entire molecule; this, in turn, alters intracellular calcium
fluxes and renders beta-cells insensitive to glucose stimulation,
leading to a reduced insulin secretion, a potential cause of PDACassociated
diabetes mellitus [40,50]. It has also been demonstrated that
glucose stimulated insulin secretion is reduced by adrenomedullin,
a pluripotent hormone overexpressed in PDAC [52]. This hormone
shares homology with amylin or islet amyloid polypeptide (IAPP),
which is co-secreted with insulin by beta-cells at a constant ratio in
the normal pancreas, while in the presence of PDAC-conditioned
media, the IAPP/insulin molar ratio increases [53]. IAPP has also
been found to reduce arginine stimulated insulin, glucagon and
somatostatin release, and might play a part in determining islet
dysfunction in PDAC patients [43]. It has been observed that betacell
proliferation impairment with apoptosis induction is dependent
on the enzyme overexpressed in PDAC, vanin 1 (VNN1), which
hydrolyzes pantetheine and produces Vitamin B5 and cysteamine
[54].
PDAC-associated diabetes mellitus and impaired glucose
metabolism in peripheral tissues
Muscle, liver and fat cells are the principal targets of insulin and
glucagon, the two main hormones regulating glucose homeostasis.
By binding its receptor, insulin favours glucose entry and storage
as glycogen in target cells, while glucagon, the counter regulatory
hormone, has the opposite effect, inducing glyogenolysis and glucose
extrusion. The Insulin Receptor (IR), a tetrameric structure made up
of two alpha and two beta subunits, binds insulin through its alpha
chains and triggers intracellular signalling by the tyrosine kinase
activity of its beta chains. The analysis of the IR signalling cascade
in skeletal muscle tissue from PDAC patients has demonstrated that
insulin binding, tirosin kinase activity of the IR and the content of
the insulin receptor binding substrate 1 (IRS1) did not change with
respect to control tissue samples, while the phosphatidylinositol
3-kinase (PI3-K) activity, glucose transport and glycogen synthase
activity were impaired in pancreatic cancer patients [43,45]. We
demonstrated that pancreatic cancer cells impair glycolysis of
both muscle and liver cells through the activity of a low molecular
weight tumor product that favours the metabolic shift of glucose
from oxidative phosphorylation to aerobic glycolysis (lactate
accumulation) and, in liver cells, to triglyceride biosynthesis through
the accumulation of the intermediate D-1,2-diacylglycerol [13,55].
Biomarkers of PDAC-associated diabetes mellitus
Experimental studies have been performed to verify the
pathophysiology of PDAC-associated diabetes mellitus and to
identify any potential tumor derived molecule involved in causing
islet cell and or peripheral glucose metabolic alterations, the end
point being to identify a biomarker able to distinguish between the
presence or absence of PDAC in patients with new onset diabetes
mellitus. When exploring emerging biomarkers in this setting, a
careful consideration should be made of the disease prevalence, since
it significantly impacts on positive and negative predictive values for
any given combination of sensitivity and specificity of the studied
biomarker. The prevalence of PDAC varies between unselected
and selected populations: in the whole asymptomatic population,
its prevalence appears almost equal to its incidence (13/100000 per
year, 0.013%) [56], being 230 fold lower than that reported among
the selected population of asymptomatic patients with diabetes
mellitus (almost 3%) [57]. Based on prevalence, the positive and
negative predictive values of a biomarker with a given sensitivity and
specificity are reported in Table 1. PDAC prevalence impacts on the
positive (PPV) and negative (NPV) predictive values of biomarkers.
PDAC prevalence in the general population (0.00013) and among
patients with new onset diabetes mellitus (0.03) were considered to
calculate PPV and NPV of biomarkers with 90, 95 and 99% sensitivity
and specificity. Negative predictive value (NPV): Sensitivity
x (1-Prevalence)/Specificity (1-Prevalence) + (1-Sensitivity) x
prevalence. Positive predictive value (PPV): Sensitivity x Prevalence/
Sensitivity x Prevalence + (1-Specificity) x (1-Prevalence) Clearly, in
the unselected general population, positive findings of a biomarker
with a very high sensitivity and specificity (99%) are due to PDAC in
about 1/100 cases, thus supporting the notion that PDAC screening
of the general population is not recommended. By contrast, in
selected patients, a biomarker with a sensitivity and specificity of
95% could allow the identification of a potentially relevant number
of cases, i.e. 37 PDAC out of 100 patients with positive results. It is
also clear that sensitivity and specificity should be at least 90% to limit
over-diagnosis and over-use of invasive diagnostic procedures. The
biomarkers suggested for diagnosing PDAC in the selected population
of patients with new-onset diabetes mellitus, include the established
CA 19-9 marker as well as emerging new potential biomarkers, such
as proteins, peptides, microRNA and mRNA, the detailed description
of which also in terms of sensitivity and specificity is reported in
Table 2. Overall none of the proposed biomarkers is superior to the
established marker CA 19-9 in terms of sensitivity and specificity
for PDAC diagnosis in patients with diabetes mellitus. Moreover,
since none attain a sensitivity and specificity of at least 90%, their use
cannot be supported in clinical practice.
In conclusion, the efforts made to translate in the clinical practice
new potential biomarkers of PDAC-associated diabetes mellitus
have failed, due to low sensitivity and specificity. Therefore the
identification and clinical validation of new biomarkers remains a
challenge for future studies.
Table 2
Table 2
Proposed biomarkers for the diagnosis of PDAC in the selected population of patients with diabetes mellitus.
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