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Cancer Cell

Review

Employing Metabolism to Improvethe Diagnosis and Treatment of Pancreatic Cancer

Christopher J. Halbrook1 and Costas A. Lyssiotis1,2,*1Department of Molecular and Integrative Physiology2Department of Internal Medicine, Division of GastroenterologyUniversity of Michigan, Ann Arbor, MI 48109, USA*Correspondence: [email protected]://dx.doi.org/10.1016/j.ccell.2016.12.006

Pancreatic ductal adenocarcinoma is on pace to become the second leading cause of cancer-related death.The highmortality rate results from a lack of methods for early detection and the inability to successfully treatpatients once diagnosed. Pancreatic cancer cells have extensively reprogrammed metabolism, which isdriven by oncogene-mediated cell-autonomous pathways, the unique physiology of the tumor microenviron-ment, and interactionswith non-cancer cells. In this review, we discuss how recent efforts delineating rewiredmetabolic networks in pancreatic cancer have revealed new in-roads to develop detection and treatmentstrategies for this dreadful disease.

Pancreatic ductal adenocarcinoma (PDAC) is the most common

form of pancreatic cancer and the most deadly major cancer,

with a 5-year survival rate of 8% (Siegel et al., 2016). The reasons

for this high mortality rate can be ascribed largely to late presen-

tation of disease when patients are no longer candidates for

surgical resection (Hidalgo, 2010). Driving this challenge is the

anatomically inaccessible location of the pancreas, which pre-

vents routine examination, and the lack of clinically informative

early diagnostic symptoms and biomarkers (Chan et al., 2013).

Furthermore, pancreatic tumorigenesis and progression occurs

undetected in a process thought to take upward of two decades

(Yachida et al., 2010), while PDAC cells disseminate readily, re-

sulting in early metastasis (Rhim et al., 2012). As a consequence

of these collective characteristics, patients are often unaware of

their disease until very late in its course.

Paralleling the diagnostic shortcomings, efficacious therapeu-

tic options are limited. While some progress in developing com-

bination therapies has been achieved in the recent past (Conroy

et al., 2010; Ryan et al., 2014; Von Hoff et al., 2013), these are

based on standard cytotoxic chemotherapy backbones that

can be difficult to tolerate, while only modestly extending sur-

vival. Moreover, targeted therapies, which can minimize harmful

side effects while providing meaningful and durable responses,

have not made a real impact on this disease (Moore et al.,

2007). Given this information, it is clear that new strategies are

required to develop effective treatment options.

Cancer cells are defined by their ability to survive and prolifer-

ate in non-native settings under nutrient and oxygen deprivation

and immune cell attack (Hanahan and Weinberg, 2011). Meta-

bolic rewiring is central to these processes, and treating cancer

by targeting the unique ways malignant cells take in and use

nutrients has emerged as a promising therapeutic approach

(Vander Heiden, 2011). Such a strategy has considerable poten-

tial in PDAC, as pancreatic tumors are under significant physical,

oxidative, and inflammatory stress while the nutrients needed to

combat these stressors are sparse. Accordingly, major headway

has been made in recent years to understand metabolic adapta-

tions in pancreatic cancer cells that facilitate survival under these

conditions (Chini et al., 2014; Commisso et al., 2013; Guillau-

mond et al., 2013, 2015; Perera et al., 2015; Son et al., 2013;

Ying et al., 2012), and efforts are underway to utilize this informa-

tion to design metabolism-targeted diagnostic tools and thera-

pies. These studies have revealed a high level of metabolic

heterogeneity in pancreatic cancer cells (Baek et al., 2014;

Boudreau et al., 2016; Daemen et al., 2015; Sancho et al.,

2015; Viale et al., 2014), mirroring the more widely described ge-

netic heterogeneity in pancreatic cancer (Bailey et al., 2016; Col-

lisson et al., 2011; Moffitt et al., 2015).

In this review, we provide a detailed overview of how the

unique physiology of pancreatic tumors creates a hostile and

nutrient-poor microenvironment, and the biochemical andmeta-

bolic adaptations that occur within and among heterogeneous

cell types of a pancreatic tumor to facilitate growth. We discuss

how these features enable therapeutic resistance and how a

detailed understanding of metabolic rearrangements will provide

new actionable drug targets, and potentially improve imaging

methods to detect and monitor disease.

A New ‘‘Addiction’’ in MetabolismOncogene addiction defines the phenomenon by which cancer

cells become dependent on the activity of an oncogene for sur-

vival and proliferation (Weinstein and Joe, 2008). Inhibition of the

addicting oncogene directly, or through downstream mediators,

is lethal to the addicted cell. Implicit in this definition is that

normal cells can tolerate inhibition of oncogenic activity without

obvious consequence. This principle has led to development of

several kinase-targeted cancer therapies (Gross et al., 2015). In

addition, it has also given rise to the notion that discrete pro-

cesses can be addicting (Luo et al., 2009), such as dependence

on heat shock factor 1 under proteotoxic stress (Dai et al., 2012)

or poly(ADP-ribose) polymerase activity in the context of BRCA

deficiency (Bryant et al., 2005; Farmer et al., 2005). In this

same vein, certain cancer cells may become dependent on

defined metabolic pathways, activities, or processes: a type of

non-oncogene addiction defined as a ‘‘metabolic addiction.’’

Importantly, these metabolic addictions can be tissue specific

Cancer Cell 31, January 9, 2017 ª 2017 Elsevier Inc. 5

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A

B

C

Figure 1. Cancer-Stromal Interactions Shape the Pathophysiologyof PDAC(A) Physical changes. Physical changes in the tumor microenvironment aredriven by cancer cell-mediated activation of fibroblasts, which produce a stiffhyaluronic acid (HA)-richmatrix that leads to increased interstitial pressure andvasculature collapse, limiting nutrient and chemotherapy availability. The stiffmatrix itself also promotes tumor aggression through physical stress exertedon the cancer cells, yet acts to restrain progression (Jacobetz et al., 2013;Laklai et al., 2016; Olive et al., 2009; Ozdemir et al., 2014; Provenzano et al.,2012; Rhim et al., 2014).(B) Immune suppression. The epithelial and stromal compartments cooperateto produce a tumormicroenvironment that is strongly immunosuppressive andinhibits T cell clearance of cancer cells (Bayne et al., 2012; Feig et al., 2013;Mathew et al., 2016; Pylayeva-Gupta et al., 2012; Zhang et al., 2017).(C) Crosstalk mechanisms. Limitation of nutrient availability is overcome inpart by exchange of growth factors, cytokines, and metabolites betweenthe stromal and epithelial compartments (Mathew et al., 2014; McAllisteret al., 2014; Pylayeva-Gupta et al., 2016; Sousa et al., 2016; Waghrayet al., 2016).

6 Cancer Cell 31, January 9, 2017

Cancer Cell

Review

in context, due to both genetic and environmental factors

(Mayers et al., 2016; Yuneva et al., 2012). Such addictions can

present therapeutic vulnerabilities, and several recent studies

in pancreatic cancer have provided concrete evidence of these

addictions and their therapeutic utility.

Pancreatic Tumor PhysiologyThe pancreatic tumor microenvironment is a source of both

intense physical and oxidative stress. Interstitial pressures in

pancreatic tumors can exceed ten times that observed in a

normal pancreas (Provenzano et al., 2012). These tumors have

low carcinoma cellularity, and the tumor is largely composed

of a dense fibrotic stroma, populated mainly by fibroblasts and

immune cells (Chu et al., 2007). When activated, fibroblasts de-

posit extensive extracellular matrix proteins including those con-

taining a high concentration of the fluid-rich glycosaminoglycan

hyaluronan (Jacobetz et al., 2013; Provenzano et al., 2012), a

major contributor to the elevated interstitial pressure (Proven-

zano et al., 2012). This intense pressure results in vascular

collapse and tumor hypoperfusion, which limits oxygen and

nutrient availability (Kamphorst et al., 2015; Koong et al., 2000)

and hinders drug delivery to cancer cells (Olive et al., 2009).

Importantly, the lack of oxygen and nutrients impose major

challenges for cancer cells to maintain redox and metabolic ho-

meostasis, as well as support macromolecular biosynthesis. To

sustain tumor viability under these circumstances, stromal com-

ponents create a metabolically supportive niche for the cancer

cells; however, the dense fibrotic stroma has also been demon-

strated to restrain cancer progression (Ozdemir et al., 2014;

Rhim et al., 2014). The mechanisms of stromal interaction can

be grouped into three categories: physical changes, immune

suppression, and crosstalk mechanisms. These concepts are

described in detail in Figure 1.

Cell-Autonomous Reprogramming of IntermediaryMetabolismNutrients in the form of carbohydrates, amino acids, and lipids

are used by cells tomaintain energy balance, assist in detoxifica-

tion, and support biosynthesis. The pathways that perform this

function are collectively referred to as intermediary metabolism.

Pancreatic cancer cells rewire intermediary metabolism to sup-

port different energetic and biosynthetic demands compared

with normal cells. Much of what has been described for this re-

programming is driven by mutations in the oncogene KRAS,

which is nearly universally mutated in PDAC (Biankin et al.,

2012). Recent studies have begun to unravel how these path-

ways are reprogrammed and the functional relevance for cancer

cells.

Glucose Metabolism

Glucose is a principle metabolic and biosynthetic nutrient. When

used as a fuel by normal cells, it is completely oxidized to carbon

dioxide in the mitochondria to produce ATP. Proliferating cells

such as cancer cells also use glucose to make ATP, but propor-

tionally more glucose carbon is used for biosynthesis of ribose,

glycosylation precursors, amino acids, and lipids (Lunt and Van-

der Heiden, 2011) (Figure 2). The hypovascular nature of the

pancreatic tumor niche imposes a bottleneck on this increased

demand for glucose carbon. To compensate, oncogenic Kras

signaling promotes extracellular glucose avidity and capture

Figure 2. Metabolic Pathways in PDACPancreatic cancer cells scavenge the limitedextracellular glucose available in the pancreatictumor microenvironment through oncogenic Kras-mediated elevation of the glucose transporterGLUT1. In addition, Krasmodulates the expressionof other glycolytic enzymes, resulting in elevatedglycolytic flux. The NAD+ necessary to maintainglycolysis is regenerated by the conversion of py-ruvate to lactate via LDHA. Glucose also serves asan important source of carbon for anabolic meta-bolism in the pentose phosphate pathway and thehexosamine biosynthetic pathway. PDAC cells relyon a Kras-rewired glutamine (Gln) metabolicpathway for redox balance. Gln is converted toglutamate (Glu) then aspartate (Asp) in the mito-chondria, after which it is shuttled to the cytosoland utilized through a series of reactions togenerate NADPH. This maintains the reducedglutathione (GSH) levels required for redox ho-meostasis. Metabolites and metabolic pathwaysutilizing Gln carbon are presented in blue. Onlythose enzymes specifically discussed in the textare presented. Ala, alanine; aKG, alpha-ketoglu-tarate; Cit, citrate; Cys, cysteine; Fum, fumarate;Gly, glycine; GSSH, oxidized glutathione; Iso, iso-citrate; Lac, lactate; Mal, malate; OAA, oxaloaceticacid; Pyr, pyruvate; R5P, ribose 5-phosphate; Suc,succinate; UDP-GlcNAC, uridine diphosphate N-acetylglucosamine.

Cancer Cell

Review

via upregulation of the glucose transporter GLUT1 and hexoki-

nase (HK), respectively (Ying et al., 2012). This glucose is utilized

in glycolysis and non-mitochondrial biosynthetic reactions.

Downstream of HK, mutant Kras also activates the expression

of several additional enzymes in glycolysis (Gaglio et al., 2011;

Ying et al., 2012). Furthermore, hypoxia and other mechanisms

also activate glycolytic gene expression (Baek et al., 2014;

Chaika et al., 2012; Cui et al., 2014; Shi et al., 2014) and coordi-

nate with mutant Kras to maintain cytosolic ATP. In contrast,

mitochondrial metabolism and ATP generation is predominantly

fueled by glutamine (Gln) carbon in cultured PDAC cells (Son

et al., 2013; Ying et al., 2012). It is important to note that recent

evidence from lung cancer studies have demonstrated that the

source of carbon used to fuel mitochondrial metabolism is

context dependent. In vitro, Gln is the predominant carbon

source for mitochondrial metabolism, whereas, in vivo, glucose

carbon contributes to a greater degree (Davidson et al., 2016;

Hensley et al., 2016; Schug et al., 2016).

Glucose carbon also plays important roles in anabolic path-

ways. Oncogenic Kras diverts glucose flux into the hexosamine

biosynthetic pathway (HBP) (Ying et al., 2012) to enhance the

generation of precursor moieties required for protein glycosyla-

tion (Ma et al., 2013; Ying et al., 2012) (Figure 2). This is

accomplished both through increased glycolytic flux and tran-

scriptional upregulation of the rate limiting enzyme in the HBP,

glutamine fructose 6-phosphate transamidase 1 (GFPT1) (Ying

et al., 2012). HBP flux can also be increased through hypoxia-

mediated induction of the GFPT2 isoform

(Guillaumond et al., 2013).

Oncogenic Kras activity also leads to

enhanced entry of glucose carbon into

the pentose phosphate pathway (PPP)

(Figure 2). The PPP is the predominant pathway by which prolif-

erating cells make ribose 5-phosphate (R5P) for DNA and RNA

biosynthesis. This pathway is traditionally subdivided into

two branches: oxidative and non-oxidative. Kras-transformed

pancreatic cancer cells activate and become dependent on

non-oxidative PPP. Knock down of Kras-regulated enzymes

that govern non-oxidative PPP flux in this context is strongly

growth inhibitory (Ying et al., 2012). Since most normal cells

generate R5P through the oxidative arm of the PPP, this differen-

tial dependence on the non-oxidative PPP represents a potential

metabolic vulnerability in PDAC (Boros et al., 1997).

Glutamine Metabolism

Gln is a non-essential amino acid (NEAA) and the most abundant

amino acid in circulation (Hensley et al., 2013). In addition to its

role in protein biosynthesis, Gln is a major source of carbon

and nitrogen for proliferating cells. Accordingly, Gln avidity is a

feature of many cancer types (DeBerardinis and Cheng, 2010;

Wise and Thompson, 2010). We recently demonstrated that

PDAC cells grown in culture are strictly dependent on Gln for

proliferation, and that Gln is used tomaintain redox balance (Lys-

siotis et al., 2013; Son et al., 2013). Gln serves two functions in

this regard. First Gln-derived glutamate (Glu) is used for gluta-

thione (GSH) biosynthesis (Figure 2), a principle component in

cellular redox balance (DeBerardinis et al., 2007). Secondly,

Gln facilitates generation of reducing equivalents in the form

of NADPH, a high-energy molecule involved in biosynthesis

and redox balance. This latter pathway is driven by oncogenic

Cancer Cell 31, January 9, 2017 7

Figure 3. Methods of Nutrient AcquisitionUtilized by PDACPancreatic cancer cells engage in metaboliccrosstalk with stromal cells by multiple avenues.Growth factors (GF) released from the PDAC cellscan metabolically reprogram fibroblasts, whichrespond by the release of different GFs capable ofreciprocal reprogramming of the epithelial cells.PDAC cells also induce autophagy in pancreaticstellate cells, stimulating the release of growth-promoting alanine (Ala). Metabolite exchange alsooccurs among cancer cells, as PDAC cells inhypoxic environments release lactate (Lac) whichfuels proliferation in normoxic cancer cells.Pancreatic cancer cells are capable of utilizing re-cycling pathways and engage in multiple mecha-nisms of scavenging extracellular nutrient sources,including non-specific macropinocytosis and lipiduptake, to obtain nutrients in the austere pancre-atic tumor microenvironment.

Cancer Cell

Review

Kras. Gln-derived carbon is converted into aspartate (Asp)

through a series of mitochondrial reactions that utilize the

mitochondrial Asp aminotransferase (GOT2). Gln-derived Asp

is then released into the cytoplasm where it is acted on by

cytosolic Asp aminotransferase (GOT1) and, finally, cytoplasmic

malic enzyme 1 (ME1), which yields NADPH-reducing equiva-

lents (Figure 2). This pathway is not used in the normal cells

examined andmay represent a promisingmetabolic vulnerability

in PDAC.

In addition to activation of the GOT2-GOT1-ME1 pathway,

oncogenic Kras signaling also initiates a nuclear factor

(erythroid-derived 2)-like 2 (Nrf2)-dependent reactive oxygen

species (ROS) detoxification program (DeNicola et al., 2011).

The Nrf2 transcriptional response is an inducible system acti-

vated by redox stress; however, mutant Kras constitutively

activates this antioxidant program to suppresses ROS and pro-

mote pancreatic tumorigenesis and proliferation (Chio et al.,

2016). Nrf2 has also been shown to redirect glucose and Gln

into anabolic and antioxidant pathways (DeNicola et al., 2015;

Mitsuishi et al., 2012). Nrf2 regulates the expression of ME1,

which provides a direct link between mutant Kras and the

ME1-dependent redox pathway described above (Son et al.,

2013) (Figure 2). Nrf2 also activates GSH biosynthesis (Lien

et al., 2016; Mitsuishi et al., 2012). Given that a central function

of NADPH in redox balance is to recycle GSH through reduction

of oxidized GSH, these results illustrate that activities down-

stream of mutant Kras, including Nrf2, ME1, and GOT1, collabo-

rate to rewire Gln metabolism to enhance cytoprotection from

redox imbalance.

Nutrient AcquisitionPancreatic tumors are hypovascular and thus in a state of con-

stant nutrient deprivation (Commisso et al., 2013; Kamphorst

et al., 2015). As such, they must find alternative sources of nutri-

ents needed to survive and grow. To address this shortfall,


pancreatic cancer cells activate pathways

that enable (1) recycling of intracellular

nutrients, (2) access to non-traditional

extracellular nutrients through scavenging

of extracellular space, and (3) engage in

metabolic crosstalk with non-malignant cells in the tumor micro-

environment (Figure 3).

Recycling Pathways

Pancreatic cancers are known to have elevated basal macroau-

tophagy (Yang et al., 2011), also known more generally as

autophagy. In healthy cells, autophagy is engaged by cellular

stress to clear damaged structures (e.g., protein aggregates or

dysfunctional organelles) or by starvation, which is regulated

by signaling of the mechanistic target of rapamycin (Neufeld,

2010; White, 2012; Yang and Klionsky, 2010). Once catabolized

by lysosomes, these digested biomolecules become available to

the cell as nutrients (Figure 3).

During PDAC progression, autophagy plays important but

opposing roles (Kimmelman, 2011). In tumor initiation, auto-

phagy is antitumorigenic owing to its role in cellular quality con-

trol. In established tumors, autophagy can support survival and

energy balance in hypoxic, nutrient-poor regions of the tumor.

Indeed, constitutive engagement of autophagy in pancreatic

cancers is nearly ubiquitous (Yang et al., 2011), even in cells

grown in culture under nutrient-replete conditions, illustrating

that this process is, at least in part, cell autonomous. More

importantly, inhibition of autophagy causes proliferative defects

across numerous pancreatic cancer models. The role of the tu-

mor suppressor p53 in this response has been debated and likely

depends on contextual factors (Rosenfeldt et al., 2013; Yang

et al., 2014). Recently, it has been shown that autophagy depen-

dence in PDAC is part of a larger transcriptional program driven

by microphthalmia/transcription factor E (MiT/TFE) proteins,

which also activate lysosomal biogenesis and nutrient-scav-

enging pathways. MiT/TFE proteins are required for the mainte-

nance of amino acid pools, and knockdown of these genes is

strongly growth inhibitory (Perera et al., 2015).

Inhibition of autophagy in PDAC leads to decreasedmitochon-

drial oxygen consumption and increased dependence on glycol-

ysis to make ATP (Yang et al., 2011). It also leads to a disrupted

Cancer Cell

Review

redox state that contributes to DNA damage. These alterations

can be reversed, in part by supplementation of autophagy-

impaired cells with antioxidants or TCA cycle intermediates

(e.g., pyruvate or Gln) (Strohecker et al., 2013; Yang et al.,

2011). Pancreatic cancers use autophagy to obtain amino acids

from catabolized proteins as biosynthetic substrates to fuel the

TCA cycle, oxidative phosphorylation (OXPHOS), and ATP

biosynthesis (Figure 3). It remains to be determined why cells

grown in high concentrations of glucose, lipids, and amino acids

would be ‘‘nutritionally deprived’’ and require autophagy-derived

substrates to fuel mitochondrial metabolism, and many labora-

tories are actively investigating this paradox.

Nucleotide-salvage pathways are another way intracellular

macromolecules can be recycled for later use. DNA/RNA can

be recycled and used to form new DNA/RNA, and nucleotides

that serve enzymatic functions in metabolic processes (e.g.,

ATP, NAD+) can be recycled rather than degraded (Figure 3).

The importance of nucleotide salvage in pancreatic cancer

cells was demonstrated by the strong inhibition of growth

through both genetic and pharmacological blockade of

nicotinamide phosphoribosyltransferase, a key enzyme in the

NAD+ salvage pathway (Chini et al., 2014; Lyssiotis and Cantley,

2014).

Scavenging Pathways

While recycling pathways play an important role in survival, cell

growth requires nutrient input to generate biomass. Mutant

Ras expression in PDAC cells has been demonstrated to induce

membrane ruffling, which leads to formation of large vacuoles,

known asmacropinosomes, which non-specifically engulf extra-

cellular space. Macropinosomes are then endocytosed and

fused with lysosomes to break down and release their contents

(Bar-Sagi and Feramisco, 1986). Cells utilize this process to

obtain proteins, lipids, and nucleotides. Following lysosomal

degradation, the constituent precursor molecules become avail-

able for macromolecular biosynthesis. Mutant Kras-expressing

PDAC cells use macropinocytosis to scavenge protein sources,

such as albumin, to survive nutrient deprivation by refilling amino

acid pools and fueling mitochondrial metabolism (Commisso

et al., 2013; Kamphorst et al., 2015; Palm et al., 2015) (Figure 3).

Inhibition of macropinocytosis blocks the ability of these cells to

obtain amino acids from protein and slows growth of orthotopic

PDAC tumors (Commisso et al., 2013).

In addition to proteins and amino acids, cancer cells require a

continuous supply of lipids for cell signaling, metabolism, and

proliferation. Lipid pools aremaintained through de novo synthe-

sis or extracellular uptake. In normoxia, themajority of fatty acids

are derived from de novo synthesis, whereas hypoxia or onco-

genic Ras mutation shifts this equilibrium to the import of fatty

acids, rendering these cells insensitive to inhibitors of fatty

acid production (Kamphorst et al., 2013). Similarly, perturbation

of the import of cholesterol-rich, low-density lipoproteins (LDLs)

through LDL receptor-mediated endocytosis has antiprolifera-

tive effects on PDAC cells, and this acts synergistically with

chemotherapy (Guillaumond et al., 2015). These studies, com-

bined with the observation that pancreatic tumors are lipid

poor relative to surrounding normal tissue (Ma et al., 2011; Ya-

bushita et al., 2013; Zhang et al., 2013), suggest that targeting

mechanisms of lipid import may prove to be attractive metabolic

vulnerabilities.

Metabolic Crosstalk

Intra-tumoral heterogeneity at the cellular and genetic level is

well documented (Bailey et al., 2014, 2016; Collisson et al.,

2011; Delgiorno et al., 2014; Li et al., 2007; Waddell et al.,

2015; Westphalen et al., 2016). While less appreciated, meta-

bolic heterogeneity also exists among cancer cells within the

same tumor (Birsoy et al., 2014; Daemen et al., 2015); such as

differences among quiescent, rapidly dividing, and invasive pop-

ulations (LeBleu et al., 2014; Sancho et al., 2015; Viale et al.,

2014). Additional metabolic heterogeneity also exists due to

environmental factors within a tumor, such as local nutrient

and oxygen concentrations.

Accordingly, metabolically distinct cell populations have

evolved crossfeeding mechanisms in which metabolites from

one population can be used to fuel growth of another. For

example, hypoxic regions of pancreatic tumors express high

levels of the lactate exporter monocarboxylate transporter 4

(MCT4), whereas normoxic regions surrounding the hypoxic re-

gions overexpress the lactate importer MCT1 (Guillaumond

et al., 2013). Lactate secreted by cancer cells grown in hypoxia

is actively taken up by cancer cells grown in normoxia, and

this increases their proliferation (Guillaumond et al., 2013)

(Figure 3). Lactate secretion also has profound effects via epithe-

lial-stromal crosstalk, as lactate secreted from PDAC cells con-

tributes to polarization of immunosuppressive macrophages

(Hutcheson et al., 2016).

In addition to the ability of cancer cells to share metabolites,

growing evidence demonstrates that stromal cells impact meta-

bolism of cancer cells. In primary tumors, cancer cells are out-

numbered by stromal cells, which include immune cells and

fibroblasts (Figure 1). Numerous studies have illustrated the

role of growth factor and cytokine exchange between cancer

cells and surrounding stromal cells (Baumgart et al., 2014; Gun-

derson et al., 2016; Ijichi et al., 2011; Incio et al., 2016; Lee et al.,

2016; Lesina et al., 2011; Mathew et al., 2014, 2016; Pylayeva-

Gupta et al., 2016; Sherman et al., 2014; Waghray et al., 2016).

More recently, evidence has also emerged that mutant Kras-

induced growth factors mediate reciprocal stromal-epithelial

crosstalk, which drives PDAC metabolic reprogramming,

including an increase in mitochondrial membrane potential and

respiratory capacity (Tape et al., 2016).

Stromal-derived metabolites also provide nutrients to fuel

biosynthesis in cancer cells. We recently found that an abun-

dant stromal cell type found in pancreatic tumors, pancreatic

stellate cells (PSCs), release NEAAs in response to culture

with PDAC cells (Sousa et al., 2016). Among these NEAAs,

PDAC cells avidly consume PSC-derived alanine (Ala) and use

it to fuel diverse biosynthetic processes, including mitochondrial

metabolism, as well as fatty acid and amino acid biosynthesis.

More striking was the observation that Ala-derived carbon

out-competed glucose and Gln carbon for incorporation into

mitochondrial metabolism and thereby enabled these mole-

cules to be used for other biosynthetic functions. Autophagy

in the PSC compartment was required for Ala release, as inhibi-

tion of autophagy machinery ablated the ability of PSCs to

excrete Ala. Together with the observation that cancer cells

stimulated autophagy and Ala release, these results provided

evidence for a new intra-tumoral metabolic crosstalk pathway

(Figure 3).


Cancer Cell

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The precisemechanism bywhich Ala is released from the stro-

mal compartment is unclear. One source by which PDAC cells

have been demonstrated to obtain PSC-derived Ala is through

uptake of exosomes released by PSCs (Zhao et al., 2016). Unlike

the Ala transfermechanism described above (Sousa et al., 2016),

exosome-mediated transfer is not specific to Ala, where

numerous amino acids are exosomal cargo. In contrast to mac-

ropinocytosis, which has been exclusively described in PDAC

cells bearing KRAS mutations, metabolic reprograming via

uptake of exosomal metabolites was found to be independent

of KRAS mutational status (Zhao et al., 2016). Collectively, the

description of these new intra-tumoral metabolic crosstalk

pathways further illustrates the proficiency of pancreatic cancer

cells to adopt unorthodox methods to thrive in a challenging

environment.

Therapeutic OpportunitiesDevelopment of successful new treatmentmodalities for pancre-

atic cancer has been limited since the establishment of gemcita-

bine as standard of care two decades ago. Nanoparticle

albumin-bound paclitaxel (nab-paclitaxel) represents one such

success (Von Hoff et al., 2011, 2013), and it is tempting to spec-

ulate that this may owe its success to rewired metabolism of

PDAC cells. Nab-paclitaxel is a formulation of the chemotherapy

paclitaxel, which is stabilized through binding to albumin. Given

that PDAC cells readily scavenge serum albumin by macropino-

cytosis, it is possible that the albumin-coated formulation of

paclitaxel is delivered disproportionally to PDAC cells (Com-

misso et al., 2013; Kamphorst et al., 2015), enhancing the

therapeutic index. While a metabolic role for the efficacy of

nab-paclitaxel may have been fortuitous, there are currently

several other strategies underway to directly target PDAC by ex-

ploiting their altered metabolism.

Inhibitors of Intermediary Metabolism

Many PDAC cells are dependent on glucose flux through glycol-

ysis to maintain bioenergetic balance, whereas normal cells are

more reliant on mitochondrial ATP generation. The final step of

glycolysis, conversion of pyruvate to lactate by lactate dehydro-

genase (LDH), is required to regenerate NAD+ and thus to

facilitate continued glycolysis (Figure 2). This makes LDH an

attractive target for pancreatic cancer, as blocking lactate pro-

duction inhibits glycolysis and results in redox imbalance. In

line with this, FX11, a small-molecule inhibitor of LDH (Le et al.,

2010), reduces growth and induces apoptosis in patient-derived

pancreatic cancer xenografts (Rajeshkumar et al., 2015).

Interestingly, the efficacy of FX11was linked to p53 function, in

which wild-type p53 function coincided with a lack of response

to FX11 treatment. The regulation of metabolism by p53 is an

important and complex topic (Berkers et al., 2013) that has not

been examined specifically in pancreatic cancer. However, as

p53 activation has been shown to be important for cell survival

in the face of glucose deprivation (Jones et al., 2005), it is

possible that the p53 statusmay be predictive of PDAC response

to treatments which modulate glucose metabolism. Variable re-

sponses of PDAC cells to LDH inhibition were also noted with the

LDH inhibitor, GNE-140 (Boudreau et al., 2016). In this study,

only a small subset of PDAC lines responded robustly to GNE-

140 treatment, while the rest were able to compensate through

increased OXPHOS.


In contrast to bulk tumor, pancreatic-tumor-initiating cells

(Sancho et al., 2015) and cells that can survive inhibition of onco-

genic signaling (Viale et al., 2014) depend on mitochondrial

OXPHOS (Viale et al., 2015). As a result, these cells are very sen-

sitive to treatment with the OXPHOS inhibitors metformin or oli-

gomycin (Sancho et al., 2015; Viale et al., 2014). Tumor-initiating

cells have also been reported to be responsible for disease

relapse after debulking chemotherapy and radiation. Therefore,

methods that target metabolism of both oncogene/glycolysis-

dependent tumor bulk (e.g., Kras inhibition) and OXPHOS-

dependent resistant cells (e.g., oligomycin) lead to more

effective and durable therapeutic responses in murine tumor

models (Viale et al., 2014). As a result, inhibitors of OXPHOS

are set to be explored in clinical trials for patients with pancreatic

and other cancers (Protopopova et al., 2016). These data have

also provided a rationale to reconsider existing literature and util-

ity of the OXPHOS inhibitor metformin.

Metformin, a biguanide prescribed for type 2 diabetes,

disrupts mitochondrial bioenergetics and inhibits hepatic gluco-

neogenesis via LBK/AMP-dependent and -independent mecha-

nisms (Andrzejewski et al., 2014; Cusi et al., 1996; Foretz et al.,

2010; Madiraju et al., 2014; Shaw et al., 2005). The direct effects

of metformin on disruption of mitochondrial bioenergetics are

experienced only by cells that express drug transporters (e.g.,

liver cells), whereas the indirect effects of reduced circulating

glucose and insulin may have important systemic antineoplastic

functions (Pollak, 2012). Importantly, alterations in systemic

glucose metabolism, either through obesity or diabetes, are

known risk factors for pancreatic cancer (Bracci, 2012; Garcia-

Jimenez et al., 2016; Garg et al., 2014).

Examination of diabetic patient populations on metformin

treatment has led to conflicting reports regarding the impact of

the treatment on the risk of developing PDAC or the prognostic

value of treatment after diagnosis (Bodmer et al., 2012; Hwang

et al., 2013; Nakai et al., 2013; Sadeghi et al., 2012; Singh

et al., 2013; Suissa and Azoulay, 2012; van Staa et al., 2012;

Walker et al., 2015). However, two recent phase 2 clinical trials

have found no benefit of metformin treatment when adminis-

tered at levels used for glycemic control in patients with

advanced or metastatic cancers (Kordes et al., 2015; Reni

et al., 2016). While these results are disappointing, there may still

be potential benefit for metformin treatment in the neoadjuvant

setting, as amaintenance therapy in patients with stabilizedmet-

astatic cancer (NCT02048384) (Yang and Rustgi, 2016), or if

used at higher concentrations. In addition, more potent bigua-

nides such as phenformin (NCT02475499) or metformin analogs

may be more efficacious, as they do not require active transport

and exhibit cell-autonomous and systemic antineoplastic activ-

ities (Cheng et al., 2016).

Cell-autonomous metabolic alterations observed in PDAC are

present to varying degrees. Recent work has classified PDAC

cell lines into three distinct metabolic subtypes: slow prolifer-

ating, glycolytic, and lipogenic (Daemen et al., 2015). Among

these, the glycolytic subtype responded robustly to inhibition

of glutaminase (GLS), the primary enzyme responsible for ana-

plerotic entry of Gln into the TCA cycle in cell culture models

(Figure 2). Despite success with GLS inhibitors in in vitro studies

(Daemen et al., 2015; Son et al., 2013), this has not yet been

effective for treating PDAC in vivo (Chakrabarti et al., 2015). As

Cancer Cell

Review

one of the primary roles for Gln in PDAC cells is to maintain redox

homeostasis (Son et al., 2013), we tested combinatorial activity

of GLS inhibition with a clinical agent that induces redox imbal-

ance. b-Lapachones (b-laps) are a class of targeted cancer ther-

apeutics that induce ROS formation and NADPH depletion in an

NADPH:quinone oxidoreductase 1 (NQO1)-dependent fashion.

NQO1 is highly upregulated in PDAC relative to normal pancre-

atic tissue and is the most widely recognized Nrf2 target, sug-

gesting a further degree of selectivity for this treatment regimen.

Indeed, subclinical doses of b-lap and a GLS1 inhibitor, which

were non-toxic as single agents, exhibited tumoricidal activity

and slowed tumor growth through on-target activity of both

agents in vivo (Chakrabarti et al., 2015).

Inhibitors Targeting Scavenging Pathways

Hyrdoxychloroquine (HCQ), a lysosomotropic drug which pre-

vents acidification of lysosomes, is a potent inhibitor of auto-

phagy that prevents degradation of autophagosomes. The

blockade of lysosomal acidification can also prevent uptake of

nutrients via macropinocytosis, as lysosomal degradation is the

terminal step in that pathway. Indeed, HCQ has moved forward

in several clinical trials for pancreatic cancer patients, including

single-agent HCQ in patients previously treated with standard

of care for metastatic cancer (NCT01273805), as well as combi-

nation treatments with gemcitabine (NCT01128296) (Boone

et al., 2015), gemcitabine/nab-paclitaxel (NCT01506973), or in

combination with capecitabine and radiation or proton therapy

(NCT01494155).

Despite its potential, clinical outcomes with HCQ have been

limited by pharmacokinetic and pharmacodynamic shortcom-

ings. Specifically, HCQ requires a long treatment regimen to

reach a therapeutic steady state, which for rheumatoid arthritis

patients has been found to take up to 6 months (Tett et al.,

1988). As such, in its current dose formulation, HCQ may not

be a sufficiently potent inhibitor of autophagy in patients. In a

recent report on clinical trials (NCT01273805), only 10% of

patients treated with HCQ demonstrated progression-free

survival (Wolpin et al., 2014). However, patients treated with

both HCQ and gemcitabine who met criteria for HCQ response

via peripheral blood mononuclear cell LC3 staining demon-

strated marked improvement in disease-free and overall survival

(Boone et al., 2015). Accordingly, there are several strategies

underway to develop new and more potent autophagy inhibitors

which may yield better clinical results (Kulkarni et al., 2016; Liu

et al., 2011; McAfee et al., 2012; Wang et al., 2015; Zhao

et al., 2015).

While early attempts to treat PDAC by targeting tumor meta-

bolism have only been met with moderate success, there is

reason for continued optimism. Many recent preclinical studies,

such as those detailed above, have revealed additional features

of altered metabolism in PDAC with more tractable therapeutic

targets. Nevertheless, a concern with designing therapies to

target metabolic vulnerabilities is the development of resistance,

which has plagued kinase-targeted therapies in pancreatic can-

cer (Alagesan et al., 2015). Indeed, like the redundancies in cell

signaling, metabolic networks also have flexibility and recent re-

ports have revealed that these can be rewired to evade targeted

therapy (Boudreau et al., 2016; Davidson et al., 2016). Finally, as

mentioned previously, the pancreatic stroma has traditionally

presented a barrier to drug delivery (Olive et al., 2009) and, as

such, effective metabolic inhibitors will need to be designed

with this in mind.

Metabolic ImagingThere is an urgent need to develop new techniques for detection,

staging, and assessment of treatment response in PDAC.

Pancreatic cancer is known to metastasize early, and it is imper-

ative to accurately determine if the disease has metastasized to

distant organs in order to avoid unnecessary surgical proced-

ures. In principle, these diagnostic limitations may be addressed

using metabolic imaging probes. Technologies associated with

these probes include positron emission tomography (PET)- and

magnetic resonance spectroscopy (MRS)-based approaches.

While there have been some successes using PET-based imag-

ing methods for PDAC, evolution of hyperpolarized probes for

in vivo nuclear MRS may provide an even more effective

strategy.

PET Imaging

PET is a non-invasive imaging approach in which gamma rays

are detected from positron-emitting isotopes. As detection of

an emission source limits spatial resolution, PET is often com-

bined with computed tomography (CT). The workhorse imaging

agent in clinical oncology for PET is the glucose analog [18F]flu-

orodeoxyglucose (FDG), which capitalizes on the observation

that glucose uptake is increased in cancer, including PDAC.

Upon uptake into cells, both glucose and FDG are phosphory-

lated by HK to prevent their release from the cell. However, in

contrast to glucose, FDG lacks a 20-hydroxyl group which pre-

vents it from being further metabolized. The end result is FDG

accumulation in cells proportional to the amount of uptake and

HK activity (Figure 4A).

The ability of FDG-PET imaging to detect PDAC was reported

early in the development of the technology (Friess et al., 1995;

Zimny et al., 1997). However, there are mixed reports on the util-

ity of FDG-PET compared with CT, MRI, and endoscopic ultra-

sound techniques. The most useful aspect of FDG-PET for

PDAC appears to be the strong correlation between levels of

FDG uptake and tumor aggressiveness in terms of pathological

grade (Ahn et al., 2014; Chen et al., 2016), prediction of distant

metastasis (Shinoto et al., 2013), and survival (Chen et al.,

2016; Kitasato et al., 2014; Lee et al., 2014; Yamamoto et al.,

2015). The strongest critique against use of FDG-PET in PDAC

is the observation that it is no more effective than conventional

imaging techniques to diagnose early stage pancreatic cancer

or to detect small metastases (Matsumoto et al., 2013; Rijkers

et al., 2014). In addition, there is concern over the ability of

FDG-PET to distinguish between PDAC and pancreatitis (Kato

et al., 2013), given that mass-forming pancreatitis also shows

an increase in FDG uptake (Kamisawa et al., 2010).

As PET imaging with FDG in PDAC is limited to prognostic

value, other PET strategies are currently being developed. In

addition to glucose-based PET-imaging agents, 18F-labeled

Gln analogs have been created (Figure 4A) (Lieberman et al.,

2011; Ploessl et al., 2012; Qu et al., 2011b; Wu et al.,

2014). Gln-based PET agents have demonstrated the ability to

selectively detect tumors in preclinical animal models (Lieber-

man et al., 2011; Ploessl et al., 2012; Venneti et al., 2015;

Wu et al., 2014) and have been successfully tested in human

glioblastoma patients (Venneti et al., 2015). Because of the


A

B

Figure 4. Metabolic Imaging Agents Available for Detection of PDAC(A) Positron emission tomography (PET)-based imaging agents accumulate in tissues and emit positrons proportional to the tissue accumulation of the probe.(B) Hyperpolarized magnetic resonance spectroscopy (HP-MRS)-based imaging agents allows both the measurement of uptake as well as a readout of con-version into other metabolites. This information can be used to monitor the flux through various metabolic pathways in the tumor. 6PG, 6-phosphogluconate;DHA, dehydroascorbate; 18F-DG, 18F-labeled fluorodeoxyglucose; Glc, glucose; Glc-6P, glucose 6-phosphate; Pyr, pyruvate.

Cancer Cell

Review

alterations in Gln metabolism described in detail above,18F-labeled Gln analogs could potentially be useful for detection

and monitoring of PDAC.

Hyperpolarized MRS

MRS has been used extensively for in vitro metabolism studies

with non-radioactive 13C-labeled metabolites; however, in vivo

imaging of metabolic pathways using 13C-labeled metabolites

has remained a challenge due to both low sensitivity of13C-MRS and the inability to deliver a sufficient amount of

labeled isotope. Recent advances in biomedical imaging have

addressed limitations in sensitivity using 13C isotopes and now

allow for 10,000-fold enhancements in signal (Ardenkjaer-Larsen

et al., 2003; Keshari and Wilson, 2014). This process is referred

to as hyperpolarization (HP) and possesses several significant

advantages over traditional imaging technologies. First, the13C-labeled imaging agent is the parent molecule; that is, it is

structurally identical to its non-labeled counterpart. Accordingly,

labeled metabolite can be detected directly and, like traditional

imaging agents, provides readout of tissue avidity. However, un-

like traditional probes, 13C-labeled metabolites, once taken into

a cell, can also participate and inform of the altered metabolism

within a cancer cell. An example of this as applied to a preclinical

PDACmodel revealed that conversion of 1-13C-labeled pyruvate


to lactate could distinguish cancer from normal tissue and even

stage disease (Figure 4B) (Serrao et al., 2015).

A limitation of this technology concerns the short half-life of

the probe, which is typically on the order of 1 min. Despite

this temporal constraint, application of HP-MRS probes as im-

aging agents in vivo is feasible (Golman et al., 2003). Metabolic

imaging via HP-MRS began with the development of HP-pyru-

vate (Golman et al., 2006), which has now been successfully

used in preclinical models to assess tumor metabolism (Dutta

et al., 2013; Harris et al., 2009; Hu et al., 2011; Keshari et al.,

2013b), correlate pyruvate metabolism to tumor grade (Albers

et al., 2008), and monitor tumor response to therapeutics (Day

et al., 2007, 2011; Park et al., 2011; Sandulache et al., 2014;

Sourbier et al., 2014). HP-pyruvate imaging has also been

used in preclinical models of PDAC, including autochthonous

mouse models (Serrao et al., 2015), and patient-derived xeno-

grafts (Rajeshkumar et al., 2015). Importantly, feasibility and

safety of HP-pyruvate imaging in human patients has been

demonstrated in a clinical trial for prostate cancer (Nelson

et al., 2013).

Other hyperpolarized metabolic probes have exhibited prom-

ising results (Salamanca-Cardona and Keshari, 2015) that are of

particular interest for the study of pancreatic cancer metabolism

Cancer Cell

Review

(Figure 4B). HP-Gln probes have been developed (Cabella et al.,

2013; Gallagher et al., 2008, 2011; Qu et al., 2011a) that would be

useful in identification of Kras-rewired Gln metabolism in vivo.

HP-glucose probes have also been described (Allouche-Arnon

et al., 2013; Christensen et al., 2014; Harris et al., 2013;

Rodrigues et al., 2014; Timm et al., 2015) that would allow iden-

tification of changes in glycolytic metabolites and the PPP.

Lastly, HP-dehydroascorbate has been used to measure the

redox state and inform on the level of ROS in tumors (Bohndiek

et al., 2011; Keshari et al., 2011, 2013a), which could be used to

select treatment modalities and monitor therapeutic response.

Despite recent progress in defining the genetic landscape of

pancreatic cancer (Bailey et al., 2016; Moffitt et al., 2015; Wad-

dell et al., 2015), genetic approaches to predict treatment

response have thus far not provided new treatment options for

the majority of patients. In light of this, profiling the metabolism

of tumors in vivo represents a promising new avenue to help

inform treatment options for these patients.

Conclusion and Future DirectionsWhile altered metabolism has long been recognized as a central

hallmark of cancer, we have only recently begun to evolve a suf-

ficient mechanistic understanding of these processes to begin to

exploit differences between cancer cells and normal cells.

Pancreatic cancer metabolism is dramatically rewired by onco-

genic Kras, presenting several opportunities for selective

targeting. Furthermore, the austere microenvironment forces

pancreatic cancer cells to rely on alternative sources of nutrients

and to utilize unique methods to obtain them. The need for new

therapies in pancreatic cancer treatment is clear. While a heroic

effort is being made to target Kras and Kras-surrogate signaling

(Cox et al., 2014), there are no clinical Kras inhibitors and few

clinically viable Ras-effector treatments have emerged, due

largely to compensatory signaling from single agents or toxicity

of combination strategies. As outlined in this review, it is our

belief that targeting tumor metabolism may overcome these

limitations.

Metabolic changes in pancreatic tumors can also provide

diagnostic information that is not available with traditional imag-

ing methods. This is particularly true of HP-MRS imaging, which

with more routine use may be able to stratify tumors for treat-

ment based on metabolic signatures. Furthermore, the ability

to trace tumor metabolism in vivo will be critical to verify that in-

formation gathered from preclinical models and studies are

applicable in PDAC patients.

Finally, immunotherapy has emerged as a promising treatment

option for several cancers (Brahmer et al., 2012; Javle et al.,

2016). Accordingly, there has been substantial interest in dis-

secting immune response to PDAC and translating these find-

ings into successful treatments (Bayne et al., 2012; Beatty

et al., 2011; Pylayeva-Gupta et al., 2012; Soares et al., 2015;

Winograd et al., 2015; Zhu et al., 2014). However, it is important

to note that immune cell metabolism is also important to the acti-

vation and differentiation of these cells (MacIver et al., 2013;

Wahl et al., 2012). As such, metabolic inhibitors targeting tumor

cells may either interfere or enhance the immune response to

therapy. Future studies will be needed to gather a more detailed

understanding of the tumor immune response to metabolic

perturbation.

AUTHOR CONTRIBUTIONS

C.J.H. and C.A.L. designed the figures, and conceived of and wrote the

manuscript.

ACKNOWLEDGMENTS

We thank Drs. Howard Crawford, Kayvan Keshari, Alec Kimmelman, MarinaPasca di Magliano, Diane Simeone, and members of the Lyssiotis laboratoryfor feedback. C.A.L. is supported by grants from the American Associationfor Cancer Research and the Pancreatic Cancer Action Network (13-70-25-LYSS), National Pancreas Foundation, Sidney Kimmel Foundation, DamonRunyon Cancer Research Foundation (DFS-09-14), and American Gastroen-terological Association.

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Cancer Cell

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