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Intersections and Clinical Translations of DiabetesMellitus with Cancer Promotion, Progression andPrognosis

Stanley S. Schwartz, Struan F.A. Grant & Mary E. Herman

To cite this article: Stanley S. Schwartz, Struan F.A. Grant & Mary E. Herman (2019):Intersections and Clinical Translations of Diabetes Mellitus with Cancer Promotion, Progression andPrognosis, Postgraduate Medicine, DOI: 10.1080/00325481.2019.1657358

To link to this article: https://doi.org/10.1080/00325481.2019.1657358

Accepted author version posted online: 16Aug 2019.Published online: 05 Sep 2019.

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CLINICAL FEATUREREVIEW

Intersections and Clinical Translations of Diabetes Mellitus with Cancer Promotion,Progression and PrognosisStanley S. Schwartza,b, Struan F.A. Grantc and Mary E. Hermand,e

aMain Line Health System, Wynnewood, PA, USA; bUniversity of Pennsylvania, Philadelphia, PA, USA; cCenter for Spatial and Functional Genomics,Divisions of Human Genetics and Endocrinology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA; dMontclair State University, UpperMontclair, NJ, USA; eSocial Alchemy Ltd. Building Research Competency in the Developing World, Edgewater, NJ, USA

ABSTRACTThe association between cancer and dysglycemia has been well documented. It is underappreciated,however, that sustained dysglycemia could potentially be a catalyst toward a pro-cancer physiologicmilieu and/or increase the burden of cancer. Hyperglycemia, hyperinsulinemia and energy metabolismat large impact a cascade of growth pathways, epi/genetic modifications, and mitochondrial changesthat could feasibly link to tumor processes. Oxidative stress is a recurring motif in cell dysfunction: indiabetes, oxidative stress and reactive oxygen species (ROS) feature prominently in the damage anddemise of pancreatic beta cells, as well as cell damage contributing to diabetes-related complications.Oxidative stress may be one intersection at which metabolic and oncogenic processes cross paths withdeleterious results in the development of precancer, cancer, and cancer progression. This would augurfor tight glucose control. Regrettably, some medical societies have recently relaxed hemoglobin A1ctargets. A framework for the hyperglycemic state is presented that helps account and translate the fullscope of effects of dysglycemia to ultimately improve clinical best practices.

ARTICLE HISTORYReceived 12 July 2019Accepted 15 August 2019

KEYWORDSType 2 diabetes; cancer;hyperglycemia; egregiouseleven; beta-cell–centricmodel; common origins ofdiabetes and itscomplications construct

Introduction

The cumulative findings in the area of hyperglycemia arefostering more pragmatic approaches to DM management,and, spawning research into the full scope of derangementsof dysmetabolism. Beyond the ‘usual suspects’ impacted bydysglycemia – insulin resistance, hypoglycemia, increasedappetite, and weight gain, obesity, dyslipidemia, endothelialdysfunction, atherosclerosis, and hypertension – a large rangeof medical conditions not traditionally associated with hyper-glycemia are impacted by it. More ‘distal’ disease stateswrought by dysglycemia include chronic inflammation,Alzheimer’s disease, dementia, depression, sleep disorders,and cancer, among others.

These authors have previously introduced a conceptualiza-tion of DM that helps bring it in line with the new science. Itwas initially published in Diabetes Care [1]; its fuller embodi-ment appeared in Trends in Endocrinology and Metabolismwith the title, A Unified Pathophysiological Construct ofDiabetes and its Complications (Figure 1) [2]. It proposes thata common pathophysiology drives the diabetic state – across itsnatural history and its varied clinical presentations.

The primary underlyingmediator of diabetes-related complica-tions is the damage wrought by hyperglycemia and other excessfuels engendered by reduced insulin or insulin effect due toabnormal beta-cell function. The development and progressionof any given complication depends on the interplay betweengenetic predisposition, environmental cues, IR, immune

dysregulation and inflammation, intracellular fuel excess, andcomorbidities (such as hypertension and hyperlipidemia).Common processes at work in all target (vulnerable) cells impli-cated in diabetes. Chronic exposure to hyperglycemia and gluco-lipotoxicity from excess fuel leads to the release of ROS. Thisactivates pathways including polyol flux, advanced glycationend-products (AGEs) formation, activation of protein kinase C(PKC), and hexosamine flux. Inflammation is produced. Thesetrigger signaling pathways, induction of transcription factors,gene transcription, and epigenetic modifications such as histonemodifications, DNA methylation, non-coding RNA in microRNA(miRNAs), and long non-coding RNAs (LncRNAs). Gene transcrip-tion favors cell hypertrophy, proliferation, remodeling, and, apop-totic signaling, which are physiologically manifested as coronaryartery disease (CAD), peripheral artery disease (PAD), retinopathy,neuropathy, and kidney impairment. Cancer also appears to be anoutcome. Systemic effects include the exacerbation of the diabeticstate, especially as insulin secretion from the laboring beta cellsdecreases, and, secondarily, as CV function is compromised.

It may seem intuitive that patients with comorbid diabeteshave poorer outcomes from cancer given overall burden to thesystem. Since it is now understood that common metabolicalterations are at the crux of each of these two diseases –diabetes and cancer – it no longer seems surprising that pertur-bations by one disease state can cause ripples in the other. But,can dysmetabolism be more directly linked to oncogenesis andtumor progression? This appears to be the case.

CONTACT Stanley S. Schwartz stschwar@gmail.com Main Line Health System, Wynnewood, PA, USA

POSTGRADUATE MEDICINEhttps://doi.org/10.1080/00325481.2019.1657358

© 2019 Informa UK Limited, trading as Taylor & Francis Group

In this article, we seek to provide an overview of numerousexamples from recent research that substantiates and zeros inon the intersections in glucose metabolism, metabolics andthe emerging epi/genetics that lie between diabetes and can-cer, including our own research in genome-wide associationsstudies. These putative points of overlap are accumulating,tantalizing, and worthy of discussion as it may be underap-preciated that sustained dysglycemia is a risk factor for cancer,and, may increase cancer burden. We also consider ramifica-tions to clinical care if this association is borne out.

Resolving the intercepting pathways of dysglycemiaand cancer

Epidemiologal linkages between dysmetabolism andcancer

Studies, including large- and mega-cohort studies and meta-analyses, have shown that cancer incidence is ~10% higher inindividuals with diabetes than in non-diabetic individuals [3–5]. Prognostically, patients with diabetes fare worse in terms ofcancer prognosis and survival than cancer patients withoutdiabetes [6–8]. Prostate cancer is the exception to the rule,with several studies reporting an observed paradoxicaldecrease in incidence in diabetic individuals (Figure 2) [9–11].

Of note, frank diabetes is not a prerequisite to observe theassociation. One large analysis of BMI – including more than900,000 U.S. adults – estimated that 14% of all deaths from cancerin men and 20% of those in women were attributable to over-weight. Death rates from cancer in morbidly obese individuals in

this mega study were found to be ~50% to 60% higher thansubjects at normal weight [8]. Overweight is associated withdysglycemia and insulin resistance in many patients [8]. In fact,in addition to overweight, a number of conditions of dysmetabo-lism have each been found to be independently associated withan increased incidence of cancers, and poorer cancer survival.These include high nutrient intake, insulin resistance, hyperglyce-mia, diabetes, hyperinsulinemia, and even inflammation [3; 12–20]. Indeed, in seminal diabetes trials, high nutrient intake provedsufficient to increase cancer mortality (DECODE Study; HR 1.71(1.35,2.17)) [21] as well as increase the risk of cancer [13]. Notably,each outcomewas related to the degree of hyperglycemia, includ-ing in prediabetes.

Cancer also increases the risk of diabetes; this relationship ismore clear cut and stems from several roots. Thorough medicalworkups in cancer patients can detect undiagnosed hyperglyce-mia. Second, cancer imposes a huge stress on the system throughinfections, bleeding episodes, and surgery, which could tip thescales for the system to be able to maintain normoglycemia. Ofconcern in treating cancer, some anticancer therapies – such assteroids, chemotherapy, and radiotherapy – increase blood glu-cose, induce hyperglycemia, and, lead to diabetes. Interestingly,the checkpoint inhibitor cancer therapies (pembrolizumab, a PD-L1 inhibitor, and ipilimumab, a CTLA4 inhibitor, as examples)have been shown to induce diabetes through the immune sys-tem. Autoimmune endocrinopathies, including autoimmuneHLA-DR4+ diabetes are associated with this class [12]. In onesmall study (n = 27), a significant number of subjects exhibitedat least one positive autoantibody. HLA-DR4, in particular, waspresent in three-quarters of the patients [12].

Figure 1. Diabetes and its complications arise from common etio-pathophysiologies. Adapted from Schwartz et al. Trends in endocrinology & metabolism. 2017.Reused with permission.

2 S. S. SCHWARTZ ET AL.

Converging pathways between dysglycemia and cancer

Research into dysglycemia suggests that it aids and abets neo-plastic transformation and tumor progression. Dysmetabolism canpropel cells into a vicious cycle of increased fuel uptake; endocrinedisruptors; altered insulin and insulin-like growth factor cascades;and, abnormalities in steroid hormones, adipokines and fat cellfunction. Dysmetabolism also desynchronizes circadian rhythms;boosts cell stress responses; tends toward pro-inflammatorymilieu and sustained inflammation; induces endoplasmic reticu-lum (ER) stress; and, leads to mitochondrial re-architecture; epige-netic alterations; and, increased DNA instability [18]. Many of theserepresent pro-cancer scenarios. Some supervene normal con-straints on neoplastic transformation and tumor growth by dis-mantling tumor suppressor activity, derailing apoptosis, orprovisioning immune evasion by tumor cells.

As examples, in vitro, high glucose concentrations havebeen shown to alter the expression of specific cell cycle reg-ulators, such as cyclin D1, and, in transformed cells, to spur ontumor cell proliferation, migration, and invasion [22]. Elevatedoxidative stress is found concomitant with many of thesechanges, and, occurs in a direct line to tumor transformation(reviewed by Cignarelli et al. 2018; 23). Tumor cells can manip-ulate elevated IGF-1 levels, a mitogen implicated in somecancers, by selectively reducing hepatic synthesis of IGFBP-1.Tumors have also been found to favor the A isoform of insulinreceptor, which has a predominant mitogenic effect overother insulin actions (reviewed by Vigneri et al. 2016; 16).

Overweight, even in the absence of diabetes, is sufficient tochange insulin/IGF signaling, adipokine pathophysiology, andchronic inflammation. These changes have been found to occurproportional to BMI [24,25]. Insulin resistance typically develops

along with overweight (and can be present at normo-weight,including in a significant proportion of type 1 DM cases; 26).Insulin resistance ‘recalibrates’ responsiveness to, and homeostasisfor, insulin, as well as other peptide and steroid hormones, andgrowth factors.

Martin and McGee (2018) recently proposed that, under thepressures of altered circulating hormones (including hyperinsu-linemia/insulin resistance, glucagon, and leptin/leptin resis-tance), substrate availability, and adipose cell dysfunction, cellgrowth regulation is ‘reprogrammed’ [27]. Putative pathwaysthat may be enlisted include fuel excess, or, ‘metabolic repro-gramming’ through cell dysfunction and/or hypoxia of tissue orsurrounding adipose tissue These appear to mirror hallmarkalterations in glucose, lipid, and amino acidmetabolism in breastcancer [27]. In their breast cancer model, this pro-transformationmilieu leads to tumorigenesis. Hyperinsulinemia and increasedcellular substrate availability have also been reported to aidcancer cells in dodging normal cell growth checkpoints throughboth direct and indirect mechanisms [27]. Tumor cells are them-selves metabolic adaptors; as two examples, tumors adapt a highglycolytic flux, and, may overexpress glucose transporters (e.g.GLUT1 and GLUT4) to survive and thrive. Dysmetabolism also‘feeds’ the Warburg effect in cancer cells – the switch frommitochondrial oxidative phosphorylation to glucose-dependentglycolysis as the chief means of energy production.

Transecting signaling pathways

Insulin is both a metabolic hormone and a mitogenic factor ofcell proliferation; this effect may be amplified in the face ofelevated insulin. Malignant cells have been seen to

Figure 2. Epidemiological association between obesity, diabetes, and cancer. Summary of the relative risk (RR) between obesity (black bars), type 2 diabetesmellitus (T2DM, gray bars), type 1 diabetes mellitus (T1DM, white bars), and different types of cancer. Data collected from meta-analyses published in the past 10years and included in the references. The graph only represents a positive or direct association (right side) and a negative or inverse association (left side) of the RRvalues when the value is significant or there is a very high trend. The bar size is proportional to the increase in RR. The values of RR given for obesity were obtainedfor a BMI≥30kg/m2. Taken from Gutiérrez-Salmerón et al. Endocrinol Diabetes Nutr. 2017 [11]. Reused with permission.

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overexpress the insulin receptor and, more specifically, insulinreceptor A, with enhanced growth factor activity.

Insulin, among other signaling molecules, appears to strad-dle energetic metabolic and tumorigenic pathways. PRKA,PI3K, SIRT1, mTOR are among putative intermediaries [11;28–31]. SIRT1 is intricately involved in energy sensing, and,bridges energy metabolism with effects on genomic in/stabi-lity, which can be involved in cancer. Interference with SIRT1by excess intracellular nutrients has been shown to limit itsprotective action on DNA stability, as well as to influenceinflammation and angiogenesis [31].

The mTOR pathway is known to be commandeered bysome cancers. mTOR is highly susceptible to epigeneticchanges [28] that favor tumor growth. It is not surprisingthat mTOR has proven a useful therapeutic target. The wellnoted anticancer activity of metformin similarly appears toinvolve reversal of the exploitation of mTOR, as well as insulinand AMPK, pathways in cancer cells [29,32]. Cell adhesion,motility, and tumor vascularity have been found to be influ-enced by insulin-like growth factor receptor-1 (IGF-IR), whichtransits through the de/activation of PI3K, AKT, TOR, RAF, MEKand ERK. IGF-IR also plays a role in cell transformation(Figure 3).

A final intersection: dysmetabolism can inhibit autophagy,an innate mechanism that removes toxic waste to keep orga-nelles in good working order. Oncogenesis has been proposedto proceed with fewer ‘checks’ by modulating autophagy [31].

Interestingly, autophagy serves a second function: it providescellular fuel during times of starvation (Figure 4).

Oxidative stress: bridge between dysglycemia and pro-cancer cellular & DNA damage?

The normal functions of ROS include maintenance of cellmetabolism, adaptation to changing nutrient availability,and, in the face of excess intracellular nutrients, protectionagainst excessive intracellular signaling and accumulation ofmetabolites. ROS serve as second messengers in the activationof proteins such as NF-kB, among others [33]. NF-kB isinvolved in the control of transcription of DNA, cytokine pro-duction, and cell survival. The ROS system can become satu-rated, however, in some instances, leading to cell demise. Inother instances, however, sustained high levels of ROS pro-duce sustained and maladaptive cell signaling and prolifera-tion; unchecked gluco-lipo-toxicity; amino acid-dependentmTOR activation; dysregulated transcription through metabo-lite-sensitive protein modifications; altered protein acetylationand O-GlcNAcylation; and, activation of hypoxia inducible fac-tors (reviewed by Wellen and Thompson, 2010 [18]). Oxidativestress is a recurring motif in cell dysfunction: in diabetes,oxidative stress and ROS feature prominently in the damageand demise of pancreatic beta cells vasculature, retina, andkidney (i.e diabetes-related complications).

It is intuitive that nutrient deprivation, such as in starvation,exerts huge cell stress. ROS can result from sustained elevated

Figure 3. Factors believed to contribute to cancer, including those of dysmetabolism (with sampling of mediators/processes). Shown are putative factorsand mechanisms linking dysmetabolism with tumorigenesis and cancer progression. Selected pathways and mechanisms are shown, but not intended to becomplete. These elucidate the complex and overlapping ‘themes’ within cell metabolism that can go awry in dysmetabolism – and instigate both cancer initiationand growth.

4 S. S. SCHWARTZ ET AL.

levels of growth factors, or mitochondrial stress, which can dys-regulate energy production, biosynthesis, calcium regulation, andsignaling, and, redox balance. Of import is that sustained excessnutrition generates as much cell stress as nutrient deprivation.ROS may also activate oncogenes or deactivate tumor suppressorgenes. Changes in mitochondrial morphology are evident in bothdisease states – diabetes and cancer. Dynamin-related (fission)protein 1 (DRP1) is one putative common intermediary of thesedeleterious changes in both diseases from ROS [34].

Adaptive long-term metabolic mechanisms: genomic‘plasticity’?

‘Metabolic memory’ refers to the long-term adaptation tohyperglycemic and hypoglycemic conditions. Glucose andinsulin levels are as involved in ‘programming’ long-term sur-vival as moment-to-moment energy metabolism. More than250 epigenetically regulated genes involved in glucose meta-bolism and adaptive survival have been reported [35,36]. Thiswas first documented as ‘legacy effects’ in diabetes outcomesthat persisted for decades after intensive glucose control insubjects of major diabetes control studies (on-trial for 5–10years) [37–40]. This again shows that glycemic state is animportant determinant of genetic status.

The composite of the research described above providescompelling, coincidental evidence linking hyperglycemia withcancer. A direct line between hyperglycemia to oncogenesis

has been charted by the recent characterization of a ‘phospho-switch’ in the DNA 5-hydroxymethylome by Wu and coworkers.Their research showed that elevated glucose levels destabilizethe TET2 tumor suppressor protein [41]. The phosphorylationstate of TET2 is controlled at serine 99 by AMP-activated kinase,a signaling pathway that is shared with glucose regulation. Thestrength of this association is supported by the finding thatmetformin – an antidiabetes agent associated with reducedcancer outcomes in some studies – was found to guard TET2levels by reinstating/maintaining the glucose/AMP-activatedkinase/TET2/5-hydroxymethylcytosine axis [41]. 5-hydroxy-methylcytosine is also particularly noteworthy for its intimaterelation to epigenetic state. Interestingly, metformin has pre-viously been shown to stabilize epigenetic status (throughhistone modifications, DNA and/or RNA methylation, and non-coding RNA) (reviewed by Yu al. 2017 [42]). Therefore, TET2represents a discrete molecular link between dysglycemia andcancer; likely, many more direct links exist to support the con-tention that cellular pathways exist at the crossroads betweenenergy metabolism, and, tumorigenesis and tumor growth.

Genetic overlap between dysmetabolism and cancer

These authors (SFAG) were the first to describe the commonvariant that, to date, is the most strongly cancer-linked variantthat is also associated with type 2 DM: embedded within thegene-encoding transcription factor 7–like 2 (TCF7L2;

Figure 4. Alterations and interactions of the energy sensing pathways within type 2 diabetes – and likely dysmetabolism, at large – with cancer. Takenand adapted from Yang et al. (J Diabetes Complications. 2017 [31]), their example is based on research in colorectal cancer cells. In the face of dysmetabolism in thediabetic state due to high glucose, insulin and IGF-1 levels, decreased genomic stability and DNA mismatch repair give rise to cancer. The ‘remodeling’ of cellmetabolism includes a milieu that promotes protein, nucleotide, and lipid synthesis, and, rapid proliferation of transformed cells. AMPK: AMP-activated kinase; IGF-1:insulin-like growth factor; mTORC1: mammalian target of rapamycin complex 1. Reused with permission.

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formerly TCF4) [43]. As example, colorectal cancer risk isstrongly influenced by specific mutations of TCF7L2 [44]. Thekey 8q24 locus found to be the most strongly associatedgenomic region with a number of cancers and contributes tothe disease pathogenesis through mutation of an upstreamTCF7L2-binding element driving the transcription of the MYCgene [5,45]. Influence on the MYC gene may help explain itsassociation with a number of cancers. TCF7L2 harbors specificmutations that strongly influence colorectal cancer risk, and,genomic sequencing of colorectal adenocarcinomas identifiedrecurrent VTI1A-TCF7L2 gene fusion.

Prostate cancer is unique among cancers for having a lowerrisk in patients with DM. Many GWAS-derived risk-conferringalleles associated with type 2 DM have also been shown toprotect against prostate cancer [46]. Loci strongly detected forrisk of both prostate cancer and type 2 DM include THADA,JAZF1, and TCF2 (also known as HNF1B) [47].

As a final example of converging genetic pathways, the Akt2gene influences diabetes-related traits, and human polymorph-isms in Akt2 have been implicated in metabolic syndrome [48].Mutations in Akt1 and Akt2 also play a major role in cancer.Interestingly, Akt1 has also recently been implicated in theendocrinopathy, Proteus Syndrome (a rare condition character-ized by overgrowth of the bones, skin, and other tissues) – anddevelopment of benign tumors [46]. Mutations in the geneencoding another member of the PI3K-AKT pathway, PTEN(germline tumor-suppressor phosphatase and tensin homolo-gue), links to constitutive insulin sensitivity and obesity [49] –and to a cancer-predisposition syndrome.

Learnings and applications from metformin, insulinand other antidiabetes agents

Diabetes outcomes studies uncovered something curious:treatment with metformin was repeatedly found to lowerrates of cancer and cancer mortality [32,42,50]. Currently,more than 100 studies of metformin for a range of tumortypes are cataloged on Clinicaltrials.gov. Some of these trialsare intervention studies that evaluate metformin, or thepotentially powerful anticancer duo of metformin + pioglita-zone, as add-ons to anticancer regimens [51].

Metformin intercepts numerous pathways relevant to onco-genesis and tumor progression. This includes the insulin hor-mone pathway, although its anticancer benefit has beenshown to be independent of insulin levels [42]. Peng andassociates have proposed that two target genes of metformininteract with ‘hub’ of six cancer-related genes – HADHB,NDUFS3, TAF1, MYC, HNFF4A, and MAX – in their colorectalcancer model [52]. Effects on mitochondrial bioenergetics mayprovide a second layer through which metformin may favor-ably influence growth and survival of transformed cells(Figure 5).

Thiazolidinediones (TZDs) are another class of antidiabetesagents associated with decreased cancer – a 7% decrease inrisk of cancer incidence was reported in one large study [20]. Alarge Veterans Administration patient record database showed>35% reductions in both head and neck and lung cancerincidence in patients with diabetics treated with TZD drugs

[53]. Paradoxically, pioglitazone has also been associated withan increase in bladder cancer [54]. Mechanistically, pioglita-zone is a peroxisome proliferator-activated receptor gamma(PPARγ) activator with demonstrated chemoprevention capa-city [51,53–57], perhaps it part by anti-inflammatory effects onNFκB. In preclinical studies, TZDs were found to achieve cellgrowth arrest, prevent cell differentiation and reduce tumorinvasiveness by inhibiting the ubiquitin-proteasome systemand the extracellular signal-regulated kinase pathway [57].

The potential effect of insulin therapy on cancer rate is lessclear [14,32,42,50,51,53–69]. A systematic review of observa-tional studies examining long-acting insulin analogs with can-cer was inconclusive [67]; although treatment with insulintherapy was associated with increased incidence of cancer inseveral studies [64–66]. In one analysis, use of insulin wasassociated with a 21% increase in the risk of cancer [20]. Inthis same study, sulfonylureas or alpha glucosidase inhibitorswere associated with a 20% and 10% increase in the risk ofcancer incidence, respectively. Of import is that elevatedserum insulin levels in nondiabetic patients have beenreported to have a higher cancer risk and poorer cancer out-comes [15,68], divorcing the incidence from purely a comorbidrelationship.

Mechanistically, insulin increases fatty acid uptake and sto-rage in most insulin-responsive cell types. It enhances aminoacid uptake, is pro-inflammatory, and, drives protein synthesis(reviewed by Martin and McGee, 2018; 27). An unavoidabledilemma with use of exogenous insulin is that it causes sus-tained, iatrogenic hyperinsulinemia – a state quite unlike theglucoregulation conferred by native insulin. Noncancerouscells have inherent strategies to protect themselves from sus-tained high levels of insulin (such as insulin resistance). Cancercells, in contrast, have evolved to thrive under conditions ofmetabolic excess and high oxidative stress (such as highNADPH flux and increased shuttling through the pentosephosphate pathway). Martin and McGee (2018) propose thatthis ‘metabolic reprogramming’ is sufficient to lead to celltransformation [27].

Other antidiabetes treatments have generally not shown astriking association with cancer. Newer agents have beenmore recently commercialized; minimal long-term follow-updata is available to correlate these modes of action withcancer. Early data has associated canagliflozin, a proposedinhibitor of complex I and mitochondrial glutamate dehydro-genase, with decreased proliferation of prostate and lungcancer cells [69].

A unified framework for dysglycemia: ramificationsto pathophysiology, research, and patient care

DM and cancer, when comorbid, have traditionally beenregarded from the perspective of co-management. That is,either managing diabetes and its complications in the faceof the physiologic burden of comorbid cancer, or, on theflip side, managing hyperglycemia and its sequelae (weightgain, frank diabetes) induced by certain anticancer treat-ments. It has been underappreciated that sustained

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dysglycemia is a risk factor, in itself, for cancer, as well asappears to increase the burden of cancer.

Ramifications to research

Our more replete model of dysmetabolism corroborates that thetentacles of dysglycemia extend far beyond conventionallyregarded reaches. This infers that research approaches shouldcast a wider net. Current genomic and other emerging technol-ogies are tools that are poised to decipher the complex inter-relationships between cell metabolism and growth regulationthat have evaded our prior research workhorses. New researchapproaches will enable multi-omic endeavors to fully resolvethese relationships. A better understanding of the full comple-ment of diseases of dysmetabolism stands to revise currentdogmas (and treatment assumptions) about hyperglycemia.

We hypothesize that the mechanisms that drive cell damageand cell death in pancreatic beta cells are fundamentally thesame processes through which damage the other cell typesimplicated in diabetes complications are accomplished [2].These are common and ubiquitous processes that can causedetriment in all cells but are only induced by hyperglycemia incell types privy to excess intracellular glucose. Beyond oxidativestress, alterations in cell signaling, genomic changes, and epige-nomic modifications each appear to be impacted by energydysmetabolism. Tantalizingly, these also contribute to the devel-opment of precancer, cancer, and cancer progression, and maybe conferred by dysglycemia among other inducers.

Ramifications to recommended A1c targets

The emerging body of knowledge suggests that tight, aggressivemanagement of blood glucose may help prevent diseasesbeyond DM and conventional diabetes-related complications –including conditions such as cancer. Suboptimal adherence toA1c target levels, and the recent controversial sanctioning oflooser A1c targets issued by the American College of Physiciansin their 2018 Diabetes Guidelines [70] are ill-founded in ouropinion, and, opposed by leading diabetes associations [71,72].Normalization of plasma glucose without increased risk of hypo-glycemia is increasingly obtainable with today’s glucose-lower-ing tools, and, might be regarded as ‘good medicine’ for cancerprevention and cancer survival, as these are for diabetesoutcomes.

Ramifications to treatments of choice amongantidiabetes agents

Safety and outcomes data for cancer-promoting or cancer-fighting properties should be gathered and added to thebenefit:risk profiles of antidiabetes agents. This informationwill be essential for optimal management of patients withconcurrent cancer or high risk for cancer. Diabetes long-termoutcomes trials have clearly shown that some drugs/classesoffset the burden of hyperglycemia through pleiotropic bene-fits on the cardiovascular and other systems. The strikingbenefits shown in the EMPAG-REG Study, which captured~30% decreases in CV outcomes and mortality with

Figure 5. Proposed molecular mechanisms of metformin action. Among its actions, metformin increases AMPK, thereby inhibiting downstream mTOR whilereducing insulin and IGF-1 levels. By blocking glycolysis, metformin favorably affects downstream histone modifications. Metformin also appears to promoteapoptosis in cancer cells by inducing the expression and/or activation of caspase 3, potentially ‘strangling’ the cells through the productive of reactive oxygenspecies or p53 tumor suppressor gene activity (reviewed by Yu et al. 2017). Metformin also appears to inhibit complex I of the electron transport chain inmitochondria, causing bioenergetic stress in cancer cells, and rendering them dependent on glycolysis for ATP production. Taken and adapted from Andrzejewski etal. Front. Endocrinol. 2018 [63]. Reused with permission.

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empagliflozin, is one example [73]. A caveat is that some otherdrug classes have been found to worsened diabetes-relatedoutcomes. It will be of interest to include outcomes of variousantidiabetes agents on cancer incidence, progression, andprognosis.

The latest trend in cancer treatment is tissue-agnostic can-cer therapy. As example, cancers found to have DNA mismatchrepair deficiencies may be good candidates for immune check-point inhibition – regardless of the origin or site of the cancer[74]. Larotrectinib, as example, targets fusion-mutations of theTRK gene and is suitable for use in any cancer type in whichthis mutation has granted uncontrolled cell growth.Larotrectinib’s targeted action showed impressive 71% dur-able responses and 55% progression-free patients in clinicalevaluation [75]. The TET2 protein, mentioned earlier in thecontext of the crosswalk between hyperglycemia and cancer,might be a good target for tissue-agnostic therapy.

Ramifications to translational medicine

We have argued that optimal management of diabetes rests inthe targeting the specific and individual pathways that give riseto the hyperglycemia in each given patient [1]. There arecurrently 11 known mediating pathways, and existing antidia-betes drugs address most of these. These include pancreaticbeta-cell dysfunction; decreased incretin effect; α-cell defect;insulin resistance arising from the liver, adipose and/or muscle;brain alterations in satiety, circadian rhythm, etc.; kidney; sto-mach/small intestine; immune dysregulation/inflammation;and, colon/gut biome [1]. Treatment of choice should factorwhich of these pathways are at work in the given patient, aswell as cancer history and risk. The best studied and mostbeneficial glucose-lowering agent to reducing cancer is met-formin. Inconclusive data exists that exogenous insulin mayalternately contribute to cancer risk and cancer outcomes. Intype 2 diabetic patient at high risk of cancer, insulin therapymight be avoided unless necessary.

Concluding remarks

Given previous observations, including the genetic common-alities between the two traits, we posit that dysmetabolismconfers long-term changes in the cell – changes that areadaptive as well as maladaptive. In beta cells, excess nutrientsand oxidative stress/ROS and its downstream outcomes con-tribute to loss of insulin manufacture and glucose-sensingcapacity. In cells of the vasculature, kidney, or retina, excessnutrients and oxidative stress/ROS leads to organ dysfunctionthat manifests as CVD, neuropathy, renal failure, and diabeticretinopathy. These common processes are detailed and mod-eled in Schwartz et al. TEM 2017 [2], and, expounded herein.

The consequences of hyperglycemia and other forms ofdysmetabolism do not stop with the classical endpoints.Mounting evidence suggest that these same dysmetabolism-driven processes may contribute to cell transformation andgrowth of tumor cells, or, at least weaken some of the intrinsicconstraints against it. In fact, agents applied against dysmeta-bolism may even serve as biomarkers – insulin, plasma

glucose, adiponectin, and leptin, are among others that havebeen proposed in this capacity [76]. In current clinical practice,this information should drive more aggressive management ofglucose – not less. The benefits reaped may well extendbeyond conventional diabetes-related complications, but tocancer prevention and management, as well.

Author contributions

S.S.S. conceived the model described. S.F.A.G. and M.E.H. criticallyreviewed, provided incisive input, edited, and approved, the final versionof the manuscript. M.E.H. also contributed moderately to synthesis of thelarger construct, and substantially to the writing of the manuscript. S.S.S. isthe guarantor of this work and as such, takes responsibility for the genesisand general framing of the models described.

Funding

S.S.S. and S.G., NIH grant R01 DK085212; S.G., Daniel B. Burke EndowedChair for Diabetes Research. No funding was received by any of authorsfor this manuscript.

Declaration of interest

S.S.S. is a speaker and advisor to Merck, Takeda, Johnson and Johnson,Boehringer Ingelheim/Eli Lilly and Company, and, a speaker forGlaxoSmithKline. S.F.A.G. and M.E.H. have no conflicts. No potential con-flicts of interest relevant to this article were reported. Peer reviewers onthis manuscript have no relevant financial or other relationships todisclose.

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