Perspectives on the bioenergetic dysregulation in insulin-resistant patients comorbid with cancer

Abstract

Insulin resistance, a pathophysiological response in metabolic syndrome, raises cancer risk. Mitochondrial dysfunction is a hallmark of cancer. The mitochondrial energetic profile of platelets in patients with cancer who have insulin resistance is unclear. Similarly, the profile of mitochondrial dysfunction in type 2 diabetes (T2-D) has not yet been published. The transmembrane protein in human adipose tissue known as dipeptidyl peptidase 4 (DPP4) is associated with T2-D secondary to obesity. Furthermore, DPP4 has been implicated in cancer pathogenesis. Studies have shown a connection between obesity and cancer. However, whether DPP4 inhibition ameliorates insulin resistance in patients with cancer has not been elucidated. This perspective aims to explore how platelet mitochondria fail in patients with cancer who have insulin resistance, discuss how blocking DPP4 might antagonize insulin resistance in cancer, and describe a cell culture model for obesity and insulin resistance. The available literature supports the proposal that patients with cancer and insulin resistance (or T2-D) have less active mitochondria in their platelets than patients with cancer without insulin resistance or healthy individuals. The platelet mitochondrial bioenergetic profile may signal early mitochondrial dysfunction in patients with cancer and insulin resistance. The proposed model is applicable to patients with T2-D and obesity.

Key Words: Insulin resistance; Platelets; Cancer; Dipeptidyl peptidase 4; Mitochondrial bioenergetics

Core Tip: This perspective proposes that among patients with cancer, those with insulin resistance exhibit reduced platelet mitochondrial bioenergetics compared with cancer patients without insulin resistance or healthy controls and that platelet mitochondrial profiling may serve as an early marker of mitochondrial dysfunction in this population. It further hypothesizes that dipeptidyl peptidase 4 inhibition may ameliorate insulin resistance in cancer patients and proposes a cell culture model to test this hypothesis. The article’s clinical relevance lies in potentially identifying non-invasive biomarkers for metabolic dysfunction in patients with cancer and exploring dipeptidyl peptidase 4 (DPP4) inhibitors as therapeutics. Strengths include the integration of cancer biology, metabolic syndrome pathophysiology, and mitochondrial bioenergetics and the proposal of testable frameworks.

INTRODUCTION

The International Diabetes Federation defines metabolic syndrome as central obesity plus any 2 of the following: Elevated plasma triglyceride levels (≥ 150 mg/dL), reduced high-density lipoprotein (< 40 mg/dL for men and < 50 mg/dL for women), increased blood pressure (≥ 130 mmHg systolic or ≥ 85 mmHg diastolic), or increased fasting plasma glucose (≥ 100 mg/dL). Accordingly, the prevalence of metabolic syndrome in the world’s population is high. Insulin resistance is a complication of metabolic syndrome and a risk factor for the development of serious complications, such as systemic hypertension. Individuals with metabolic syndrome have an increased risk of developing type 2 diabetes (T2-D), inflammation, and oxidative stress. Platelets are crucial cells in maintaining hemostasis, and their function relies on a delicate balance between activation and inactivation signaling pathways. Key regulatory pathways of platelet function include integrins, transmembrane G protein-coupled receptors, mitogen-activated protein kinases (MAPKs), the small GTPase transforming protein Ras homolog family( Rho)/Rho-associated protein kinase kinases, and thromboxane pathways. Dysregulation or failure of such pathways promotes the development of complex pathogenesis, including thrombosis[1,2], glioblastoma[3], nephrogenic diabetes insipidus[4], obesity[5,6], and lymphoma[7]. Early studies revealed the functional relevance of the interaction between platelet activation and mitochondrial oxidative phosphorylation. Platelet activation is accompanied by an increased rate of aerobic glycolysis compared with that of oxidative phosphorylation, showing changes in platelet metabolic flexibility. This perspective aims to explore how platelet mitochondria fail in cancer patients with insulin resistance, discuss how blocking DPP4 might antagonize insulin resistance in cancer, and describe a cell culture model for obesity and insulin resistance.

MOLECULAR MECHANISMS CONNECTING INSULIN RESISTANCE TO MITOCHONDRIAL DYSFUNCTION AND CANCER PROGRESSION

Tumor growth and metastasis may be facilitated by high levels of insulin, persistent inflammation, and altered cellular energy utilization linked to insulin resistance. The underlying pathways include mitochondrial dysfunction, chronic inflammation, metabolic reprogramming, and the integrated functions of the insulin/insulin-like growth factor (IGF) system. These pathways support one another in a dependent cycle. The insulin/IGF system is directly impacted by sustained hyperinsulinemia[8]. The insulin receptor (IR) and IGF-1 receptor (IGF-1R) are important components of this system. There are 2 isoforms of IR: IR-A and IR-B. IR-A is the predominant isoform in fetal tissues and is often overexpressed in cancer cells[9], whereas IR-B is the primary metabolic isoform in adult tissues. IR-A is a primary physiological receptor for IGF-2 because it not only binds insulin but also binds the powerful mitogen IGF-2 with high affinity, acting as an antitumor agent[8].

Insulin resistance and IGF-1R can be directly activated by persistent hyperinsulinemia. These receptors initiate 2 main signaling cascades upon binding. First, the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) pathway dramatically inhibits apoptosis (programmed cell death) while boosting glucose absorption, protein synthesis, and cell development[10]. The second is the Ras/MAPK pathway, which contributes to tumor growth and metastasis by mainly promoting cell motility, proliferation, and differentiation[11]. Modified IGF-axis signaling is a third pathway in which hepatic synthesis of IGF-binding proteins (IGFBP-1 and IGFBP-2) is suppressed by hyperinsulinemia, which may increase IGF-1’s1 bioavailability[12]. However, there is still disagreement regarding the direct connection between circulating IGF-1 levels and cancer risk. The relevance of the IGF-1/IGF-1R axis as a main driver of malignancy has been questioned because of the clinical failure of all IGF-1R pharmacological blockers and the inconsistent reproducibility of circulating IGF-1 levels as prognostic indicators[13].

The strong cellular and tissue growth-promoting signals (e.g., via the PI3K and MAPK pathways) brought on by hyperinsulinemia are thought to have a role in the benign proliferative stages of tumor development. When combined with other intratumoral processes required for the transition to a malignant phenotype, those signals can produce a favorable environment. As yet, there is no conclusive proof that the “benign vs malignant transformation switch” can be triggered solely by insulin or IGF-1R activation. On the other hand, IGF-2, which is frequently released by cancer cells and functions as a crucial autocrine/paracrine factor in the tumor microenvironment, has been shown to play a more direct role in tumor progression, encouraging the angiogenic switch and malignant progression[14].

INSULIN RESISTANCE AND PROLONGED INFLAMMATION

Insulin resistance is characterized by persistent mild inflammation, which is mostly caused by obesity and is a key factor in cancer induction[14]. In this condition, visceral adipose tissue overproduces pro-inflammatory cytokines, including interleukin-6 (IL-6) and tumor necrosis factor-alpha, which are consistently higher in patients with insulin resistance[15]. Nuclear factor kappa B and other inflammatory signaling pathways that support cell survival and proliferation are triggered by these cytokines[16]. This setting of ongoing inflammation promotes cancer development by producing reactive oxygen species, which lead to genetic instability and DNA damage[17]; promoting angiogenesis through vascular endothelial growth factor[18]; and suppressing immunological surveillance against tumors[19].

Adipokines, bioactive compounds released from adipose tissue, further mediate this process. Their dysregulated secretion of those substances in obesity is associated with increased leptin, which stimulates the PI3K/Akt and MAPK signaling pathways. This pro-inflammatory adipokine promotes the growth, angiogenesis, and metastasis of cancer cells[20]. Overexpression of leptin in obese individuals is associated with atypical interferon alpha secretion[21,22], thus accelerating inflammatory reactions in patients with diabetes. Likewise, ectopic expression of leptin may accelerate the unfavorable outcomes of insulin resistance in patients with diabetes comorbid with obesity and/or cancer. Further, T helper 1/toll-like receptor 3 (TLR3) enhancers might activate interferon alpha production; therefore, manipulating the expression of interferon alpha initiators (T helper 1/TLR3) may help ameliorate such inflammatory conditions. Downregulation of adiponectin, by triggering adenosine monophosphate-activated protein kinase (AMPK), stops cell division and triggers apoptosis. This anti-inflammatory adipokine often has anti-tumorigenic effects. This protective mechanism is lost when adiponectin is reduced in obesity[23]. Together with the systemic inflammation caused by insulin resistance, the imbalance between high leptin and low adiponectin produces a pro-tumorigenic environment that is highly favorable to the development and progression of metastatic cancer[24].

INSULIN RESISTANCE AND MITOCHONDRIAL DYSFUNCTION

One important mechanism connecting insulin resistance and cancer is mitochondrial dysfunction, which is both a cause of carcinogenesis and an effect of insulin resistance[25]. Impaired cellular metabolism in the insulin-resistant state places greater strain on mitochondria, which has several pro-tumorigenic effects: (1) Enhanced oxidative stress, in which mitochondrial dysfunction produces excessive reactive oxygen species. Eventually, chronic oxidative stress contributes to genomic instability that initiates cancer by damaging nuclear and mitochondrial DNA; (2) Impaired apoptosis, which is largely dependent on mitochondria, prevents cytochrome c release. This is a crucial mechanism of resistance to numerous chemotherapies in addition to promoting tumor survival. Restoring apoptotic sensitivity may be accomplished by using the BH3-only subfamily protein (BH3) mimetics, such as venetoclax, to target the BCL2 prosurvival family of proteins; and (3) Pro-inflammatory signaling, including the pyrin domain-containing protein 3 inflammasome, is activated by signals released by damaged mitochondria, adding to the chronic inflammatory state that drives the development of both insulin resistance and cancer.

EXPERIMENTAL AND HUMAN MODELS OF PLATELET INACTIVATION IN CANCER

Cancers exhibit varied energy utilization patterns over time and space, both inside and outside the body. Mitochondria and platelets play different roles in such differential patterns. Key changes in cancer metabolism help tumors grow and survive. These include increased sugar uptake, higher glutamine utilization, and increased fatty acid production. This metabolic deregulation halts the body’s natural cancer-fighting responses. High sugar levels reduce mitochondrial function. Studies have found that platelets can transfer their mitochondria to cancer cells. This transfer, through small sacs called microparticles, changes the energy utilization of breast cancer cells. Cells that readily accepted these microparticles exhibited higher oxygen consumption. They also had more adenosine triphosphate[26].

As shown in Figure 1, platelet activation links diabetes and tumor growth. Platelets accelerate tumor metastasis, but the exact mechanism remains unclear. They do this by triggering the epithelial-mesenchymal transition of tumor cells[27]. One study examined hepatocellular carcinoma metastasis. Platelets caused hepatocellular carcinoma metastasis by affecting the cancer cells’ (Toll-like Receptor4) TLR4/A-disintegrin and metalloproteinase domain-containing protein 10 (ADAM10)/chemokine (C-X3-C motif) ligand 1 pathway. Blocking this pathway prevented platelets from promoting lung metastasis. The study observed increased ADAM10 levels in hepatocellular carcinoma cells with more platelets. This associated with the worse patient outcomes. They tested the TLR4/nuclear factor kappa B pathway. ADAM10 released chemokine (C-X3-C motif) ligand 1. This molecule then attached to C-X3-C R1. This process induced epithelial-mesenchymal transition and activated RhoA signaling in cancer cells. Blocking TLR4 or ADAM10 prevented platelet transfer to tumor cells. It also blocked cancer cells from invading and making blood vessels leaky. This was confirmed using mouse models. Platelets accelerate tumor metastasis through this pathway[28]. Separately, another team developed a method to separate platelets. This method aimed to prevent platelets from adhering to tumor cells and to reduce metastasis. They placed tissue plasminogen activator on platelet decoys. These platelets were freeze-dried. They tested both systems. The treated platelets maintained tissue plasminogen activator activity, bound to tumor cells, and broke up tumor cell clumps. The tissue plasminogen activator-decoy reduced tumor size and improved survival[29].

Figure 1 Schematic presentation of the interplay between factors predisposing to insulin resistance and activated platelets in patients with diabetes comorbid with cancer. Insulin deficiency and other factors contributing to metabolic syndrome precipitate insulin resistance. This, together with increased reactive oxygen species and reduced nitric oxide and prostaglandin E1 and E2 functions, can activate platelet aggregation and the release of microparticles, proteins, and metabolites that promote proteolysis and inflammation. Such a microenvironment promotes neoplastic tissue remodeling and tumor progression. Further, circulating cancer cells facilitate platelet aggregation. Circulating tumor thrombi protect circulating tumor cells from immune cell attack. Tumor thrombi accelerate cancer cell invasion, epithelial-mesenchymal transition, and tumor plasticity. Tumor invasion and entry into the vasculature and subsequent proliferation in endothelial cells promote tumor progression. In hepatocellular carcinoma, blocking ADAM10 and knocking down TLR4 inhibited tumor growth and blocked metastasis. The roles of ACE2/RAS, DPP4, MPO, NETs, IL-37, and NOD-like receptor family pyrin domain-containing protein 3 inflammasomes in cancer progression remain unclear. Areas of research presented with question marks are to be investigated. ACE2/RAS: Angiotensin-converting enzyme 2/renin-angiotensin system; ADAM10: A-disintegrin and metalloproteinase domain-containing protein 10; ADP: Adenosine diphosphate; DPP4: Dipeptidyl peptidase 4; EMT: Epithelial-mesenchymal transition; IL: Interleukin; MPO: Myeloperoxidase; NET: Neutrophil extracellular trap; NK: Natural killer cell; NLRP3: NOD-like receptor family pyrin domain-containing protein 3; NO: Nitric oxide; PDGF: Platelet-derived growth factor; PGE1: Prostaglandin E1; PGE2: Prostaglandin E2; ROS: Reactive oxygen species; T1-D: Type 1 diabetes; T2-D: Type 2 diabetes; TGF: Transforming growth factor; Th1: T helper 1; TLR: Toll-like receptor; VEGF: Vascular endothelial growth factor.

For a long time, inactivating platelet function was the approach of choice to block platelet-tumor interactions. Bleeding was one of the drawbacks associated with traditional methods of inactivating platelets. Hence, novel strategies to block platelet-tumor interactions without affecting platelet function were developed, based on blocking platelet energy metabolism through reprogramming of platelet glycolysis. Kulkarni et al[30] examined how energy utilization in platelets changes. They looked at using small molecules as a new antiplatelet tactic for heart attacks, strokes, and blood clots in the legs and lungs. They explained how sugar utilization and fat burning affect blood clots. They tested drugs that block fat burning, including etomoxir, trimetazidine, and oxfenicine. They used these drugs on resting platelets and platelets activated by thrombin. In all cases, energy production from cell respiration failed. Trimetazidine and oxfenicine reduced platelet clumping. They also decreased P-selectin release and integrin activation. Etomoxir and trimetazidine blocked dense granule release. They also stopped platelet plugs from forming on collagen. This occurred under high blood flow. Fat burning was required for energy in activated platelets. It was also crucial for platelet actions triggered by signals. In short, blocking fat burning offers a promising way to prevent clots[31].

Platelet membrane-hybridized liposomes were used in other studies. These liposomes carried quercetin and shikonin. They blocked lactate transporter monocarboxylase 4. They also blocked the enzyme pyruvate kinase subtype 2 in both healthy and cancer cells. This delivery system successfully stopped platelets from interacting with tumors. Further, because this system is attached to circulating tumor cells, it reduced the ability of circulating tumor cells to metastasize in laboratory tests. It also slowed primary tumor growth in living subjects. The authors proposed that inactivating platelets could affect the tumor’s immune environment. This could be done by reducing regulatory T cells. It could also boost cytotoxic T cells[27]. In 2024, a study by Kong et al[32] focused on calcium release from the platelet endoplasmic reticulum. It examined how this affects cancer cell metabolism and growth. The research aimed to investigate proteins called disulfide isomerases. The latter are chaperones that move to the cell surface when the endoplasmic reticulum is stressed. Their data support the endoplasmic reticulum regulation of platelet function, although the exact mechanism is still unclear.

A study by the National Human Genome Research Institute revealed new findings. The clinical trial NCT03854318, which included 214 people from early 2019 to late 2021, was a natural history study. It showed that RUNX1 variant changes cause familial platelet disorder with associated myeloid malignancy. The latter is an inherited platelet disorder that reduces platelet counts, dysregulates their function, and increases the risk of blood cancers[33]. Tutuianu et al[34] analyzed gene activity in tiny sacs from blood platelets of patients with T2-D. These sacs promoted cancer progression, especially breast cancer growth. Laboratory tests showed that these sacs were taken up by triple-negative breast cancer cells. When mixed with cancer cells, sacs from patients with T2-D increased markers of cell transformation and invasion. This differed from sacs from healthy people. A study of obese children and teens found a link between circulating microvesicles and energy utilization. Protein studies found many changes in microvesicles. These proteins affect the body’s first defense. They also affect how blood platelets release their contents. This can change how the body handles fat and sugar. It impacts muscle growth and heart health. It also relates to swelling and the body’s defense system. Cancer growth may also be affected[35].

BIOENERGETICS OF PLATELET MITOCHONDRIA

Conventionally, assessment of the bioenergetic profile that reflects mitochondrial function has been performed through muscle biopsies, an invasive technique with known limitations in the clinical setting. Mitochondria are ubiquitous in peripheral blood platelets, which are a non-invasive model for assessing mitochondrial function[36,37]. Individuals with a family history of diabetes have significantly lower platelet mitochondrial bioenergetics than healthy subjects without a family history of diabetes[38]. Diabetes induces changes in oxidative metabolism in animal models and clinical studies[39-41], as well as proteome changes throughout development[42]. Such proteome changes are associated with endocrine imbalance and epigenetic regulation of protein misfolding[43]. The protein networks linking Warburg and reverse Warburg effects to cancer cell metabolism have been reviewed[44]. The association between microRNA (miRNA) in monocytes and mitochondrial dysfunction in patients with metabolic syndrome comorbid with cancer remains to be determined. Diabetes and metabolic syndrome share common interrelated pathogenesis, etiology, and risk factors. This section of the review specifically aims to provide better insights into the pathogenesis of insulin resistance in patients with T2-D and cancer, focusing on platelet mitochondria, and to shed light on current studies that link platelet activation to cancer.

Among patients with T2-D, those with cancer share a common pathogenesis of insulin resistance seen in cancer-free patients; however, they may still exhibit different platelet mitochondrial bioenergetic patterns compared with cancer-free patients with diabetes, healthy adults without cancer, or healthy adults without a family history of T2-D. Early markers of diabetes in platelet mitochondria of patients with cancer, compared with euglycemic adults with cancer, can be studied in a prospective cohort of 5 groups. We propose a 5-group cohort study (n = 5-10/group) to measure platelet basal and maximal respiration as primary endpoints. Explicit exclusion criteria are recent infections, other metabolic disorders, and medications known to affect platelet function. The 5 groups are: (1) Adults diagnosed with T2-D; (2) Sex- and age-matched adults with T2-D and cancer; (3) Sex and age-matched adults with cancer and a first-degree family history of T2-D; (4) Sex- and age-matched adults with normal glucose and a first-degree family history of T2-D; (5) Sex- and age-matched adults with normal glucose and no family history of T2-D; and (6) Patients with cancer but without T2-D. A model involving the collection of 5-10 mL of non-fasting blood from each group is shown in Supplementary Figure 1.

A PROTOCOL FOR PLATELET ACQUISITION AND PREPARATION

Plasma-containing platelets are separated by centrifugation (200 × g for 15 minutes) at room temperature. Platelets are isolated using additional centrifugation at 2500 × g for 10 minutes and then counted by microscopy. Monocytes are separated from blood cells using Ficoll-Hydroplaque as previously described[45]. Classically, the bioenergetic pattern of platelet mitochondria is measured using a high-resolution Oxygraph-2k (Oroboros Instruments, Innsbruck, Austria[46]). The technique is the gold standard for recording platelet mitochondrial respirometry at a constant temperature of 37 °C. Conventionally, data are recorded with DatLab software 4.3, with the sampling rate set to 2 seconds. A 2-mL fresh platelet suspension in mitochondrial respiratory medium is incubated in the chambers of the Oxygraph-2k at a concentration of 100 × 10⁶ platelets/mL, with stirring. Potent uncouplers of mitochondrial oxidative phosphorylation, such as carbonylcyanide-p-trifluoromethoxyphenylhydrazone, oligomycin, rotenone, and antimycin-A, are added in consecutive order, as described previously[36]. Primary outcome measures include platelet mitochondrial basal and maximal respiration, adenosine triphosphate-based respiration, non-mitochondrial respiration, efficiency of coupling, respiratory control ratio, and spare respiratory capacity[47]. A secondary outcome is a correlation analysis of bioenergetics vs miRNA expression, as briefly discussed in the following section.

miRNA PROFILE IN MONOCYTES OF PATIENTS WITH CANCER AND T2-D

The proposed approaches can be demonstrated using total RNA. Monocytes are used to isolate total RNA. A statistically appropriate sample size that achieves 85% power, minimizes type I and type II error rates while accounting for biological heterogeneity, and minimizes bias is at n = 3-6. This effect size estimate is based on published data[21]. Subjects comprise individuals with or without T2-D or a family history of T2-D, with body mass index-matching criteria, as described in the groups above. miRNA sequencing is conducted to determine the miRNA profile in monocytes from the above cohort with or without T2-D or a family history of T2-D and is then compared with the platelet mitochondrial bioenergetic pattern. Eventually, selected miRNAs in monocytes from patients with and without T2-D or a family history of T2-D are assessed using real-time polymerase chain reaction.

DATA VALIDATION, SAMPLE SIZE, AND ENDPOINT ASSESSMENT OF PLATELET MITOCHONDRIAL BIOENERGETIC PATTERN

The primary endpoint is basal respiration in platelet mitochondria among cancer patients with T2-D, cancer patients who have a first-degree family history of T2-D, cancer patients without T2-D. Although no primary data have been published at present, a difference in the means between healthy adults with a first-degree family history of T2-D and those without a family history is expected. To achieve a powerful model, the expected within-group standard deviation is 25.5 pmol O₂/10⁶ platelets. The sample size at α = 0.05 and β = 0.8 is 5/group. The sample size is achievable in the proposed study. The results may demonstrate that the platelet mitochondrial bioenergetic profile in cancer patients with T2-D is lower than that in diabetes-free patients with cancer or normal controls. Reduced platelet mitochondrial respiration may be associated with altered miRNA expression in their monocytes. The platelet mitochondrial bioenergetic profile may be used as an early marker of platelet mitochondrial dysfunction in patients with insulin resistance and patients with T2-D comorbid with cancer.

ANGIOTENSIN-CONVERTING ENZYME 2 (ACE2)/RENIN ANGIOTENSIN SYSTEM (RAS) AND DPP4 IN T2-D

Human DPP4 has been associated with obesity-related T2-D. DPP4 is a serine protease that rapidly inactivates glucagon-like peptide-1. Glucagon-like peptide-1 is a glucose-dependent insulinotropic polypeptide and an incretin hormone that plays key role in modulating insulin resistance. ACE2 in adipose cells acts as a key enzymatic regulator of the local RAS. ACE2 functions as an enzyme that breaks down the vasoconstrictor peptide angiotensin 2 into the protective vasodilator angiotensin AT 1-7, counterbalancing the harmful effects of the conventional ACE/angiotensin II pathway. AT 1-7 play a major role in the attenuation of metabolic syndrome, enhancing glucose uptake and also protecting the cells against oxidative stress that can induce insulin resistance. Further, ACE2, a signaling receptor for RAS, is mainly expressed in human white pre-adipocytes (HWPs) and consequently activates the RAS. Elevated ACE2 reduces hyperglycemia in diabetic rats[48]. Overall activation of the ACE/RAS axis is a key player in the pathophysiology of obesity and insulin sensing[49]. ACE inhibitors are antihypertensive drugs with a well-known ability to improve insulin sensitivity and reduce the development of new-onset T2-D[50]. Several observations suggest that RAS and glucagon-like peptide-1/DPP4 could possibly share a common inhibitor[51].

DPP4 INHIBITION AS AN ANTAGONIST OF INSULIN RESISTANCE IN PATIENTS WITH T2-D COMORBID WITH CANCER

ACE2/RAS signaling is central to the pathogenesis of obesity and insulin resistance[49]. CD26 is a cell-surface form of DPP4 that can costimulate T-cell proliferation, suggesting that DPP4 inhibitors might adversely affect immune functions. The role of ACE2/RAS and DPP4 in cancer remains to be elucidated. The ACE2 receptor is ubiquitous in HWPs and activates the RAS[48]. DPP4 is associated with T2-D secondary to obesity[50]. Vildagliptin is a DPP4 inhibitor that was approved by the European Medicines Agency at a dose of 100 mg/day. Vildagliptin-mediated inhibition of DPP4 was associated with a significant decrease in the oxidative stress marker nitrotyrosine and the inflammatory markers IL-6 and IL-18. DPP4 inhibition improved the unfavorable pro-inflammatory/anti-inflammatory phenotypes of peripheral blood monocytes in patients with diabetes[52,53]. However, the role of ACE2/RAS and DPP4 in cancer or insulin resistance remains to be elucidated. DPP4 inhibition may antagonize insulin resistance in patients with cancer. One of the current research objectives is to test the efficacy of targeting DPP4 and the resultant impact on obesity and insulin resistance in vitro. A specific aim is to test the impact of DPP4 inhibition on the ACE2/RAS pathway and the cellular response to insulin resistance in patients who have cancer with or without obesity.

DPP4 INHIBITION IN A CELL CULTURE MODEL OF OBESITY AND INSULIN RESISTANCE

Mouse models cannot exactly mimic all aspects of human metabolic syndrome. For this reason, studying obesity and insulin resistance that coincide with human disease in commercially available primary HWPs is a suitable approach. HWPs are isolated from adult subcutaneous or visceral adipose tissues. The effect of DPP4 inhibition on the ACE2/RAS axis can be assessed using a positive control group, such as HWP cell cultures treated with 5 mg, 25 mg, and 50 mg final concentration of vildagliptin, or short hairpin RNA specific for silencing DPP4. The negative control is an untreated HWP cell culture. In such a model, cells are seeded in 6-well plates. Confluent cultures of HWPs in Dulbecco’s Modified Eagle Medium are supplemented with 10% fetal bovine serum, penicillin, and streptomycin. Cultures are maintained under a 95% humidified atmosphere containing 5% carbon dioxide at 37 °C. In a parallel experiment, DPP4-silencing short hairpin RNA is added, and cells are co-incubated for 0, 4, 8, 12, and 24 hours. An equal volume of medium serves as the negative control. At the end of the experiment, extracts of HWP positive controls and untreated HWPs (negative controls) are collected for the determination of DPP4 inhibition by immunoblotting. The protein concentration is measured using a protein assay kit at 562 nm with a plate reader. Dose-response curves can be generated in vitro. A correlation between DPP4 levels and readouts for functional metabolic parameters can be concluded using metabolomic analysis. Examples include glucose uptake assays, insulin signaling (phospho-AKT/IR substrate 1), mitochondrial respiration, and relevant cancer phenotypes (proliferation, migration, and epithelial-mesenchymal transition markers).

FUTURE RESEARCH

Myeloperoxidase (MPO) levels and neutrophil extracellular traps (NETs) in patients with obesity

Human MPO is a peroxidase enzyme and lysosomal protein encoded by the MPO gene on chromosome 17. MPO is ubiquitously expressed in neutrophils. Higher levels of neutrophils have been observed in patients with obesity, possibly rendering neutrophil recruitment during an inflammatory process more potent than in patients with normal body mass index[54]. The neutrophil extracellular traps (NETs) are networks of extracellular fibers, primarily composed of DNA from neutrophils, that bind pathogens. The presence of neutrophil aggregates constitutes a characteristic histopathological feature of patients with severe obesity, and a higher number of thromboembolic events has been reported[55]. Whether NETs aggregation is higher than normal or MPO is upregulated in patients with cancer is still unknown.

A new research perspective is to use double-negative T cells (CD4-CD8-) in patients with insulin resistance secondary to T2-D, hypertension, or obesity and test whether activation of metabolic dendritic T cells, followed by their re-transplantation as a spontaneous immune-activating strategy, may combat dysregulated NETs and MPO. The nucleotide-binding oligomerization domain- and leucine-rich repeat-family of pyrin domain-containing protein 3 inflammasomes may play the same counter-regulatory role. If the above proposed molecular tools prove successful in combating dysregulated NETs and MPO, the same model can be reproduced using cancer cell lines. Identifying putative antioxidants that upregulate the inhibition of the inflammatory signaling complex as a strategy to improve the quality of life of patients with cancer comorbid with metabolic syndrome is worthwhile.

Proteomics and metabolomics approaches

The ultimate goal of proteomics and metabolomics approaches is to identify tumor-associated changes in the proteome and metabolome using a mass spectrometry-based open screening strategy. Studies publishing such data lead to numerous physiological advances, such as: (1) Identification of new biomarkers for early prognosis and monitoring of cancers; (2) Using the identified hits for high-throughput screening of the malignant phenotype; (3) Development of workflows and data analysis strategies using bioinformatics platforms. Proteomic profiling of patients with cancer provides a global overview of protein deregulation. Building a proteomics data repository for several types of cancers would provide better insights into protein alterations in such cancers; (4) Identification of early prognostic biomarkers, especially in tumors with high metastatic rates such as Ewing’s sarcoma; (5) Metaproteomics analysis of the crosstalk between the host and microbiome and the role of the latter in disease development; and (6) Analysis of how the microbiome-host interaction impacts the metaproteome. A novel perspective is to reduce the mean amplitude of glycemic excursions, oxidative stress, and systemic inflammatory markers concomitantly in patients with insulin resistance secondary to obesity. This can be achieved through macrophage polarization associated with a shift in metabolic programs. Quantified measures could include amino acids, glucose, lipids, mediators of iron metabolism, lipid oxidative metabolism, the energy sensor 5’ AMPK, the mammalian target of rapamycin pathway, and finally, plasticity of macrophage polarization. Further studies could investigate the effects on systemic inflammation and pro-inflammatory/anti-inflammatory-like phenotypes of peripheral blood monocytes in patients with insulin resistance secondary to obesity. CD26 can costimulate T-cell proliferation, raising the possibility that DPP4 inhibitors might adversely affect immune function. A flow cytometric analysis is a suitable platform for such studies. Specific biomarkers such as the immunoregulatory family of peptides IL-1 control lymphocyte proliferation, differentiation, and effector function. IL-37, a member of the IL-1 family, exerts anti-inflammatory effects by suppressing innate immune responses through attenuating the production of pro-inflammatory cytokines such as tumor necrosis factor alpha, IL-1α, IL-1β, and IL-6. Serum IL-37 levels are measured using enzyme-linked immunosorbent assay.

Significance and translational potential

Patients with metabolic syndrome comorbid with cancer are among the most marginalized. The objectives of this perspective closely link patients’ health and familial chronic diseases. It investigates early markers of metabolic syndrome in platelets of patients with cancer. If the above-described in vitro approaches demonstrate significant DPP4 inhibition and relevance to insulin resistance, this model can be reproduced in vivo. The proposed model is suitable for translational studies and hence is very likely to achieve sustainability. This perspective addresses the complex interplay of platelet bioenergetic profiling in patients with cancer who have predisposing factors for metabolic syndrome, such as T2-D and obesity. The suggested models may help with early prognosis and prevention to avoid the accelerated development of metabolic syndrome-associated complications.

LIMITATIONS AND FUTURE STUDIES

State-of-the-art mass spectrometry technology, flow cytometry, and liquid chromatography-tandem mass spectrometry remain limited resources in developing nations despite their importance in identifying new specific biomarkers for early prognosis and monitoring cancer-associated bioenergetic deregulation. Studying a single protein in an individual or single disease limits our current understanding of i) how this protein interacts with or contributes to platelet function, ii) how genetic modulation and epigenetic modifications of proteins may integrate in reprogramming metabolic processes such as glycolysis to therapeutically target cancer cells. By contrast, comprehensive proteomic analysis of diverse patient populations across disease stages is more conclusive. Building a proteomics data repository for several types of cancers in individuals with insulin resistance would provide better insights into protein function and metabolic alterations in such cases. Through metabolomics approaches for studying platelets in cancer, clinical outcome studies of DPP4 inhibitors in patients with cancer comorbid with diabetes are informative. Through metaproteomics approaches, the crosstalk between the host and microbiome and the role of the latter in disease development can be investigated. This study recommends further investigation into reducing the mean amplitude of glycemic excursions, oxidative stress, and systemic inflammatory markers in patients with T2-D, particularly those with concurrent insulin resistance and obesity. Inflammation-induced metabolic shifts in amino acids, glucose, lipids, iron, lipid oxidative metabolism, and the bioenergetic sensors AMPK and mammalian target of rapamycin should provide more insight into metabolic deregulation associated with such comorbidities. Studying CD26 regulation provides better insight into the impact of DPP4 inhibition on T-cell proliferation, systemic inflammation, and pro-inflammatory/anti-inflammatory-like phenotypes of monocytes in patients with diabetes. Research should explore secondary metabolites as nutritional supplements that strengthen the immune system and reduce vulnerability to oxidative stress. Different formulations of such metabolites should be easily applicable to older adults and patients with diabetes, obesity, or cancer.

CONCLUSION

Based on findings in non-cancer diabetic populations, the platelet mitochondrial bioenergetic profile is a non-invasive biomarker for measuring platelet bioenergetics. This pattern may serve as a biomarker for metabolic dysfunction in patients with diabetes comorbid with cancer as well. DPP4 inhibition may improve platelet mitochondrial function or cancer outcomes.