Mathematical Modeling of the Function of Warburg Effect in Tumor Microenvironment

IGF2BP1 accelerates the aerobic glycolysis to boost its immune escape in hepatocellular carcinoma microenvironment

Introduction

Energy metabolism abnormity emerges as a crucial factor that facilitates tumorigenesis by accelerating aerobic glycolysis. However, the function of N6-methyladenosine (m6A) on hepatocellular carcinoma (HCC) aerobic glycolysis and immune escape is still unclear. Here, this investigation was intended to elucidate the regulation of m6A 'reader' IGF2BP1 involved in HCC aerobic glycolysis and immune escape.

Methods

The aerobic glycolysis was tested by glucose uptake, lactate, ATP generation and ECAR. The CD8+ T cell-mediated killing effect was tested by cytotoxicity, IFN-γ and granzyme B. The molecular interaction was confirmed by luciferase reporter assay, immunoprecipitation assay and chromatin immunoprecipitation (ChIP)-PCR.

Results

Elevated IGF2BP1 expression was associated with poor prognosis in HCC patients. Functionally, IGF2BP1 emerged as an oncogenic factor that accelerated HCC aerobic glycolysis (glucose uptake, lactate, ATP generation and ECAR) and oxaliplatin resistance. Meanwhile, IGF2BP1 repressed the activated CD8+ T cell-mediated killing effect (cytotoxicity, IFN-γ and granzyme B) and apoptosis of HCC cells, indicating a suppressed cytotoxic T-cell response. By recognizing and binding to the m6A-modified sites on c-Myc mRNA, IGF2BP1 enhanced the stability of c-Myc mRNA, consequently upregulating c-Myc expression. In addition, transcription factor c-Myc targeted the programmed death ligand 1 (PD-L1) promoter region to strengthen its transcription.

Discussion

Taken together, this study illustrates IGF2BP1 as a potential therapeutic target in HCC, aiming to disrupt the interplay between aberrant metabolism and immune escape.

Bone marrow mesenchymal stem cell-derived exosomes improve cancer drug delivery in human cell lines and a mouse osteosarcoma model

Introduction

Osteosarcoma is the most common primary bone tumor. Patients require chemotherapy drugs with high-targeting ability and low off-target toxicity to improve their survival. Exosomes are biological vesicles that mediate long-distance communication between cells and naturally target their source sites. Exosomes derived from bone marrow mesenchymal stem cells (BMSCs) naturally target bone tumor sites, suggesting their potential as effective anti-tumor therapy vectors. In this study, we evaluated the potential of BMSC-derived exosomes in targeting osteosarcoma and serving as a carrier for doxorubicin (DOX).

Methods

We isolated exosomes from human BMSCs and synthesized hybrid exosomes (HEs) by fusing these exosomes with liposomes. These HEs were loaded with DOX to produce a novel drug, HE/DOX.

Results

We confirmed the successful synthesis of HE/DOX using fluorescence spectroscopy and estimated its size to be 151.1 ± 10.2 nm. HEs expressed the known exosomal proteins ALIX, CD63, and TSG101. Under acidic conditions similar to those observed in the tumor microenvironment, the drug release from HE/DOX was enhanced. In osteosarcoma cell lines and in a mouse osteosarcoma model, HE/DOX exhibited stronger tumor-inhibitory effects than free DOX.

Conclusions

Our study demonstrates that BMSC-derived exosomes could effectively target osteosarcoma. Furthermore, HEs can serve as effective carriers of DOX, enabling the treatment of osteosarcoma. These findings highlight a promising direction for tumor-targeted therapy.

Computational model of the cancer necrotic core formation in a tumor-on-a-chip device

The mechanisms underlying the formation of necrotic regions within avascular tumors are complex and poorly understood. In this paper, we investigate the formation of a necrotic core in a 3D tumor cell culture within a microfluidic device, considering oxygen, nutrients, and the microenvironment acidification by means of a computational-mathematical model. Our objective is to simulate cell processes, including proliferation and death inside a microfluidic device, according to the microenvironmental conditions. We employed approximation utilizing finite element models taking into account glucose, oxygen, and hydrogen ions diffusion, consumption and production, as well as cell proliferation, migration and death, addressing how tumor cells evolve under different conditions. The resulting mathematical model was examined under different scenarios, being capable of reproducing cell death and proliferation under different cell concentrations, and the formation of a necrotic core, in good agreement with experimental data reported in the literature. This approach not only advances our fundamental understanding of necrotic core formation but also provides a robust computational platform to study personalized therapeutic strategies, offering an important tool in cancer research and treatment design.

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

Metabolic symbiosis between oxygenated and hypoxic tumour cells: An agent-based modelling study

Deregulated metabolism is one of the hallmarks of cancer. It is well-known that tumour cells tend to metabolize glucose via glycolysis even when oxygen is available and mitochondrial respiration is functional. However, the lower energy efficiency of aerobic glycolysis with respect to mitochondrial respiration makes this behaviour, namely the Warburg effect, counter-intuitive, although it has now been recognized as source of anabolic precursors. On the other hand, there is evidence that oxygenated tumour cells could be fuelled by exogenous lactate produced from glycolysis. We employed a multi-scale approach that integrates multi-agent modelling, diffusion-reaction, stoichiometric equations, and Boolean networks to study metabolic cooperation between hypoxic and oxygenated cells exposed to varying oxygen, nutrient, and inhibitor concentrations. The results show that the cooperation reduces the depletion of environmental glucose, resulting in an overall advantage of using aerobic glycolysis. In addition, the oxygen level was found to be decreased by symbiosis, promoting a further shift towards anaerobic glycolysis. However, the oxygenated and hypoxic populations may gradually reach quasi-equilibrium. A sensitivity analysis using Latin hypercube sampling and partial rank correlation shows that the symbiotic dynamics depends on properties of the specific cell such as the minimum glucose level needed for glycolysis. Our results suggest that strategies that block glucose transporters may be more effective to reduce tumour growth than those blocking lactate intake transporters.

Exosome engineering for efficient and targeted drug delivery: Current status and future perspective

Exosomes are membrane-bound vesicles that are released by most cells. They carry nucleic acids, cytokines, growth factors, proteins, lipids, and metabolites. They are responsible for inter- and intracellular communications and their role in drug delivery is well defined. Exosomes have great potential for therapeutic applications, but the clinical use is restricted because of limitations in standardized procedures for isolation, purification, and drug delivery. Bioengineering of exosomes could be one approach to achieve standardization and reproducible isolation for clinical use. Exosomes are important transporters for targeted drug delivery because of their small size, stable structure, non-immunogenicity, and non-toxic nature, as well as their ability to carry a wide variety of compounds. These features of exosomes can be enhanced further by bioengineering. In this review, possible exosome bioengineering approaches, their biomedical applications, and targeted drug delivery are discussed.

A physicochemical model of X-ray induced photodynamic therapy (X-PDT) with an emphasis on tissue oxygen concentration and oxygenation

X-PDT is one of the novel cancer treatment approaches that uses high penetration X-ray radiation to activate photosensitizers (PSs) placed in deep seated tumors. After PS activation, some reactive oxygen species (ROS) like singlet oxygen (1O2) are produced that are very toxic for adjacent cells. Efficiency of X-PDT depends on 1O2 quantum yield as well as X-ray mortality rate. Despite many studies have been modeled X-PDT, little is known about the investigation of tissue oxygen content in treatment outcome. In the present study, we predicted X-PDT efficiency through a feedback of physiological parameters of tumor microenvironment includes tissue oxygen and oxygenation properties. The introduced physicochemical model of X-PDT estimates 1O2 production in a vascularized and non-vascularized tumor under different tissue oxygen levels to predict cell death probability in tumor and adjacent normal tissue. The results emphasized the importance of molecular oxygen and the presence of a vascular network in predicting X-PDT efficiency.

RFC2 promotes aerobic glycolysis and progression of colorectal cancer

BACKGROUND

Replication factor C subunit 2 (RFC2) participates in the growth and metastasis of various malignancies. Our study investigated the roles of RFC2 in colorectal cancer (CRC).

RESULTS

RFC2 expression was upregulated in CRC tissues and cells. High RFC2 expression was associated with poor prognosis. Knockdown RFC2 inhibited proliferation, induced apoptosis, and suppressed migration and invasion of CRC cells. CREB5 was a transcription factor of RFC2, and CREB5 knockdown suppressed RFC2 expression. Furthermore, RFC2 promoted aerobic glycolysis and MET/PI3K/AKT/mTOR pathway.

CONCLUSION

RFC2 promoted the progression of CRC cells via activating aerobic glycolysis and the MET/PI3K/AKT/mTOR pathway.

DDQN-based optimal targeted therapy with reversible inhibitors to combat the Warburg effect

We cover the Warburg effect with a three-component evolutionary model, where each component represents a different metabolic strategy. In this context, a scenario involving cells expressing three different phenotypes is presented. One tumour phenotype exhibits glycolytic metabolism through glucose uptake and lactate secretion. Lactate is used by a second malignant phenotype to proliferate. The third phenotype represents healthy cells, which performs oxidative phosphorylation. The purpose of this model is to gain a better understanding of the metabolic alterations associated with the Warburg effect. It is suitable to reproduce some of the clinical trials obtained in colorectal cancer and other even more aggressive tumours. It shows that lactate is an indicator of poor prognosis, since it favours the setting of polymorphic tumour equilibria that complicates its treatment. This model is also used to train a reinforcement learning algorithm, known as Double Deep Q-networks, in order to provide the first optimal targeted therapy based on experimental tumour growth inhibitors as genistein and AR-C155858. Our in silico solution includes the optimal therapy for all the tumour state space and also ensures the best possible quality of life for the patients, by considering the duration of treatment, the use of low-dose medications and the existence of possible contraindications. Optimal therapies obtained with Double Deep Q-networks are validated with the solutions of the Hamilton-Jacobi-Bellman equation.

Targeting endothelial permeability in the EPR effect

The characteristics of the primary tumor blood vessels and the tumor microenvironment drive the enhanced permeability and retention (EPR) effect, which confers an advantage towards enhanced delivery of anti-cancer nanomedicine and has shown beneficial effects in preclinical models. Increased vascular permeability is a landmark feature of the tumor vessels and an important driver of the EPR. The main focus of this review is the endothelial regulation of vascular permeability. We discuss current challenges of targeting vascular permeability towards clinical translation and summarize the structural components and mechanisms of endothelial permeability, the principal mediators and signaling players, the targeted approaches that have been used and their outcomes to date. We also critically discuss the effects of the tumor-infiltrating immune cells, their interplay with the tumor vessels and the impact of immune responses on nanomedicine delivery, the impact of anti-angiogenic and tumor-stroma targeting approaches, and desirable nanoparticle design approaches for greater translational benefit.

Computational simulations of tumor growth and treatment response: Benefits of high-frequency, low-dose drug regimens and concurrent vascular normalization

Implementation of effective cancer treatment strategies requires consideration of how the spatiotemporal heterogeneities within the tumor microenvironment (TME) influence tumor progression and treatment response. Here, we developed a multi-scale three-dimensional mathematical model of the TME to simulate tumor growth and angiogenesis and then employed the model to evaluate an array of single and combination therapy approaches. Treatments included maximum tolerated dose or metronomic (i.e., frequent low doses) scheduling of anti-cancer drugs combined with anti-angiogenic therapy. The results show that metronomic therapy normalizes the tumor vasculature to improve drug delivery, modulates cancer metabolism, decreases interstitial fluid pressure and decreases cancer cell invasion. Further, we find that combining an anti-cancer drug with anti-angiogenic treatment enhances tumor killing and reduces drug accumulation in normal tissues. We also show that combined anti-angiogenic and anti-cancer drugs can decrease cancer invasiveness and normalize the cancer metabolic microenvironment leading to reduced hypoxia and hypoglycemia. Our model simulations suggest that vessel normalization combined with metronomic cytotoxic therapy has beneficial effects by enhancing tumor killing and limiting normal tissue toxicity.

Modeling and simulation of smart magnetic self-assembled nanomicelle trajectories in an internal thoracic artery flow for breast cancer therapy

Magnetic drug targeting (MDT) is one of the most modern techniques in cancer therapy for its ability to reduce the side effects of chemotherapy experienced by systemic drug administration. In this study, a comprehensive mathematical model has been developed to predict the drug particle trajectories of anticancer dasatinib magnetic nanomicelles (DAS-MNM) released in an internal thoracic artery (ITA) blood flow for breast cancer therapy using an external magnetic field. Several factors are investigated in regard to the efficiency of MDT through the ITA, including magnetic field strength (MFS), relative magnetic permeability, magnet size, drug particle size, and initial position of drug particle. The drug particle trajectory results confirmed the successful MDT using an external magnetic field with a capture efficiency of more than 90%. This was achieved by employing a wide range of particle sizes of DAS-MNM close to the external magnetic field source at the arterial wall than in other positions. Moreover, the results showed that the number of trapped particles increased with increasing both MFS and drug particle diameter within the target tissue, while the drug particle permeability did not have a considerable effect on the particle retention. In addition, for achieving a successful drug/cargo delivery through the arteries, the magnetic field, the particle size, and the initial release locations should be adjusted simultaneously. The present work offers insights into the critical factors in MDT with a significant impact on breast cancer therapy, tissue engineering, and regenerative medicine. Magnetic drug targeting model of anticancer dasatinib magnetic nanomicelles (DAS-MNM) released in an internal thoracic artery blood flow for breast cancer therapy.

Hybrid computational models of multicellular tumour growth considering glucose metabolism

Cancer cells metabolize glucose through metabolic pathways that differ from those used by healthy and differentiated cells. In particular, tumours have been shown to consume more glucose than their healthy counterparts and to use anaerobic metabolic pathways, even under aerobic conditions. Nevertheless, scientists have still not been able to explain why cancer cells evolved to present an altered metabolism and what evolutionary advantage this might provide them. Experimental and computational models have been increasingly used in recent years to understand some of these biological questions. Multicellular tumour spheroids are effective experimental models as they replicate the initial stages of avascular solid tumour growth. Furthermore, these experiments generate data which can be used to calibrate and validate computational studies that aim to simulate tumour growth. Hybrid models are of particular relevance in this field of research because they model cells as individual agents while also incorporating continuum representations of the substances present in the surrounding microenvironment that may participate in intracellular metabolic networks as concentration or density distributions. Henceforth, in this review, we explore the potential of computational modelling to reveal the role of metabolic reprogramming in tumour growth.

A novel NSUN5/ENO3 pathway promotes the Warburg effect and cell growth in clear cell renal cell carcinoma by 5-methylcytosine-stabilized ENO3 mRNA

OBJECTIVES

Clear cell renal cell carcinoma (ccRCC) cells often reprogram their metabolisms. Enolase 3 (ENO3) is closely related to the Warburg effect observed in cells during tumor progression. However, the expression and function of ENO3 in ccRCC cells remain unclear. Therefore, this study investigated the expression and functional significance of ENO3 in the Warburg effect observed in ccRCC cells.

METHODS

In this study, B-mode and microflow imaging ultrasound examinations were performed to evaluate patients with ccRCC. The extracellular acidification rate test and glucose uptake and lactate production assays were used to examine the Warburg effect in ccRCC cells. Western blotting, quantitative reverse transcription polymerase chain reaction, and immunochemistry were used to detect the expression of ENO3 and NOP2/Sun RNA methyltransferase 5 (NSUN5).

RESULTS

ENO3 upregulation in ccRCC tumor tissues was accompanied by an increase in tumor size. Importantly, ENO3 participated in the Warburg effect observed in ccRCC cells, and high levels of ENO3 indicated a poor prognosis for patients. Loss of ENO3 reduced glucose uptake, lactate production, and extracellular acidification rate as well as inhibited ccRCC cell proliferation. Furthermore, NSUN5 was involved in the ENO3-regulated Warburg effect and ccRCC cell progression. Mechanically, NSUN5 was upregulated in ccRCC tissues, and NSUN5 upregulation mediated 5-methylcytosine modification of messenger RNA (mRNA) in ccRCC cells to promote mRNA stability and ENO3 expression.

CONCLUSIONS

Collectively, the destruction of the NSUN5/ENO3 axis prevents ccRCC growth in vivo and in vitro, and targeting this pathway may be an effective strategy against ccRCC progression.

Implications of cancer stem cells in diabetes and pancreatic cancer

This review provides a detailed study of pancreatic cancer (PC) and the implication of different types of cancers concerning diabetes. The combination of anti-diabetic drugs with other anti-cancer drugs and phytochemicals can help prevent and treat this disease. PC cancer stem cells (CSCs) and how they migrate and develop into malignant tumors are discussed. A detailed explanation of the different mechanisms of diabetes development, which can enhance the pancreatic CSCs' proliferation by increasing the IGF factor levels, epigenetic modifications, DNA damage, and the influence of lifestyle factors like obesity, and inflammation, has been discussed. It also explains how cancer due to diabetes is associated with high mortality rates. One of the well-known diabetic drugs, metformin, can be combined with other anti-cancer drugs and prevent the development of PC and has been taken as one of the prime focus in this review. Overall, this paper provides insight into the relationship between diabetes and PC and the methods that can be employed to diagnose this disease at an earlier stage successfully.

Searching for the Metabolic Signature of Cancer: A Review from Warburg's Time to Now

This review focuses on the evolving understanding that we have of tumor cell metabolism, particularly glycolytic and oxidative metabolism, and traces back its evolution through time. This understanding has developed since the pioneering work of Otto Warburg, but the understanding of tumor cell metabolism continues to be hampered by misinterpretation of his work. This has contributed to the use of the new concepts of metabolic switch and metabolic reprogramming， that are out of step with reality. The Warburg effect is often considered to be a hallmark of cancer, but is it really? More generally, is there a metabolic signature of cancer? We draw the conclusion that the signature of cancer cannot be reduced to a single factor, but is expressed at the tissue level in terms of the capacity of cells to dynamically explore a vast metabolic landscape in the context of significant environmental heterogeneities.

αvβ3 integrin-specific exosomes engineered with cyclopeptide for targeted delivery of triptolide against malignant melanoma

Background

Melanoma is the most malignant skin tumor and is difficult to cure with the alternative treatments of chemotherapy, biotherapy, and immunotherapy. Our previous study showed that triptolide (TP) exhibited powerful tumoricidal activity against melanoma. However, the clinical potential of TP is plagued by its poor aqueous solubility, short half-life, and biotoxicity. Therefore, developing an ideal vehicle to efficiently load TP and achieving targeted delivery to melanoma is a prospective approach for making full use of its antitumor efficacy.

Results

We applied exosome (Exo) derived from human umbilical cord mesenchymal stromal cells (hUCMSCs) and engineered them exogenously with a cyclic peptide, arginine-glycine-aspartate (cRGD), to encapsulate TP to establish a bionic-targeted drug delivery system (cRGD-Exo/TP), achieving synergism and toxicity reduction. The average size of cRGD-Exo/TP was 157.34 ± 6.21 nm, with a high drug loading of 10.76 ± 1.21%. The in vitro antitumor results showed that the designed Exo delivery platform could be effectively taken up by targeted cells and performed significantly in antiproliferation, anti-invasion, and proapoptotic activities in A375 cells via the caspase cascade and mitochondrial pathways and cell cycle alteration. Furthermore, the biodistribution and pharmacokinetics results demonstrated that cRGD-Exo/TP possessed superior tumor targetability and prolonged the half-life of TP. Notably, cRGD-Exo/TP significantly inhibited tumor growth and extended survival time with negligible systemic toxicity in tumor-bearing mice.

Conclusion

The results indicated that the functionalized Exo platform provides a promising strategy for targeted therapy of malignant melanoma.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-022-01597-1.

Remodeling “cold” tumor immune microenvironment via epigenetic-based therapy using targeted liposomes with in situ formed albumin corona

There is a close connection between epigenetic regulation, cancer metabolism, and immunology. The combination of epigenetic therapy and immunotherapy provides a promising avenue for cancer management. As an epigenetic regulator of histone acetylation, panobinostat can induce histone acetylation and inhibit tumor cell proliferation, as well as regulate aerobic glycolysis and reprogram intratumoral immune cells. JQ1 is a BRD4 inhibitor that can suppress PD-L1 expression. Herein, we proposed a chemo-free, epigenetic-based combination therapy of panobinostat/JQ1 for metastatic colorectal cancer. A novel targeted binary-drug liposome was developed based on lactoferrin-mediated binding with the LRP-1 receptor. It was found that the tumor-targeted delivery was further enhanced by in situ formation of albumin corona. The lactoferrin modification and endogenous albumin adsorption contribute a dual-targeting effect on the receptors of both LRP-1 and SPARC that were overexpressed in tumor cells and immune cells (e.g., tumor-associated macrophages). The targeted liposomal therapy was effective to suppress the crosstalk between tumor metabolism and immune evasion via glycolysis inhibition and immune normalization. Consequently, lactic acid production was reduced and angiogenesis inhibited; TAM switched to an anti-tumor phenotype, and the anti-tumor function of the effector CD8⁺ T cells was reinforced. The strategy provides a potential method for remodeling the tumor immune microenvironment (TIME).

PDGF-BB/PDGFRβ Promotes Epithelial-Mesenchymal Transition by Affecting PI3K/AKT/mTOR-Driven Aerobic Glycolysis in Wilms' tumor G401 Cells

Wilms' tumor (WT) is the most common pediatric renal malignancy. PDGFRβ belongs to the type III receptor tyrosine kinase family and is known to be involved in tumor metastasis and angiogenesis. Here, we studied the effect and underlying mechanism of PDGFRβ on Wilms' tumor G401 cells. Transwell assay and wound-healing assay were used to detect the effect of PDGFRβ on G401 cells invasion and migration. Western blot and immunofluorescence were used to detect the expression of EMT-related genes. The expression of PI3K/AKT/mTOR pathway proteins was detected by western blot. The relationship between PDGFRβ and aerobic glycolysis was studied by assessing the expression of glycolysis-related enzymes detected by qRT-PCR and western blot. The activity of HK, PK and LDH was detected by corresponding enzyme activity kits. The concentration of lactic acid and glucose was detected by Lactic Acid Assay Kit and Glucose Assay Kit-glucose oxidase method separately. To investigate the mechanism of PDGFRβ in the development of Wilms' tumor, the changes of glucose and lactic acid were analyzed after blocking PI3K pathway, aerobic glycolysis or PDGFRβ. The key enzyme was screened by western blot and glucose metabolism experiment after HK2, PKM2 and PDK1 were inhibited. The results showed that PDGFRβ promoted the EMT process by modulating aerobic glycolysis through PI3K/AKT/mTOR pathway in which PKM2 plays a key role. Therefore, our study of the mechanism of PDGFRβ in G401 cells provides a new target for the treatment of Wilms' tumor. This article is protected by copyright. All rights reserved.

Chemo-mechanistic multi-scale model of a three-dimensional tumor microenvironment to quantify the chemotherapy response of cancer

Exploring efficient chemotherapy would benefit from a deeper understanding of the tumor microenvironment (TME) and its role in tumor progression. As in vivo experimental methods are unable to isolate or control individual factors of the TME, and in vitro models often cannot include all the contributing factors, some questions are best addressed with mathematical models of systems biology. In this study, we establish a multi-scale mathematical model of the TME to simulate three-dimensional tumor growth and angiogenesis and then implement the model for an array of chemotherapy approaches to elucidate the effect of TME conditions and drug scheduling on controlling tumor progression. The hyperglycemic condition as the most common disorder for cancer patients is considered to evaluate its impact on cancer response to chemotherapy. We show that combining antiangiogenic and anticancer drugs improves the outcome of treatment and can decrease accumulation of the drug in normal tissue and enhance drug delivery to the tumor. Our results demonstrate that although both concurrent and neoadjuvant combination therapies can increase intratumoral drug exposure and therapeutic accuracy, neoadjuvant therapy surpasses this, especially against hyperglycemia. Our model provides mechanistic explanations for clinical observations of tumor progression and response to treatment and establishes a computational framework for exploring better treatment strategies.

Shikonin inhibits the Warburg effect, cell proliferation, invasion and migration by downregulating PFKFB2 expression in lung cancer

Lung cancer is one of the most lethal diseases and therefore poses a significant threat to human health. The Warburg effect, which is the observation that cancer cells predominately produce energy through glycolysis, even under aerobic conditions, is a hallmark of cancer. 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 2 (PFKFB) is an important regulator of glycolysis. Shikonin is a Traditional Chinese herbal medicine, which has been reported to exert antitumor effects. The present study aimed to investigate the anticancer activity of shikonin in lung cancer. Cell Counting Kit-8 (CCK-8) and colony formation assays were used to analyze proliferation in A549 and H446 cells. Wound healing and Transwell assays were used to measure migration and invasion in A549 and H446 cells. Cell apoptosis was analyzed using flow cytometry. Lactate levels, glucose uptake and cellular ATP levels were measured using their corresponding commercial kits. Western blotting was performed to analyze the protein expression levels of key enzymes involved in aerobic glucose metabolism. Reverse transcription-quantitative PCR was used to analyze the mRNA expression levels of PFKFB2. The results of the present study revealed that PFKFB2 expression levels were significantly upregulated in NSCLC tissues. Shikonin treatment decreased the proliferation, migration, invasion, glucose uptake, lactate levels, ATP levels and PFKFB2 expression levels and increased apoptosis in lung cancer cells in a dose-dependent manner. The overexpression of PFKFB2 increased the proliferation, migration, glucose uptake, lactate levels and ATP levels in lung cancer cells, while the knockdown of PFKFB2 expression exerted the opposite effects. Moreover, there were no significant differences in lung cancer cell migration, apoptosis, glucose uptake, lactate levels and ATP levels between cells with knocked down PFKFB2 expression or treated with shikonin and the knockdown of PFKFB2 in cells treated with shikonin. In conclusion, the results of the present study revealed that shikonin inhibited the Warburg effect and exerted antitumor activity in lung cancer cells, which was associated with the downregulation of PFKFB2 expression.

Therapeutic Approach of KRAS Mutant Tumours by the Combination of Pharmacologic Ascorbate and Chloroquine

The Warburg effect has been considered a potential therapeutic target to fight against cancer progression. In KRAS mutant cells, PKM2 (pyruvate kinase isozyme M2) is hyper-activated, and it induces GLUT1 expression; therefore, KRAS has been closely involved in the initiation of Warburg metabolism. Although mTOR (mammalian target of rapamycin), a well-known inhibitor of autophagy-dependent survival in physiological conditions, is also activated in KRAS mutants, many recent studies have revealed that autophagy becomes hyper-active in KRAS mutant cancer cells. In the present study, a mathematical model was built containing the main elements of the regulatory network in KRAS mutant cancer cells to explore the further possible therapeutic strategies. Our dynamical analysis suggests that the downregulation of KRAS, mTOR and autophagy are crucial in anti-cancer therapy. PKM2 has been assumed to be the key switch in the stress response mechanism. We predicted that the addition of both pharmacologic ascorbate and chloroquine is able to block both KRAS and mTOR pathways: in this case, no GLUT1 expression is observed, meanwhile autophagy, essential for KRAS mutant cancer cells, is blocked. Corresponding to our system biological analysis, this combined pharmacologic ascorbate and chloroquine treatment in KRAS mutant cancers might be a therapeutic approach in anti-cancer therapies.

Modeling the bidirectional glutamine/ammonium conversion between cancer cells and cancer-associated fibroblasts

Like in an ecosystem, cancer and other cells residing in the tumor microenvironment engage in various modes of interactions to buffer the negative effects of environmental changes. One such change is the consumption of common nutrients (such as glutamine/Gln) and the consequent accumulation of toxic metabolic byproducts (such as ammonium/NH4). Ammonium is a waste product of cellular metabolism whose accumulation causes cell stress. In tumors, it is known that it can be recycled into nutrients by cancer associated fibroblasts (CAFs). Here we present monoculture and coculture growth of cancer cells and CAFs on different substrates: glutamine and ammonium. We propose a mathematical model to aid our understanding. We find that cancer cells are able to survive on ammonium and recycle it to glutamine for limited periods of time. CAFs are able to even grow on ammonium. In coculture, the presence of CAFs results in an improved survival of cancer cells compared to their monoculture when exposed to ammonium. Interestingly, the ratio between the two cell populations is maintained under various concentrations of NH4, suggesting the ability of the mixed cell system to survive temporary metabolic stress and sustain the size and cell composition as a stable entity.

Metabolic Reprogramming of Fibroblasts as Therapeutic Target in Rheumatoid Arthritis and Cancer: Deciphering Key Mechanisms Using Computational Systems Biology Approaches

Fibroblasts, the most abundant cells in the connective tissue, are key modulators of the extracellular matrix (ECM) composition. These spindle-shaped cells are capable of synthesizing various extracellular matrix proteins and collagen. They also provide the structural framework (stroma) for tissues and play a pivotal role in the wound healing process. While they are maintainers of the ECM turnover and regulate several physiological processes, they can also undergo transformations responding to certain stimuli and display aggressive phenotypes that contribute to disease pathophysiology. In this review, we focus on the metabolic pathways of glucose and highlight metabolic reprogramming as a critical event that contributes to the transition of fibroblasts from quiescent to activated and aggressive cells. We also cover the emerging evidence that allows us to draw parallels between fibroblasts in autoimmune disorders and more specifically in rheumatoid arthritis and cancer. We link the metabolic changes of fibroblasts to the toxic environment created by the disease condition and discuss how targeting of metabolic reprogramming could be employed in the treatment of such diseases. Lastly, we discuss Systems Biology approaches, and more specifically, computational modeling, as a means to elucidate pathogenetic mechanisms and accelerate the identification of novel therapeutic targets.

Atypical immunometabolism and metabolic reprogramming in liver cancer: Deciphering the role of gut microbiome

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related mortality worldwide. Much recent research has delved into understanding the underlying molecular mechanisms of HCC pathogenesis, which has revealed to be heterogenous and complex. Two major hallmarks of HCC include: (i) a hijacked immunometabolism and (ii) a reprogramming in metabolic processes. We posit that the gut microbiota is a third component in an entanglement triangle contributing to HCC progression. Besides metagenomic studies highlighting the diagnostic potential in the gut microbiota profile, recent research is pinpointing the gut microbiota as an instigator, not just a mere bystander, in HCC. In this chapter, we discuss mechanistic insights on atypical immunometabolism and metabolic reprogramming in HCC, including the examination of tumor-associated macrophages and neutrophils, tumor-infiltrating lymphocytes (e.g., T-cell exhaustion, regulatory T-cells, natural killer T-cells), the Warburg effect, rewiring of the tricarboxylic acid cycle, and glutamine addiction. We further discuss the potential involvement of the gut microbiota in these characteristics of hepatocarcinogenesis. An immediate highlight is that microbiota metabolites (e.g., short chain fatty acids, secondary bile acids) can impair anti-tumor responses, which aggravates HCC. Lastly, we describe the rising 'new era' of immunotherapies (e.g., immune checkpoint inhibitors, adoptive T-cell transfer) and discuss for the potential incorporation of gut microbiota targeted therapeutics (e.g., probiotics, fecal microbiota transplantation) to alleviate HCC. Altogether, this chapter invigorates for continuous research to decipher the role of gut microbiome in HCC from its influence on immunometabolism and metabolic reprogramming.

A Flux-Limited Model for Glioma Patterning with Hypoxia-Induced Angiogenesis

We propose a model for glioma patterns in a microlocal tumor environment under the influence of acidity, angiogenesis, and tissue anisotropy. The bottom-up model deduction eventually leads to a system of reaction–diffusion–taxis equations for glioma and endothelial cell population densities, of which the former infers flux limitation both in the self-diffusion and taxis terms. The model extends a recently introduced (Kumar, Li and Surulescu, 2020) description of glioma pseudopalisade formation with the aim of studying the effect of hypoxia-induced tumor vascularization on the establishment and maintenance of these histological patterns which are typical for high-grade brain cancer. Numerical simulations of the population level dynamics are performed to investigate several model scenarios containing this and further effects.

Effects of buoyant and Saffman lift force on magnetic drug targeting in microvessel in the presence of inertia

The conventional techniques in treating cancerous cells in a human body are conducted either by surgery or oral medication or injecting anticancer drugs, which may have several side effects on healthy cells. Compared to these techniques, site-specific delivery of drugs can be one of the pillars of cancer treatment. It could allow for better treatment efficiency and lesser adverse effects. A promising drug delivery approach is magnetic drug targeting, which can be realized if a drug delivery vehicle possesses an intense magnetic moment. Here, we discuss different types of magnetic nanomaterials, which can be used as magnetic drug delivery vehicles, approaches to magnetically targeted delivery, and promising strategies for the enhancement of the imaging-guided delivery and the therapeutic action. The present study aims to discuss all significant factors that influence the process of magnetic drug targeting through microvessels, such as fluidic force, magnetic force, particle-particle interaction, inertia force, Saffman lift force, and permeability of the microvessel. We consider the nature of blood flow as non-Newtonian in single-phase and two-phase models so that a realistic rheological model for an effective magnetic drug targeting can be established through proper comparison. Here we present a comprehensive mathematical model on magnetic drug targeting that could help the medical experts and biomedical engineers in applying the methodology of magnetic drug targeting effectively to cure cancerous disease.

Circ_0032821 Facilitates Gastric Cancer Cell Proliferation, Migration, Invasion and Glycolysis by Regulating MiR-1236-3p/HMGB1 Axis

Background

Circular RNAs (circRNAs) play an essential role in the pathogenesis of malignant tumors, including gastric cancer (GC). However, the effect of circ_0032821 on GC remains largely unknown.

Methods

QRT-PCR assay was employed to examine the levels of circ_0032821, CEP128 mRNA and miR-1236-3p. RNase R digestion assay was utilized to verify the feature of circ_0032821. Cell Counting Kit-8 (CCK-8) assay and transwell assay were adopted to evaluate cell proliferation and metastasis. The level of glycolysis was evaluated through detecting ECAR, OCR, lactate production, glucose uptake and ATP synthesis. Dual-luciferase reporter assay and RIP assay were conducted to analyze the relationship between miR-1236-3p and circ_0032821 or HMGB1. Western blot assay was adopted for high mobility group box 1 (HMGB1) level. Murine xenograft model assay was utilized for the effect of circ_0032821 in vivo.

Results

High level of circ_0032821 was observed in GC tissues and cells. Silencing of circ_0032821 markedly repressed cell proliferation, metastasis and glycolysis in GC cells in vitro and blocked tumorigenesis of GC in vivo. For mechanism analysis, circ_0032821 was identified as the sponge of miR-1236-3p and HMGB1 was the target gene of miR-1236-3p. Moreover, miR-1236-3p suppression restored the influences of circ_0032821 deficiency on GC cell proliferation, metastasis and glycolysis. Overexpression of miR-1236-3p relieved the malignant behaviors of GC cells by targeting HMGB1.

Conclusion

Circ_0032821 accelerated GC development through elevating HMGB1 expression via sponging miR-1236-3p.

Human intratumoral therapy: Linking drug properties and tumor transport of drugs in clinical trials

Cancer therapies aim to kill tumor cells directly or engage the immune system to fight malignancy. Checkpoint inhibitors, oncolytic viruses, cell-based immunotherapies, cytokines, and adjuvants have been applied to prompt the immune system to recognize and attack cancer cells. However, systemic exposure of cancer therapies can induce unwanted adverse events. Intratumoral administration of potent therapies utilizes small amounts of drugs, in an effort to minimize systemic exposure and off-target toxicities. Here, we discuss the properties of the tumor microenvironment and transport considerations for intratumoral drug delivery. Specifically, we consider various tumor tissue factors and physicochemical factors that can affect tumor retention after intratumoral injection. We also review approved and clinical-stage intratumoral therapies and consider how the molecular and biophysical properties (e.g. size and charge) of these therapies influences intratumoral transport (e.g. tumor retention and cellular uptake). Finally, we offer a critical review and highlight several emerging approaches to promote tumor retention and limit systemic exposure of potent intratumoral therapies.

Smart Nanotheranostics Responsive to Pathological Stimuli

The development of nanotheranostics represents one of the most dynamic technological frontiers in the treatment of different pathological conditions. With the goal in mind to generate nanocarriers with both therapeutic and diagnostic properties, current research aims at implementing these technologies with multiple functions, including targeting, multimodal imaging, and synergistic therapies. The working mechanism of some nanotheranostics relies on physical, chemical, and biological triggers allowing for the activation of the therapeutic and/or the diagnostic properties only at the diseased site. In this review, we explored new advances in the development of smart nanotheranostics responsive to pathological stimuli, including altered pH, oxidative stress, enzymatic expression, and reactive biological molecules with a deep focus on the material used in the field to generate the particles in the context of the analyzed disease.

A multi-scale model for determining the effects of pathophysiology and metabolic disorders on tumor growth

The search for efficient chemotherapy drugs and other anti-cancer treatments would benefit from a deeper understanding of the tumor microenvironment (TME) and its role in tumor progression. Because in vivo experimental methods are unable to isolate or control individual factors of the TME and in vitro models often do not include all the contributing factors, some questions are best addressed with systems biology mathematical models. In this work, we present a new fully-coupled, agent-based, multi-scale mathematical model of tumor growth, angiogenesis and metabolism that includes important aspects of the TME spanning subcellular-, cellular- and tissue-level scales. The mathematical model is computationally implemented for a three-dimensional TME, and a double hybrid continuous-discrete (DHCD) method is applied to solve the governing equations. The model recapitulates the distinct morphological and metabolic stages of a solid tumor, starting with an avascular tumor and progressing through angiogenesis and vascularized tumor growth. To examine the robustness of the model, we simulated normal and abnormal blood conditions, including hyperglycemia/hypoglycemia, hyperoxemia/hypoxemia, and hypercarbia/hypocarbia - conditions common in cancer patients. The results demonstrate that tumor progression is accelerated by hyperoxemia, hyperglycemia and hypercarbia but inhibited by hypoxemia and hypoglycemia; hypocarbia had no appreciable effect. Because of the importance of interstitial fluid flow in tumor physiology, we also examined the effects of hypo- or hypertension, and the impact of decreased hydraulic conductivity common in desmoplastic tumors. The simulations show that chemotherapy-increased blood pressure, or reduction of interstitial hydraulic conductivity increase tumor growth rate and contribute to tumor malignancy.

Magnetic aerosol drug targeting in lung cancer therapy using permanent magnet

Primary bronchial cancer accounts for almost 20% of all cancer death worldwide. One of the emerging techniques with tremendous power for lung cancer therapy is magnetic aerosol drug targeting (MADT). The use of a permanent magnet for effective drug delivery in a desired location throughout the lung requires extensive optimization, but it has not been addressed yet. In the present study, the possibility of using a permanent magnet for trapping the particles on a lung tumor is evaluated numerically in the Weibel's model from G0 to G3. The effect of different parameters is considered on the efficiency of particle deposition in a tumor located on a distant position of the lung bronchi and bronchioles. Also, the effective position of the magnetic source, tumor size, and location are the objectives for particle deposition. The results show that a limited particle deposition occurs on the lung branches in passive targeting. However, the incorporation of a permanent magnet next to the tumor enhanced the particle deposition fraction on G2 to up to 49% for the particles of 7 µm diameter. Optimizing the magnet size could also improve the particle deposition fraction by 68%. It was also shown that the utilization of MADT is essential for effective drug delivery to the tumors located on the lower wall of airway branches given the dominance of the air velocity and resultant drag force in this region. The results demonstrated the high competence and necessity of MADT as a noninvasive drug delivery method for lung cancer therapy.

Macrophage-derived exosome-mimetic hybrid vesicles for tumor targeted drug delivery

Extracellular vesicles (EVs) are phospholipid and protein constructs which are continuously secreted by cells in the form of smaller (30-200 nm) and larger (micron size) particles. While all of these vesicles are called as EVs, the smaller size are normally called as exosomes. Small EVs (sEVs) have now been explored as a potential candidate in therapeutics delivery owing to their endogenous functionality, intrinsic targeting property, and ability to cooperate with a host defense mechanism. Considering these potentials, we hypothesize that immune cell-derived sEVs can mimic immune cell to target cancer. However, different sEVs isolation technique reported poor yield and loss of functional properties. To solve this problem, herein we hybridized sEVs with synthetic liposome to engineer vesicles with size less than 200 nm to mimic the size of exosome and named as hybrid exosome (HE). To achieve this goal, sEVs from mouse macrophage was hybridized with synthetic liposome to engineer HE. The fluorescence-based experiment confirmed the successful hybridization process yielding HE with the size of 177 ± 21 nm. Major protein analysis from Blot techniques reveal the presence of EV marker proteins CD81, CD63, and CD9. Differential cellular interaction of HE was observed when treated with normal and cancerous cells thereby supporting our hypothesis. Moreover, a water-soluble doxorubicin was loaded in HE. Drug-loaded HE showed enhanced toxicity against cancer cells and pH-sensitive drug release in acidic condition, benefiting drug delivery to acidic cancer environment. These results suggest that the engineered HE would be an exciting platform for tumor-targeted drug delivery. STATEMENT OF SIGNIFICANCE: Extracellular vesicles (EVs) are phospholipid and protein constructs which are continuously secreted by cells in the human body. These vesicles can efficiently deliver their parental biomolecules to the recipient cells and assist in intracellular communication without a direct cell-to-cell contact. Moreover, they have the ability to perform some of the molecular task similar to that of its parent cells. For example, exosome derived from immune cells can seek for diseased and/or inflammatory cells by reading the cell surface proteins. However, different EVs isolation techniques reported poor yield and loss of functional properties. Therefore, to overcome this limitation, we herein propose to re-engineer immuno-exosome with a synthetic liposome as a refined biomimetic nanostructure for the delivery of doxorubicin (clinical drug) for breast cancer treatment.

Delivery of magnetic micro/nanoparticles and magnetic-based drug/cargo into arterial flow for targeted therapy

Magnetic drug targeting (MDT) and magnetic-based drug/cargo delivery are emerging treatment methods which attracting the attention of many researchers for curing different cancers and artery diseases such as atherosclerosis. Herein, computational studies are accomplished by utilizing magnetic approaches for cancer and artery atherosclerosis drug delivery, including nanomagnetic drug delivery and magnetic-based drug/cargo delivery. For the first time, the four-layer structural model of the artery tissue and its porosity parameters are modeled in this study which enables the interaction of particles with the tissue walls in blood flow. The effects of parameters, including magnetic field strength (MFS), magnet size, particle size, the initial position of particles, and the relative magnetic permeability of particles, on the efficacy of MDT through the artery walls are characterized. The magnetic particle penetration into artery layers and fibrous cap (the covering layer over the inflamed part of the artery) is further simulated. The MDT in healthy and diseased arteries demonstrates that some of the particles stuck in these tissues due to the collision of particles or blood flow deviation in the vicinity of the inflamed part of the artery. Therefore the geometry of artery and porosity of its layers should be considered to show the real interaction of particles with the artery walls. Also, the results show that increasing the particles/drug/cargo size and MFS leads to more particles/drug/cargo retention within the tissue. The present work provides insights into the decisive factors in arterial MDT with an obvious impact on locoregional cancer treatment, tissue engineering, and regenerative medicine.

miR-613 inhibits Warburg effect in gastric cancer by targeting PFKFB2

miR-613 has been demonstrated to play critical roles in tumorigenesis and progression of a various type of cancers. However, its role and expression significance remain unclear in gastric cancer (GC). We detected the expression of miR-613 in 176 paired GC tissues and adjacent normal tissues, and found that miR-613 was significantly downregulated in GC tissues and its downregulation was correlated with T stage, lymph node invasion and advanced AJCC stages. Moreover, miR-613 expression could be an independent prognostic factor of GC. Biological function analysis indicated that miR-613 inhibited cell proliferation and invasion. Further analysis suggested that miR-613 inhibited Warburg effect of GC cells. Mechanically, we identified that miR-613 could directly bind to the 3'UTR of PFKFB2, thereby suppressing the expression of PFKFB2, which in turn, regulating glycolysis metabolism and cell growth. In conclusion, miR-613 served as a tumor suppressor by targeting PFKFB2, indicating that detecting miR-613 and modulation of miR-613 expression could be potential marker and clinical approach in GC patients.

Multi-scale computational study of the Warburg effect, reverse Warburg effect and glutamine addiction in solid tumors

Cancer metabolism has received renewed interest as a potential target for cancer therapy. In this study, we use a multi-scale modeling approach to interrogate the implications of three metabolic scenarios of potential clinical relevance: the Warburg effect, the reverse Warburg effect and glutamine addiction. At the intracellular level, we construct a network of central metabolism and perform flux balance analysis (FBA) to estimate metabolic fluxes; at the cellular level, we exploit this metabolic network to calculate parameters for a coarse-grained description of cellular growth kinetics; and at the multicellular level, we incorporate these kinetic schemes into the cellular automata of an agent-based model (ABM), iDynoMiCS. This ABM evaluates the reaction-diffusion of the metabolites, cellular division and motion over a simulation domain. Our multi-scale simulations suggest that the Warburg effect provides a growth advantage to the tumor cells under resource limitation. However, we identify a non-monotonic dependence of growth rate on the strength of glycolytic pathway. On the other hand, the reverse Warburg scenario provides an initial growth advantage in tumors that originate deeper in the tissue. The metabolic profile of stromal cells considered in this scenario allows more oxygen to reach the tumor cells in the deeper tissue and thus promotes tumor growth at earlier stages. Lastly, we suggest that glutamine addiction does not confer a selective advantage to tumor growth with glutamine acting as a carbon source in the tricarboxylic acid (TCA) cycle, any advantage of glutamine uptake must come through other pathways not included in our model (e.g., as a nitrogen donor). Our analysis illustrates the importance of accounting explicitly for spatial and temporal evolution of tumor microenvironment in the interpretation of metabolic scenarios and hence provides a basis for further studies, including evaluation of specific therapeutic strategies that target metabolism.

Cancer metabolism is an emerging hallmark of cancer. In the past decade, a renewed focus on cancer metabolism has led to several distinct hypotheses describing the role of metabolism in cancer. To complement experimental efforts in this field, a scale-bridging computational framework is needed to allow rapid evaluation of emerging hypotheses in cancer metabolism. In this study, we present a multi-scale modeling platform and demonstrate the distinct outcomes in population-scale growth dynamics under different metabolic scenarios: the Warburg effect, the reverse Warburg effect and glutamine addiction. Within this modeling framework, we confirmed population-scale growth advantage enabled by the Warburg effect, provided insights into the symbiosis between stromal cells and tumor cells in the reverse Warburg effect and argued that the anaplerotic role of glutamine is not exploited by tumor cells to gain growth advantage under resource limitations. We point to the opportunity for this framework to help understand tissue-scale response to therapeutic strategies that target cancer metabolism while accounting for the tumor complexity at multiple scales.