Study of tumor growth under hyperthermia condition

Novel Photo- and Thermo-Responsive Nanocomposite Hydrogels Based on Functionalized rGO and Modified SIS/Chitosan Polymers for Localized Treatment of Malignant Cutaneous Melanoma

Melanoma is an aggressive type of skin cancer that accounts for over 75% of skin cancer deaths despite comprising less than 5% of all skin cancers. Despite promising improvements in surgical approaches for melanoma resection, the survival of undetectable microtumor residues has remained a concern. As a result, hyperthermia- and drug-based therapies have grown as attractive techniques to target and treat cancer. In this work, we aim to develop a stimuli-responsive hydrogel based on chitosan methacrylate (ChiMA), porcine small intestine submucosa methacrylate (SISMA), and doxorubicin-functionalized reduced graphene oxide (rGO-DOX) that eliminates microtumor residues from surgically resected melanoma through the coupled effect of NIR light-induced photothermal therapy and heat-induced doxorubicin release. Furthermore, we developed an in silico model to optimize heat and mass transport and evaluate the proposed chemo/photothermal therapy in vitro over melanoma cell cultures.

Blocking the IGF2BP1-promoted glucose metabolism of colon cancer cells via direct de-stabilizing mRNA of the LDHA enhances anticancer effects

Colorectal cancer (CRC) is a commonly diagnosed cancer with poor prognosis and high mortality rate. Hyperthermia (HT) is an adjunctive therapy to enhance the antitumor effects of traditional chemo- or radio- therapy. Here, we report that a cluster of essential regulator genes and speed-limit enzymes of glucose metabolism were significantly elevated under HT from a glucose metabolism PCR array analysis. Under low glucose supply or glucose metabolism inhibition, CRC cells displayed increased sensitivity to HT treatments. By transcript sequencing from the established HT resistant (HTR) colon cancer cell line LoVo HTR, we observed that IGF2BP1, an RNA-binding protein, was significantly upregulated in HTR cells compared with parental cells. Furthermore, LDHA mRNA was identified as an IGF2BP1 direct target. An RNA immunoprecipitation assay and RNA pull-down assay consistently illustrated IGF2BP1 specifically bonds to the 3′ UTR of LDHA mRNA, leading to enhanced stability of LDHA mRNA. Finally, we demonstrated that inhibiting the IGF2BP1-promoted glycolysis sensitized colon cancer cells to HT treatment via both in vitro and in vivo experiments. Our findings suggest that targeting the IGF2BP1-LDHA-glycolysis pathway might be a promising therapeutic approach to enhance the anti-cancer effects of HT treatment.

Prediction of Gold Nanoparticle and Microwave-Induced Hyperthermia Effects on Tumor Control via a Simulation Approach

Hyperthermia acts as a powerful adjuvant to radiation therapy and chemotherapy. Recent advances show that gold nanoparticles (Au-NPs) can mediate highly localized thermal effects upon interaction with laser radiation. The purpose of the present study was to investigate via in silico simulations the mechanisms of Au-NPs and microwave-induced hyperthermia, in correlation to predictions of tumor control (biological endpoints: tumor shrinkage and cell death) after hyperthermia treatment. We also study in detail the dependence of the size, shape and structure of the gold nanoparticles on their absorption efficiency, and provide general guidelines on how one could modify the absorption spectrum of the nanoparticles in order to meet the needs of specific applications. We calculated the hyperthermia effect using two types of Au-NPs and two types of spherical tumors (prostate and melanoma) with a radius of 3 mm. The plasmon peak for the 30 nm Si-core Au-coated NPs and the 20 nm Au-NPs was found at 590 nm and 540 nm, respectively. Considering the plasmon peaks and the distribution of NPs in the tumor tissue, the induced thermal profile was estimated for different intervals of time. Predictions of hyperthermic cell death were performed by adopting a three-state mathematical model, where “three-state” includes (i) alive, (ii) vulnerable, and (iii) dead states of the cell, and it was coupled with a tumor growth model. Our proposed methodology and preliminary results could be considered as a proof-of-principle for the significance of simulating accurately the hyperthermia-based tumor control involving the immune system. We also propose a method for the optimization of treatment by overcoming thermoresistance by biological means and specifically through the targeting of the heat shock protein 90 (HSP90), which plays a critical role in the thermotolerance of cells and tissues.

Computational Model Predicts the Effects of Targeting Cellular Metabolism in Pancreatic Cancer

Reprogramming of energy metabolism is a hallmark of cancer that enables the cancer cells to meet the increased energetic requirements due to uncontrolled proliferation. One prominent example is pancreatic ductal adenocarcinoma, an aggressive form of cancer with an overall 5-year survival rate of 5%. The reprogramming mechanism in pancreatic cancer involves deregulated uptake of glucose and glutamine and other opportunistic modes of satisfying energetic demands in a hypoxic and nutrient-poor environment. In the current study, we apply systems biology approaches to enable a better understanding of the dynamics of the distinct metabolic alterations in KRAS-mediated pancreatic cancer, with the goal of impeding early cell proliferation by identifying the optimal metabolic enzymes to target. We have constructed a kinetic model of metabolism represented as a set of ordinary differential equations that describe time evolution of the metabolite concentrations in glycolysis, glutaminolysis, tricarboxylic acid cycle and the pentose phosphate pathway. The model is comprised of 46 metabolites and 53 reactions. The mathematical model is fit to published enzyme knockdown experimental data. We then applied the model to perform in silico enzyme modulations and evaluate the effects on cell proliferation. Our work identifies potential combinations of enzyme knockdown, metabolite inhibition, and extracellular conditions that impede cell proliferation. Excitingly, the model predicts novel targets that can be tested experimentally. Therefore, the model is a tool to predict the effects of inhibiting specific metabolic reactions within pancreatic cancer cells, which is difficult to measure experimentally, as well as test further hypotheses toward targeted therapies.