Hybrid Modelling of Transarterial Chemoembolisation Therapies (TACE) for Hepatocellular Carcinoma (HCC)

Arterial enhancement fraction in evaluating the therapeutic effect and survival for hepatocellular carcinoma patients treated with DEB-TACE

BACKGROUND

Arterial enhancement fraction (AEF), derived from triphasic CT scans, is considered to indirectly reflect the ratio of hepatic arterial perfusion to total perfusion. The purpose of this study was to retrospectively investigate the relationship between AEF and treatment response and survival in hepatocellular carcinoma (HCC) patients treated with drug-eluting bead (DEB) TACE.

METHODS

AEF of primary lesion (AEF_pre) and residual tumor (AEF_post) in 158 HCC patients were obtained from triphasic liver CT examinations pre- and post-treatment. Wilcoxon-signed rank test was used to compare the AEF_pre and AEF_post for different response groups. Survival curves for overall survival (OS) in patients with different AEF were created by using Kaplan-Meier method. Cox regression analyses were used to determine the association between AEF and OS.

RESULTS

There was no correlation between AEF_pre and treatment response. After DEB-TACE, AEF_post was significantly lower than AEF_pre either in the partial response group (38.9% vs. 52.7%, p <  0.001) or in the stable disease group (49.3% vs. 52.1%, p = 0.029). In the progression disease group, AEF_post was numerically higher than AEF_pre (55.5% vs. 53.0%, p = 0.604). Cox regression analyses showed that risk of death increased in patients with AEF_pre > 57.95% (HR = 1.66, p = 0.019) or AEF_post > 54.85% (HR = 2.47, p <  0.001), and the risk reduced in patients with any reduction in tumor AEF (decrease ratio ≥ 0) and with increased AEF but not exceeding the ratio of 0.102 (increase ratio <  0.102) (HR = 0.32, p <  0.001).

CONCLUSIONS

The change in AEF of viable tumor is correlated with response of HCC to DEB-TACE. In addition, the AEF could be a helpful predictor in future studies on the embolization treatment for HCC.

Integrating a dynamic central metabolism model of cancer cells with a hybrid 3D multiscale model for vascular hepatocellular carcinoma growth

We develop here a novel modelling approach with the aim of closing the conceptual gap between tumour-level metabolic processes and the metabolic processes occurring in individual cancer cells. In particular, the metabolism in hepatocellular carcinoma derived cell lines (HEPG2 cells) has been well characterized but implementations of multiscale models integrating this known metabolism have not been previously reported. We therefore extend a previously published multiscale model of vascular tumour growth, and integrate it with an experimentally verified network of central metabolism in HEPG2 cells. This resultant combined model links spatially heterogeneous vascular tumour growth with known metabolic networks within tumour cells and accounts for blood flow, angiogenesis, vascular remodelling and nutrient/growth factor transport within a growing tumour, as well as the movement of, and interactions between normal and cancer cells. Model simulations report for the first time, predictions of spatially resolved time courses of core metabolites in HEPG2 cells. These simulations can be performed at a sufficient scale to incorporate clinically relevant features of different tumour systems using reasonable computational resources. Our results predict larger than expected temporal and spatial heterogeneity in the intracellular concentrations of glucose, oxygen, lactate pyruvate, f16bp and Acetyl-CoA. The integrated multiscale model developed here provides an ideal quantitative framework in which to study the relationship between dosage, timing, and scheduling of anti-neoplastic agents and the physiological effects of tumour metabolism at the cellular level. Such models, therefore, have the potential to inform treatment decisions when drug response is dependent on the metabolic state of individual cancer cells.

Response comparison of PLC and SLC with magnetic resonance elastography after TACE

The aim of this study was to detect a response difference in primary (PLC) and secondary liver tumors (SLC) with magnetic resonance elastography (MRE) after TACE therapy. Thirty-one patients (25/31 male; mean age 69.6 years [range: 39-85 years]) with repeated TACE therapy of HCC were compared with twenty-seven patients (27/27 female; mean age 61.2 years [range 39-81 years]) with repeated TACE therapy of metastatic liver disease due to breast cancer. Both groups underwent either one (n = 31) or two (n = 27) repetitive magnetic resonance imaging (MRI) and MRE exams in 4- to 6-week intervals using a 1.5-T-scanner. MRE-based liver stiffness and size measurements were evaluated in tumorous lesions and in healthy liver lobe controls. PLC showed a significantly larger tumor size compared to SLC (26.4 cm2 vs. 11 cm2, p = 0.007) and a higher degree of stiffness (5.8 kPa vs. 5.1 kPa, p = 0.04). Both tumors decreased in size during the cycles (PLC: p = 0.8 and SLC: p < 0.0001) and lesions showed an increase in stiffness (PLC: p = 0.002 and SLC: p = 0.006). MRE demonstrates that PLC and SLC have similar responses to TACE therapy. PLC had a greater increase in stiffness and SLC got smaller. An increasing stiffness and decrease in size could show a good response.

Artificial Nanoplatelets Depend on Size for Precisely Inducing Thrombosis in Tumor Vessels

Due to the heterogeneity of a tumor, the tumor vascular interruption-based therapy has become an ideal treatment strategy. Herein, artificial nanoplatelets are reported to induce selective thrombosis in tumor vessels, which can achieve rapid and large-scale necrosis of tumor cells. For one, the nanoplatelets are exploited to specially release thrombin into target regions without affecting the established coagulation factors system. For another, the thrombin elicits vascular infarction to provide tumor-ablation effects. More importantly, the size-dependent effect of nanoplatelets (with diameters of 200, 400, and 800 nm) in vivo on blocking the tumor vessels is evaluated. The results show that the nanoplatelets from nanometer to submicron have achieved different biodistribution and therapeutic effects through the vascular transport. Notably, 400 nm scale nanoplatelets can induce thrombosis in tumor vessels and achieve 83% of the tumor elimination rate, thus manifesting the effectiveness of anti-tumor strategy compared with the other two scales of nanoplatelets (200 and 800 nm). These findings highlight the need of concern about nanoparticle size, providing a promising strategy for the future design of advanced vascular targeting reagents and the clinical translation of tumor vascular interruption-based therapy.

The Expression and Prognostic Value of Cancer Stem Cell Markers, NRF2, and Its Target Genes in TAE/TACE-Treated Hepatocellular Carcinoma

Background and Objectives: Activation of NRF2, a key transcription factor of cytoprotectant against oxidative stress, and its target genes are associated with aggressive tumor progression, metastasis and poor survival. In addition, NRF2 signaling mediates cancer stem cell (CSC)-like properties in hepatocellular carcinoma (HCC) cells. Moreover, CSCs have been associated with HCC onset and unfavorable prognosis. Transcatheter arterial embolization (TAE) and/or transcatheter arterial chemoembolization (TACE), which attempt to restrict blood supply to diminish tumor growth, can create a hypoxic environment. However, its effect on NRF2 signaling and CSC marker CD133 in the context of prognosis of HCCs have not been investigated. Therefore, we studied the possible role of the expressions of NRF2, its target genes and CSC markers CD133 and EpCAM on the survival of HCC patients after TAE/TACE. Materials and Methods: RT-qPCR was performed with 120 tumor (T) and adjacent tumor (N) tissue pairs. Expression of a single marker or combination was assessed for associations with survival of HCC patients after TAE/TACE. Results: The result of multivariate Cox regression showed that vascular invasion (HR, 1.821; p = 0.015), metastasis (HR, 2.033; p = 0.049) and CD133 overexpression (HR, 2.013; p = 0.006) were associated with poor survival. In a Kaplan–Meier survival analysis, patients with high expression of CD133 had shorter overall survival (OS) than those with low expression of CD133 in post-TAE/TACE HCC (p < 0.001). In contrast, neither NRF2 nor components of its signaling pathway correlated with survival. Combination marker analysis showed that co-expression of NQO1 and CD133 was associated with poor outcome. Conclusions: This study suggests that analyzing the expression status of CD133 alone and co-expression of NQO1 and CD133 may have additional value in predicting the outcome of TAE/TACE-treated HCC patients.

Systems biology of angiogenesis signaling: Computational models and omics

Angiogenesis is a highly regulated multiscale process that involves a plethora of cells, their cellular signal transduction, activation, proliferation, differentiation, as well as their intercellular communication. The coordinated execution and integration of such complex signaling programs is critical for physiological angiogenesis to take place in normal growth, development, exercise, and wound healing, while its dysregulation is critically linked to many major human diseases such as cancer, cardiovascular diseases, and ocular disorders; it is also crucial in regenerative medicine. Although huge efforts have been devoted to drug development for these diseases by investigation of angiogenesis‐targeted therapies, only a few therapeutics and targets have proved effective in humans due to the innate multiscale complexity and nonlinearity in the process of angiogenic signaling. As a promising approach that can help better address this challenge, systems biology modeling allows the integration of knowledge across studies and scales and provides a powerful means to mechanistically elucidate and connect the individual molecular and cellular signaling components that function in concert to regulate angiogenesis. In this review, we summarize and discuss how systems biology modeling studies, at the pathway‐, cell‐, tissue‐, and whole body‐levels, have advanced our understanding of signaling in angiogenesis and thereby delivered new translational insights for human diseases.

This article is categorized under:

Cardiovascular Diseases > Computational Models

Cancer > Computational Models