A correlative study between IVIM-DWI parameters and VEGF and MMPs expression in hepatocellular carcinoma

Association between radiomics of diffusion-weighted imaging and histopathology in hepatocellular carcinoma. A preliminary investigation

OBJECTIVE

Diffusion-weighted imaging and the quantified apparent diffusion coefficient (ADC) correlate with cell density and histopathological features in tumors. Radiomics analysis may provide more insight into the underlying microstructure and may better correlate with histopathology. The present study used cross-sectional guided biopsy specimens to exploit the precise spatial localization of the performed biopsy to correlate radiomics features of the ADC map with immunohistochemical features in hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

A total of 51 patients (11 female patients, 21.6 %) were included in the present study. The mean age was 71.9 ± 9.9 years, ranging from 42 to 91 years. Prebioptic liver MRI with diffusion-weighted imaging was used to correlate the radiomics features of the ADC maps with the immunohistochemical features quantified in liver biopsy. Proliferation potential Ki 67, leukocyte count and tumor-stroma ratio were evaluated as histopathological parameters.

RESULTS

The following ADC texture features were correlated with the Ki 67 index _MinNorm (r = -0.307, p = 0.03), Vertl_RLNonUni (r = - 0.309, p = 0.03), 135dr_RLNonUni (r = -0.346, p = 0.01). The texture feature _MinNorm achieved the best diagnostic accuracy with an area under the curve of 0.76 (95 % CI 0.60-0.91, p < 0.01) to discriminate between low and high proliferative HCC. Multiple statistically significant correlations were found between ADC texture features and tumor-stroma-ratio, the highest for S(0,1)Contrast (r = 0.460, p = 0.001). No statistically significant correlations were found between the ADC texture features with the CD45+ leukocyte count and grading.

CONCLUSION

Radiomics features of the ADC maps can reflect the underlying histopathology in HCC patients including the proliferation potential and tumor-stroma ratio but not CD45 positive cells and tumor grading. The complex interactions between quantitative imaging and histopathology need to be further investigated in a validation cohort.

Integrated network pharmacology, proteomics, molecular docking, and experiments in vivo and in vitro to explore the efficacy and potential mechanism of bufalin against hepatocellular carcinoma angiogenesis

ETHNOPHARMACOLOGICAL RELEVANCE

Bufalin is a potent bioactive compound extracted from the venom of toads such as Bufo gargarizans. It has rich pharmacological effects, and its traditional applications mainly include anti-cancer, anti-inflammatory and analgesic, especially in cancer treatment, which has been a hot topic of research. Prior research has suggested that bufalin may have anti-tumor angiogenic effects. However, the efficacy and mechanism of bufalin inhibiting hepatocellular carcinoma (HCC) angiogenesis have yet to be further investigated.

AIM OF THE STUDY

An extensive detailed strategy via network pharmacology, proteomics, histopathological analysis, molecular docking, in vitro experiments, and in vivo magnetic resonance imaging (MRI) examinations were adopted to investigate the efficacy and mechanisms of bufalin against HCC angiogenesis.

MATERIALS AND METHODS

Micro-vessel density (MVD) and intravoxel incoherent motion (IVIM) perfusion-related parameters based on magnetic resonance diffusion-weighted imaging were used to identify the effect of bufalin against HCC angiogenesis. Potential bufalin and HCC targets were gathered from appropriate databases. The STRING database was used to construct the target protein interaction networks. The "clusterprofiler" package (version 4.2.2) in R was applied to conduct the target-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) analysis. Network pharmacology and proteomics were integrated to identify key targets and pathways related to bufalin against HCC angiogenesis. Molecular docking and Western Blot were utilized to validate the findings.

RESULTS

Analysis through IVIM and MVD showed that bufalin could inhibit HCC angiogenesis in nude mice models. A total of 159 common targets of bufalin and HCC were identified by network pharmacology. GO analysis revealed that these targets focused on multiple angiogenesis-related biological processes, including endothelial cell proliferation and migration, sprouting angiogenesis, and regulation of angiogenesis. The KEGG enrichment results suggested that bufalin could regulate multiple signaling pathways to inhibit HCC angiogenesis, including VEGF, MAPK, PI3K-Akt, mTOR, and HIF-1 signaling pathways. MAPK1, MAPK14, PRKCA, EIF4E, and APEX1 might be critical targets in regulating the above pathways. The molecular docking and Western blot analysis verified the effects of bufalin on target proteins.

CONCLUSION

This study demonstrated that bufalin might inhibit HCC angiogenesis by regulating multiple targets and pathways. These findings offer theoretical insights and experimental foundations for the clinical application and commercial development of bufalin in the treatment of HCC.

Advances in imaging techniques for tumor microenvironment evaluation in hepatocellular carcinoma

The tumor microenvironment (TME) plays a critical role in the development and treatment of liver cancer, which ranks sixth in incidence and third in mortality worldwide, according to the "Global Cancer Statistics 2022". Hepatocellular carcinoma (HCC), the most common form of liver cancer, is heavily influenced by the TME, which affects tumor growth, invasion, metastasis, and the response to various treatments. Despite advancements in surgery, liver transplantation, targeted therapies, and immunotherapy, the complexity of the TME often limits treatment efficacy, especially in advanced-stage HCC cases. The TME consists of a dynamic interaction between tumor cells, immune cells, fibroblasts, blood vessels, and signaling molecules, all of which contribute to cancer progression and therapy resistance. Assessing the HCC TME is essential for designing effective, personalized treatments and improving patient outcomes. Recent research highlights the value of imaging technologies as non-invasive tools to evaluate the TME, offering new possibilities for more targeted therapies and better prognosis monitoring in HCC patients.

Multi-b-value DWI to evaluate the synergistic antiproliferation and anti-heterogeneity effects of bufalin plus sorafenib in an orthotopic HCC model

BACKGROUND

Multi-b-value diffusion-weighted imaging (DWI) with different postprocessing models allows for evaluating hepatocellular carcinoma (HCC) proliferation, spatial heterogeneity, and feasibility of treatment strategies. We assessed synergistic effects of bufalin+sorafenib in orthotopic HCC-LM3 xenograft nude mice by using intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), a stretched exponential model (SEM), and a fractional-order calculus (FROC) model.

METHODS

Twenty-four orthotopic HCC-LM3 xenograft mice were divided into bufalin+sorafenib, bufalin, sorafenib treatment groups, and a control group. Multi-b-value DWI was performed using a 3-T scanner after 3 weeks' treatment to obtain true diffusion coefficient Dt, pseudo-diffusion coefficient Dp, perfusion fraction f, mean diffusivity (MD), mean kurtosis (MK), distributed diffusion coefficient (DDC), heterogeneity index α, diffusion coefficient D, fractional order parameter β, and microstructural quantity μ. Necrotic fraction (NF), standard deviation (SD) of hematoxylin-eosin staining, and microvessel density (MVD) of anti-CD31 staining were evaluated. Correlations of DWI parameters with histopathological results were analyzed, and measurements were compared among four groups.

RESULTS

In the final 22 mice, f positively correlated with MVD (r = 0.679, p = 0.001). Significantly good correlations of MK (r = 0.677), α (r = -0.696), and β (r= -0.639) with SD were observed (all p < 0.010). f, MK, MVD, and SD were much lower, while MD, α, β, and NF were higher in bufalin plus sorafenib group than control group (all p < 0.050).

CONCLUSION

Evaluated by IVIM, DKI, SEM, and FROC, bufalin+sorafenib was found to inhibit tumor proliferation and angiogenesis and reduce spatial heterogeneity in HCC-LM3 models.

RELEVANCE STATEMENT

Multi-b-value DWI provides potential metrics for evaluating the efficacy of treatment in HCC.

KEY POINTS

• Bufalin plus sorafenib combination may increase the effectiveness of HCC therapy. • Multi-b-value DWI depicted HCC proliferation, angiogenesis, and spatial heterogeneity. • Multi-b-value DWI may be a noninvasive method to assess HCC therapeutic efficacy.