Concurrent imaging of vascularization and metabolism in a mouse model of paraganglioma under anti-angiogenic treatment

Deciphering oxygen distribution and hypoxia profiles in the tumor microenvironment: a data-driven mechanistic modeling approach

Objective. The distribution of hypoxia within tissues plays a critical role in tumor diagnosis and prognosis. Recognizing the significance of tumor oxygenation and hypoxia gradients, we introduce mathematical frameworks grounded in mechanistic modeling approaches for their quantitative assessment within a tumor microenvironment. By utilizing known blood vasculature, we aim to predict hypoxia levels across different tumor types.Approach. Our approach offers a computational method to measure and predict hypoxia using known blood vasculature. By formulating a reaction-diffusion model for oxygen distribution, we derive the corresponding hypoxia profile.Main results. The framework successfully replicates observed inter- and intra-tumor heterogeneity in experimentally obtained hypoxia profiles across various tumor types (breast, ovarian, pancreatic). Additionally, we propose a data-driven method to deduce partial differential equation models with spatially dependent parameters, which allows us to comprehend the variability of hypoxia profiles within tissues. The versatility of our framework lies in capturing diverse and dynamic behaviors of tumor oxygenation, as well as categorizing states of vascularization based on the dynamics of oxygen molecules, as identified by the model parameters.Significance. The proposed data-informed mechanistic method quantitatively assesses hypoxia in the tumor microenvironment by integrating diverse histopathological data and making predictions across different types of data. The framework provides valuable insights from both modeling and biological perspectives, advancing our comprehension of spatio-temporal dynamics of tumor oxygenation.

Artesunate Sensitizes human hepatocellular carcinoma to sorafenib via exacerbating AFAP1L2-SRC-FUNDC1 axis-dependent mitophagy

Sorafenib is the most widely used first-line drug for the treatment of the advanced hepatocellular carcinoma (HCC). Unfortunately, sorafenib resistance often limits its therapeutic efficacy. To evaluate the efficacy of artesunate against sorafenib-resistant HCC and to investigate its underlying pharmacological mechanisms, a "sorafenib resistance related gene-ART candidate target" interaction network was constructed, and a signaling axis consisting with artesunate candidate target AFAP1L2 and sorafenib target SRC, and the downstream FUNDC1-dependent mitophagy was identified as a major contributor to the sorafenib resistance and a potential way of artesunate to mitigate resistance. Notably, our clinical data demonstrated that AFAP1L2 expression in HCC tissues was markedly higher than that in adjacent non-cancerous liver tissues (P < 0.05), and high AFAP1L2 expression was also significantly associated with an unfavorable overall survival of HCC patients (P < 0.05). Experimentally, AFAP1L2 was overexpressed in sorafenib resistant cells, leading to the activation of downstream SRC-FUNDC1 signaling axis, further blocking the FUNDC1 recruitment of LC3B to mitochondria and inhibiting the activation of mitophagy, based on both in vitro and in vivo systems. Moreover, artesunate significantly enhanced the inhibitory effects of sorafenib on resistant cells and tumors by inducing excessive mitophagy. Mechanically, artesunate reduced the expression of AFAP1L2 protein, suppressed the phosphorylation levels of SRC and FUNDC1 proteins, promoted the FUNDC1 recruitment of massive LC3B to mitochondria, and further overactivated the mitophagy and subsequent cell apoptosis of sorafenib resistant cells. In conclusion, artesunate may be a promising strategy to mitigate sorafenib resistance in HCC via exacerbating AFAP1L2-SRC-FUNDC1 axis-dependent mitophagy.Abbreviations: AFAP1L2, actin filament associated protein 1 like 2; ANOVA, analysis of variance; ANXA5, annexin V; ART: artesunate; CETSA, cellular thermal shift assay; CI: combination index; CO-IP: co-immunoprecipitation; CQ: chloroquine; CT, computed tomography; [18F]-FDG, fluoro-2-D-deoxyglucose F18; FUNDC1: FUN14 domain containing 1; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; HCC, hepatocellular carcinoma; H&E Staining: hematoxylin - eosin staining; HepG2R, sorafenib resistant HepG2; IF, immunofluorescence; IHC, immunohistochemistry; LAMP1: lysosomal associated membrane protein 1; MAP1LC3B/LC3B: microtubule associated protein 1 light chain 3 beta; miR, microRNA; mRNA: messenger RNA; OE, overexpression; OS, overall survival; PET, positron emission tomography; qRT-PCR: quantitative real-time PCR; sh, short hairpin; shNC: negative control shRNA; shAFAP1L2: short hairpin AFAP1L2; SORA, sorafenib; SPR, surface plasmon resonance; SRC, SRC proto-oncogene, non-receptor tyrosine kinase; SUV, standardized uptake value; TEM, transmission electron microscopy; TOMM20: translocase of outer mitochondrial membrane 20.

Chemoproteomics reveals berberine directly binds to PKM2 to inhibit the progression of colorectal cancer

Colorectal cancer is one of the most serious tumors and berberine can inhibit the recurrence and transformation of colorectal adenoma into colorectal cancer. However, the direct binding target proteins of berberine in inhibiting colorectal cancer remain unclear. In this study, the chemical proteomics method was used and demonstrated that berberine is directly bound to pyruvate kinase isozyme type M2 (PKM2) in colorectal cancer cells. The triangular N-O-O triangular structure of berberine contributed to hydrophobic interaction with I119 amino acid residues and π-π interaction with F244 amino acid residues of PKM2 protein. Moreover, berberine was shown to inhibit the reprogramming of glucose metabolism and the phosphorylation of STAT3, down regulate the expression of Bcl-2 and Cyclin D1 genes, ultimately inhibiting the progression of colorectal cancer. This study uncovered the direct binding target protein and mechanism of berberine to improve metabolic reprogramming in colorectal cancer, which is helpful to guide the optimization of berberine.

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Berberine directly targets PKM2 to inhibit colorectal cancer

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Berberine forms hydrophobic interaction with I119 and π-π interaction with F244 of PKM2

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P-aminobenzoic acid-berberine ester was synthesized to improve the biological activity

FIBER-ML, an Open-Source Supervised Machine Learning Tool for Quantification of Fibrosis in Tissue Sections

Pathologic fibrosis is a major hallmark of tissue insult in many chronic diseases. Although the amount of fibrosis is recognized as a direct indicator of the extent of disease, there is no consentaneous method for its quantification in tissue sections. This study tested FIBER-ML, a semi-automated, open-source freeware that uses a machine-learning approach to quantify fibrosis automatically after a short user-controlled learning phase. Fibrosis was quantified in sirius red-stained tissue sections from two fibrogenic animal models: acute stress-induced cardiomyopathy in rats (Takotsubo syndrome-like) and HIV-induced nephropathy in mice (chronic kidney disease). The quantitative results of FIBER-ML software version 1.0 were compared with those of ImageJ in Takotsubo syndrome, and with those of inForm in chronic kidney disease. Intra- and inter-operator and inter-software correlation and agreement were assessed. All correlations were excellent (>0.95) in both data sets. The values of discriminatory power between the pathologic and healthy groups were <10^-3 for data on Takotsubo syndrome and <10^-4 for data on chronic kidney disease. Intra-operator agreement, assessed by intra-class coefficient correlation, was good (>0.8), while inter-operator and inter-software agreement ranged from moderate to good (>0.7). FIBER-ML performed in a fast and user-friendly manner, with reproducible and consistent quantification of fibrosis in tissue sections. It offers an open-source alternative to currently used software, including quality control and file management.

Model systems in SDHx-related pheochromocytoma/paraganglioma

Pheochromocytoma (PHEO) and paraganglioma (PGL) (together PPGL) are tumors with poor outcomes that arise from neuroendocrine cells in the adrenal gland, and sympathetic and parasympathetic ganglia outside the adrenal gland, respectively. Many follow germline mutations in genes coding for subunits of succinate dehydrogenase (SDH), a tetrameric enzyme in the tricarboxylic acid (TCA) cycle that both converts succinate to fumarate and participates in electron transport. Germline SDH subunit B (SDHB) mutations have a high metastatic potential. Herein, we review the spectrum of model organisms that have contributed hugely to our understanding of SDH dysfunction. In Saccharomyces cerevisiae (yeast), succinate accumulation inhibits alpha-ketoglutarate-dependent dioxygenase enzymes leading to DNA demethylation. In the worm Caenorhabditis elegans, mutated SDH creates developmental abnormalities, metabolic rewiring, an energy deficit and oxygen hypersensitivity (the latter is also found in Drosophila melanogaster). In the zebrafish Danio rerio, sdhb mutants display a shorter lifespan with defective energy metabolism. Recently, SDHB-deficient pheochromocytoma has been cultivated in xenografts and has generated cell lines, which can be traced back to a heterozygous SDHB-deficient rat. We propose that a combination of such models can be efficiently and effectively used in both pathophysiological studies and drug-screening projects in order to find novel strategies in PPGL treatment.

Imaging pheochromocytoma in small animals: preclinical models to improve diagnosis and treatment

Pheochromocytomas (PCCs) and paragangliomas (PGLs), together referred to as PPGLs, are rare chromaffin cell-derived tumors. They require timely diagnosis as this is the only way to achieve a cure through surgery and because of the potentially serious cardiovascular complications and sometimes life-threatening comorbidities that can occur if left untreated. The biochemical diagnosis of PPGLs has improved over the last decades, and the knowledge of the underlying genetics has dramatically increased. In addition to conventional anatomical imaging by CT and MRI for PPGL detection, new functional imaging modalities have emerged as very useful for patient surveillance and stratification for therapy. The availability of validated and predictive animal models of cancer is essential for translating molecular, imaging and therapy response findings from the bench to the bedside. This is especially true for rare tumors, such as PPGLs, for which access to large cohorts of patients is limited. There are few animal models of PPGLs that have been instrumental in refining imaging modalities for early tumor detection, as well as in identifying and evaluating novel imaging tracers holding promise for the detection and/or treatment of human PPGLs. The in vivo PPGL models mainly include xenografts/allografts generated by engrafting rat or mouse cell lines, as no representative human cell line is available. In addition, there is a model of endogenous PCCs (i.e., MENX rats) that was characterized in our laboratory. In this review, we will summarize the contribution that various representative models of PPGL have given to the visualization of these tumors in vivo and we present an example of a tracer first evaluated in MENX rats, and then translated to the detection of these tumors in human patients. In addition, we will illustrate briefly the potential of ex vivo biological imaging of intact adrenal glands in MENX rats.

Sunitinib Treatment for Advanced Paraganglioma: Case Report of a Novel SDHD Gene Mutation Variant and Systematic Review of the Literature

Background

Paragangliomas (PGLs) are neuroendocrine neoplasms arising from chromaffin cells of sympathetic or parasympathetic paraganglia. Systemic therapies have been used only in metastatic PGLs. Antiangiogenic agents, such as sunitinib, could be a viable therapeutic choice in the subgroup of patients with SDH-positive PGLs. We describe the case of a man with Familial Paraganglioma Syndrome type 1 (FPGL) related to a novel mutation in SDHD gene treated with sunitinib. Furthermore, we performed a systematic review of the literature aimed to address the following question: is sunitinib treatment effective in patients with advanced/progressive/metastatic PGL?

Methods

We performed a data search using MEDLINE, Cochrane Library, and Scopus between April 2019 and September 2020. We included studies reporting data on clinical or biological characteristics, or clinical outcomes of patients with PGLs treated with sunitinib.

Results

The search leaded to the selection of 25 publications. Data from case reports and case series showed that disease control rate (DCR = stable disease + partial response + complete response) was achieved in 34.7% of cases under sunitinib treatment. In 39% of patients DCR was followed by progressive disease (PD) or tumor relapse, 26.1% patients showed PD. Data from clinical trials showed that DCR was 83%, and the median progression free survival was 13.4 months.

Discussion

Data from the present literature review suggested that sunitinib could be a viable therapeutic option in advanced/progressive/metastatic inoperable PGLs. However, further trials on the efficacy of sunitinib in FPGL and sporadic PGL are needed.

Sunitinib-induced cardiac hypertrophy and the endothelin axis

Anti-angiogenics drugs in clinical use for cancer treatment induce cardiotoxic side effects. The endothelin axis is involved in hypertension and cardiac remodelling, and addition of an endothelin receptor antagonist to the anti-angiogenic sunitinib was shown to reduce cardiotoxicity of sunitinib in mice. Here, we explored further the antidote effect of the endothelin receptor antagonist macitentan in sunitinib-treated animals on cardiac remodeling.

Methods: Tumor-bearing mice treated per os daily by sunitinib or vehicle were imaged before and after 1, 3 and 6 weeks of treatment by positron emission tomography using [¹⁸F]fluorodeoxyglucose and by echocardiography. Non-tumor-bearing animals were randomly assigned to be treated per os daily by vehicle or sunitinib or macitentan or sunitinib+macitentan, and imaged by echocardiography after 5 weeks. Hearts were harvested for histology and molecular analysis at the end of in vivo exploration.

Results: Sunitinib treatment increases left ventricular mass and ejection fraction and induces cardiac fibrosis. Sunitinib also induces an early increase in cardiac uptake of [¹⁸F]fluorodeoxyglucose, which is significantly correlated with increased left ventricular mass at the end of treatment. Co-administration of macitentan prevents sunitinib-induced hypertension, increase in ejection fraction and cardiac fibrosis, but fails to prevent increase of the left ventricular mass.

Conclusion: Early metabolic changes predict sunitinib-induced cardiac remodeling. Endothelin blockade can prevent some but not all cardiotoxic side-effects of sunitinib, in particular left ventricle hypertrophy that appears to be induced by sunitinib through an endothelin-independent mechanism.

The VHL/HIF Axis in the Development and Treatment of Pheochromocytoma/Paraganglioma

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from chromaffin cells in the adrenal medulla (PCCs) or extra-adrenal sympathetic or parasympathetic paraganglia (PGLs). About 40% of PPGLs result from germline mutations and therefore they are highly inheritable. Although dysfunction of any one of a panel of more than 20 genes can lead to PPGLs, mutations in genes involved in the VHL/HIF axis including PHD, VHL, HIF-2A (EPAS1), and SDHx are more frequently found in PPGLs. Multiple lines of evidence indicate that pseudohypoxia plays a crucial role in the tumorigenesis of PPGLs, and therefore PPGLs are also known as metabolic diseases. However, the interplay between VHL/HIF-mediated pseudohypoxia and metabolic disorder in PPGLs cells is not well-defined. In this review, we will first discuss the VHL/HIF axis and genetic alterations in this axis. Then, we will dissect the underlying mechanisms in VHL/HIF axis-driven PPGL pathogenesis, with special attention paid to the interplay between the VHL/HIF axis and cancer cell metabolism. Finally, we will summarize the currently available compounds/drugs targeting this axis which could be potentially used as PPGLs treatment, as well as their underlying pharmacological mechanisms. The overall goal of this review is to better understand the role of VHL/HIF axis in PPGLs development, to establish more accurate tools in PPGLs diagnosis, and to pave the road toward efficacious therapeutics against metastatic PPGLs.