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Van De Vijver, E.

Publications and source records attributed to Van De Vijver, E..

2 recordsLinked to original sources

Pharmacological inhibition of deubiquitinase UCH-L1 by LDN57444 sensitises hepatocellular carcinoma to sorafenib by reverting drug-induced adaptive responses

Background and aimsTherapeutic outcomes for advanced hepatocellular carcinoma remain inadequate, despite recent advances using immunotherapy. Long-term effectiveness of systemic therapies, including second-line multi-tyrosine kinase inhibitor sorafenib, is limited by resistance mechanisms and adverse effects. Upregulated deubiquitinase UCH-L1 is frequently correlated with poor prognosis in cancers. Here, we investigated the therapeutic potential of combining pharmacological UCH-L1-inhibition with sorafenib in HCC. MethodsUCH-L1 expression was analysed in TCGA-LIHC data and patient-derived HCC tissues. Sorafenib and LDN57444 effects were evaluated in vitro in cytotoxicity and invasion assays. Gene and protein expression were examined by RT-qPCR, Western blotting and immunohistochemistry. In vivo efficacy of drug synergy was assessed in an orthotopic xenograft mouse HCC model. ResultsIn silico data-analysis revealed significantly higher UCH-L1 levels in patient HCC tumours versus non-tumour, associated with reduced overall survival. Low-dose sorafenib upregulated UCH-L1 in HCC cell line Hep3B. Paradoxically, this also promoted invasiveness and sustained MEK1/2-ERK1/2-pathway activation. Combining low-dose sorafenib with LDN57444 produced strong synergistic cytotoxicity in vitro, reverted MAPK-activation and suppressed invasion. Consistently, at low sorafenib dose co-treatment with LDN57444 completely inhibited tumour growth of Hep3B xenografts and enhanced sorafenib efficacy. ConclusionLDN57444 sensitises HCC cells to low-dose sorafenib by reverting drug-induced pro-oncogenic signalling and thereby strongly synergises with sorafenib to enhance anti-tumour efficacy in a HCC mouse model. This presents UCH-L1 as a player in treatment-induced adaptive response and supports further exploring UCH-L1-targeting in combination with sorafenib as therapeutic avenue for advanced HCC. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=144 SRC="FIGDIR/small/725527v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@176dc91org.highwire.dtl.DTLVardef@8acae8org.highwire.dtl.DTLVardef@f71bborg.highwire.dtl.DTLVardef@1f3c5aa_HPS_FORMAT_FIGEXP M_FIG C_FIG Lay summaryThis study explores a new treatment approach for hepatocellular carcinoma (HCC) by combining two drugs: LDN57444, which blocks the enzyme UCH-L1, and sorafenib, a FDA-approved multi-tyrosine kinase inhibitor. We evaluated the effect of this drug combination in vitro using a HCC cell line and in an mouse HCC-model. The drug combination displayed strong, synergy in lowering HCC cell viability, and greatly reduced invasiveness and in vivo tumour growth. LDN57444 sensitised HCC cells to low doses of sorafenib by preventing UCH-L1-mediated activation of pro-oncogenic signalling. These findings highlight the potential of this new drug combination for treating advanced HCC thereby potentially reducing side-effects and countering drug resistance. Impact and implicationsOur preclinical research introduces a novel combination strategy against advanced HCC that holds potential to improve existing therapies, particularly the second-line multi-tyrosine kinase inhibitor sorafenib. The proposed combination of sorafenib with an inhibitor of the deubiquitinase UCH-L1 not only enhances sorafenib efficacy but present promise to also counter resistance mechanisms. Moreover, because effective responses are achieved at lower drug doses, this may in addition reduce therapy-associated adverse effects further increasing potential impact. While sorafenib is FDA-approved, the UCH-L1 inhibitor LDN57444 needs further (clinical) development to bring our promising findings to full translational potential for HCC patients and physicians.

cancer biology↗

SImBA-SiQuAl: a new tool enabling high-content high-throughput phenotypic profiling of 3D microtumours.

Three-dimensional microtumour models such as spheroids are increasingly used in cancer research as they better capture tumour architecture, growth and invasion than conventional two-dimensional cultures. However, robust and accessible tools for quantitative analysis remain limited. Here we present SImBA-SiQuAl, an integrated open-source workflow for high-throughput quantitative phenotyping of 3D spheroids and organoids. The pipeline combines SImBA, an automated image-analysis framework for performant quality-controlled image segmentation and multi-feature extraction from spheroid assays, with SiQuAl, a downstream analysis platform that automatically performs comprehensive statistical and multivariate analyses to reveal phenotypic differences between experimental conditions. In a first case study, we showcase how SImBA-SiQuAl resolves intrinsic invasion phenotypes between cancer cell lines. In a second case study, it quantifies heterogeneous responses in a spheroid drug screening assay. Together, SImBA-SiQuAl provides an effective timely tool for high-throughput, high-content microtumour phenomics in cancer research. MOTIVATION3D-microtumour assays such as spheroids and organoids are increasingly used in preclinical research. These assays generate rich phenotypic imaging data, but automated quantitative analysis remains a major bottleneck. This limits reproducibility, scalability, and broad adoption for large-scale, high-content phenomics studies. Moreover, it impedes comprehensively addressing biologically relevant phenotypic (heterogeneous) responses in e.g. perturbation studies. SImBA-SiQuAl (Spheroid Image Batch Analysis - Simba Quantitative output Analysis) is developed to address this gap by providing an open-source, integrated workflow offering solutions in both the image processing and downstream analysis. Together, this enables in-depth quantitative analysis of 3D microtumour phenotypes across experimental settings.

cancer biology↗