Abstract BACKGROUND The discovery of somatic mutations in ACVR1, which encodes the serine/threonine kinase ALK2, in 20-25% of diffuse midline glioma H3K27-altered (DMG-H3K27) patients has led to the development of numerous chemotypes of ALK2 inhibitor (ALK2i). However, in models of ACVR1-mutant DMG-H3K27 the efficacy of single-agent ALK2i’s has been modest and new combinatorial treatment approaches are desperately needed. METHODS We performed unbiased combinatorial genetic and drug screens in patient-derived ACVR1-mutant DMG-H3K27 cells in vitro, using multiple chemotypes of ALK2i. We also generated in vitro transcriptomic, proteomic and metabolomic profiles of three ACVR1-mutant DMG-H3K27 models following ALK2i treatment. RESULTS The top ALK2i sensitising CRISPR hits (vehicle vs. ALK2i) were analysed using gene set enrichment analysis (GSEA) which revealed specific genetic dependencies in cholesterol synthesis/regulation following both M4K2009 and TP-0184 treatment. The top CRISPR hits included multiple key nodes of cholesterol biosynthesis such as HMGCR (HMG-CoA>mevalonate), LSS (squalene-2-2-epoxide>lanosterol) and DHCR24 (lanosterol>cholesterol). These hits were pharmacologically mirrored in the top hits identified from the drug screen, including drugs that either directly or indirectly target cholesterol synthesis. Integration of the multi-omic data revealed a raft of changes associated with cholesterol biosynthesis/efflux. The expression of HMGCR/HMGCS1 (cholesterol synthesis) and LXR/ABCA1 (cholesterol export) were down and upregulated, respectively, with metabolomic data showing a reduction in cholesterol and it’s derivative 4-cholesten-3-one and an increase in desmosterol, an immediate precursor to cholesterol synthesis. Highly synergistic interactions were observed between multiple ALK2i and a panel of pharmacological agents targeting the cholesterol synthesis/efflux pathway, including routinely used drugs such as simvastatin and lovastatin, clinically well-tolerated and with good CNS penetrance in immuno-compromised and immune-competent mouse models, in whom in vivo combination studies are ongoing. CONCLUSIONS These data provide evidence for a previously unappreciated link between ALK2 signalling and metabolism, and identify readily translatable combination partners for ALK2i in the clinic.
Additional file 2. Table S1. Heat map ranking the total phosphopeptide intensity for specific kinases across the 19 PDX samples. Table S2. Heat map ranking individual phosphopeptide intensity for specific kinases across the 19 PDX samples.
Abstract Oncogenic FGFR4 signalling represents a potential therapeutic target in various cancer types, including triple negative breast cancer (TNBC) and hepatocellular carcinoma (HCC). However, resistance to FGFR4 single-agent therapy remains a major challenge, emphasizing the need for effective combinatorial treatments. Our study sought to develop a comprehensive computational model of FGFR4 signalling and provide network-level insights into resistance mechanisms driven by signalling dynamics. Our integrated approach, combining computational network modelling with experimental validation, uncovered potent AKT reactivation following FGFR4 targeting in the TNBC cell line MDA-MB-453. By systematically simulating the model to analyse the effects of co-targeting specific network nodes, we were able to predict, and subsequently confirm through experimental validation, the strong synergy of co-targeting FGFR4 and AKT or specific ErbB kinases, but not PI3K. Incorporating protein expression data from hundreds of cancer cell lines, we then adapted our model to diverse cellular contexts. This revealed that while AKT rebound is common, it is not a general phenomenon. ERK reactivation, for example, occurs in certain cell types, including the FGFR4-driven HCC cell line Hep3B, where there is a synergistic effect of co-targeting FGFR4 and MEK, but not AKT. In summary, our study offers key insights into drug-induced network remodelling and the role of protein expression heterogeneity in targeted therapy responses. We underscore the utility of computational network modelling for designing cell type-selective combination therapies and enhancing precision cancer treatment. Significance This study underscores the potential of computational predictive modelling in deciphering mechanisms of cancer cell resistance to targeted therapies and in designing more effective, cancer type-specific combination treatments.
Abstract Background Triple negative breast cancer (TNBC) accounts for 16% of breast cancers and represents an aggressive subtype that lacks targeted therapeutic options. In this study, mass spectrometry (MS)-based tyrosine phosphorylation profiling identified aberrant FGFR3 activation in a subset of TNBC cell lines. This kinase was therefore evaluated as a potential therapeutic target. Methods MS-based tyrosine phosphorylation profiling was undertaken across a panel of 24 TNBC cell lines. Immunoprecipitation and Western blot were used to further characterize FGFR3 phosphorylation. Indirect immunofluorescence and confocal microscopy were used to determine FGFR3 localization. The selective FGFR1–3 inhibitor, PD173074 and siRNA knockdowns were used to characterize the functional role of FGFR3 in vitro. The TCGA and Metabric breast cancer datasets were interrogated to identify FGFR3 alterations and how they relate to breast cancer subtype and overall patient survival. Results High FGFR3 expression and phosphorylation were detected in SUM185PE cells, which harbor a FGFR3-TACC3 gene fusion. Low FGFR3 phosphorylation was detected in CAL51, MFM-223 and MDA-MB-231 cells. In SUM185PE cells, the FGFR3-TACC3 fusion protein contributed the majority of phosphorylated FGFR3, and largely localized to the cytoplasm and plasma membrane, with staining at the mitotic spindle in a small subset of cells. Knockdown of the FGFR3-TACC3 fusion and wildtype FGFR3 in SUM185PE cells decreased FRS2, AKT and ERK phosphorylation, and induced cell death. Knockdown of wildtype FGFR3 resulted in only a trend for decreased proliferation. PD173074 significantly decreased FRS2, AKT and ERK activation, and reduced SUM185PE cell proliferation. Cyclin A and pRb were also decreased in the presence of PD173074, while cleaved PARP was increased, indicating cell cycle arrest in G1 phase and apoptosis. Knockdown of FGFR3 in CAL51, MFM-223 and MDA-MB-231 cells had no significant effect on cell proliferation. Interrogation of public datasets revealed that increased FGFR3 expression in breast cancer was significantly associated with reduced overall survival, and that potentially oncogenic FGFR3 alterations (eg mutation and amplification) occur in the TNBC/basal, luminal A and luminal B subtypes, but are rare. Conclusions These results indicate that targeting FGFR3 may represent a therapeutic option for TNBC, but only for patients with oncogenic FGFR3 alterations, such as the FGFR3-TACC3 fusion.
Pediatric high-grade gliomas (pHGGs) are the most aggressive brain tumors in children, necessitating innovative therapies to improve outcomes. Unlike adult gliomas, recent research reveals that childhood gliomas have distinct biological features, requiring specific treatment strategies. Here, we focused on deciphering unique genetic dependencies specific to childhood gliomas. Using a pooled CRISPR/Cas9 knockout screening approach on 65 pediatric and 10 adult high-grade glioma (HGG) cell lines, myeloid cell leukemia 1 (MCL1) emerged as a key antiapoptotic gene essential in pediatric but not adult gliomas. We demonstrated that MCL1 is targetable using current small molecule inhibitors, and its inhibition leads to potent anticancer activity across pediatric HGG cell lines irrespective of genotype. Employing predictive modeling approaches on a large set of childhood cancer cell lines with multiomics data features, we identified a potentially previously unreported cluster of CpG sites in the antiapoptotic BCL-xL/BCL2L1 gene, which predicted MCL1 inhibitor response. We extended these data across multiple pediatric tumor types, showing that BCL2L1 methylation is a broad predictor of MCL1 dependency in vitro and in vivo. Overall, our multidimensional, integrated genomic approach identified MCL1 as a promising therapeutic target in several BCL2L1-methylated pediatric cancers, offering a translational strategy to identify patients most likely to benefit from MCL1 inhibitor therapy.
Abstract Pediatric Central Nervous System (CNS) tumors are the leading cause of cancer-related death among children. Identifying new targeted therapies necessitates the use of pediatric cancer models that faithfully recapitulate the patient’s disease. However, the generation and characterization of pediatric cancer models has significantly lagged adult cancers, underscoring the urgent need to develop and characterize pediatric CNS models of disease. Herein, we establish a single-site collection of 233 CNS tumour cell lines, representing 14 distinct brain childhood tumor types. We subjected >200 cell lines to multi-omics analyses (DNA-sequencing, RNA-sequencing, DNA methylation, proteomics, phospho-proteomics), and in parallel performed pharmacological and genetic CRISPR-Cas9 loss of function screens to identify pediatric-specific treatment opportunities and biomarkers. Our work provides insight into specific pathway vulnerabilities in molecularly defined pediatric tumor classes and uncovers biomarker-linked therapeutic opportunities of clinical relevance. Cell line data and resources are provided in an open access portal (vicpcc.org.au/dashboard).
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