bioRxivCancer BiologyPreprint
Integrative multi-omics combined with functional pharmacological profiling in patient-derived organoids identifies personalized therapeutic vulnerabilities of adult high-grade gliomas
Luca ErminiiD, Anuja LipsaiD, Ann‐Christin HauiD, Iryna Krokhmal, Bakhtiyor NosiroviD, Réka TóthiD, Eliane KleiniD, Anaïs OudiniD, Linsey Houben, Sabrina FritahiD, Christel C. Herold‐MendeiD, Katrin B. M. FrauenknechtiD, Michel Guy André MittelbronniD, Guy BerchemiD, Frank HerteliD, Tathiane Maistro MaltaiD, Petr V. NazaroviD, Simone P. NiclouiD, Anna GolebiewskaiD
Abstract
BackgroundPrecision medicine has transformed cancer treatment by tailoring therapies to specific molecular aberrations. Integrating high-resolution multi-omics with high-throughput functional profiling in patient-derived organoids of-fers a powerful strategy to further refine patient stratification. While (epi)genetic profiling has drastically improved the classification in diffuse adult gliomas, these advances have not yet translated into effective therapeutic interventions and precision medicine approaches remain to be established. Material and MethodsWe investigated a panel of 48 patient-derived organoid and orthotopic xenograft models of adult high-grade gliomas, comprehensively characterized at genomic, epigenomic and transcriptomic levels. A functional drug screen was performed on 27 organoid models using a 202-compound library targeting cancer-related pathways and epigenetic regulators. Unsupervised multi-omics factor analysis was employed to identify patient-specific therapeutic vulnerabilities. Validation included dose-dependent drug efficacy assessments, as well as biomarker assessment in patient tumors across molecular subgroups. ResultsMulti-omics analysis revealed a broad spectrum of molecular profiles capturing the genetic, epigenetic, and transcriptomic diversity of high-grade gliomas. Multi-omics factor analysis, integrating multi-omics and drug response profiles, identified distinct subgroups associated with IDH1 mutation and MYCN amplification. IDH1 mutant grade 4 astrocytomas showed selective sensitivity to histone deacetylase 3 inhibitors, while a MYCN-amplified glioblastoma responded preferentially to histone methyltransferase inhibitors. The differential drug responses were linked to specific (epi)genetic and transcriptomic biomarkers. While other glioblastomas exhibited heterogeneous treatment responses, no robust biomarker-defined responder subgroups were identified. ConclusionOur findings highlight the value of integrating multi-omics and functional profiling to inform precision medicine strategies. This approach enables the stratification of distinct patient subgroups in preclinical models, paving the way for tailored therapeutic interventions. While we observed distinct pharmacogenomic profiles in IDH1 mutant grade 4 astrocytomas and a MYCN-amplified glioblastoma, implementing precision medicine in other glioblastoma subtypes remains a substantial challenge. Key pointsO_LIIntegrating drug screening in a panel of patient-derived organoids with multi-omics enables pharmacogenomic profiling in adult diffuse high-grade gliomas C_LIO_LIIDH1 mutant grade 4 astrocytomas are sensitive to histone deacetylase 3 inhibitors C_LIO_LIMYCN-amplified glioblastoma exhibits distinct DNA methylation pattern and drug responses C_LI Study importanceTo date, attempts to develop effective precision medicine in adult high-grade gliomas failed. Here, we provide a preclinical framework for identifying personalized therapeutic by integrating multi-omics profiling with functional drug screening in patient-derived organoids. We show that IDH1 mutant high-grade astrocytomas present distinct therapeutic vulnerabilities compared to glioblastomas, linked to sensitivity to histone deacetylase 3 inhibitors. Within glioblastomas, we identified a distinct MYCN-amplified tumor, sensitive to histone methyltransferase inhibitors. Applying pharmacogenomic approaches using novel drug libraries holds promise for uncovering additional clinically relevant patient subgroups in the future. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/675145v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@12c04f9org.highwire.dtl.DTLVardef@fa8872org.highwire.dtl.DTLVardef@141de6org.highwire.dtl.DTLVardef@b72086_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- assay: bulk RNA-seq
- assay: DNA methylation
- assay: multiome
- research focus: drug response / drug discovery
- research focus: cell type annotation
- approach: deep learning
- approach: statistical model
- Citations
- 5
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