Biology subjects

Saarela, J.

Publications and source records attributed to Saarela, J..

11 recordsLinked to original sources

bioRxiv2026

Pathway-centric multi-omics and functional precision medicine reveal shared drug vulnerabilities in heterogeneous adult Wilms tumor

Wilms tumor, i.e., nephroblastoma, is rare in adults and lacks standardized treatment, complicating clinical decision-making. Within the functional precision medicine study (DEDUCER), we profiled two spatially distinct tumor regions (T1 and T2) of an adult Wilms tumor patient using integrated histopathology, whole-exome sequencing, FFPE transcriptomics, and ex vivo drug screening of short-term cultured patient-derived cancer cells (PDCs) with 528 compounds. Genomic profiling revealed a truncal ASXL1 frameshift and shared F7, UBA1, COL21A1, and ATM variants alongside region-specific alterations: a TP53 mutation and broad copy-number (CN) gains in T1, versus ARID1A and KMT2D stop-gains in copy-neutral T2. Transcriptomics of tumor areas identified convergent activation of the G2/M checkpoint, E2F targets, and mitotic spindle programs across regions, consistent with high proliferation and partially comparable biomarker signatures to those observed in an open-source pediatric Wilms tumor dataset (n = 130). Functional assays uncovered distinct and shared drug vulnerabilities: although ATM alterations were present in both tumors, T1 PDCs showed selective sensitivity to topoisomerase I and BCL-2 inhibition in the context of an additional T1-specific TP53 alteration, while broader single-agent sensitivity and stronger drug synergies were observed in T2. Pathway-centric data integration indicated that differential gene expression and copy-number gains, rather than single mutations alone, better predicted ex vivo drug responses, revealing actionable shared dependencies despite pronounced spatial heterogeneity and establishing a translational framework for individualized management in this rare disease. HIGHLIGHTS- In the adult Wilms tumor, multi-region genomics revealed a truncal ASXL1 frameshift together with F7, UBA1, COL21A1 and ATM mutations across two tumor regions (T1 and T2), as well as region-specific alterations: TP53 mutation and widespread copy-number gains in T1, versus ARID1A and KMT2D stop-gains in copy-neutral T2, illustrating spatial heterogeneity. - Transcriptomics showed convergent activation of E2F targets, G2/M checkpoint, and mitotic spindle programs in both regions, consistent with high proliferation and aligning with Wilms tumor signatures (TARGET dataset); these pathways were associated with higher ex vivo drug sensitivity scores. - Functional drug sensitivity testing of patient -derived cancer cells ex vivo uncovered distinct and shared vulnerabilities: Although both tumors shared an ATM mutation, T1-specific TP53 alteration and death-pathway/stress-response alterations may underlie selective sensitivity to topoisomerase I inhibitors and BCL-2 inhibition. - Clinically relevant combinations, including vincristine plus dactinomycin and doxorubicin plus dactinomycin, showed ex vivo synergy. These findings are consistent with the patients more than five-year relapse-free outcome following vincristine, doxorubicin, and dactinomycin treatment combined with surgery, supporting the translational relevance of the ex vivo drug testing approach. - Pathway-centric integration (copy-number gains and differential expression) predicted drug response better than single-gene biomarkers. Overall, pathway-level dependencies provide robust, actionable targets despite genomic and phenotypic heterogeneity in adult Wilms tumor.

Cancer Biology↗

bioRxiv2025

Spatial artefact detection improves reproducibility of drug screening experiments

Reliable and reproducible drug screening experiments are essential for drug discovery and personalized medicine. Here, we demonstrate how systematic experimental errors negatively impact reproducibility, and that conventional quality control (QC) methods based on plate controls fail to detect these errors. To address this limitation, we developed a control-independent QC approach using normalized residual fit error (NRFE) to identify systematic errors in drug screening experiments. Comprehensive analysis of >100,000 duplicate measurements from the PRISM pharmacogenomic study revealed that the NRFE-flagged experiments show three-fold lower reproducibility between technical replicates. By integrating NRFE with existing QC methods to analyze 41,762 matched drug-cell line pairs between two datasets from the Genomics of Drug Sensitivity in Cancer project, we improved the cross-dataset correlation from 0.66 to 0.76. Available as an R package at https://github.com/IanevskiAleksandr/plateQC, plateQC provides a robust toolset for enhancing drug screening data reliability and consistency for basic research and translational applications.

bioinformatics↗

bioRxiv2024

T cell correction pipeline for Inborn Errors of Immunity

CRISPR/Cas9 gene editing technology is a promising tool for correcting pathogenic variants for autologous cell therapies for Inborn Errors of Immunity (IEI). The present IEI correction strategies mainly focus on the knock-in of therapeutic cDNAs, or knockout of the disease-causing gene when feasible. These strategies address many single-gene defects but may disrupt gene expression and require significant optimization for each newly discovered IEI-causing gene, highlighting the need for complementary platforms that can precisely correct diverse pathogenic variants. Here, we present a safe and efficient T cell single nucleotide variant (SNV) correction pipeline based on homology-directed repair (HDR), suitable for diverse monogenic mutations. By using founder mutations of Deficiency of ADA2 (DADA2), Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) and Cartilage Hair Hypoplasia (CHH) as IEI models, we show that our pipeline can achieve up to 80% bi-allelic editing, with resultant functional correction of the disease phenotype in patient T cells. We do not find detectable pre-malignant off-target effects or karyotypic, transcriptomic or proteomic aberrations upon profiling patient T cells with GUIDE-seq, single cell RNA sequencing, PacBio based long-read whole genome sequencing, and high-throughput proteomics. This study demonstrates that HDR-based SNV editing is a safe and effective option for IEI T cell correction and that it could be developed to an autologous T cell therapy, as the presented protocol is scalable for a GMP-compatible workflow. This study is a step towards the development of gene correction platform that targets a broad number of monogenic mutations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/610811v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1f1eb47org.highwire.dtl.DTLVardef@18dbcc2org.highwire.dtl.DTLVardef@63862dorg.highwire.dtl.DTLVardef@1fe1561_HPS_FORMAT_FIGEXP M_FIG GRAPHICAL ABSTRACT C_FIG

bioengineering↗

bioRxiv2023

Designing patient-oriented combination therapies for acute myeloid leukemia based on efficacy/toxicity integration and bipartite network modeling

Acute myeloid leukemia (AML), a heterogeneous and aggressive blood cancer, does not respond well to single-drug therapy. A combination of drugs is required to effectively treat this disease. Computational models are critical for combination therapy discovery due to the tens of thousands of two-drug combinations, even with approved drugs. While predicting synergistic drugs is the focus of current methods, few consider drug efficacy and potential toxicity, which are crucial for treatment success. To find effective new drug candidates, we constructed a bipartite network using patient-derived tumor samples and drugs. The network is based on drug-response screening and summarizes all treatment response heterogeneity as drug response weights. This bipartite network is then projected onto the drug part, resulting in the drug similarity network. Distinct drug clusters were identified using community detection methods, each targeting different biological processes and pathways as revealed by enrichment and pathway analysis of the drugs protein targets. Four drugs with the highest efficacy and lowest toxicity from each cluster were selected and tested for drug sensitivity using cell viability assays on various samples. Results show that the combinations of ruxolitinib-ulixertinib and sapanisertib-LY3009120 are the most effective with the least toxicity and best synergistic effects on blasts. These findings lay the foundation for personalized and successful AML therapies, ultimately leading to the development of drug combinations that can be used alongside standard first-line AML treatment. Key PointsO_LIRuxolitinib-ulixertinib and sapanisertib-LY3009120 have the best synergistic effects on AML, with the least toxicity. C_LIO_LIThis studys combinations destroy blasts without harming other healthy cells, unlike standard chemotherapy, which is less specific. C_LI

cancer biology↗

bioRxiv2020

Minimal information for Chemosensitivity assays (MICHA): A next-generation pipeline to enable the FAIRification of drug screening experiments

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of MICHA (Minimal Information for Chemosensitivity Assays), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents, and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets, and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies, as well as six recently conducted COVID-19 studies. With the MICHA webserver and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.

bioinformatics↗

bioRxiv2019

The kinase inhibitor AT9283 selectively kills colorectal cancer cells with hyperactive NRF2

Aberrant hyperactivation of NRF2 is a common event in many tumour types and associates with resistance to therapy and poor patient prognosis. The identification of ways to overcome the protection provided by NRF2 and selectively kill cancer cells addicted to NRF2 is a desirable goal. Exploiting the CRISPR/Cas9 technology, we generated colorectal cancer cell lines with hyperactive NRF2, and used them to perform a drug screen. We identified AT9283, an Aurora kinase inhibitor, for its selectivity towards killing cancer cells with hyperactive NRF2 as a consequence to either genetic or pharmacological activation. Our results show that hyperactivation of NRF2 presents a potential vulnerability that could be therapeutically exploited, and further suggest that AT9283, a drug that is currently in clinical trials, holds promise for the treatment of tumours with hyperactive NRF2.\n\nHighlightsO_LIWe present a new model for NRF2 hyperactivation in colorectal cancer cells.\nC_LIO_LIAT9283 selectively kills cancer cells with hyperactive NRF2\nC_LIO_LIBoth genetic and pharmacological activation of NRF2 sensitise cells to AT9283\nC_LI

cancer biology↗

bioRxiv2018

Haploinsufficiency of A20 impairs protein-protein interactome and leads into caspase-8-dependent enhancement of NLRP3 inflammasome activation

ObjectivesTNFAIP3 encodes A20 that negatively regulates nuclear factor kappa light chain enhancer of activated B cells (NF-{kappa}B), the major transcription factor coordinating inflammatory gene expression. TNFAIP3 polymorphisms have been linked with a spectrum of inflammatory and autoimmune diseases and recently, loss-of-function mutations in A20 were found to cause a novel inflammatory disease haploinsufficiency of A20 (HA20). Here we describe a family with HA20 caused by a novel TNFAIP3 loss-of-function mutation and elucidate the upstream molecular mechanisms linking HA20 to dysregulation of NF-{kappa}B and the related inflammasome pathway.\n\nMethodsNF-{kappa}B activation was studied in a mutation-expressing cell line using luciferase reporter assay. Physical and close-proximity protein-protein interactions of wild-type and TNFAIP3 p.(Lys91*) mutant A20 were analyzed using mass spectrometry. NF-{kappa}B -dependent transcription, cytokine secretion, and inflammasome activation were compared in immune cells of the HA20 patients and control subjects.\n\nResultsThe protein-protein interactome of p.(Lys91*) mutant A20 was severely impaired, including inter-actions with proteins regulating NF-{kappa}B activation, DNA repair responses, and the NLR family pyrin domain containing 3 (NLRP3) inflammasome. The p.(Lys91*) mutant A20 failed to suppress NF-{kappa}B signaling, which led to increased NF-{kappa}B -dependent proinflammatory cytokine transcription. Functional experiments in the HA20 patients immune cells uncovered a novel caspase-8-dependent mechanism of NLRP3 inflammasome hyperresponsiveness that mediated the excessive secretion of interleukin-1{beta} and -18.\n\nConclusionsThe current findings significantly deepen our understanding of the molecular mechanisms underlying HA20 and other diseases associated with reduced A20 expression or function, paving the way for future therapeutic targeting of the pathway.

molecular biology↗

bioRxiv2018

Characterization of novel TMEM173 mutation with additive IFIH1 risk allele

TMEM173 encodes for STING that is a transmembrane protein activated by pathogen or self-derived cytosolic nucleic acids causing its translocation from ER to Golgi, and further to vesicles. Monogenic STING gain-of-function mutations cause early-onset type I interferonopathy, with disease presentation ranging from fatal vasculopathy to mild chilblain lupus. Molecular mechanisms causing the poor phenotypegenotype correlation are presently unclear. Here we report a novel gain-of-function G207E STING mutation causing a distinct phenotype with alopecia, photosensitivity, thyroid dysfunction, and STING-associated vasculopathy with onset in infancy (SAVI) -features; livedo reticularis, nasal septum perforation, facial erythema, bacterial infections and skin vasculitis. Single residue polymorphisms in TMEM173 and an IFIH1 T946 risk allele modify disease presentation in the affected multigeneration family, explaining the varying clinical phenotypes. The G207E mutation causes constitutive activation of inflammation-related pathways in HEK cells, as well as aberrant interferon signature and inflammasome activation in patient PBMCs. Protein-protein interactions further propose impaired cellular trafficking of G207E mutant STING. These findings reveal the molecular landscape of STING and highlight the complex additive effects on the phenotype.\n\nBRIEF SUMMARYNovel gain-of-function mutation in TMEM173, associated with single residue polymorphisms in TMEM173 and IFIH1, causes a distinct clinical phenotype with some shared features of SAVI.

immunology↗

bioRxiv2018

Low frequency and rare coding variation contributes to multiple sclerosis risk

Multiple sclerosis is a common, complex neurological disease, where almost 20% of risk heritability can be attributed to common genetic variants, including >230 identified by genome-wide association studies (Patsopoulos et al., 2017). Multiple strands of evidence suggest that the majority of the remaining heritability is also due to the additive effects of individual variants, rather than epistatic interactions between these variants, or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that as much as 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common variant signals, which highlight a key role for regulatory T cell homeostasis and regulation, IFN{gamma} biology and NF{kappa}B signaling in MS pathogenesis. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.

genetics↗

bioRxiv2017

Genetics of vaccination-related narcolepsy

Narcolepsy type 1 is a severe hypersomnia affecting 1/3000 individuals. It is caused by a loss of neurons producing hypocretin/orexin in the hypothalamus. In 2009/2010, an immunization campaign directed towards the new pandemic H1N1 Influenza-A strain was launched and increased risk of narcolepsy reported in Northern European countries following vaccination with Pandemrix(R), an adjuvanted H1N1 vaccine resulting in ~250 vaccination-related cases in Finland alone. Using whole genome sequencing data of 2000 controls, exome sequencing data of 5000 controls and HumanCoreExome chip genotypes of 81 cases with vaccination-related narcolepsy and 2796 controls, we, built a multilocus genetic risk score with established narcolepsy risk variants. We also analyzed, whether novel risk variants would explain vaccine-related narcolepsy. We found that previously discovered risk variants had strong predictive power (accuracy of 73% and P<2.2*10-16; and ROC curve AUC 0.88) in vaccine-related narcolepsy cases with only 4.9% of cases being assigned to the low risk category. Our findings indicate genetic predisposition to vaccine-triggered narcolepsy, with the possibility of identifying 95% of people at risk.

genetics↗

bioRxiv2017

The Multiple Sclerosis Genomic Map: Role of peripheral immune cells and resident microglia in susceptibility

AbstractWe assembled and analyzed genetic data of 47,351 multiple sclerosis (MS) subjects and 68,284 control subjects and establish a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 independent associations within the extended MHC. We used an ensemble of methods to prioritize up to 551 potentially associated MS susceptibility genes, that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we do find enrichment for MS genes in these brain - resident immune cells. Thus, while MS is most likely initially triggered by perturbation of peripheral immune responses the functional responses of microglia and other brain cells are also altered and may have a role in targeting an autoimmune process to the central nervous system.\n\nOne Sentence SummaryWe report a detailed genetic and genomic map of multiple sclerosis, and describe the role of putatively affected genes in the peripheral immune system and brain resident microglia.

genetics↗