| 1. |
- Abdelrazak Morsy, Mohammad Hamdy, et al.
(författare)
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SOX11 is a novel binding partner and endogenous inhibitor of SAMHD1 ara-CTPase activity in mantle cell lymphoma
- 2024
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Ingår i: Blood. - : American Society of Hematology. - 0006-4971 .- 1528-0020. ; 143:19, s. 1953-1964
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Tidskriftsartikel (refereegranskat)abstract
- Sterile alpha motif and histidine-aspartate (HD) domain-containing protein 1 (SAMHD1) is a deoxynucleoside triphosphate triphosphohydrolase with ara-CTPase activity that confers cytarabine (ara -C) resistance in several hematological malignancies. Targeting SAMHD1's ara-CTPase activity has recently been demonstrated to enhance ara -C ef fi cacy in acute myeloid leukemia. Here, we identify the transcription factor SRY-related HMGbox containing protein 11 (SOX11) as a novel direct binding partner and fi rst known endogenous inhibitor of SAMHD1. SOX11 is aberrantly expressed not only in mantle cell lymphoma (MCL), but also in some Burkitt lymphomas. Coimmunoprecipitation of SOX11 followed by mass spectrometry in MCL cell lines identi fi ed SAMHD1 as the top SOX11 interaction partner, which was validated by proximity ligation assay. In vitro, SAMHD1 bound to the HMG box of SOX11 with low-micromolar af fi nity. In situ crosslinking studies further indicated that SOX11-SAMHD1 binding resulted in a reduced tetramerization of SAMHD1. Functionally, expression of SOX11 inhibited SAMHD1 ara-CTPase activity in a dose-dependent manner resulting in ara -C sensitization in cell lines and in a SOX11-inducible mouse model of MCL. In SOX11-negative MCL, SOX11-mediated ara-CTPase inhibition could be mimicked by adding the recently identi fi ed SAMHD1 inhibitor hydroxyurea. Taken together, our results identify SOX11 as a novel SAMHD1 interaction partner and its fi rst known endogenous inhibitor with potentially important implications for clinical therapy strati fi cation.
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| 2. |
- Babacic, Haris, et al.
(författare)
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Glioblastoma stem cells express non-canonical proteins and exclusive mesenchymal-like or non-mesenchymal-like protein signatures
- 2023
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Ingår i: Molecular Oncology. - : John Wiley & Sons. - 1574-7891 .- 1878-0261. ; 17:2, s. 238-260
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Tidskriftsartikel (refereegranskat)abstract
- Glioblastoma (GBM) cancer stem cells (GSCs) contribute to GBM's origin, recurrence, and resistance to treatment. However, the understanding of how mRNA expression patterns of GBM subtypes are reflected at global proteome level in GSCs is limited. To characterize protein expression in GSCs, we performed in-depth proteogenomic analysis of patient-derived GSCs by RNA-sequencing and mass-spectrometry. We quantified > 10 000 proteins in two independent GSC panels and propose a GSC-associated proteomic signature characterizing two distinct phenotypic conditions; one defined by proteins upregulated in proneural and classical GSCs (GPC-like), and another by proteins upregulated in mesenchymal GSCs (GM-like). The GM-like protein set in GBM tissue was associated with necrosis, recurrence, and worse overall survival. Through proteogenomics, we discovered 252 non-canonical peptides in the GSCs, i.e., protein sequences that are variant or derive from genome regions previously considered non-protein-coding, including variants of the heterogeneous ribonucleoproteins implicated in RNA splicing. In summary, GSCs express two protein sets that have an inverse association with clinical outcomes in GBM. The discovery of non-canonical protein sequences questions existing gene models and pinpoints new protein targets for research in GBM.
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| 3. |
- Edsjö, Anders, et al.
(författare)
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Precision cancer medicine : Concepts, current practice, and future developments
- 2023
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Ingår i: Journal of Internal Medicine. - 0954-6820 .- 1365-2796. ; 294:4, s. 455-481
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Forskningsöversikt (refereegranskat)abstract
- Precision cancer medicine is a multidisciplinary team effort that requires involvement and commitment of many stakeholders including the society at large. Building on the success of significant advances in precision therapy for oncological patients over the last two decades, future developments will be significantly shaped by improvements in scalable molecular diagnostics in which increasingly complex multilayered datasets require transformation into clinically useful information guiding patient management at fast turnaround times. Adaptive profiling strategies involving tissue- and liquid-based testing that account for the immense plasticity of cancer during the patient's journey and also include early detection approaches are already finding their way into clinical routine and will become paramount. A second major driver is the development of smart clinical trials and trial concepts which, complemented by real-world evidence, rapidly broaden the spectrum of therapeutic options. Tight coordination with regulatory agencies and health technology assessment bodies is crucial in this context. Multicentric networks operating nationally and internationally are key in implementing precision oncology in clinical practice and support developing and improving the ecosystem and framework needed to turn invocation into benefits for patients. The review provides an overview of the diagnostic tools, innovative clinical studies, and collaborative efforts needed to realize precision cancer medicine.
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| 4. |
- Lehtiö, Janne, et al.
(författare)
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Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune-evasion mechanisms
- 2021
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Ingår i: Nature Cancer. - : Springer Science and Business Media LLC. - 2662-1347. ; 2:11, s. 1224-1242
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Tidskriftsartikel (refereegranskat)abstract
- Despite major advancements in lung cancer treatment, long-term survival is still rare and a deeper understanding of molecular phenotypes would allow the identification of specific cancer dependencies and immune-evasion mechanisms. Here we performed in-depth mass-spectrometry-based proteogenomic analysis of 141 tumors representing all major histologies of non-small cell lung cancer (NSCLC). We identified six distinct proteome subtypes with striking differences in immune cell composition and subtype-specific expression of immune checkpoints. Unexpectedly, high neoantigen burden was linked to global hypomethylation and complex neoantigens mapped to genomic regions, such as endogenous retroviral elements and introns, in immune-cold subtypes. Further, we linked immune evasion with LAG-3 via STK11 mutation-dependent HNF1A activation and FGL1 expression. Finally, we develop a data-independent acquisition mass-spectrometry-based NSCLC subtype classification method, validate it in an independent cohort of 208 NSCLC cases and demonstrate its clinical utility by analyzing an additional cohort of 84 late-stage NSCLC biopsy samples.
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| 5. |
- Rudd, Sean, et al.
(författare)
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Ribonucleotide reductase inhibitors suppress SAMHD1 ara-CTPase activity enhancing cytarabine efficacy
- 2020
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Ingår i: EMBO Molecular Medicine. - : Blackwell Publishing Ltd. - 1757-4676 .- 1757-4684.
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Tidskriftsartikel (refereegranskat)abstract
- The deoxycytidine analogue cytarabine (ara-C) remains the backbone treatment of acute myeloid leukaemia (AML) as well as other haematological and lymphoid malignancies, but must be combined with other chemotherapeutics to achieve cure. Yet, the underlying mechanism dictating synergistic efficacy of combination chemotherapy remains largely unknown. The dNTPase SAMHD1, which regulates dNTP homoeostasis antagonistically to ribonucleotide reductase (RNR), limits ara-C efficacy by hydrolysing the active triphosphate metabolite ara-CTP. Here, we report that clinically used inhibitors of RNR, such as gemcitabine and hydroxyurea, overcome the SAMHD1-mediated barrier to ara-C efficacy in primary blasts and mouse models of AML, displaying SAMHD1-dependent synergy with ara-C. We present evidence that this is mediated by dNTP pool imbalances leading to allosteric reduction of SAMHD1 ara-CTPase activity. Thus, SAMHD1 constitutes a novel biomarker for combination therapies of ara-C and RNR inhibitors with immediate consequences for clinical practice to improve treatment of AML. © 2020 The Authors. Published under the terms of the CC BY 4.0 license
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| 6. |
- Struyf, Nona, et al.
(författare)
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Delineating functional and molecular impact of ex vivo sample handling in precision medicine
- 2024
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Ingår i: npj Precision Oncology. - : Springer Nature. - 2397-768X. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Consistent handling of samples is crucial for achieving reproducible molecular and functional testing results in translational research. Here, we used 229 acute myeloid leukemia (AML) patient samples to assess the impact of sample handling on high-throughput functional drug testing, mass spectrometry-based proteomics, and flow cytometry. Our data revealed novel and previously described changes in cell phenotype and drug response dependent on sample biobanking. Specifically, myeloid cells with a CD117 (c-KIT) positive phenotype decreased after biobanking, potentially distorting cell population representations and affecting drugs targeting these cells. Additionally, highly granular AML cell numbers decreased after freezing. Secondly, protein expression levels, as well as sensitivity to drugs targeting cell proliferation, metabolism, tyrosine kinases (e.g., JAK, KIT, FLT3), and BH3 mimetics were notably affected by biobanking. Moreover, drug response profiles of paired fresh and frozen samples showed that freezing samples can lead to systematic errors in drug sensitivity scores. While a high correlation between fresh and frozen for the entire drug library was observed, freezing cells had a considerable impact at an individual level, which could influence outcomes in translational studies. Our study highlights conditions where standardization is needed to improve reproducibility, and where validation of data generated from biobanked cohorts may be particularly important.
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| 7. |
- Trac, Quang Thinh, et al.
(författare)
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Prediction model for drug response of acute myeloid leukemia patients
- 2023
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Ingår i: npj Precision Oncology. - : Springer Nature. - 2397-768X. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Despite some encouraging successes, predicting the therapy response of acute myeloid leukemia (AML) patients remains highly challenging due to tumor heterogeneity. Here we aim to develop and validate MDREAM, a robust ensemble-based prediction model for drug response in AML based on an integration of omics data, including mutations and gene expression, and large-scale drug testing. Briefly, MDREAM is first trained in the BeatAML cohort (n = 278), and then validated in the BeatAML (n = 183) and two external cohorts, including a Swedish AML cohort (n = 45) and a relapsed/refractory acute leukemia cohort (n = 12). The final prediction is based on 122 ensemble models, each corresponding to a drug. A confidence score metric is used to convey the uncertainty of predictions; among predictions with a confidence score >0.75, the validated proportion of good responders is 77%. The Spearman correlations between the predicted and the observed drug response are 0.68 (95% CI: [0.64, 0.68]) in the BeatAML validation set, -0.49 (95% CI: [-0.53, -0.44]) in the Swedish cohort and 0.59 (95% CI: [0.51, 0.67]) in the relapsed/refractory cohort. A web-based implementation of MDREAM is publicly available at https://www.meb.ki.se/shiny/truvu/MDREAM/.
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