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The tumour suppressor p16/CDKN2A and the metabolic gene, methyl-thio-adenosine phosphorylase (MTAP), are frequently co-deleted in some of the most aggressive and currently untreatable cancers. Cells with MTAP deletion are vulnerable to inhibition of the metabolic enzyme, methionine-adenosyl transferase 2A (MAT2A), and the protein arginine methyl transferase (PRMT5). This synthetic lethality has paved the way for the rapid development of drugs targeting the MAT2A/PRMT5 axis. MAT2A and its liver- and pancreas-specific isoform, MAT1A, generate the universal methyl donor S-adenosylmethionine (SAM) from ATP and methionine. Given the pleiotropic role SAM plays in methylation of diverse substrates, characterising the extent of SAM depletion and downstream perturbations following MAT2A/MAT1A inhibition (MATi) is critical for safety assessment. We have assessed in vivo target engagement and the resultant systemic phenotype using multi-omic tools to characterise response to a MAT2A inhibitor (AZ'9567). We observed significant SAM depletion and extensive methionine accumulation in the plasma, liver, brain and heart of treated rats, providing the first assessment of both global SAM depletion and evidence of hepatic MAT1A target engagement. An integrative analysis of multi-omic data from liver tissue identified broad perturbations in pathways covering one-carbon metabolism, trans-sulfuration and lipid metabolism. We infer that these pathway-wide perturbations represent adaptive responses to SAM depletion and confer a risk of oxidative stress, hepatic steatosis and an associated disturbance in plasma and cellular lipid homeostasis. The alterations also explain the dramatic increase in plasma and tissue methionine, which could be used as a safety and PD biomarker going forward to the clinic.
Assuntos
Metionina Adenosiltransferase , S-Adenosilmetionina , Animais , Metionina Adenosiltransferase/genética , Metionina Adenosiltransferase/metabolismo , S-Adenosilmetionina/metabolismo , Masculino , Fígado/efeitos dos fármacos , Fígado/metabolismo , Ratos , Metionina/metabolismo , Ratos Sprague-Dawley , Purina-Núcleosídeo Fosforilase/metabolismo , Purina-Núcleosídeo Fosforilase/genética , Proteína-Arginina N-Metiltransferases/genética , Proteína-Arginina N-Metiltransferases/metabolismo , Proteína-Arginina N-Metiltransferases/antagonistas & inibidores , MultiômicaRESUMO
OBJECTIVES: This study explored self-reported knowledge and interest to learn more about medicines research, development and health technology assessment among Finnish general public. It also aimed to define possible knowledge gaps and needs for public education regarding these topics. DESIGN: Online survey with 503 participants. The questionnaire was originally developed as a part of the Needs Assessment Work Package of the European Patients' Academy on Therapeutic Innovation Project. The survey was carried out in Finland in 2019. METHODS: The survey was conducted as an online survey by Kantar TNS Gallup Forum online panel. The data were analysed by using the freely available programming language R. Relationships between the demographic characteristics (such as age, gender and education level) of respondents and their knowledge or interest in medicines research and development were determined using Pearson's χ2 tests. Statistically significant responses of demographic characteristics in the respondents' knowledge or interest in medicines research were determined by logistic regression. RESULTS: Of the 503 respondents (age 16-64) only 12% reported having good or very good knowledge of medicines research and development in general. Regarding health technology assessment, pharmacoeconomics and regulation, the percentage of respondents reporting good or very good knowledge was as low as 8%. Respondents were most interested in learning more about predictive and personalised medicine (47%) and least interested in medicines regulation (30%) and pharmacoeconomics (31%). CONCLUSIONS: Self-reported knowledge about medicines research and development and health technology assessment appears to be very low in Finland. Patient and public participation is recognised as an important and essential element in up-to-date medical research and assessment of new treatments. In order to participate as an active and equal partner in these processes, the public needs more information and education in these topics.
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Pesquisa Biomédica , Avaliação da Tecnologia Biomédica , Adolescente , Adulto , Finlândia , Humanos , Pessoa de Meia-Idade , Avaliação das Necessidades , Inquéritos e Questionários , Adulto JovemRESUMO
Despite several new therapeutic options, multiple myeloma (MM) patients experience multiple relapses and inevitably become refractory to treatment. Insights into drug resistance mechanisms may lead to the development of novel treatment strategies. The S100 family is comprised of 21 calcium binding protein members with 17 S100 genes located in the 1q21 region, which is commonly amplified in MM. Dysregulated expression of S100 family members is associated with tumor initiation, progression and inflammation. However, the relationship between the S100 family and MM pathogenesis and drug response is unknown. In this study, the roles of S100 members were systematically studied at the copy number, transcriptional and protein level with patients' survival and drug response. Copy number analysis revealed a predominant pattern of gains occurring in S100 genes clustering in the 1q21 locus. In general, gains of genes encoding S100 family members associated with worse patient survival. However, S100 gene copy number and S100 gene expression did not necessarily correlate, and high expression of S100A4 associated with poor patient survival. Furthermore, integrated analysis of S100 gene expression and ex vivo drug sensitivity data showed significant negative correlation between expression of S100 family members (S100A8, S100A9, and S100A12) and sensitivity to some drugs used in current MM treatment, including proteasome inhibitors (bortezomib, carfilzomib, and ixazomib) and histone deacetylase inhibitor panobinostat. Combined proteomic and pharmacological data exhibited significant negative association of S100 members (S100A4, S100A8, and S100A9) with proteasome inhibitors and panobinostat. Clinically, the higher expression of S100A4 and S100A10 were significantly linked to shorter progression free survival in patients receiving carfilzomib-based therapy. The results indicate an association and highlight the potential functional importance of S100 members on chromosome 1q21 in the development of MM and resistance to established myeloma drugs, including proteasome inhibitors.
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BACKGROUND: Esterase enzymes differ in substrate specificity and biological function and may display dysregulated expression in cancer. This study evaluated the biological significance of esterase expression in multiple myeloma (MM). METHODS: For gene expression profiling and evaluation of genomic variants in the Institute for Molecular Medicine Finland (FIMM) cohort, bone marrow aspirates were obtained from patients with newly diagnosed MM (NDMM) or relapsed/refractory MM (RRMM). CD138+ plasma cells were enriched and used for RNA sequencing and analysis, and to evaluate genomic variation. The Multiple Myeloma Research Foundation (MMRF) Relating Clinical Outcomes in MM to Personal Assessment of Genetic Profile (CoMMpass) dataset was used for validation of the findings from FIMM. RESULTS: MM patients (NDMM, n = 56; RRMM, n = 78) provided 171 bone marrow aspirates (NDMM, n = 56; RRMM, n = 115). Specific esterases exhibited relatively high or low expression in MM, and expression of specific esterases (UCHL5, SIAE, ESD, PAFAH1B3, PNPLA4 and PON1) was significantly altered on progression from NDMM to RRMM. High expression of OVCA2, PAFAH1B3, SIAE and USP4, and low expression of PCED1B, were identified as poor prognostic markers (P < 0.05). The MMRF CoMMpass dataset provided validation that higher expression of PAFAH1B3 and SIAE, and lower expression of PCED1B, were associated with poor prognosis. CONCLUSIONS: Esterase gene expression levels change as patients progress from NDMM to RRMM. High expression of OVCA2, PAFAH1B3, USP4 and SIAE, and low expression of PCED1B, are poor prognostic markers in MM, suggesting a role for these esterases in myeloma biology.
Assuntos
Esterases/genética , Sequenciamento do Exoma/métodos , Perfilação da Expressão Gênica/métodos , Mieloma Múltiplo/genética , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Feminino , Finlândia , Regulação Neoplásica da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Masculino , Pessoa de Meia-Idade , Prognóstico , Análise de Sequência de RNARESUMO
High-throughput drug screening has facilitated the discovery of drug combinations in cancer. Many existing studies adopted a full matrix design, aiming for the characterization of drug pair effects for cancer cells. However, the full matrix design may be suboptimal as it requires a drug pair to be combined at multiple concentrations in a full factorial manner. Furthermore, many of the computational tools assess only the synergy but not the sensitivity of drug combinations, which might lead to false positive discoveries. We proposed a novel cross design to enable a more cost-effective and simultaneous testing of drug combination sensitivity and synergy. We developed a drug combination sensitivity score (CSS) to determine the sensitivity of a drug pair, and showed that the CSS is highly reproducible between the replicates and thus supported its usage as a robust metric. We further showed that CSS can be predicted using machine learning approaches which determined the top pharmaco-features to cluster cancer cell lines based on their drug combination sensitivity profiles. To assess the degree of drug interactions using the cross design, we developed an S synergy score based on the difference between the drug combination and the single drug dose-response curves. We showed that the S score is able to detect true synergistic and antagonistic drug combinations at an accuracy level comparable to that using the full matrix design. Taken together, we showed that the cross design coupled with the CSS sensitivity and S synergy scoring methods may provide a robust and accurate characterization of both drug combination sensitivity and synergy levels, with minimal experimental materials required. Our experimental-computational approach could be utilized as an efficient pipeline for improving the discovery rate in high-throughput drug combination screening, particularly for primary patient samples which are difficult to obtain.
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Biologia Computacional/métodos , Avaliação Pré-Clínica de Medicamentos/métodos , Protocolos de Quimioterapia Combinada Antineoplásica/metabolismo , Protocolos de Quimioterapia Combinada Antineoplásica/farmacologia , Linhagem Celular Tumoral , Combinação de Medicamentos , Sinergismo Farmacológico , Humanos , Aprendizado de MáquinaRESUMO
Multiple myeloma (MM) is a tumor of plasmablasts/plasma cells (PCs) characterized by the expansion of malignant PCs with complex genetic aberrations in the bone marrow (BM). Recent reports, by us and others, have highlighted the polycomb group (PcG) proteins as potential targets for therapy in MM. The PcG protein BMI-1 of the polycomb repressive complex 1 (PRC1) has been reported to be overexpressed and to possess oncogenic functions in MM. Herein, we report on the anti-myeloma effects of the BMI-1 inhibitor PTC-209 and demonstrate that PTC-209 is a potent anti-myeloma agent in vitro using MM cell lines and primary MM cells. We show that PTC-209 reduces the viability of MM cells via induction of apoptosis and reveal that the anti-MM actions of PTC-209 are mediated by on-target effects i.e. downregulation of BMI-1 protein and the associated repressive histone mark H2AK119ub, leaving other PRC1 subunits such as CBX-7 and the catalytic subunit RING1B unaffected. Importantly, we demonstrate that PTC-209 exhibits synergistic and additive anti-myeloma activity when combined with other epigenetic inhibitors targeting EZH2 and BET bromodomains. Collectively, these data qualify BMI-1 as a candidate for targeted therapy in MM alone or in combinations with epigenetic inhibitors directed to PRC2/EZH2 or BET bromodomains.
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Novel agents have increased survival of multiple myeloma (MM) patients, however high-risk and relapsed/refractory patients remain challenging to treat and their outcome is poor. To identify novel therapies and aid treatment selection for MM, we assessed the ex vivo sensitivity of 50 MM patient samples to 308 approved and investigational drugs. With the results we i) classified patients based on their ex vivo drug response profile; ii) identified and matched potential drug candidates to recurrent cytogenetic alterations; and iii) correlated ex vivo drug sensitivity to patient outcome. Based on their drug sensitivity profiles, MM patients were stratified into four distinct subgroups with varied survival outcomes. Patients with progressive disease and poor survival clustered in a drug response group exhibiting high sensitivity to signal transduction inhibitors. Del(17p) positive samples were resistant to most drugs tested with the exception of histone deacetylase and BCL2 inhibitors. Samples positive for t(4;14) were highly sensitive to immunomodulatory drugs, proteasome inhibitors and several targeted drugs. Three patients treated based on the ex vivo results showed good response to the selected treatments. Our results demonstrate that ex vivo drug testing may potentially be applied to optimize treatment selection and achieve therapeutic benefit for relapsed/refractory MM.
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We developed a systematic algorithmic solution for quantitative drug sensitivity scoring (DSS), based on continuous modeling and integration of multiple dose-response relationships in high-throughput compound testing studies. Mathematical model estimation and continuous interpolation makes the scoring approach robust against sources of technical variability and widely applicable to various experimental settings, both in cancer cell line models and primary patient-derived cells. Here, we demonstrate its improved performance over other response parameters especially in a leukemia patient case study, where differential DSS between patient and control cells enabled identification of both cancer-selective drugs and drug-sensitive patient sub-groups, as well as dynamic monitoring of the response patterns and oncogenic driver signals during cancer progression and relapse in individual patient cells ex vivo. An open-source and easily extendable implementation of the DSS calculation is made freely available to support its tailored application to translating drug sensitivity testing results into clinically actionable treatment options.
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Antineoplásicos/farmacologia , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Leucemia Mieloide Aguda/tratamento farmacológico , Recidiva Local de Neoplasia/tratamento farmacológico , Medicina de Precisão , Algoritmos , Estudos de Casos e Controles , Humanos , Modelos Teóricos , Células Tumorais CultivadasRESUMO
UNLABELLED: We present an individualized systems medicine (ISM) approach to optimize cancer drug therapies one patient at a time. ISM is based on (i) molecular profiling and ex vivo drug sensitivity and resistance testing (DSRT) of patients' cancer cells to 187 oncology drugs, (ii) clinical implementation of therapies predicted to be effective, and (iii) studying consecutive samples from the treated patients to understand the basis of resistance. Here, application of ISM to 28 samples from patients with acute myeloid leukemia (AML) uncovered five major taxonomic drug-response subtypes based on DSRT profiles, some with distinct genomic features (e.g., MLL gene fusions in subgroup IV and FLT3-ITD mutations in subgroup V). Therapy based on DSRT resulted in several clinical responses. After progression under DSRT-guided therapies, AML cells displayed significant clonal evolution and novel genomic changes potentially explaining resistance, whereas ex vivo DSRT data showed resistance to the clinically applied drugs and new vulnerabilities to previously ineffective drugs. SIGNIFICANCE: Here, we demonstrate an ISM strategy to optimize safe and effective personalized cancer therapies for individual patients as well as to understand and predict disease evolution and the next line of therapy. This approach could facilitate systematic drug repositioning of approved targeted drugs as well as help to prioritize and de-risk emerging drugs for clinical testing.
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Antineoplásicos/uso terapêutico , Resistencia a Medicamentos Antineoplásicos/genética , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/genética , Medicina de Precisão/métodos , Antineoplásicos/farmacologia , Progressão da Doença , Reposicionamento de Medicamentos , Perfilação da Expressão Gênica , Genoma Humano , Humanos , Transdução de Sinais/efeitos dos fármacos , Resultado do TratamentoRESUMO
BACKGROUND: T-cell large granular lymphocytic leukemia is a rare lymphoproliferative disorder characterized by the expansion of clonal CD3+CD8+ cytotoxic T lymphocytes (CTLs) and often associated with autoimmune disorders and immune-mediated cytopenias. METHODS: We used next-generation exome sequencing to identify somatic mutations in CTLs from an index patient with large granular lymphocytic leukemia. Targeted resequencing was performed in a well-characterized cohort of 76 patients with this disorder, characterized by clonal T-cell-receptor rearrangements and increased numbers of large granular lymphocytes. RESULTS: Mutations in the signal transducer and activator of transcription 3 gene (STAT3) were found in 31 of 77 patients (40%) with large granular lymphocytic leukemia. Among these 31 patients, recurrent mutational hot spots included Y640F in 13 (17%), D661V in 7 (9%), D661Y in 7 (9%), and N647I in 3 (4%). All mutations were located in exon 21, encoding the Src homology 2 (SH2) domain, which mediates the dimerization and activation of STAT protein. The amino acid changes resulted in a more hydrophobic protein surface and were associated with phosphorylation of STAT3 and its localization in the nucleus. In vitro functional studies showed that the Y640F and D661V mutations increased the transcriptional activity of STAT3. In the affected patients, downstream target genes of the STAT3 pathway (IFNGR2, BCL2L1, and JAK2) were up-regulated. Patients with STAT3 mutations presented more often with neutropenia and rheumatoid arthritis than did patients without these mutations. CONCLUSIONS: The SH2 dimerization and activation domain of STAT3 is frequently mutated in patients with large granular lymphocytic leukemia; these findings suggest that aberrant STAT3 signaling underlies the pathogenesis of this disease. (Funded by the Academy of Finland and others.).
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Leucemia Linfocítica Granular Grande/genética , Fator de Transcrição STAT3/genética , Idoso , Exoma , Expressão Gênica , Humanos , Masculino , Mutação , Receptores de Antígenos de Linfócitos T , Análise de Sequência de RNA , Transcrição Gênica , Regulação para CimaRESUMO
Ionizing radiation (IR) produces direct two-ended DNA double-strand breaks (DSBs) primarily repaired by non-homologous end joining (NHEJ). It is, however, well established that homologous recombination (HR) is induced and required for repair of a subset of DSBs formed following IR. Here, we find that HR induced by IR is drastically reduced when post-DNA damage replication is inhibited in mammalian cells. Both IR-induced RAD51 foci and HR events in the hprt gene are reduced in the presence of replication polymerase inhibitor aphidicolin (APH). Interestingly, we also detect reduced IR-induced toxicity in HR deficient cells when inhibiting post-DNA damage replication. When studying DSB formation following IR exposure, we find that apart from the direct DSBs the treatment also triggers formation of secondary DSBs peaking at 7-9 h after exposure. These secondary DSBs are restricted to newly replicated DNA and abolished by inhibiting post-DNA damage replication. Further, we find that IR-induced RAD51 foci are decreased by APH only in cells replicating at the time of IR exposure, suggesting distinct differences between IR-induced HR in S- and G2-phases of the cell cycle. Altogether, our data indicate that secondary replication-associated DSBs formed following exposure to IR are major substrates for IR-induced HR repair.
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Quebras de DNA de Cadeia Dupla , Replicação do DNA , Radiação Ionizante , Reparo de DNA por Recombinação , Animais , Células CHO , Linhagem Celular , Cricetinae , Cricetulus , HumanosRESUMO
Even though DNA alkylating agents have been used for many decades in the treatment of cancer, it remains unclear what happens when replication forks encounter alkylated DNA. Here, we used the DNA fibre assay to study the impact of alkylating agents on replication fork progression. We found that the alkylator methyl methanesulfonate (MMS) inhibits replication elongation in a manner that is dose dependent and related to the overall alkylation grade. Replication forks seem to be completely blocked as no nucleotide incorporation can be detected following 1 h of MMS treatment. A high dose of 5 mM caffeine, inhibiting most DNA damage signalling, decreases replication rates overall but does not reverse MMS-induced replication inhibition, showing that the replication block is independent of DNA damage signalling. Furthermore, the block of replication fork progression does not correlate with the level of DNA single-strand breaks. Overexpression of O(6)-methylguanine (O6meG)-DNA methyltransferase protein, responsible for removing the most toxic alkylation, O6meG, did not affect replication elongation following exposure to N-methyl-N'-nitro-N-nitrosoguanidine. This demonstrates that O6meG lesions are efficiently bypassed in mammalian cells. In addition, we find that MMS-induced gammaH2AX foci co-localise with 53BP1 foci and newly replicated areas, suggesting that DNA double-strand breaks are formed at MMS-blocked replication forks. Altogether, our data suggest that N-alkylations formed during exposure to alkylating agents physically block replication fork elongation in mammalian cells, causing formation of replication-associated DNA lesions, likely double-strand breaks.