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MOTIVATION: A key goal of computational personalized medicine is to systematically utilize genomic and other molecular features of samples to predict drug responses for a previously unseen sample. Such predictions are valuable for developing hypotheses for selecting therapies tailored for individual patients. This is especially valuable in oncology, where molecular and genetic heterogeneity of the cells has a major impact on the response. However, the prediction task is extremely challenging, raising the need for methods that can effectively model and predict drug responses. RESULTS: In this study, we propose a novel formulation of multi-task matrix factorization that allows selective data integration for predicting drug responses. To solve the modeling task, we extend the state-of-the-art kernelized Bayesian matrix factorization (KBMF) method with component-wise multiple kernel learning. In addition, our approach exploits the known pathway information in a novel and biologically meaningful fashion to learn the drug response associations. Our method quantitatively outperforms the state of the art on predicting drug responses in two publicly available cancer datasets as well as on a synthetic dataset. In addition, we validated our model predictions with lab experiments using an in-house cancer cell line panel. We finally show the practical applicability of the proposed method by utilizing prior knowledge to infer pathway-drug response associations, opening up the opportunity for elucidating drug action mechanisms. We demonstrate that pathway-response associations can be learned by the proposed model for the well-known EGFR and MEK inhibitors. AVAILABILITY AND IMPLEMENTATION: The source code implementing the method is available at http://research.cs.aalto.fi/pml/software/cwkbmf/ CONTACTS: muhammad.ammad-ud-din@aalto.fi or samuel.kaski@aalto.fi SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Assuntos
Genômica , Neoplasias , Algoritmos , Teorema de Bayes , Sistemas de Liberação de Medicamentos , Descoberta de Drogas , Humanos , Redes e Vias Metabólicas , SoftwareRESUMO
ABSTRACT: Monosomy 7 and del(7q) (-7/-7q) are frequent chromosomal abnormalities detected in up to 10% of patients with acute myeloid leukemia (AML). Despite unfavorable treatment outcomes, no approved targeted therapies exist for patients with -7/-7q. Therefore, we aimed to identify novel vulnerabilities. Through an analysis of data from ex vivo drug screens of 114 primary AML samples, we discovered that -7/-7q AML cells are highly sensitive to the inhibition of nicotinamide phosphoribosyltransferase (NAMPT). NAMPT is the rate-limiting enzyme in the nicotinamide adenine dinucleotide salvage pathway. Mechanistically, the NAMPT gene is located at 7q22.3, and deletion of 1 copy due to -7/-7q results in NAMPT haploinsufficiency, leading to reduced expression and a therapeutically targetable vulnerability to the inhibition of NAMPT. Our results show that in -7/-7q AML, differentiated CD34+CD38+ myeloblasts are more sensitive to the inhibition of NAMPT than less differentiated CD34+CD38- myeloblasts. Furthermore, the combination of the BCL2 inhibitor venetoclax and the NAMPT inhibitor KPT-9274 resulted in the death of significantly more leukemic blasts in AML samples with -7/-7q than the NAMPT inhibitor alone. In conclusion, our findings demonstrate that AML with -7/-7q is highly sensitive to NAMPT inhibition, suggesting that NAMPT inhibitors have the potential to be an effective targeted therapy for patients with monosomy 7 or del(7q).
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Antineoplásicos , Leucemia Mieloide Aguda , Humanos , Nicotinamida Fosforribosiltransferase , Leucemia Mieloide Aguda/genética , Deleção Cromossômica , Cromossomos Humanos Par 7RESUMO
In many cancers, mortality is associated with the emergence of relapse with multidrug resistance (MDR). Thus far, the investigation of cancer relapse mechanisms has largely focused on acquired genetic mutations. Using acute myeloid leukemia (AML) patient-derived xenografts (PDX), we systematically elucidated a basis of MDR and identified drug sensitivity in relapsed AML. We derived pharmacologic sensitivity for 22 AML PDX models using dynamic BH3 profiling (DBP), together with genomics and transcriptomics. Using in vivo acquired resistant PDXs, we found that resistance to unrelated, narrowly targeted agents in distinct PDXs was accompanied by broad resistance to drugs with disparate mechanisms. Moreover, baseline mitochondrial apoptotic priming was consistently reduced regardless of the class of drug-inducing selection. By applying DBP, we identified drugs showing effective in vivo activity in resistant models. This study implies evasion of apoptosis drives drug resistance and demonstrates the feasibility of the DBP approach to identify active drugs for patients with relapsed AML. SIGNIFICANCE: Acquired resistance to targeted therapy remains challenging in AML. We found that reduction in mitochondrial priming and common transcriptomic signatures was a conserved mechanism of acquired resistance across different drug classes in vivo. Drugs active in vivo can be identified even in the multidrug resistant state by DBP.
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Apoptose , Resistência a Múltiplos Medicamentos , Resistencia a Medicamentos Antineoplásicos , Leucemia Mieloide Aguda , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/patologia , Leucemia Mieloide Aguda/genética , Humanos , Apoptose/efeitos dos fármacos , Animais , Camundongos , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Resistencia a Medicamentos Antineoplásicos/genética , Resistência a Múltiplos Medicamentos/genética , Resistência a Múltiplos Medicamentos/efeitos dos fármacos , Ensaios Antitumorais Modelo de Xenoenxerto , Células Precursoras de Granulócitos/efeitos dos fármacos , Células Precursoras de Granulócitos/patologia , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêuticoRESUMO
We generated ex vivo drug-response and multiomics profiling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identification of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profiling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. SIGNIFICANCE: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes significant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB.See related commentary by Letai, p. 290.This article is highlighted in the In This Issue feature, p. 275.
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Técnicas de Apoio para a Decisão , Leucemia Mieloide Aguda/tratamento farmacológico , Equipe de Assistência ao Paciente , Medicina de Precisão , Feminino , Finlândia , Humanos , Leucemia Mieloide Aguda/mortalidade , Masculino , Pessoa de Meia-Idade , Indução de Remissão , Análise de SobrevidaRESUMO
FLT3 internal tandem duplication (FLT3-ITD) is a frequent mutation in acute myeloid leukemia (AML) and remains a strong prognostic factor due to high rate of disease recurrence. Several FLT3-targeted agents have been developed, but determinants of variable responses to these agents remain understudied. Here, we investigated the role FLT3-ITD allelic ratio (ITD-AR), ITD length, and associated gene expression signatures on FLT3 inhibitor response in adult AML. We performed fragment analysis, ex vivo drug testing, and next generation sequencing (RNA, exome) to 119 samples from 87 AML patients and 13 healthy bone marrow controls. We found that ex vivo response to FLT3 inhibitors is significantly associated with ITD-AR, but not with ITD length. Interestingly, we found that the HLF gene is overexpressed in FLT3-ITD+ AML and associated with ITD-AR. The retrospective analysis of AML patients treated with FLT3 inhibitor sorafenib showed that patients with high HLF expression and ITD-AR had better clinical response to therapy compared to those with low ITD-AR and HLF expression. Thus, our findings suggest that FLT3 ITD-AR together with increased HLF expression play a role in variable FLT3 inhibitor responses observed in FLT3-ITD+ AML patients.
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Fatores de Transcrição de Zíper de Leucina Básica/genética , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/genética , Tirosina Quinase 3 Semelhante a fms/antagonistas & inibidores , Tirosina Quinase 3 Semelhante a fms/genética , Adulto , Idoso , Alelos , Antineoplásicos/uso terapêutico , Estudos de Casos e Controles , Feminino , Duplicação Gênica , Expressão Gênica , Humanos , Técnicas In Vitro , Masculino , Pessoa de Meia-Idade , Mutação , Inibidores de Proteínas Quinases/uso terapêutico , Estudos Retrospectivos , Sorafenibe/uso terapêutico , Sequências de Repetição em Tandem , Resultado do TratamentoRESUMO
Increasingly powerful microscopy, liquid handling, and computational techniques have enabled cell imaging in high throughput. Microscopy images are quantified using high-content analysis platforms linking object features to cell behavior. This can be attempted on physiologically relevant cell models, including stem cells and primary cells, in complex environments, and conceivably in the presence of perturbations. Recently, substantial focus has been devoted to cell profiling for cell therapy, assays for drug discovery or biomarker identification for clinical decision-making protocols, bringing this wealth of information into translational applications. In this chapter, we focus on two protocols enabling to (1) benchmark human cells, in particular human endothelial cells as a case study and (2) extract cells from blood for follow-up experiments including image-based drug testing. We also present concepts of high-content imaging and discuss the benefits and challenges, with the aim of enabling readers to tailor existing pipelines and bring such approaches closer to translational research and the clinic.
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Técnicas de Reprogramação Celular , Diagnóstico por Imagem , Ensaios de Triagem em Larga Escala , Células-Tronco Pluripotentes Induzidas/metabolismo , Humanos , Células-Tronco Pluripotentes Induzidas/citologia , Pesquisa Translacional BiomédicaRESUMO
The FDA recently approved eight targeted therapies for acute myeloid leukemia (AML), including the BCL-2 inhibitor venetoclax. Maximizing efficacy of these treatments requires refining patient selection. To this end, we analyzed two recent AML studies profiling the gene expression and ex vivo drug response of primary patient samples. We find that ex vivo samples often exhibit a general sensitivity to (any) drug exposure, independent of drug target. We observe that this "general response across drugs" (GRD) is associated with FLT3-ITD mutations, clinical response to standard induction chemotherapy, and overall survival. Further, incorporating GRD into expression-based regression models trained on one of the studies improved their performance in predicting ex vivo response in the second study, thus signifying its relevance to precision oncology efforts. We find that venetoclax response is independent of GRD but instead show that it is linked to expression of monocyte-associated genes by developing and applying a multi-source Bayesian regression approach. The method shares information across studies to robustly identify biomarkers of drug response and is broadly applicable in integrative analyses.
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Understanding factors that shape the immune landscape across hematological malignancies is essential for immunotherapy development. We integrated over 8,000 transcriptomes and 2,000 samples with multilevel genomics of hematological cancers to investigate how immunological features are linked to cancer subtypes, genetic and epigenetic alterations, and patient survival, and validated key findings experimentally. Infiltration of cytotoxic lymphocytes was associated with TP53 and myelodysplasia-related changes in acute myeloid leukemia, and activated B cell-like phenotype and interferon-γ response in lymphoma. CIITA methylation regulating antigen presentation, cancer type-specific immune checkpoints, such as VISTA in myeloid malignancies, and variation in cancer antigen expression further contributed to immune heterogeneity and predicted survival. Our study provides a resource linking immunology with cancer subtypes and genomics in hematological malignancies.
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Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica , Leucemia Mieloide/genética , Linfoma Difuso de Grandes Células B/genética , Doença Aguda , Epigênese Genética , Genômica/métodos , Antígenos HLA/genética , Humanos , Imunoterapia/métodos , Leucemia Mieloide/imunologia , Leucemia Mieloide/terapia , Linfócitos do Interstício Tumoral/imunologia , Linfócitos do Interstício Tumoral/metabolismo , Linfoma Difuso de Grandes Células B/imunologia , Linfoma Difuso de Grandes Células B/terapia , Mieloma Múltiplo/genética , Mieloma Múltiplo/imunologia , Mieloma Múltiplo/terapia , Mutação , Proteína Supressora de Tumor p53/genéticaRESUMO
Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease context for new therapeutic approaches. We analyzed 9,544 transcriptomes from more than 30 hematologic malignancies, normal blood cell types, and cell lines, and showed that disease types could be stratified in a data-driven manner. We then identified cluster-specific pathway activity, new biomarkers, and in silico drug target prioritization through interrogation of drug target databases. Using known vulnerabilities and available drug screens, we highlighted the importance of integrating molecular phenotype with drug target expression for in silico prediction of drug responsiveness. Our analysis implicated BCL2 expression level as an important indicator of venetoclax responsiveness and provided a rationale for its targeting in specific leukemia subtypes and multiple myeloma, linked several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7, and EZH1) with chronic lymphocytic leukemia, and supported CDK6 as a disease-specific target in acute myeloid leukemia. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our publicly available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies. SIGNIFICANCE: This study describes a data resource for researching derailed cellular pathways and candidate drug targets across hematologic malignancies.
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Neoplasias Hematológicas/genética , Antineoplásicos/uso terapêutico , Biomarcadores Tumorais/genética , Compostos Bicíclicos Heterocíclicos com Pontes/uso terapêutico , Neoplasias Hematológicas/tratamento farmacológico , Humanos , Imunoterapia/métodos , Internet , Leucemia Mieloide Aguda/genética , Leucemia Mieloide Aguda/terapia , Linfoma de Células B/tratamento farmacológico , Fenótipo , Proteínas Proto-Oncogênicas c-bcl-2/genética , Bibliotecas de Moléculas Pequenas/uso terapêutico , Sulfonamidas/uso terapêutico , Transcriptoma/genéticaRESUMO
Aggressive natural killer-cell (NK-cell) leukemia (ANKL) is an extremely aggressive malignancy with dismal prognosis and lack of targeted therapies. Here, we elucidate the molecular pathogenesis of ANKL using a combination of genomic and drug sensitivity profiling. We study 14 ANKL patients using whole-exome sequencing (WES) and identify mutations in STAT3 (21%) and RAS-MAPK pathway genes (21%) as well as in DDX3X (29%) and epigenetic modifiers (50%). Additional alterations include JAK-STAT copy gains and tyrosine phosphatase mutations, which we show recurrent also in extranodal NK/T-cell lymphoma, nasal type (NKTCL) through integration of public genomic data. Drug sensitivity profiling further demonstrates the role of the JAK-STAT pathway in the pathogenesis of NK-cell malignancies, identifying NK cells to be highly sensitive to JAK and BCL2 inhibition compared to other hematopoietic cell lineages. Our results provide insight into ANKL genetics and a framework for application of targeted therapies in NK-cell malignancies.
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Janus Quinases/genética , Leucemia Linfocítica Granular Grande/genética , Mutação , Fator de Transcrição STAT3/genética , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , RNA Helicases DEAD-box/genética , RNA Helicases DEAD-box/metabolismo , Feminino , Humanos , Janus Quinases/metabolismo , Leucemia Linfocítica Granular Grande/metabolismo , Leucemia Linfocítica Granular Grande/terapia , Masculino , Pessoa de Meia-Idade , Fator de Transcrição STAT3/metabolismo , Transdução de Sinais , Sequenciamento do Exoma , Adulto JovemRESUMO
Although conventional therapies for acute myeloid leukemia (AML) and diffuse large B-cell lymphoma (DLBCL) are effective in inducing remission, many patients relapse upon treatment. Hence, there is an urgent need for novel therapies. PIM kinases are often overexpressed in AML and DLBCL and are therefore an attractive therapeutic target. However, in vitro experiments have demonstrated that intrinsic resistance to PIM inhibition is common. It is therefore likely that only a minority of patients will benefit from single agent PIM inhibitor treatment. In this study, we performed an shRNA-based genetic screen to identify kinases whose suppression is synergistic with PIM inhibition. Here, we report that suppression of p38α (MAPK14) is synthetic lethal with the PIM kinase inhibitor AZD1208. PIM inhibition elevates reactive oxygen species (ROS) levels, which subsequently activates p38α and downstream AKT/mTOR signaling. We found that p38α inhibitors sensitize hematological tumor cell lines to AZD1208 treatment in vitro and in vivo. These results were validated in ex vivo patient-derived AML cells. Our findings provide mechanistic and translational evidence supporting the rationale to test a combination of p38α and PIM inhibitors in clinical trials for AML and DLBCL.
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Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/enzimologia , Inibidores de Proteínas Quinases/farmacologia , Proteínas Proto-Oncogênicas c-pim-1/antagonistas & inibidores , Serina-Treonina Quinases TOR/metabolismo , Animais , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Humanos , Células K562 , Leucemia Mieloide Aguda/patologia , Masculino , Camundongos , Camundongos Transgênicos , Proteína Quinase 14 Ativada por Mitógeno/antagonistas & inibidores , Proteína Quinase 14 Ativada por Mitógeno/metabolismo , Transdução de Sinais , Ensaios Antitumorais Modelo de XenoenxertoAssuntos
Antineoplásicos/farmacologia , Dasatinibe/farmacologia , Leucemia Mieloide Aguda/metabolismo , Inibidores de Proteínas Quinases/farmacologia , Proteínas Proto-Oncogênicas c-kit/metabolismo , Transdução de Sinais/efeitos dos fármacos , Antineoplásicos/uso terapêutico , Biomarcadores Tumorais , Dasatinibe/uso terapêutico , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Resistencia a Medicamentos Antineoplásicos/genética , Humanos , Leucemia Mieloide Aguda/diagnóstico , Leucemia Mieloide Aguda/tratamento farmacológico , Prognóstico , Inibidores de Proteínas Quinases/uso terapêuticoAssuntos
Antineoplásicos/farmacologia , Compostos Bicíclicos Heterocíclicos com Pontes/farmacologia , Calgranulina A/genética , Calgranulina B/genética , Resistencia a Medicamentos Antineoplásicos/genética , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/genética , Proteínas Proto-Oncogênicas c-bcl-2/genética , Sulfonamidas/farmacologia , Linhagem Celular Tumoral , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , HumanosRESUMO
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.