Project description:We undertook a comprehensive clinical and biological investigation of serial medulloblastoma biopsies obtained at diagnosis and relapse. Combined MYC gene family amplifications and P53 pathway defects commonly emerged at relapse, and all patients in this molecular group died of rapidly progressive disease post-relapse. To study this genetic interaction, we investigated a transgenic model of MYCN-driven medulloblastoma and found spontaneous development of Trp53 inactivating mutations. Abrogation of Trp53 function in this model produced aggressive tumors that mimicked the characteristics of relapsed human tumors with combined P53-MYC dysfunction. Restoration of p53 activity, genetic and therapeutic suppression of MYCN all reduced tumor growth and prolonged survival. Our findings identify P53–MYC interactions which emerge at medulloblastoma relapse as biomarkers of clinically aggressive disease that may be targeted therapeutically. Using this dataset, assignation of medulloblastoma molecular subgroup by Illumina 450k microarray was performed for diagnostic and relapsed medulloblastoma samples to compare subgroup membership at diagnosis and relapse. We investigated the DNA methylation profiles of 18 diagnostic and 22 relapsing samples (including 15 diagnostic / relapse pairs) using the Illumina 450k methylation microarray
Project description:We undertook a comprehensive clinical and biological investigation of serial medulloblastoma biopsies obtained at diagnosis and relapse. Combined MYC gene family amplifications and P53 pathway defects commonly emerged at relapse, and all patients in this molecular group died of rapidly progressive disease post-relapse. To study this genetic interaction, we investigated a transgenic model of MYCN-driven medulloblastoma and found spontaneous development of Trp53 inactivating mutations. Abrogation of Trp53 function in this model produced aggressive tumors that mimicked the characteristics of relapsed human tumors with combined P53-MYC dysfunction. Restoration of p53 activity, genetic and therapeutic suppression of MYCN all reduced tumor growth and prolonged survival. Our findings identify P53–MYC interactions which emerge at medulloblastoma relapse as biomarkers of clinically aggressive disease that may be targeted therapeutically. Using this dataset, assignation of medulloblastoma molecular subgroup by Illumina 450k microarray was performed for diagnostic and relapsed medulloblastoma samples to compare subgroup membership at diagnosis and relapse.
Project description:Despite improvement of current treatment strategies and novel targeted drugs, relapse and treatment resistance determine the major cause of death for acute myeloid leukemia (AML) patients. To identify the underlying molecular characteristics, numerous studies have been aimed to decipher the genomic- and transcriptomic landscape of AML. Nevertheless, further molecular changes allowing malignant cells to escape treatment are yet to be elucidated. Mass spectrometry is a powerful tool enabling detailed insights into proteomic changes that could explain AML relapse and resistance. Here, we investigated AML samples from 47 adult and 22 pediatric patients at serial time-points during disease progression using high resolution isoelectric focusing liquid chromatography mass spectrometry. We show that the proteomic profile at relapse is enriched for mitochondrial ribosomal proteins and subunits of the respiratory chain complex, indicative of reprogrammed energy metabolism from diagnosis to relapse. Further, higher levels of granzymes and lower levels of the anti-inflammatory protein CR1/CD35 suggest an inflammatory signature promoting disease progression. Finally, through a proteogenomic approach, we detected novel peptides, which present a promising repertoire in the search for biomarkers and tumor-specific druggable targets. Altogether, this study highlights the importance of proteomic studies in holistic approaches to improve treatment and survival of AML patients.
Project description:FL patients with high GLUT1 levels are at increased risk for early relapse and show only limited responses to PI3K inhibitors. The development of new therapies requires an understanding of the changes in their tumor immune microenvironment (TIME). Using novel IMC and proteomics techniques, we comprehensively identified distinguishing features in the TIME as a function of GLUT1 levels. Bioinformatics analyses identified a crosstalk between GLUT1 and TIME in tumor development and suggest that FL patients expressing high GLUT1 may benefit from metabolic-modulating therapies to prevent early relapse.
Project description:Medulloblastoma is the most frequent malignant primary brain tumor in children. Despite recent advances in integrated genomics, the prognosis in children with high-risk medulloblastoma remains devastating, and new tumor-specific therapeutic approaches are needed. Here, we present an atlas of naturally presented T-cell antigens in medulloblastoma. We mapped the human leukocyte antigen (HLA)-presented peptidomes of 28 tumors and performed comparative immunopeptidome profiling against an in-house benign database. Medulloblastoma proved to be a rich source of novel tumor-associated antigens, naturally presented on HLA class I and II molecules. Remarkably, most tumor-associated peptides and proteins were subgroup-specific, whereas shared presentation among all subgroups of medulloblastoma (WNT, SHH, Group 3 and Group 4) was rare. Functional testing of top-ranking novel candidate antigens demonstrated the induction of peptide-specific T-cell responses, supporting their potential for T-cell immunotherapy. This study is an in-depth mapping of naturally presented T-cell antigens in medulloblastoma. Integration of immunopeptidomics, transcriptomics, and epigenetic data led to the identification of a large set of actionable targets that can be further used for the translation into the clinical setting by facilitating the informed design of immunotherapeutic approaches to children with medulloblastoma.
Project description:This SuperSeries is composed of the following subset Series: GSE28460: Expression data from ALL diagnosis and relapse pediatric acute lymphoblastic leukemia cases GSE28461: Promoter methylation data from ALL diagnosis and relapse pediatric acute lymphoblastic leukemia cases Refer to individual Series
Project description:Multiple myeloma (MM) is a common hematological malignancy with poorly understood recurrence and relapse mechanisms. Notably, bortezomib resistance leading to relapse makes MM treatment significantly challenging. To clarify the drug resistance mechanism, we employed a quantitative proteomics approach to identify differentially expressed protein candidates implicated in bortezomib-resistant recurrent and relapsed MM (RRMM). Bone marrow biopsy specimens from five patients newly diagnosed with MM (NDMM) were compared with those from five patients diagnosed with bortezomib-resistant RRMM using tandem mass tag-mass spectrometry (TMT-MS). Subcellular localization and functional classification of the differentially expressed proteins were determined by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and hierarchical clustering. Top candidates identified were validated with parallel reaction monitoring (PRM) analysis using tissue samples from 11 NDMM and 8 RRMM patients, followed by comparison with the NCBI Gene Expression Omnibus (GEO) dataset of 10 MM patients and 10 healthy controls (Accession No.: GSE80608). Thirty-four differentially expressed proteins in RRMM, including proteinase inhibitor 9 (SERPINB9) were identified by TMT-MS. Subsequent functional enrichment analyses of the identified protein candidates indicated their involvement in regulating cellular metabolism, apoptosis, programmed cell death, lymphocyte-mediated immunity, and defense response pathways in RRMM. The top protein candidate SERPINB9 was confirmed by PRM analysis as well as by comparison with an NCBI GEO dataset. We elucidated the proteome landscape of bortezomib-resistant RRMM and identified SERPINB9 as a promising novel therapeutic target. Our results provide a resource for future studies on the mechanism of RRMM.
Project description:We undertook a comprehensive clinical and biological investigation of serial medulloblastoma biopsies obtained at diagnosis and relapse. Combined MYC gene family amplifications and P53 pathway defects commonly emerged at relapse, and all patients in this molecular group died of rapidly progressive disease post-relapse. To study this genetic interaction, we investigated a transgenic model of MYCN-driven medulloblastoma and found spontaneous development of Trp53 inactivating mutations. Abrogation of Trp53 function in this model produced aggressive tumors that mimicked the characteristics of relapsed human tumors with combined P53–MYC dysfunction. Restoration of p53 activity, genetic and therapeutic suppression of MYCN all reduced tumor growth and prolonged survival. Our findings identify P53–MYC interactions which emerge at medulloblastoma relapse as biomarkers of clinically aggressive disease that may be targeted therapeutically. There are currently no effective therapies for children with relapsed medulloblastoma. While clinical and biological features of the disease at diagnosis are increasingly well understood, biopsy is rarely performed at relapse and few biological data are available to guide more effective treatments. Here, we show that medulloblastomas develop altered biology at relapse which is predictive of disease course and cannot be detected at diagnosis. We have discovered the emergence of P53–MYC interactions at relapse, as biomarkers of clinically aggressive relapsed disease, which can be modelled and targeted therapeutically in genetically-engineered mice. These data provide clear precedent for the incorporation of biopsy at relapse into routine clinical practice, to direct palliative care and the development of improved treatment strategies. mouse model expression profiles from various mouse Medulloblastoma models MYCN/MYC overexpressing with/without p53 Mutations were compared to human MB expression profiles using Non-negative Matrix Factorization projection in order to sub-type the mouse models