Diagnosis-relapse in ALL
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE18497 | GEO | 2010/03/10
SECONDARY ACCESSION(S): PRJNA120247
REPOSITORIES: GEO
Similar Datasets
Project description:Almost a quarter of pediatric patients with Acute Lymphoblastic Leukemia (ALL) suffer from relapses. The biological mechanisms underlying therapy response and development of relapses have remained unclear. In an attempt to better understand this phenomenon, we have analyzed 41 matched diagnosis relapse pairs of ALL patients using genomeâ??wide expression arrays (82 arrays) on purified leukemic cells. In roughly half of the patients very few differences between diagnosis and relapse samples were found (â??stable groupâ??), suggesting that mostly extra-leukemic factors (e.g., drug distribution, drug metabolism, compliance) contributed to the relapse. Therefore, we focused our further analysis on 20 samples with clear differences in gene expression (â??skewed groupâ??), reasoning that these would allow us to better study the biological mechanisms underlying relapsed ALL. After finding the differences between diagnosis and relapse pairs in this group, we identified four major gene clusters corresponding to several pathways associated with changes in cell cycle, DNA replication, recombination and repair, as well as B cell developmental genes. We also identified cancer genes commonly associated with colon carcinomas and ubiquitination to be upregulated in relapsed ALL. Thus, about half of relapses are due to selection or emergence of a clone with deregulated expression of a genes involved in pathways that regulate B cell signaling, development, cell cycle, cellular division and replication. The study contains 41 pairs of samples taken from patients at diagnosis and relapse (a total of 82 arrays).
2010-03-23 | E-GEOD-18497 | biostudies-arrayexpress
Project description:Here we characterize an association between disease progression and DNA methylation in Diffuse Large B cell Lymphoma (DLBCL). By profiling genome-wide DNA methylation at single base-pair resolution in thirteen DLBCL diagnosis-relapse sample pairs, we show DLBCL patients exhibit heterogeneous evolution of tumor methylomes during relapse. We identify differentially methylated regulatory elements and determine a relapse–associated methylation signature converging on key pathways such as transforming growth factor beta (TGF-beta) receptor activity. We also observe decreased intra-tumor methylation heterogeneity from diagnosis to relapsed tumor samples. Relapse-free patients display lower intra-tumor methylation heterogeneity at diagnosis compared to relapsed patients in an independent validation cohort. Furthermore, intra-tumor methylation heterogeneity is predictive of time to relapse. Therefore, we propose that epigenomic heterogeneity may support or drive the relapse phenotype and can be used to predict DLBCL relapse. Using ERRBS, we profiled genome-wide DNA methylation patterns of non-relapse DLBCL tumor samples at diagnosis, relaspe DLBCL patient samples at diagnosis and relaspe.
2015-04-14 | E-GEOD-66329 | biostudies-arrayexpress
Project description:Relapse of acute myeloid leukemia (AML) is highly aggressive and often treatment refractory. We analyzed previously published AML relapse cohorts and found that 40% of relapses occur without changes in driver mutations, suggesting that non-genetic mechanisms drive relapse in a large proportion of cases. We therefore characterized epigenetic patterns of AML relapse using 26 matched diagnosis-relapse samples with ATAC-seq. This analysis identified a relapse-specific chromatin accessibility signature for mutationally stable AML, suggesting that AML undergoes epigenetic evolution at relapse independent of mutational changes. Analysis of leukemia stem cell (LSC) chromatin changes at relapse indicated that this leukemic compartment underwent significantly less epigenetic evolution than non-LSCs, while epigenetic changes in non-LSCs reflected overall evolution of the bulk leukemia. Finally, we used single-cell ATAC-seq paired with mitochondrial sequencing (mtscATAC) to map clones from diagnosis into relapse along with their epigenetic features. We found that distinct mitochondrially-defined clones exhibit more similar chromatin accessibility at relapse relative to diagnosis, demonstrating convergent epigenetic evolution in relapsed AML. These results demonstrate that epigenetic evolution is a feature of relapsed AML and that convergent epigenetic evolution can occur following treatment with induction chemotherapy.
2024-04-17 | GSE256495 | GEO
Project description:Here we characterize an association between disease progression and DNA methylation in Diffuse Large B cell Lymphoma (DLBCL). By profiling genome-wide DNA methylation at single base-pair resolution in thirteen DLBCL diagnosis-relapse sample pairs, we show DLBCL patients exhibit heterogeneous evolution of tumor methylomes during relapse. We identify differentially methylated regulatory elements and determine a relapse–associated methylation signature converging on key pathways such as transforming growth factor beta (TGF-beta) receptor activity. We also observe decreased intra-tumor methylation heterogeneity from diagnosis to relapsed tumor samples. Relapse-free patients display lower intra-tumor methylation heterogeneity at diagnosis compared to relapsed patients in an independent validation cohort. Furthermore, intra-tumor methylation heterogeneity is predictive of time to relapse. Therefore, we propose that epigenomic heterogeneity may support or drive the relapse phenotype and can be used to predict DLBCL relapse.
2015-04-14 | GSE66329 | GEO
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
2015-04-23 | E-GEOD-62618 | biostudies-arrayexpress
Project description:In high income countries 90% of the patients achieve complete remission after induction chemotherapy. However, 30-40% of these patients suffer from relapse. These patients face a dismal prognosis, as the majority (>60%) of relapsed patients die within 5 years. As a result, outcome for pediatric acute myeloid leukemia (AML) patients remains poor and has stabilized over the past 15 years. To prevent or better treat relapse of AML is the best option to improve outcome. Despite patient specific differences, most patients do respond to initial therapy. This suggests that at relapse, mechanisms are active that cause the altered response to chemotherapy. Detailed understanding of mechanisms that cause relapse remain largely elusive. To gain insight in the molecular pathways that characterize relapsed AML, we performed genome wide gene expression profiling on paired initial diagnosis and relapsed AML samples of 23 pediatric AML patients. We used pathway analysis to find which molecular pathways are involved in altered gene expression between diagnosis and relapse samples of individual AML patients. 23 paired diagnosis and relapse bone marrow or peripheral blood samples were collected and cryo-preserved. They were later thawed and processed for hybridization to Affymetrix U133 Plus 2.0 arrays.
2015-05-07 | E-GEOD-52891 | biostudies-arrayexpress
Project description:In high income countries 90% of the patients achieve complete remission after induction chemotherapy. However, 30-40% of these patients suffer from relapse. These patients face a dismal prognosis, as the majority (>60%) of relapsed patients die within 5 years. As a result, outcome for pediatric acute myeloid leukemia (AML) patients remains poor and has stabilized over the past 15 years. To prevent or better treat relapse of AML is the best option to improve outcome. Despite patient specific differences, most patients do respond to initial therapy. This suggests that at relapse, mechanisms are active that cause the altered response to chemotherapy. Detailed understanding of mechanisms that cause relapse remain largely elusive. To gain insight in the molecular pathways that characterize relapsed AML, we performed genome wide gene expression profiling on paired initial diagnosis and relapsed AML samples of 23 pediatric AML patients. We used pathway analysis to find which molecular pathways are involved in altered gene expression between diagnosis and relapse samples of individual AML patients.
2015-05-07 | GSE52891 | GEO
Project description:Background In childhood acute lymphoblastic leukemia (ALL), central nervous system (CNS) involvement is rare at diagnosis (1-4%), but more frequent at relapse (~30%). Minimal residual disease diagnostics predict most bone marrow (BM) relapses, but likely cannot predict isolated CNS relapses. Consequently, CNS relapses may become relatively more important. Because of the significant late sequelae of CNS treatment, early identification of patients at risk of CNS relapse is crucial. Methods Gene expression profiles of ALL cells from cerebrospinal fluid (CSF) and ALL cells from BM were compared and differences were confirmed by real-time quantitative PCR. For a selected set of overexpressed genes, protein expression levels of ALL cells in CSF at relapse and of ALL cells in diagnostic BM samples were evaluated by 8-color flow cytometry. Results CSF-derived ALL cells showed a clearly different gene expression profile than BM-derived ALL cells, with differentially-expressed genes (including SCD and OPN) involved in survival and apoptosis pathways and linked to the JAK-STAT pathway. Flowcytometric analysis showed that a subpopulation of ALL cells (>1%) with a â??CNS signatureâ?? (SCD positivity and increased OPN expression) was already present in BM at diagnosis in ALL patients who later developed a CNS relapse, but was <1% or absent in virtually all other patients. Conclusions The presence of a subpopulation of ALL cells with a â??CNS signatureâ?? at diagnosis may predict isolated CNS relapse. Such information can be used to design new diagnostic and treatment strategies that aim at prevention of CNS relapse with reduced toxicity. We compared gene expression profiles of ALL cells obtained from cerebrospinal fluid (n=8) with profiles of ALL cells obtained from bone marrow at diagnosis (n=22) or at relapse (n=20)
2015-12-31 | E-GEOD-60926 | biostudies-arrayexpress
Project description:The gene expression patterns of favorable histology Wilms tumors (FHWT) that relapsed were compared with those that did not relapse using oligonucleotide arrays; Description: 250 FHWT of all stages enriched for relapses treated on National Wilms Tumor Study 5 passed quality parameters and were suitable for analysis using oligonucleotide arrays. Relapse risk stratification utilized Support Vector Machine; two and ten fold cross-validation was applied. The number of genes associated with relapse was less than that predicted by chance alone for 106 patients (32 relapses) with stages I and II FHWT and no further analyses were performed. This number was greater than expected by chance for 76 local stage III patients. Cross validation including an additional 68 local stage III patients (total 144 patients, 53 relapses) demonstrated that classifiers for relapse composed of 50 genes were associated with a median sensitivity of 47%, specificity 70%, and total error rate of 38%. Analysis of genes differentially expressed in relapse patients revealed apoptosis, Wnt signaling, IGF pathway, and epigenetic modification to be mechanisms important in relapse. Potential therapeutic targets include FRAP/MTOR and CD40. Experiment Overall Design: 144 stage 3 FHWT, with fifty-three relapses (cases) and ninety-one non-relapses (controls) with a minimum of three years follow-up, included all relapses and a 30% random selection of non-relapses for which frozen tumor tissue was available who passed all quality control parameters. The NWTS-5 protocol was approved by the review boards of institutions that registered patients. Histological diagnosis and local stage were confirmed by central review. Experiment Overall Design: Quality control steps taken: Experiment Overall Design: 1. Samples were snap frozen immediately following surgery and were mailed on dry ice to the Tumor Bank and retained at -80C. Experiment Overall Design: 2. Frozen sections were evaluated histologically and tumors with less than 80% viable tumor cellularity were excluded. Experiment Overall Design: 3. Array images were assessed by eye to confirm scanner alignment and the absence of significant bubbles or scratches. Experiment Overall Design: 4. Samples for which the 3'/5' ratios for GAPDH were greater than 3.2 were excluded. Experiment Overall Design: 5. The BioB spike controls were confirmed as present; BioC, BioD and cre were confirmed as increasing intensity. Experiment Overall Design: 6. When scaled to a target intensity of 2500, scaling factors were between 12 and 53; background levels were 34 â 115: Q values were 1.3 â 3.7 and mean intensities were within acceptable limits. Experiment Overall Design: 7. The range of percent present calls was from 38% to 52%. Experiment Overall Design: 8. Verification of gene expression was performed utilizing quantitative RT-PCR for five genes. Â Â Experiment Overall Design: Statistical Analysis: Positional-dependent-nearest-neighbor model (PDNN) software was used to translate the scanned images into expression analysis files and to normalize the data across all arrays (http://odin.mdacc.tmc.edu/~zhangli/PerfectMatch/). Genes with maximum expression less than a log scale of 6 across all tumors and Affymetrix control genes were excluded, resulting in 20,931 probe sets for analysis. Support Vector Machine (SVM) as developed by Chang and Lin (http://www.csie.ntu.edu.tw/~cjlin/libsvm) and implemented in an R software package, e1071 was chosen for relapse risk stratification using the p-value of the t-test comparison between case and control to select the genes. Using all 144 tumors, 109 genes were identified with p-value <0.001 and are provided in the data table labelled "t-test comparison between case and control" (ie, Supplemental table 2, in related publication)." Two and ten fold cross validations were utilized to investigate the ability of classifiers established in randomly selected training set to predict relapse in an independent test set comprised of the remaining tumors. For two-fold cross validation, the dataset was randomly divided 500 times into training and corresponding test sets of equal size, each including half the patients who relapsed. A classifier for relapse was identified for each training set and used to assign tumors in the corresponding test set to low and high risk categories. The training and test sets were then swapped. The number of top K genes in each classifier evaluated ranged from 1-150. Therefore, a total of 150,000 different classifiers were developed, one for each value of K from 1-150, for each of the 1,000 (500*2) training sets. For ten-fold cross validation the dataset was randomly divided 500 times into ten groups of approximately equal size. Each group included approximately the same number of relapses. For each such group, a classifier was built with the remaining 9/10 of the samples and then used to categorize tumors in the group as low or high risk; the process was repeated until all tumor samples were categorized as low or high risk. For all the cross validation procedures, to avoid gene-selection bias, classifiers were completely rebuilt in each cross validation iteration.
2009-02-09 | E-GEOD-10320 | biostudies-arrayexpress
Project description:A comparison of RNA expression profiles from leukemic cells of 8 single B-ALL patients at diagnosis and relapse. For all patients, clonality of the blast cells at diagnosis and relapse was demonstrated to be the same (Germano, G., del Giudice, L., Palatron, S., Giarin, E., Cazzaniga, G., Biondi, A., Basso, G., Clonality profile in relapsed precursor-B-ALL children by GeneScan and sequencing analyses. Consequences on minimal residual disease monitoring. Leukemia, 2003). The study protocol was approved by the Research committee of the AIEOP and written informed consent was obtained from all participants before samples were taken. RNA extracted from BM samples was used for microarray analysis. The blast cell infiltration both at diagnosis and relapse was 75% and mononuclear cell were isolated using a Lymphoprep density gradient (1.077 g/ml, Nycomed Pharma, Oslo, Norway). RNA was extracted from blast cells at diagnosis and relapse and both samples were hybridized on an MWG 30K Human Array A (MWG, München) after direct labeling using two different fluorochromes (Cy3 and Cy5) for the respective samples. Keywords = Homo sapiens, B-lymphoblastic leukemia, diagnosis, relapse
2003-06-13 | GSE416 | GEO