Predicting Relapse in Favorable Histology Wilms Tumor Using Gene Expression
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE10320 | GEO | 2009/01/30
SECONDARY ACCESSION(S): PRJNA108555
REPOSITORIES: GEO
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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: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: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:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. KaplanâMeier analysis with peritoneal relapse free survival showed a significant difference between âgood signature groupâ and âpoor signature groupâ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers. Of 141 samples, 56 represented the retrospective phase and 85 represented the prospective phase.
2010-05-23 | E-GEOD-15081 | biostudies-arrayexpress
Project description:Background: We have previously shown that the Gene expression Grade Index (GGI) was able to identify two subtypes of estrogen receptor (ER)-positive tumors that were associated with statistically distinct clinical outcomes in both untreated and tamoxifen-treated patients. Here, we aim to investigate the ability of the GGI to predict relapses in postmenopausal women who were treated with tamoxifen (T) or letrozole (L) within the BIG 1-98 trial. Methods: We generated gene expression profiles (Affymetrix) and computed the GGI for a matched, case-control sample of patients enrolled in the BIG 1-98 trial from the two hospitals where frozen samples were available. All relapses (cases) were identified from patients randomized to receive monotherapy or from the switching treatment arms for whom relapse occurred before the switch. Each case was randomly matched with four controls based upon nodal status and treatment (T or L). The prognostic value of GGI was assessed as a continuous predictor and divided at the median. Predictive accuracy of GGI was estimated using time-dependent area under the curve (AUC) of the ROC curves. Results: Frozen samples were analyzable for 48 patients (10 cases and 38 controls). Seven of the 10 cases had been assigned to receive L. Cases and controls were comparable with respect to menopausal and nodal status, local and chemotherapy, and HER2 positivity. Cases were slightly older than controls and had a larger proportion of large, poorly differentiated ER+/PgR- tumors. The GGI was significantly and linearly related to risk of relapse: each 10-unit increase in GGI resulted in an increase of approximately 11% in the hazard rate (p=0.02). Within the subgroups of patients with node-positive disease or who were treated with L, the hazard of relapse was significantly greater for patients with GGI at or above the median. AUC reached a maximum of 78% at 27 months. Conclusions: This analysis supports the GGI as a good predictor of relapse for ER-positive patients, even among patients who receive L. Validation of these results, in a larger series from BIG 1-98, is planned using the simplified GGI represented by a smaller set of genes and tested by qRT-PCR on paraffin-embedded tissues. Test whether the Gene expression Grade Index (GGI) is a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial. 55 microarray experiments from primary breast tumors of endocrine-treated patients. No replicate, no reference sample.
2009-07-09 | E-GEOD-16391 | biostudies-arrayexpress
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 “CNS signature” (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 “CNS signature” 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.
2015-12-31 | GSE60926 | GEO
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 genome–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 (“stable group”), 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 (“skewed group”), 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.
2010-03-10 | GSE18497 | GEO
Project description:paired comparison of RNA expression in peripheral blood mononuclear cells in the same group of 14 multiple sclerosis patients while stable and while in relapse. A defining feature of multiple sclerosis is the occurrence of clinical relapses separated by periods of clinical stability. Better understanding of the events underlying clinical relapse might suggest new approaches to treatment. We used microarrays to measure mRNA expression in the peripheral blood of 14 MS patients during clinical relapse and while stable. Seventy-one transcripts changed expression at the p<0.001 significance level. The most notable finding was decreased expression of transcripts with regulatory function, expressed primarily in non-T cells. Transcripts with increased expression were primarily expressed in T cells. Pathways analysis suggested involvement of the cytokine network, coagulation and complement cascades, IL-10 signaling, and NF-?B signaling. total RNA from PBMC in relapse and while stable from 14 multiple sclerosis patients
2010-07-30 | E-GEOD-19224 | biostudies-arrayexpress
Project description:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. Kaplan–Meier analysis with peritoneal relapse free survival showed a significant difference between ‘good signature group’ and ‘poor signature group’ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers.
2009-03-04 | GSE15081 | GEO
Project description:Recurrences of diffuse large B-cell lymphomas (DLBCL) result in significant morbidity and mortality, but their underlying genetic and biological mechanisms are unclear. Clonal relationship in DLBCL relapses so far is mostly addressed by the investigation of immunoglobulin (IG) rearrangements, therefore lacking deeper insights into genome-wide lymphoma evolution. We studied mutations and copy number aberrations in 20 paired relapsing and 20 non-relapsing DLBCL cases aiming to test the clonal relationship between primaries and relapses, to track tumorsâ genetic evolution and to investigate the genetic background of DLBCL recurrence. Three clonally-unrelated DLBCL relapses were identified (15%). Also, two distinct patterns of genetic evolution in clonally-related relapses were detected: (1) early-divergent/branching evolution from a common progenitor in 6 patients (30%), and (2) late-divergent/linear progression of relapses in 11 patients (65%). Analysis of recurrent genetic events identified potential early drivers of lymphomagenesis (KMT2D, MYD88, CD79B and PIM1). The most frequent relapse-specific events were additional mutations in KMT2D and alterations of MEF2B. SOCS1 mutations were exclusive to non-relapsing DLBCL, whereas primaries of relapsing DLBCL more commonly displayed gains of 10p15.3-p12.1 containing the potential oncogenes PRKCQ, GATA3, MLLT10 and ABI1. Altogether, our study expands knowledge on clonal relationship, genetic evolution and mutational basis of DLBCL relapses. There are 62 copy number Agilent 180k SurePrint arrays in total, which represent 40 cases. There are 21 arrays of primary relapsing DLBCL tumors, 21 arrys of matched relapses and 20 arrays of non relapsing DLBCLs.
2016-06-01 | E-GEOD-65720 | biostudies-arrayexpress