Genome-Wide Expression Profiling and Minimal Residual Disease in Childhood Acute Lymphoblastic Leukemia.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 87-87
Author(s):  
Christian Flotho ◽  
Elaine Coustan-Smith ◽  
Guangchun Song ◽  
Cheng Cheng ◽  
Deiqing Pei ◽  
...  

Abstract The assessment of early treatment response based on minimal residual disease (MRD) detection is a powerful prognostic indicator in childhood acute lymphoblastic leukemia (ALL). To identify genes whose expression is associated with poorer early response and to define gene expression signatures predictive of MRD findings, we correlated gene expression profiles of diagnostic bone marrow blasts in 236 children with ALL enrolled in St. Jude Total Therapy XIIIA-XV protocols with MRD results obtained at days 19 and 46 of remission induction treatment. The dataset consisted of 46 T-lineage ALL and 190 B-lineage ALL; the latter included 10 BCR-ABL, 11 E2A-PBX1, 12 MLL rearranged, 49 TEL-AML1, 46 hyperdiploid >50 chromosomes (HD>50) karyotype, 3 BCR-ABL plus HD>50, and 59 other cases. RNA expression profiles were obtained using Affymetrix U133A gene chips; MRD was assessed by a flow cytometric assay that allows the identification of one leukemic cell among 10,000 normal bone marrow cells or greater and is applicable to approximately 95% of patients. We used a general linear model to eliminate the possible confounding influence of genetic subtypes known to be associated with treatment response. Then, we applied a t-test with the P value threshold of 0.006, determined by the profile information criterion for large-scale multiple tests. By this criterion, 279 probe sets were associated with MRD at day 19 (estimated false-discovery rate [FDR] 0.42) and 606 probe sets with MRD at day 46 (estimated FDR 0.17); 41 probe sets were associated with MRD at both time points. The expression of CASP8A2 (FLASH, CED-4), which encodes a key mediator of apoptosis and participates in glucocorticoid signaling, was significantly lower in cases with MRD at both time points. In a cluster analysis using the probe sets associated with MRD, the capacity to predict results of the MRD assay was limited. For example, only 69% of MRD-negative and 81% of MRD-positive results at day 19 were correctly classified. Similar results were obtained using the day 46 data. We also determined whether MRD status could be predicted by an unsupervised cluster analysis of all 236 cases with 17,269 probe sets (after removing transcripts not expressed in any of the samples). Although there was a strong association of cluster formation with lineage and genetic subtypes, there was no significant association with MRD status at days 19 or 46. Moreover, there was no significant association with MRD status in analyses limited to a series of 66 ‘standard-risk’ B-lineage ALL cases (excluding those with BCR-ABL, TEL-AML1, MLL, hypodiploid <45 chromosomes or HD>50), or to cases of each individual genetic subtype. In conclusion, leukemic cells at diagnosis express genes that are associated with MRD. Although gene expression profiles can accurately identify leukemia cell lineage and genotype, they cannot accurately predict MRD status, probably owing to the multifactorial nature of treatment response, which is influenced not only by cellular drug resistance but also by clinical and pharmacologic variables of the host.

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1390-1390
Author(s):  
Jitsuda Sitthi-Amorn ◽  
Betty Herrington ◽  
Gail Megason ◽  
Jeanette Pullen ◽  
Catherine Gordon ◽  
...  

Abstract Introduction Despite advances in diagnosis and treatment, B-precursor acute lymphoblastic leukemia (B-ALL) remains the most common childhood cancer and one of the leading causes of cancer-related death in children and adolescents. Although B-ALL is highly curable, approximately 10 - 20% of children diagnosed with B-ALL still do not respond to the current treatment protocols. Minimal residual disease (MRD) at the end of induction of remission is strongly associated with prognosis. Therefore there is an urgent need to understand the molecular mechanisms underpinning MRD and to identify biomarkers for the development of novel and more effective therapeutic strategies. This project was undertaken to determine whether molecular perturbation in patients with positive MRD at day 46 differs from those with negative MRD in different subtypes of B-ALL and to identify biological pathways dysregulated. We hypothesized that gene expression profiles differ significantly between patients with positive MRD at day 46 and patients with negative MRD. Methods We analyzed publicly available gene expression data derived from samples obtained from 189 patients with B-ALL (47 with positive MRD at day 46 and 142 with negative MRD). The data was downloaded from the NCBI’s Gene Expression Omnibus (GEO) database under accession number GSE33315. Patients were classified into seven subtypes of B-ALL which are hyperdiploid, ETV6-RUNX1, MLL rearrangement, hypodiploid, BCR-ABL1, TCF3-PBX1 and others (no detectable recurring genetic abnormalities). Samples from patients with BCR-ABL1 were excluded due to a different prognosis and treatment approach. Patients with TCF3-PBX1 were excluded due to the small sample size; leaving 165 patients in the analysis (35 with positive MRD at day 46 and 130 with negative MRD). We analyzed gene expression data using both supervised and unsupervised analysis. Supervised analysis was performed between patients with positive MRD and negative MRD for each subtype of B-ALL. Unsupervised analysis using hierarchical clustering was performed on significantly differently expressed genes (P < 0.005) to identify functionally related genes with similar patterns of expression profiles. Pathway analysis was performed using the Ingenuity Pathways Analysis (IPA) system to identify biological pathways that are dysregulated in response to positive MRD in different subtypes of B-ALL. Result Comparison of gene expression profiles between positive MRD and negative MRD revealed significantly differentially expressed genes between the two groups. The numbers of significantly (P < 0.005) differentially expressed genes for hyperdiploid, ETV6-RUNX1, MLL rearrangement, hypodiploid and others were 93, 82, 87, 140 and 289 genes; respectively. The identified genes included BCL2, BECN1, CBFB, IKZF1, PAX5, SH2B3 and TOX which are known to be associated with B-ALL. Unsupervised analysis using hierarchical clustering and GO analysis revealed similarity in patterns of gene expression within subtypes of B-ALL and functional relationships among the identified genes. Among the identified genes included genes involved in cell death and survival, cellular development and DNA replication, recombination, and repair. Network and Pathway analysis revealed multi-gene regulatory networks and key biological pathways including granzyme B signaling, TCA cycle II and B cell receptor signaling. Pathway analysis also revealed upstream regulators including RB1, CDKN2A and TP53 which have been reported to be involved in the hypodiploid subtype, a subtype characterized with poorer prognosis. Conclusion Although the sample size is small, our analysis demonstrates that molecular perturbation significantly differs between pediatric B-ALL patients with positive MRD and those with negative MRD, and that these differences are subtype-specific. The results further demonstrate that biological pathways are dysregulated in response to MRD status and that use of gene expression analysis has the promise to stratify patients on the basis of MRD status and to identify potential biomarkers. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 2755-2755 ◽  
Author(s):  
Claudia D. Baldus ◽  
Michael Radmacher ◽  
Guido Marcucci ◽  
Dieter Hoelzer ◽  
Eckhard Thiel ◽  
...  

Abstract The human gene BAALC (Brain And Acute Leukemia, Cytoplasmic) is a molecular marker of hematopoietic progenitor cells and is aberrantly expressed in subsets of acute myeloid (AML) and lymphoblastic (ALL) leukemias. High mRNA expression levels of BAALC have been shown to adversely impact outcome in newly diagnosed AML patients (pts) with normal cytogenetics. To gain insight into the functional role of BAALC and its significance to normal hematopoiesis and leukemogenesis we compared gene expression profiles of normal CD34+ progenitors with those of AML and ALL blasts (using oligonucleotide microarrays; HG-U133 plus 2.0, Affymetrix, Santa Clara, CA). First we explored the regulation of BAALC expression during lineage specific maturation of in vitro differentiated human CD34+ bone marrow cells selected from healthy individuals. Microarray analyses were carried out using CD34+ cells stimulated in vitro with EPO, TPO, or G/GM-CSF to induce lineage-specific differentiation. At day 0 of culture and at three different time points during differentiation (days 4, 7, 11) cells were harvested, and if necessary purified by immunomagnetic beads and used for microarray studies. Experiments of all lineages and time points were done in triplicates. A total of 276 genes were identified showing similar changes in expression (with downregulation during differentiation) as BAALC at the three time points in all lineages with a correlation coefficient of R&gt;0.95. This set of 276 BAALC co-expressed genes was investigated in an AML expression dataset generated from 51 adult pts with newly diagnosed de novo AML and normal cytogenetics (Cancer and Leukemia Group B). After exclusion of probesets expressed in fewer than 20% of pt samples, 21 probesets representing 14 named genes 6 of which are known to be involved in AML (BAALC, CD34, CD133, SOX4, ERG, SEPT6) and 4 implicated in lymphoid development (TCF4, SH2D1A, ITM2A, ITM2C) were found to be overexpressed (a significance level of P=0.01 was used) in pts of the highest third compared to pts of the lowest third of BAALC expression values as measured by real-time RT-PCR. We next applied these same 21 BAALC co-expressed probesets to an ALL expression dataset generated from 66 adult pts with newly diagnosed standard risk B-lineage precursor ALL (from the German ALL GMALL study group). A BAALC specific cluster uncovered 7 probesets representing 4 different co-expressed genes: BAALC, CD133, and the transcription factors ERG and TCF4. Thus, applying a BAALC specific expression signature to AML and ALL gene expression profiles revealed 3 genes (CD133, ERG, TCF4), which are highly associated with BAALC in myeloid and lymphoid blasts. Interestingly in non-malignant lymphoid and myeloid cells the oncogeneic ETS transcription factor ERG has shown specificity to immature cells, while its mechanistical role in leukemogenesis remains unknown. ERG and TCF4 may directly regulate BAALC and indicate a specific pathway implicated in leukemogenesis, while co-expression of CD133 and BAALC suggests shared stem cell characteristics. Functional studies are in progress to further explore these findings.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 4789-4789
Author(s):  
Xiang-Qin Weng ◽  
Yang Shen ◽  
Yan Sheng ◽  
Bing Chen ◽  
Jing-han Wang ◽  
...  

Abstract Abstract 4789 Monitoring of minimal residual disease (MRD) in patients with acute lymphoblastic leukemia (ALL) by immunophenotyping and/or molecular techniques provides a way to precisely evaluate early treatment response and predict relapse. In this study, we have investigated the prognostic significance of MRD in adult patients with B-lineage acute lymphoblastic leukemia (B-ALL) by 8-color flow cytometry. A cohort of 106 patients with B-ALL who had achieved a complete remission (CR) and at least 1 LAIP characteristics were enrolled to perform MRD assessment at the end of induction and 1 cycle of consolidation. LAIPs were identifiable in 96% of the patients by 8-color flow cytometric assay, in which, most cases (90.6%) containing 2 or more LAIPs had a sensitivity as high as identifying 1 leukemic blast among 1×105 BM nucleated cells. MRD negative status could clearly predict a favorable 1 year relapse free survival (RFS) and 2 year overall survival (OS) when a cut-off level of 0.01% was used to define MRD positivity at the point of achieving CR (P=0.000 and 0.000, respectively) and after 1 cycle of consolidation (P=0.000 and 0.000, respectively), respectively. In multivariate analysis including cytogenetic abnormalities, clinical factors and MRD status, late CR (P=0.046), MRD status at the points of obtaining CR (P=0.016) and 1 consolidation (P=0.007) were associated with RFS independently, while only MRD status after 1 course of consolidation was independent prognostic factor for OS (P=0.000). Of note, in exploring the fewer patients with MRD negative status experienced recent relapse, we have identified that most of such patients had a MRD level of 10−4−10−5 comparing to undetectable MRD level. Furthermore, our evidences showed that MRD assessed by flow cytometry and by RQ-PCR assay targeting to BCR-ABL fusion gene yielded concordant results in the vast majority of cases (90%). In conclusion, immunophenotypic evaluation of MRD by 8-color flow cytometry could work as an important tool to assess the treatment response and prognosis precisely in adult B-ALL. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2016 ◽  
Vol 127 (15) ◽  
pp. 1896-1906 ◽  
Author(s):  
Bruno Paiva ◽  
Luis A. Corchete ◽  
Maria-Belen Vidriales ◽  
Noemi Puig ◽  
Patricia Maiso ◽  
...  

Key Points We report for the first time the biological features of MRD cells in MM and unravel that clonal selection is already present at the MRD stage. MRD cells show a singular phenotypic signature that may result from persisting clones with different genetic and gene expression profiles.


Blood ◽  
2001 ◽  
Vol 97 (7) ◽  
pp. 2115-2120 ◽  
Author(s):  
Jiann-Shiuh Chen ◽  
Elaine Coustan-Smith ◽  
Toshio Suzuki ◽  
Geoffrey A. Neale ◽  
Keichiro Mihara ◽  
...  

Abstract To identify new markers of minimal residual disease (MRD) in B-lineage acute lymphoblastic leukemia (ALL), gene expression of leukemic cells obtained from 4 patients with newly diagnosed ALL was compared with that of normal CD19+CD10+ B-cell progenitors obtained from 2 healthy donors. By cDNA array analysis, 334 of 4132 genes studied were expressed 1.5- to 5.8-fold higher in leukemic cells relative to both normal samples; 238 of these genes were also overexpressed in the leukemic cell line RS4;11. Nine genes were selected among the 274 overexpressed in at least 2 leukemic samples, and expression of the encoded proteins was measured by flow cytometry. Two proteins (caldesmon and myeloid nuclear differentiation antigen) were only weakly expressed in leukemic cells despite strong hybridization signals in the array. By contrast, 7 proteins (CD58, creatine kinase B, ninjurin1, Ref1, calpastatin, HDJ-2, and annexin VI) were expressed in B-lineage ALL cells at higher levels than in normal CD19+CD10+ B-cell progenitors (P &lt; .05 in all comparisons). CD58 was chosen for further analysis because of its abundant and prevalent overexpression. An anti-CD58 antibody identified residual leukemic cells (0.01% to 1.13%; median, 0.03%) in 9 of 104 bone marrow samples from children with ALL in clinical remission. MRD estimates by CD58 staining correlated well with those of polymerase chain reaction amplification of immunoglobulin genes. These results indicate that studies of gene expression with cDNA arrays can aid the discovery of leukemia markers.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4985-4985
Author(s):  
Neelam Varma ◽  
Sandeep R. ◽  
Shano Naseem ◽  
Man Updesh Singh Sachdeva ◽  
Deepak Bansal ◽  
...  

Abstract Introduction: Minimal residual disease (MRD) determination involves the measurement of very low levels of leukemia using sensitive techniques which at present are complex, time consuming and require expertise for performance and interpretation. A ''panleukemic''marker such as Wilm's tumor 1 gene (WT1) which is frequently over expressed in acute leukemia could simplify MRD detection and serve as a useful prognostic marker. Aim of study: To evaluate the usefulness of WT1 gene expression, as a marker for MRD in B-lineage acute lymphoblastic leukemia (B-ALL). Method and Material: Flow cytometric immunophenotyping (FCMI) and real time-polymerase chain reaction (RQ-PCR) for WT1 gene expression were performed usingbone marrow at diagnosis and at day 15 (mid-induction). Of the 23 patients recruited, day 15 MRD analyses by both these methods was performed on 11 bone marrow samples of patients who showed WT1 over expression at day 0. Results: WT1 over expression at diagnosis was found in 69.5% cases (16/23). MRD was detectable in 54.5% cases by WT1 RQ-PCR and by FCM in 72% cases. A statistically significant correlation was seen between WT1 normalized copy number (NCN) at diagnosis with MRD levels detected by FCM. Conclusion: WT1 represents a candidate MRD and prognostic marker. The significant correlation between WT1 over expression at diagnosis and MRD positivity by flow cytometry at day 15 (mid induction) of chemotherapy suggests that high WT1 expression could correlate with unfavourable outcome in childhood ALL. However, as not all patients of B-ALL over-express WT1 at diagnosis, quantitative assessment of WT1 transcripts can be used as useful molecular marker for MRD detection, but only in a subset of patients. Disclosures No relevant conflicts of interest to declare.


Blood ◽  
2006 ◽  
Vol 108 (3) ◽  
pp. 1050-1057 ◽  
Author(s):  
Christian Flotho ◽  
Elaine Coustan-Smith ◽  
Deqing Pei ◽  
Shotaro Iwamoto ◽  
Guangchun Song ◽  
...  

Abstract In childhood acute lymphoblastic leukemia (ALL), early response to treatment is a powerful prognostic indicator. To identify genes associated with this response, we analyzed gene expression of diagnostic lymphoblasts from 189 children with ALL and compared the findings with minimal residual disease (MRD) levels on days 19 and 46 of remission induction treatment. After excluding genes associated with genetic subgroups, we identified 17 genes that were significantly associated with MRD. The caspase 8–associated protein 2 (CASP8AP2) gene was studied further because of its reported role in apoptosis and glucocorticoid signaling. In a separate cohort of 99 patients not included in the comparison of gene expression profiles and MRD, low levels of CASP8AP2 expression predicted a lower event-free survival (P = .02) and a higher rate of leukemia relapse (P = .01) and were an independent predictor of outcome. High levels of CASP8AP2 expression were associated with a greater propensity of leukemic lymphoblasts to undergo apoptosis. We conclude that measurement of CASP8AP2 expression at diagnosis offers a means to identify patients whose leukemic cells are highly susceptible to chemotherapy. Therefore, this gene is a strong candidate for inclusion in gene expression arrays specifically designed for leukemia diagnosis.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Arika Fukushima ◽  
Masahiro Sugimoto ◽  
Satoru Hiwa ◽  
Tomoyuki Hiroyasu

Abstract Background Historical and updated information provided by time-course data collected during an entire treatment period proves to be more useful than information provided by single-point data. Accurate predictions made using time-course data on multiple biomarkers that indicate a patient’s response to therapy contribute positively to the decision-making process associated with designing effective treatment programs for various diseases. Therefore, the development of prediction methods incorporating time-course data on multiple markers is necessary. Results We proposed new methods that may be used for prediction and gene selection via time-course gene expression profiles. Our prediction method consolidated multiple probabilities calculated using gene expression profiles collected over a series of time points to predict therapy response. Using two data sets collected from patients with hepatitis C virus (HCV) infection and multiple sclerosis (MS), we performed numerical experiments that predicted response to therapy and evaluated their accuracies. Our methods were more accurate than conventional methods and successfully selected genes, the functions of which were associated with the pathology of HCV infection and MS. Conclusions The proposed method accurately predicted response to therapy using data at multiple time points. It showed higher accuracies at early time points compared to those of conventional methods. Furthermore, this method successfully selected genes that were directly associated with diseases.


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