Co-Expression of BAALC with ERG, TCF4, and CD133 Indicates a Shared Pathway in Acute Myeloid and Lymphoblastic Leukemia.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 2755-2755 ◽  
Author(s):  
Claudia D. Baldus ◽  
Michael Radmacher ◽  
Guido Marcucci ◽  
Dieter Hoelzer ◽  
Eckhard Thiel ◽  
...  
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Expression Profiles ◽  
Newly Diagnosed ◽  
Time Points ◽  
Normal Cytogenetics ◽  
Acute Myeloid

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>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.

Overexpression of BRE in Pediatric MLL-Rearranged Acute Myeloid Leukemia Associated with t(9;11)(p22;q23).

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 3471-3471
Author(s):  
Brian Balgobind ◽  
C. Michel Zwaan ◽  
Susan T.C.J.M. Arentsen-Peters ◽  
Dirk Reinhardt ◽  
Ursula Creutzig ◽  
...  
Keyword(s):  
Gene Expression ◽  
Myeloid Leukemia ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Apoptotic Effect ◽  
The Mean ◽  
Pediatric Aml ◽  
Acute Myeloid

Abstract Abstract 3471 Poster Board III-359 One important cytogenetic subgroup of pediatric acute myeloid leukemia (AML) is characterized by translocations of chromosome 11q23, which accounts for 15 to 20% of all cases with an evaluable chromosome analysis. In most of these cases, the mixed lineage leukemia (MLL) gene is involved. More than 50 fusion translocation partners of the MLL gene have been identified and outcome differs by translocation partner, suggesting differences in the biological background. So far these biological differences have not been unravelled. Therefore, we investigated the gene expression profiles of MLL-rearranged subgroups in pediatric AML in order to discover and identify the role of differentially expressed genes. Affymetrix Human Genome U133 plus 2.0 microarrays were used to generate gene expression profiles of 257 pediatric AML cases, which included 21 pediatric AML cases with t(9;11)(p22;q23) and 33 with other MLL-rearrangements. With these profiles, we were able to identify a specific gene expression signature for t(9;11)(p22;q23) using an empirical Bayes linear regression model (Bioconductor package: Limma). This signature was mainly determined by overexpression of the BRE (brain and reproductive organ-expressed) gene. The mean average VSN normalized expression for BRE in the t(9;11)(p22;q23) subgroup was 3.7-fold higher compared with that in other MLL-rearranged cases (p<0.001). Validation by RQ-PCR confirmed this higher expression in t(9;11)(p22;q23) cases (p<0.001). In addition, we confirmed that overexpression of BRE was predominantly found in t(9;11)(p22;q23) in an independent gene expression profile cohort (Ross et al, Blood 2002). Remarkably, MLL-rearranged cases with a BRE expression higher than the mean expression showed a significant better 3 year disease free survival than MLL-rearranged cases with a lower expression (80±13% vs. 30±10%, p=0.02). Previously, overexpression of BRE has been described in hepatocellular carcinomas (HCC) (Chang et al., Oncogene 2008) and an anti-apoptotic effect was described. We transfected BRE in the monomac-1 cell line, which harbors a t(9;11)(p22;q23). We did not find a proliferative advantage for BRE overexpression using a BrDU-assay nor changes in drug sensitivity, indicating that the anti-apoptotic effect as described for HCC in vivo could not be confirmed in vitro in AML. In conclusion, overexpression of the BRE gene is predominantly involved in pediatric MLL-rearranged AML with t(9;11)(p22;q23). Moreover, high expression of BRE showed a favorable prognosis. We did not find any influence of BRE expression on cell proliferation or apoptosis in vitro. This indicates that further studies involving the role of the MLL-fusion protein on BRE transcription are necessary to unravel the leukemogenic role in pediatric AML. Disclosures No relevant conflicts of interest to declare.

scholarly journals Gammaherpesvirus Lytic Gene Expression as Characterized by DNA Array

2002 ◽  
Vol 76 (12) ◽  
pp. 6244-6256 ◽  
Author(s):  
Joo Wook Ahn ◽  
Kenneth L. Powell ◽  
Paul Kellam ◽  
Dagmar G. Alber
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Expression Profiles ◽  
Cdna Array ◽  
Gene Expression Profiles ◽  
Hierarchical Cluster ◽  
Murine Gammaherpesvirus ◽  
Transcription Profiles ◽  
A Genome

ABSTRACT Gammaherpesviruses are associated with a number of diseases including lymphomas and other malignancies. Murine gammaherpesvirus 68 (MHV-68) constitutes the most amenable animal model for this family of pathogens. However experimental characterization of gammaherpesvirus gene expression, at either the protein or RNA level, lags behind that of other, better-studied alpha- and beta-herpesviruses. We have developed a cDNA array to globally characterize MHV-68 gene expression profiles, thus providing an experimental supplement to a genome that is chiefly annotated by homology. Viral genes started to be transcribed as early as 3 h postinfection (p.i.), and this was followed by a rapid escalation of gene expression that could be seen at 5 h p.i. Individual genes showed their own transcription profiles, and most genes were still being expressed at 18 h p.i. Open reading frames (ORFs) M3 (chemokine-binding protein), 52, and M9 (capsid protein) were particularly noticeable due to their very high levels of expression. Hierarchical cluster analysis of transcription profiles revealed four main groups of genes and allowed functional predictions to be made by comparing expression profiles of uncharacterized genes to those of genes of known function. Each gene was also categorized according to kinetic class by blocking de novo protein synthesis and viral DNA replication in vitro. One gene, ORF 73, was found to be expressed with α-kinetics, 30 genes were found to be expressed with β-kinetics, and 42 genes were found to be expressed with γ-kinetics. This fundamental characterization furthers the development of this model and provides an experimental basis for continued investigation of gammaherpesvirus pathology.

Gene Expression Profiling in Adult Acute Lymphoblastic Leukemia, Biphenotypic Acute Leukemia, and Acute Myeloid Leukemia M0: Confirmation of Immunophenotypic and Cytogenetic Diagnostic Findings.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 993-993
Author(s):  
Wolfgang Kern ◽  
Alexander Kohlmann ◽  
Claudia Schoch ◽  
Martin Dugas ◽  
Sylvia Merk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Diagnostic Criteria ◽  
Prediction Accuracy ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Expression Profiles ◽  
Support Vector ◽  
Specific Gene ◽  
Acute Leukemias ◽  
Acute Myeloid

Abstract Diagnosis and classification of acute lymphoblastic leukemias (ALL) and their distinction from biphenotypic acute leukemias (BAL) and acute myeloid leukemias with minimal differentiation (AML M0) is largely based on immunophenotyping. The EGIL classification, adopted by the WHO classification, defines 4 different subtypes of both B-precursor and T-precursor ALL as well as detailed criteria for BAL. Specific cytogenetic features useful for classificationare found in some cases only. We analyzed gene expression profiles in 173 such patients (Pro-B-ALL n=25, c-ALL/Pre-B-ALL n=65 (with t(9;22) n=35, without t(9;22) n=30), mature B-ALL n=13, Pro-T-ALL n=6, Pre-T-ALL n=13, cortical T-ALL n=20, BAL (myeloid and T-lineage) n=17, AML M0 n=14). All cases were assessed by cytomorphology, immunophenotyping, cytogenetics, and molecular genetics. All cases with Pro-B-ALL had t(4;11)/MLL-AF4, all cases with mature B-ALL had t(8;14). Samples were hybridized to both U133A and U133B microarrays (Affymetrix). Top 300 differentially expressed genes were identified for each group in comparison to all other groups and individual other groups and used for classification by various Support Vector Machines (SVM) with 10-fold cross validation (CV). Prediction accuracy for discriminating T- from B-precursor ALL was 100%. Accordingly, principal component analysis (PCA) yielded a complete separation of both groups. PCA of B-precursor ALL cases showed distinct clusters for Pro-B-ALL, c-ALL/Pre-B-ALL, and mature B-ALL, however, c-ALL/Pre-B-ALL with t(9;22) were not completely discriminated from those without. Accordingly, classifying B-precursor ALL with SVM resulted in a 87.4% accuracy. Pre-T-ALL cases clustered distinct from cortical T-ALL with hte exception of two cases. The other Pre-T-ALLs clustered together with Pro-T-ALL. Analyzing T-precusor ALL with SVM and 10-fold CV resulted in an accuracy of only 56.4%. Including BAL and AML M0 into these analyses revealed significant overlaps between samples from these entities and T-ALL cases in PCA; prediction accuracy using SVM and 10-fold CV was 79.8%. This accuracy was confirmed applying 100 runs of SVM with 2/3 of samples being randomly selected as training set and 1/3 as test set which resulted in a median accuracy of 77.2% (range, 67.5% to 85.1%). A 100% prediction accuracy was achieved in Pro-B-ALL and mature B-ALL. Misclassifications were: c-ALL/Pre-B-ALL with t(9;22) as c-ALL/Pre-B-ALL without t(9;22) (6/35) and vice versa (6/30). Of the 13 Pre-T-ALL cases 4 were classified as BAL and 3 as cortical T-ALL. Of the 6 Pro-T-ALL cases 2 were classified as AML M0, 3 as BAL, and 1 as Pre-T-ALL. Of the 17 BAL cases 2 were classified as AML M0, 1 as c-ALL/Pre-B-ALL, 2 as Pre-T-ALL, and 1 as Pro-T-ALL. These analyses confirm that gene expression profiles allow the identification of Pro-B-ALL with t(4;11) and mature B-ALL with t(8;14) but do not unequivocally identify the presence of t(9;22) in c-ALL/Pre-B-ALL. Cortical T-ALL are characterized by a specific gene expression profile which is, however, shared by few cases currently diagnosed as Pre-T-ALL. Thus, diagnostic criteria (surface expression of CD1a only) should be optimized. The same applies to diagnostic criteria for more immature T-ALL, BAL, and AML M0. Loss of 5q is frequently observed in all of these latter entities and may be a future diagnostic marker superseding flow cytometry.

Rearranged Infant Acute Lymphoblastic Leukemia.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1913-1913 ◽  
Author(s):  
Ronald W. Stam ◽  
Monique L. Den Boer ◽  
Pauline Schneider ◽  
Jasper de Boer ◽  
Jill Hagelstein ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Expression Profiles ◽  
Glucocorticoid Resistance ◽  
Glucocorticoid Treatment ◽  
Pediatric All

Abstract MLL rearranged Acute Lymphoblastic Leukemia (ALL) represents an unfavorable and difficult to treat type of leukemia that often is highly resistant to glucocorticoids like prednisone and dexamethasone. As the response to prednisone largely determines the clinical outcome of pediatric ALL patients, overcoming resistance to these drugs may be an important step towards improved prognosis. Here we compared gene expression profiles between prednisone-resistant and prednisone-sensitive pediatric ALL patients to obtain gene expression signatures associated with prednisone resistance for both childhood (&gt;1 year of age) and MLL rearranged infant (&lt;1 year of age) ALL. Merging both signatures in search for overlapping genes associated with prednisone resistance in both patient groups we, found that elevated expression of MCL-1 (an anti-apoptotic member of the BCL-2 protein family) appeared to be characteristic for both prednisone-resistant ALL samples. To validate this observation, we determined MCL-1 expression using quantitative RT-PCR in a cohort of MLL rearranged infant ALL samples (n=23), and confirm that high-level MCL-1 expression significantly confers glucocorticoid resistance both in vitro and in vivo. Finally, down-regulation of MCL-1 in prednisone resistant MLL rearranged ALL cells by RNA interference (RNAi) markedly sensitized these cells to prednisone. Therefore we conclude that MCL-1 plays an important role in glucocorticoid resistance and that MCL- 1 suppressing agents co-administered during glucocorticoid treatment may be beneficial especially for MLL rearranged infant ALL patients.

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 ◽  
...  
Keyword(s):  
Gene Expression ◽  
Treatment Response ◽  
Residual Disease ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Expression Profiles ◽  
Time Points ◽  
Genetic Subtypes ◽  
B Lineage ◽  
Minimal Residual

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 &gt;50 chromosomes (HD&gt;50) karyotype, 3 BCR-ABL plus HD&gt;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 &lt;45 chromosomes or HD&gt;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.

Effective Targeting Of The P53/MDM2 Axis In Preclinical Models Of Infant MLL-Rearranged Acute Lymphoblastic Leukemia

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 71-71 ◽  
Author(s):  
Richard B Lock ◽  
Jennifer Richmond ◽  
Laura High ◽  
Hernan Carol ◽  
Kathryn Evans ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
Cell Lines ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Expression Profiles ◽  
Wild Type ◽  
Induction Type ◽  
P53 Status

Abstract Introduction While the overall cure rate for the most common pediatric cancer, acute lymphoblastic leukemia (ALL) now approaches 90%, infants (<12 months) diagnosed with ALL harboring translocations in the mixed-lineage leukemia oncogene (infant MLL-ALL) experience shorter remission duration and a significantly reduced likelihood of survival (∼50%). Therefore, new treatments that can be incorporated into conventional chemotherapy regimens to extend patient remission and improve survival are urgently required. Mutations in the p53 tumor suppressor are uncommon in infant MLL-ALL, and drugs that release p53 from inhibitory mechanisms may be of therapeutic benefit. Nutlin cis-imidazole molecules selectively inhibit p53-MDM2 binding, resulting in activation of the p53 pathway in cancer cells leading to cell cycle arrest and apoptosis. The purpose of this study was to assess the efficacy of the orally available nutlin, RG7112, against patient-derived MLL-ALL xenograft models. Methods In vitro cytotoxicity was assessed by mitochondrial metabolic activity assay (Alamar blue) following 48h drug exposures. P53 protein levels and subcellular distribution were assessed by immunoblotting. Patient-derived xenografts were established from infant MLL-ALL, B-cell precursor (BCP)-ALL, or T-lineage ALL (T-ALL) bone marrow or peripheral blood (PB) biopsies in immune-deficient (NOD/SCID or NSG) mice, and their gene expression profiles generated using Illumina Human Ref-12 Expression BeadChips. Engraftment and drug responses were assessed by enumeration of the proportion of human versus mouse CD45+ cells in the PB. Mice with established disease received vehicle, RG7112 (100 mg/kg daily x 5 p.o.), a combination of vincristine (0.15 mg/kg once i.p.) dexamethasone (5 mg/kg daily x 5 i.p.) and L-asparaginase (1,000 IU/kg daily x 5 i.p.) (VXL), or RG7112 plus VXL. Anti-leukemic efficacy was assessed using an objective response measure modeled after the clinical setting, as well as the median event-free survival (EFS) of treated or control groups from treatment initiation. Therapeutic enhancement was considered to occur when the RG7112/VXL combination significantly extended mouse EFS compared with that of both of the RG7112 and VXL treated groups. Results Unsupervised hierarchical clustering of gene expression profiles revealed that the MLL-ALL (n=9), BCP-ALL (n=7) and T-ALL (n=13) xenografts clustered according to leukemia subtype. Moreover, genes previously reported to be overexpressed in MLL-ALL, including MEIS1, CCNA1, and members of the HOXA gene family, were significantly upregulated in MLL-ALL xenografts. The specificity of RG7112 was validated by cytotoxicity assays against leukemia cell lines of known p53 status; p53 wild-type cell lines (RS4;11, IC50 1.4 µM; NALM-6, IC50 3.0 µM) were markedly more sensitive than those with mutant p53 (CEM, IC50 >10 µM; JURKAT, IC50 >10 µM). The in vitro sensitivity of BCP-ALL (n=3) and infant MLL-ALL (n=4) xenografts was consistent with wild-type p53 status, with IC50s of 0.11 - 2.2 µM. Exposure of ALL xenograft cells to nutlin-3 (10 µM, 6h) caused marked p53 up-regulation and nuclear translocation. Since we had previously shown that RG7112 administered as a single agent for 14 days induced significant regressions [Complete Responses (CRs) or greater] in 7/7 infant MLL-ALL xenografts in vivo, we assessed its efficacy in a 5-day combination treatment with an induction-type regimen (VXL) against two infant MLL-ALL xenografts (MLL-5 and MLL-14). The RG7112/VXL combination caused a Partial Response in MLL-5 compared with Progressive Disease for both RG7112 and VXL. The efficacy of RG7112/VXL was even more pronounced against MLL-14, causing a Maintained CR compared with CRs for both RG7112 and VXL, which met the criteria for Therapeutic Enhancement (the median EFS of RG7112/VXL-treated mice, 65.0 days, was significantly greater, P< 0.0001, than that of RG7112, 22.2 days, and VXL, 28.5 days). Conclusions RG7112 induces significant regressions in a high proportion of infant MLL-ALL xenografts and enhances the efficacy of an induction-type regimen. The utility of targeting the p53-MDM2 axis in combination with established drugs for the clinical management of infant MLL-ALL warrants further investigation. This study was supported by NCI NO1CM42216. The authors thank Roche Pharmaceuticals, Inc., for providing RG7112. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Arika Fukushima ◽  
Masahiro Sugimoto ◽  
Satoru Hiwa ◽  
Tomoyuki Hiroyasu
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Response To Therapy ◽  
Hcv Infection ◽  
Entire Treatment Period ◽  
Time Points ◽  
Time Course Data ◽  
Conventional Methods

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.

scholarly journals Transcriptome analysis of gravitational effects on mouse skeletal muscles under microgravity and artificial 1 g onboard environment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Risa Okada ◽  
Shin-ichiro Fujita ◽  
Riku Suzuki ◽  
Takuto Hayashi ◽  
Hirona Tsubouchi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Muscle Mass ◽  
Muscle Atrophy ◽  
Transcriptome Analysis ◽  
Fiber Type ◽  
Expression Profiles ◽  
Space Station ◽  
Gene Expression Profiles

AbstractSpaceflight causes a decrease in skeletal muscle mass and strength. We set two murine experimental groups in orbit for 35 days aboard the International Space Station, under artificial earth-gravity (artificial 1 g; AG) and microgravity (μg; MG), to investigate whether artificial 1 g exposure prevents muscle atrophy at the molecular level. Our main findings indicated that AG onboard environment prevented changes under microgravity in soleus muscle not only in muscle mass and fiber type composition but also in the alteration of gene expression profiles. In particular, transcriptome analysis suggested that AG condition could prevent the alterations of some atrophy-related genes. We further screened novel candidate genes to reveal the muscle atrophy mechanism from these gene expression profiles. We suggest the potential role of Cacng1 in the atrophy of myotubes using in vitro and in vivo gene transductions. This critical project may accelerate the elucidation of muscle atrophy mechanisms.

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