scholarly journals Three Years Follow-Up Study Showed Prenatal Methamphetamine Exposure May Cause Chronic Abnormalities In Transcriptomic Pattern

2021 ◽  
Author(s):  
Arvin Haghighatfard ◽  
Soha Seifollahi ◽  
Pegah Rajabi ◽  
Niloofar Rahmani ◽  
Rojin Ghannadzadeh
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Rna Extraction ◽  
Childbearing Age ◽  
Methamphetamine Use ◽  
Methamphetamine Use Disorder

Abstract Background: The high rate of methamphetamine use disorder among young adults and women of childbearing age makes it imperative to clarify the long-term effects of Methamphetamine exposure on the offspring. Behavioral and cognitive problems had been reported in children with parental Methamphetamine exposure (PME). The present study aimed to assess the acute and chronic effects of PME in molecular regulations and gene expression profiles of children during their first years of life.Methods: All subjects were recruited before birth, and sampling was conducted from the first ten days of birth, twelve months, twenty months, and thirty-six months of age. Finally, 2658 children with PME and 3573 normal children had been finished the follow-up. RNA extraction was operated from blood samples and gene expression profiling was conducted by using the Affymetrix GeneChip Human Genome U133 plus 2.0 Array Platform. Gene expression data were confirmed by Real-time PCR. Results: Gene expression profiling during thirty-six months showed several constant mRNA level alterations in children with PME compared with normal. These genes are involved in several gene ontologies and pathways involved with the immune system, neuronal functions, and bioenergetic metabolism. It seems that Methamphetamine use disorder before and during the pregnancy period may affect the expression profile of children, and these changes could remain years after birth. Affected genes have some similarities with the gene expression patterns of addiction, psychiatric disorders, neurodevelopmental disabilities, and immune deficiencies. Conclusion: Findings may shed light on the molecular effects of prenatal methamphetamine exposure and may lead to new psychological and somatic caring protocols for these children based on their potential abnormalities.

scholarly journals Prenatal Methamphetamine Exposure could Cause Chronic Abnormalities in Transcriptomic Pattern; an Extended Follow-up Cohort Study

2021 ◽  
Author(s):  
Arvin Haghighatfard ◽  
Soha Seifollahi ◽  
Pegah Rajabi ◽  
Niloofar Rahmani ◽  
Rojin Ghannad zadeh
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Rna Extraction ◽  
High Rate ◽  
Childbearing Age ◽  
Methamphetamine Abuse

Abstract BackgroundThe high rate of methamphetamine abuse among young adults and women of childbearing age makes it imperative to clarify the long-term effects of Methamphetamine exposure on the offspring. Behavioral and cognitive problems had reported in children with parental Methamphetamine exposure (PME). The present study aimed to assess the acute and chronic effects of PME in molecular regulations and gene expression profiles of children during their first years of life.ResultsAll subjects were recruited before birth, and sampling was conducted from the first ten days of birth, twelve months, twenty months and thirty-six months of age. Finally, 2658 children with PME and 3573 normal children had been finished the follow-up. RNA extraction was operated from blood samples and gene expression profiling was conducted by using the Affymetrix GeneChip Human Genome U133 plus 2.0 Array Platform. Gene expression data were confirmed by Real-time PCR. Gene expression profiling during thirty-six months showed several constant mRNA level alterations in children with PME compared with normal. These genes are involved in several gene ontology and pathways involved with the immune system, neuronal functions and bioenergetic metabolism. It seems that Methamphetamine abuse before and during the pregnancy period may affect the expression profile of children, and these changes could be remain years after birth. Affected genes have some similarities to the gene expression patterns of addiction, psychiatric disorders, neurodevelopmental disabilities and immune deficiencies. ConclusionFindings may shed light on the molecular effects of prenatal methamphetamine exposure and may lead to new psychological and somatic caring protocols for these children based on their potential abnormalities.

scholarly journals Effects of Storage, RNA Extraction, Genechip Type, and Donor Sex on Gene Expression Profiling of Human Whole Blood

2007 ◽  
Vol 53 (6) ◽  
pp. 1038-1045 ◽  
Author(s):  
Sung Jae Kim ◽  
David J Dix ◽  
Kary E Thompson ◽  
Rachel N Murrell ◽  
Judith E Schmid ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Whole Blood ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Rna Extraction ◽  
Extraction Technique ◽  
Interindividual Differences ◽  
Human Whole Blood ◽  
Rna Quality

Abstract Background: Gene expression profiling of whole blood may be useful for monitoring toxicological exposure and for diagnosis and monitoring of various diseases. Several methods are available that can be used to transport, store, and extract RNA from whole blood, but it is not clear which procedures alter results. In addition, characterization of interindividual and sex-based variation in gene expression is needed to understand sources and extent of variability. Methods: Whole blood was obtained from adult male and female volunteers (n = 42) and stored at various temperatures for various lengths of time. RNA was isolated and RNA quality analyzed. Affymetrix GeneChips (n = 23) were used to characterize gene expression profiles (GEPs) and to determine the effects on GEP of storage conditions, extraction techniques, types of GeneChip, or donor sex. Hierarchical clustering and principal component analysis were used to assess interindividual differences. Regression analysis was used to assess the relative impact of the studied variables. Results: Storage of blood samples for >1 week at 4 °C diminished subsequent RNA quality. Interindividual GEP differences were seen, but larger effects were observed related to RNA extraction technique, GeneChip, and donor sex. The relative importance of the variables was as follows: storage < genechip < extraction technique < donor sex. Conclusion: Sample storage and extraction methods and interindividual differences, particularly donor sex, affect GEP of human whole blood.

scholarly journals Distinct Gene Expression Profiling after Infection of Immature Human Monocyte-Derived Dendritic Cells by the Attenuated Poxvirus Vectors MVA and NYVAC

2007 ◽  
Vol 81 (16) ◽  
pp. 8707-8721 ◽  
Author(s):  
Susana Guerra ◽  
José Luis Nájera ◽  
José Manuel González ◽  
Luis A. López-Fernández ◽  
Nuria Climent ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dendritic Cells ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Human Monocyte ◽  
Type I ◽  
Mrna Levels ◽  
Antigen Uptake

ABSTRACT Although recombinants based on the attenuated poxvirus vectors MVA and NYVAC are currently in clinical trials, the nature of the genes triggered by these vectors in antigen-presenting cells is poorly characterized. Using microarray technology and various analysis conditions, we compared specific changes in gene expression profiling following MVA and NYVAC infection of immature human monocyte-derived dendritic cells (MDDC). Microarray analysis was performed at 6 h postinfection, since these viruses induced extensive cytopathic effects, rRNA breakdown, and apoptosis at late times postinfection. MVA- and NYVAC-infected MDDC shared upregulation of 195 genes compared to uninfected cells: MVA specifically upregulated 359 genes, and NYVAC upregulated 165 genes. Microarray comparison of NYVAC and MVA infection revealed 544 genes with distinct expression patterns after poxvirus infection and 283 genes specifically upregulated after MVA infection. Both vectors upregulated genes for cytokines, cytokine receptors, chemokines, chemokine receptors, and molecules involved in antigen uptake and processing, including major histocompatibility complex genes. mRNA levels for interleukin 12β (IL-12β), beta interferon, and tumor necrosis factor alpha were higher after MVA infection than after NYVAC infection. The expression profiles of transcription factors such as NF-κB/Rel and STAT were regulated similarly by both viruses; in contrast, OASL, MDA5, and IRIG-I expression increased only during MVA infection. Type I interferon, IL-6, and Toll-like receptor pathways were specifically induced after MVA infection. Following MVA or NYVAC infection in MDDC, we found similarities as well as differences between these virus strains in the expression of cellular genes with immunological function, which should have an impact when these vectors are used as recombinant vaccines.

All Clinically Relevant Leukemia Subtypes Can Be Diagnosed and Classified Based Solely on Gene Expression Profiling with an Accuracy of 95.1%: A Study on 1337 Adult Patients.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 143-143
Author(s):  
Torsten Haferlach ◽  
Alexander Kohlmann ◽  
Susanne Schnittger ◽  
Martin Dugas ◽  
Sylvia Merk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Sensitivity And Specificity ◽  
Diagnostic Tool ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Second Step ◽  
Support Vector ◽  
Therapeutic Decisions

Abstract So far, comprehensive diagnosis of leukemia requires a combination of cytomorphology, immunophenotyping, and genetic methods. We aimed at developing a new diagnostic tool based solely on gene expression profiling to accurately predict all clinically relevant subtypes of leukemia in adults and to distinguish these from normal bone marrow. Therefore, we analyzed samples from 1337 untreated patients at diagnosis and healthy donors using oligonucleotide microarrays. The first series of 937 cases was hybridized to HG-U133A+B microarrays (Affymetrix). The following 13 subgroups were included: 620 AML (42 t(15;17); 38 t(8;21); 49 inv(16); 47 t(11q23); 75 complex aberrant karyotype; 193 normal karyotype; 176 other cytogenetic abn.); 152 ALL (26 Pro-B-ALL/t(11q23); 12 ALL-t(8;14); 32 T-ALL; 82 c-ALL/Pre-B-ALL); 75 CML, 45 CLL, and 45 bone marrows from healthy volunteers or non-leukemia pts. (nBM). For each disease entity the top 100 differentially expressed genes were calculated in a one-versus-all (OVA) approach. Class prediction was performed using support vector machines (SVM). Prediction accuracy was estimated by 10-fold cross validation (CV) and assessed for robustness in a resampling approach. 891 of the 937 samples (95.1%) were correctly classified (10-fold CV). A resampling approach with 2/3 training and 1/3 test cohort (100 runs of SVM) confirmed this high accuracy (median, 93.8%). In particular, a median of 100% sensitivity and specificity was achieved for AML with t(15;17), t(8;21), and inv(16), as well as for Pro-B-ALL/t(11q23), and CLL. The median specificity was at least 99.7% in all subgroups except for AML normal/other (median specificity, 93.7%). In a second step T-ALL cases were separated into cortical and immature ones (accuracy, 84.4%) and c-ALL/Pre-B-ALL into cases with and without t(9;22) (accuracy, 82.9%). The second prospective series comprized 400 unselected cases which were hybridized to the new generation HG-U133 Plus 2.0 microarrays (Affymetrix). To validate the diagnostic accuracy of our approach these cases were processed blinded in parallel to routine diagnostic work-up and classified based on the gene expression signatures discovered in the first series described above. Applying a first classification step as described above the 13 different diagnoses were predicted with an accuracy of 94.5%. Failures were mostly due to misclassification into biologically related subgroups, e.g. AML with del(5q) aberrations classified as AML with complex aberrant karyotype. In the second step (separation of the two T-ALL subtypes, and c-ALL/Pre-B-ALL with or without t(9;22)) accuracies of 100% and 70.6% respectively were achieved. In conclusion, we were able to identify within a routine diagnostic workflow distinct expression profiles for all clinically and prognostically relevant adult leukemia subtypes and their discrimination from nBM based only on gene expression data. Accuracy, sensitivity, and specificity were higher than achieved with each of the gold standard techniques alone used today. Thus, gene expression patterns analyzed by microarrays qualify as a diagnostic tool in a routine setting for leukemia diagnosis and classification and may guide relevant therapeutic decisions.

Pharmacogenomic analysis of needle biopsies obtained before preoperative docetaxel/capecitabine/FEC (TX/FEC) chemotherapy for breast cancer

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 10595-10595 ◽  
Author(s):  
F. A. Holmes ◽  
J. A. O’Shaughnessy ◽  
B. Hellerstedt ◽  
J. Pippen ◽  
S. Vukelja ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Rna Extraction ◽  
Tumor Biology ◽  
Pathologic Complete Response ◽  
Research Network ◽  
Community Practice ◽  
Oncology Research

10595 Background: Our goal was to evaluate the feasibility of obtaining fine needle biopsies, for pharmacogenomic analysis, in community based oncology practices and develop gene expression-based predictors of pathologic complete response (pCR) to preoperative sequential docetaxel/capecitabine and 5-fluorouracil, epirubicin, cyclophosphamide chemotherapy. Methods: One hundred seventy-five patients were accrued at 29 sites in the US Oncology Research network. FNA specimens were mailed to a central laboratory (MDACC) and gene expression profiling was performed on Affymetrix U133A chips. Results: RNA extraction was started on 140 specimens, 112 of these (80%) yielded ≥1 μg total RNA, 69 were hybridized and 65 (94%) gene expression profiles have passed quality control as of abstract submission date. The analysis plan is to develop a multigene predictor of pCR from the first 80 cases and test its performance independently in the remaining cases. Conclusions: Collection of mandatory research FNA biopsies for pharmacogenomic research is feasible in community practice. Approximately 80% of biopsies yield sufficient RNA for gene expression profiling. In 20% of patients, either technical factors, which can be addressed, or tumor biology (necrotic, rapidly growing tumors) were limiting. Supported by Roche Laboratories, Inc., Nutley, NJ; Pfizer, New York, NY; and Precision Therapeutics, Pittsburgh, PA. [Table: see text]

Automated Sorting of Monocytes from Whole Blood for Reproducible Gene Expression Profiling.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3840-3840
Author(s):  
Carsten Poggel ◽  
Timo Adams ◽  
Sabine Martin ◽  
Carola Pickel ◽  
Nicole Prahl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Gene Expression Profiling ◽  
Whole Blood ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Specific Gene

Abstract Microarray-based gene expression profiling has been used to develop clinically relevant molecular classifiers for many different diseases. Furthermore, it has been shown for various chronic diseases that specific gene expression patterns are reflected at the level of blood cells. However, blood is a complex tissue comprising numerous cell types. Therefore, the contribution of rare cell types to a whole blood expression profile might not be detected and a substantial proportion of what is usually reported as “up-regulation” or “down-regulation” might actually be the result of a shift in cell populations and not of a true regulatory process. In order to circumvent these problems, several techniques have been established to analyze purified subpopulations rather than whole blood samples. Previously, it has been shown, for example, that reproducible gene expression profiles can be generated by positive selection of blood cell subsets from PBMCs1. As the preparation of PBMCs by, for example, Ficoll is time-consuming, inconvenient, and not amenable to automation, we have set up a combined direct whole blood cell separation and gene expression profiling protocol. By using Whole Blood CD14 MicroBeads in combination with the autoMACS Pro™ Separator, the separation protocol generally allowed enrichment of monocytes from whole blood within 30 min with purities higher than 90%. In combination with the depletion of neutrophils, the major source of contaminating RNA, purities increased to over 95% for all tested blood donors. Monocytes included the CD14bright/CD16− as well as the CD14dim/CD16+ populations. To assess the reproducibility of gene expression profiles and the influence of several experimental parameters, monocytes were sorted from 5 ml whole blood. RNA was extracted and hybridized to microarrays and the Pearson correlation coefficients of pairwise comparisons were calculated. Technical repeats of monocyte analysis from blood donated at different days showed a higher correlation coefficient than whole blood RNA. Blood storage at room temperature resulted in a strong deregulation of many genes, whereas blood stored at 4°C showed minimal changes, which is in agreement with previous studies. Skipping the centrifugation step, which is used to remove unbound MicroBeads did not alter the gene expression profiles. Incubation of sorted cells in PrepProtect™ Stabilization Buffer showed no alteration of gene expression thus enabling the shipping of cells without liquid nitrogen. Monocytes play a crucial role in diseases like atherosclerosis. Our rapid and simple protocol for combined direct cell sorting from whole blood and gene expression profiling of monocytes might help to ease the discovery of new biomarkers and to screen and monitor patients. 1 Lyons et al., BMC Genomics (2007), 8:64.

scholarly journals 256CONSTRUCTION OF A BOVINE CDNA ARRAY TO MONITOR GENE EXPRESSION PROFILES IN BOVINE PREIMPLANTATION EMBRYOS

2004 ◽  
Vol 16 (2) ◽  
pp. 248
Author(s):  
C. Wrenzycki ◽  
T. Brambrink ◽  
D. Herrmann ◽  
J.W. Carnwath ◽  
H. Niemann
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Cdna Array ◽  
Preimplantation Embryos ◽  
Average Insert Size ◽  
Rt Pcr ◽  
Public Data

Array technology is a widely used tool for gene expression profiling, providing the possibility to monitor expression levels of an unlimited number of genes in various biological systems including preimplantation embryos. The objective of the present study was to develop and validate a bovine cDNA array and to compare expression profiles of embryos derived from different origins. A bovine blastocyst cDNA library was generated. Poly(A+)RNA was extracted from in vitro-produced embryos using a Dynabead mRNA purification kit. First-strand synthesis was performed with SacIT21 primer followed by randomly primed second-strand synthesis with a DOP primer mix (Roche) and a global PCR with 35 cycles using SacIT21 and DOP primers. Complementary DNA fragments from 300 to 1500bp were extracted from the gel and normalized via reassoziation and hydroxyapatite chromatography. Resulting cDNAs were digested with SacI and XhoI, ligated into a pBKs vector, and transfected into competent bacteria (Stratagene). After blue/white colony selection, plasmids were extracted and the inserts were subjected to PCR using vector specific primers. Average insert size was determined by size idenfication on agarose gels stained with ethidium bromide. After purification via precipitation and denaturation, 192 cDNA probes were double-spotted onto a nylon membrane and bound to the membrane by UV cross linking. Amplified RNA (aRNA) probes from pools of three or single blastocysts were generated as described recently (Brambrink et al., 2002 BioTechniques, 33, 3–9) and hybridized to the membranes. Expression profiles of in vitro-produced blastocysts cultured in either SOF plus BSA or TCM plus serum were compared with those of diploid parthenogenetic ones generated by chemical activation. Thirty-three probes have been sequenced and, after comparison with public data bases, 26 were identified as cDNAs or genes. Twelve out of 192 (6%) seem to be differentially expressed within the three groups;; 7/12 (58%) were down-regulated, 3/12 (25%) were up-regulated in SOF-derived embryos, and 2/12 (20%) were up-regulated in parthenogenetic blastocysts compared to their in vitro-generated counterparts. Three of these genes involved in calcium signaling (calmodulin, calreticulin) and regulation of actin cytoskeleton (destrin) were validated by semi-quantitative RT-PCR (Wrenzycki et al., 2001 Biol. Reprod. 65, 309–317) employing poly(A+) RNA from a single blastocyst as starting material. No differences were detected in the relative abundance of the analysed gene transcripts within the different groups. These findings were confirmed employing the aRNA used for hybridization in RT-PCR and showed a good representativity of the selected transcripts. Results indicate that it is possible to construct a homologous cDNA array which could be used for gene expression profiling of bovine preimplantation embryos. Supported by the Deutsche Forschungsgemeinschaft (DFG Ni 256/18-1).

scholarly journals Effectiveness of Gene Expression Profiling for Response Prediction of Rectal Adenocarcinomas to Preoperative Chemoradiotherapy

2005 ◽  
Vol 23 (9) ◽  
pp. 1826-1838 ◽  
Author(s):  
B. Michael Ghadimi ◽  
Marian Grade ◽  
Michael J. Difilippantonio ◽  
Sudhir Varma ◽  
Richard Simon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Response Prediction ◽  
Preoperative Chemoradiotherapy ◽  
Response To Therapy ◽  
Phase Iii ◽  
Correct Prediction

Purpose There is a wide spectrum of tumor responsiveness of rectal adenocarcinomas to preoperative chemoradiotherapy ranging from complete response to complete resistance. This study aimed to investigate whether parallel gene expression profiling of the primary tumor can contribute to stratification of patients into groups of responders or nonresponders. Patients and Methods Pretherapeutic biopsies from 30 locally advanced rectal carcinomas were analyzed for gene expression signatures using microarrays. All patients were participants of a phase III clinical trial (CAO/ARO/AIO-94, German Rectal Cancer Trial) and were randomized to receive a preoperative combined-modality therapy including fluorouracil and radiation. Class comparison was used to identify a set of genes that were differentially expressed between responders and nonresponders as measured by T level downsizing and histopathologic tumor regression grading. Results In an initial set of 23 patients, responders and nonresponders showed significantly different expression levels for 54 genes (P < .001). The ability to predict response to therapy using gene expression profiles was rigorously evaluated using leave-one-out cross-validation. Tumor behavior was correctly predicted in 83% of patients (P = .02). Sensitivity (correct prediction of response) was 78%, and specificity (correct prediction of nonresponse) was 86%, with a positive and negative predictive value of 78% and 86%, respectively. Conclusion Our results suggest that pretherapeutic gene expression profiling may assist in response prediction of rectal adenocarcinomas to preoperative chemoradiotherapy. The implementation of gene expression profiles for treatment stratification and clinical management of cancer patients requires validation in large, independent studies, which are now warranted.

Gene Expression Profiling Reveals Fundamental Differences between Leukemic Stem Cells (Lin-CD34+CD38−) and Mature Blasts (Lin−CD34+CD38+) of Acute Myeloid Leukaemia (AML) Patients.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 1377-1377
Author(s):  
Kazem Zibara ◽  
Daniel Pearce ◽  
David Taussig ◽  
Spyros Skoulakis ◽  
Simon Tomlinson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Populations ◽  
Leukemic Stem Cells ◽  
Significant Differential Expression ◽  
New Genes

Abstract The identification of LSC has important implications for future research as well as for the development of novel therapies. The phenotypic description of LSC now enables their purification and should facilitate the identification of genes that are preferentially expressed in these cells compared to normal HSC. However, gene-expression profiling is usually conducted on mononuclear cells of AML patients from either peripheral blood and/or bone marrow. These samples contain a mixture of blasts cells, normal hematopoietic cells and limited number of leukemic stem cells. Thus, this results in a composite profile that obscure differences between LSC and blasts cells with low proliferative potential. The aim of this study was to compare the gene expression profile of highly purified LSC versus leukemic blasts in order to identify genes that might have important roles in driving the leukemia. For this purpose, we analyzed the gene expression profiles of highly purified LSCs (Lin−CD34+CD38−) and more mature blast cells (Lin−CD34+CD38+) isolated from 7 adult AML patients. All samples were previously tested for the ability of the Lin−CD34+CD38− cells but not the Lin−CD34+CD38+ fraction to engraft using the non-obese diabetic/severe combined immuno-deficiency (NOD-SCID) repopulation assay. Affymetrix microarrays (U133A chip), containing 22,283 genes, were used for the analysis. Comparison of Lin-CD34+CD38- cell population to the Lin−CD34+CD38+ cell fraction showed 5421 genes to be expressed in both fractions. Comparative analysis of gene-expression profiles showed statistically significant differential expression of 133 genes between the 2 cell populations. Most of the genes were downregulated in the LSC-enriched fraction, compared to the more differentiated fraction. Gene ontology was used to determine the categories of the up-regulated transcripts. These transcripts, which are selectively expressed, include a number of known genes (e.g., receptors, signalling genes, proliferation and cell cycle genes and transcription factors). These genes play important roles in differentiation, self-renewal, migration and adhesion of HSCs. Among the genes showing the highest differences in expression levels were the following: ribonucleotide reductase M2 polypeptide, thymidylate synthetase, ZW10 interactor, cathepsin G, azurocidin 1, topoisomerase II, CDC20, nucleolar and spindle associated protein 1, Rac GTPase activating protein 1, leukocyte immunoglobulin-like receptor, proliferating cell nuclear antigen, myeloperoxidase, cyclin A1 (RRM2, TYMS, ZWINT, CTSG, AZU1, TOP2A, CDC20, NUSAP1, RACGAP1, LILRB2, PCNA, MPO, CCNA1). Some transcripts detected have not been implicated in HSC functions, and others have unknown function so far. This work identifies new genes that might play a role in leukemogenesis and cancer stem cells. It also leads to a better description and understanding of the molecular phenotypes of these 2 cell populations. Hence, in addition to being a more efficient way to further understand the biology of LSC, this should also provide a more efficient way of identifying new therapeutics and diagnostic targets.

Gene Expression Profiling of Paired Pre- and Post-Prednisolone (PRED) BM Samples from Childhood ALL Identifies Robust Signatures for PRED Response and Eventual Outcome.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 222-222 ◽  
Author(s):  
Yi Lu ◽  
Huiqing Liu ◽  
Ying Xu ◽  
Pei Lin Koh ◽  
Ariffin Hany ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Response To Therapy ◽  
Test Set ◽  
Childhood All ◽  
Blast Count ◽  
Highly Correlated ◽  
Eventual Outcome

Abstract Early response to therapy is the most important prognostic factor for childhood ALL. CCG investigators have shown that Day-7 and Day-14 BM blast counts were prognostically important although there is great inter-observer variability. BFM group have shown that day 8 prednisolone (PRED) response is highly predictive of the treatment outcome. While gene expression profiling (GEP) of diagnostic marrow can discern a pattern of PRED sensitivity as determined by in vitro MTT assay, the accuracy was low at only 70%. We hypothesized that changes in global GEP after therapy have a higher likelihood to predict response as the signatures of sensitivity and resistance may be unmasked during the therapy. We prospectively studied the changes in GEP using Affymetrix HG-U133A or Plus 2 chips on paired BM samples before and after 7-day course of PRED and one dose IT MTX in 58 patients with newly diagnosed or relapsed ALL. Unsupervised hierarchical clustering revealed that pre- and post- PRED samples in the patients still tended to cluster together, indicating that expression profiles of molecular subgroups were still most important. To remove intrinsic influence of molecular subtypes and identify potential signatures independent of genetic abnormalities, we subtracted Day-0 GEP from its paired Day-8 profile and retained probe sets with significant changes (≥ 10-fold). To avoid the ambiguity of variation in BM blast counting at Day-8, we divided the samples into a stringently reproducible group where “Good” PRED response was defined as that Day-8 blast count in PBL < 109/L and BM lymphoblasts ≤ 30% (n=16). “Poor” response was when Day 8 PBL ≥ 109/L (n=11). This stringently reproducible group (n=27) formed the training group to help define a distinct signature while the rest (n=31 pairs) were used as a blinded test set. 54 and 19 discriminating genes were identified by 2 independent statistical methods respectively, and an integrated predictor model was constructed based on shortlisted entries. This model predicted the PRED response with 100% accuracy for the training set using the leave-one-out cross validation but was less accurate in predicting the BM blast count in blinded test set. But intriguingly, in the blinded test set, this model predicted correctly 19 out of 21 reliable “Good” PRED responses are in CCR (91%), while among 8 predicted as “Poor” responses, only 2 are in CCR (25%). This suggests that as gene expression profiling as early as day 8 of PRED could discern the beginning of leukaemia cell death even before morphological changes are discernable and is highly correlated to eventual outcome. In conclusion, we have shown that analyses on the relative changes of gene expression profile can identify real genetic signatures indicating the sensitivity to PRED administration which is highly correlated with outcome.

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