Gene Expression Profiling Reveals Genes Predictive of Outcome In Infant Acute Lymphoblastic Leukemia (ALL) and Distinctive Age-Related Gene Expression Profiles ( 90 Days): A Children's Oncology Group Study

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 412-412
Author(s):  
Huining Kang ◽  
Carla S. Wilson ◽  
Richard C. Harvey ◽  
I-Ming Chen ◽  
Maurice H. Murphy ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Event Free Survival ◽  
Patient Age ◽  
Free Survival ◽  
Entire Cohort ◽  
Patient Âgé

Abstract Abstract 412 ALL arising in infants is a highly refractory disease. Overall event-free survival (EFS) remains poor and infants with MLL rearrangements (MLL-R) or those <90 days of age are known to have particularly poor outcomes. To identify genes predictive of event-free survival (EFS) that might serve as new diagnostic and therapeutic targets, we completed gene expression profiling (Affymetrix HG_U133Plus2) in 97 infant ALL cases registered to COG Clinical Trial P9407. Of these 97 infants, 78 were most recently uniformly treated on P9407 cohort 3. In the 97 cases, median age at diagnosis was 166 days (range 1–365) and increased age at diagnosis was significantly associated with improved EFS (P = 0.001). 89/97 infants had MLL-R, of which 49 had an AF4 partner gene (MLL-AF4 (AFF1)). Infants <90 days of age (P=.0001) and those with MLL-R (MLL-AF4, MLL-ENL (MLLT1), MLL-Other) had a significantly decreased EFS, while infants with MLL-AF9 (MLLT3) or cases lacking MLL-R had a significantly better EFS (P=0.014). From modeling expression profiles and multivariate analyses, a number of genes were identified that had a significant effect on EFS and were independent of patient age or MLL-R status, including: TACC2 and IRX2 (from modeling the entire cohort of 97 cases); RORA, IGJ, ZEB1, YES1 (cohort 3 modeled alone); and IRX1, IRX2, ST3GAL6, HLA-DQB1, STAB1, NEGR1, IRX5 (MLL-AF4 cases modeled alone). The significant effect of MEIS1 and KCNK12 expression on EFS was lost after consideration of MLL-R status, while the significance of many genes (particularly in the HOXA family) was not independent of patient age in multivariate analyses. Assessment of the expression levels of two genes alone at diagnosis: TACC2 and IRX2 in the entire cohort of 97 cases (P<0.0001; Fig. A), or, NEGRI and IRX2 in the MLL-AF4 cases (P<0.0001; Fig. B), were highly predictive of outcome on current treatment regimens. Distinctive and strikingly different gene expression profiles were also seen in infant ALL cases <90 days of age vs. >90 days of age (in the overall cohort and in the MLL-AF4 cases). Specifically evaluating the impact of patient age treated as a continuous variable revealed a striking transition in expression profiles at 90 days with a differential expression pattern involving many genes encoding histone-related, heat shock family, or immune response regulators (including HLA-DRB4, IL1R2, HSPA1A///1B). These distinctive profiles may reflect different transformed stem/precursor cells or susceptibilities to leukemic transformation at different patient ages, altered marrow microenvironments, or altered immune status; high expression of the heat shock proteins in particular among the youngest infants may reflect a more limited immune surveillance capacity. Given the rarity of infant ALL, this study represents one of the largest uniformly treated groups of infant leukemia to undergo gene expression profiling. In these studies we have identified genes that are highly predictive of outcome at diagnosis, in all infant ALL and in MLL-AF4 cases. Further analysis of these expression profiles, coupled with validation studies in other infant ALL cohorts, may allow for the identification of novel therapeutic targets among the genes discovered herein and ultimately for the development of more effective therapies. Disclosures: Felix: None: Patent not licensed.

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.

Rotator Cuff Tear Size Regulates Fibroadipogenic Progenitor Number and Gene Expression Profile in the Supraspinatus Independent of Patient Age

2021 ◽  
pp. 036354652110545
Author(s):  
Michael R. Davies ◽  
Hannah Chi ◽  
Gurbani Kaur ◽  
Mengyao Liu ◽  
C. Benjamin Ma ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rotator Cuff ◽  
Rotator Cuff Tear ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Patient Age ◽  
Cuff Tear ◽  
Patient Âgé ◽  
Beige Adipocytes ◽  
Tear Size

Background: Fatty infiltration of rotator cuff muscle is a limiting factor in the success of repairs. Fibroadipogenic progenitors (FAPs) are a population of stem cells within the rotator cuff that can differentiate into white adipocytes, fibroblasts, and beige adipocytes. The effects of patient age and rotator cuff tendon tear size on the number, differentiation patterns, and gene expression profiles of FAPs have not yet been analyzed. Purpose: To determine if patient age and rotator cuff tear size independently regulate FAP number, differentiation patterns, and gene expression profiles. Study Design: Controlled laboratory study. Methods: Supraspinatus muscle samples were collected from 26 patients between the ages of 42 and 76 years with partial- or full-thickness rotator cuff tears. FAPs were quantified using fluorescence-activated cell sorting. Gene expression analysis was performed across a custom 96-gene panel using NanoString. In vitro differentiation assays of FAPs were conducted using adipogenic, fibrogenic, and beige-inducing (amibegron-treated) media, and quantitative polymerase chain reaction was used to assess gene expression differences between adipogenic and amibegron media conditions. Multivariable linear regressions were performed using Stata to independently analyze the effects of age and rotator cuff tear size on FAP number, differentiation, and gene expression. Results: Increasing age and tear size were independently correlated with increased FAP number (βage = 0.21, P = .03; βtear size = 3.86, P = .05). There was no clear association between age and gene expression of freshly sorted FAPs. Under adipogenic and fibrogenic media conditions, increasing age and tear size were independently associated with increased adipogenic and fibrogenic differentiation of FAPs. Under amibegron treatment conditions, age positively correlated with increased beige differentiation (β = 1.03; P < .0001), while increasing tear size showed a trend toward decreased beige differentiation (β = −4.87; P = .1). When gene expression patterns between adipogenic and amibegron media conditions were compared, larger tear size strongly inhibited beige gene expression, while advanced age did not. Conclusion: Patient age and rotator cuff tear size independently regulated FAP number, differentiation, and gene expression. Age and tear size were positively correlated with increased FAP number and fibrogenic/adipogenic differentiation. Advancing patient age did not limit FAP beige differentiation and gene expression, while increasing rotator cuff tear size strongly inhibited these processes.

A New Molecular Classification of Multiple Myeloma Using Gene Expression Profiling and Fluorescence In Situ Hybridisation as Predictor for Event Free Survival.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 73-73 ◽  
Author(s):  
Dirk Hose ◽  
Jean-Francois Rossi ◽  
Carina Ittrich ◽  
John deVos ◽  
Axel Benner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Molecular Classification ◽  
Differentially Expressed ◽  
Event Free Survival ◽  
Free Survival ◽  
Cytogenetic Aberrations

Abstract AIM was to establish a new molecular classification of Multiple Myeloma (MM) based on changes in global gene expression attributable to cytogenetic aberrations detected by interphase FISH (iFISH) in order to (i) predict event free survival (EFS) and (ii) investigate differentially expressed genes as basis for a group specific and risk adapted therapy. PATIENTS AND METHODS. Bone marrow aspirates of 105 newly diagnosed MM-patients (65 trial (TG) / 40 independent validation group (VG)) and 7 normal donors (ND) were CD138-purified by magnetic activated cell sorting. RNA was in-vitro transcribed and hybridised to Affymetrix HG U133 A+B GeneChip (TG) and HG U133 2.0 plus arrays (VG). CCND1 and CCND2 expression was verified by real time RT-PCR. iFISH was performed on purified MM-cells using probes for chromosomes 11q23, 11q13, 13q14, 17p13 and the IgH-translocations t(4;14) and t(11;14). Expression data were normalised (Bioconductor package gcrma) and nearest shrunken centroids (NSC) applied to calculate and cross validate a predictor on 40 patients of the TG with a comprehensive iFISH panel available combined with CCND overexpression. Differentially expressed genes were identified using empirical Bayes statistics for pairwise comparison. RESULTS. Overexpression of a D-type cyclin (D1 or D2) was found in 61/65 patients with MM compared to ND. CCND3 overexpression only appeared concomitantly with CCND2 overexpression. Four groups could be distinguished: (1.1) CCND1 (11q13) overexpression and trisomy 11q13, (1.2) CCND1 overexpression and translocations involving 11q13 i.e. t(11;14), (2.1) CCND2 overexpression without 11q13+, t(11;14), t(4;14), (2.2) CCND2 overexpression with t(4;14) and FGFR3 upregulation. A predictor of 6 to 566 genes correctly classifies all 40 patients of the TG (estimated cross validated error rate 0%). An independent VG of 40 patients was used. Genes with highest scores in NSC are: (1.1) CCND1, ribosomal proteins (e.g. RPL 28, 29), GPX1, CCRL2, (1.2) CCND1, TGIF, and NCAM (non-overexpression), (2.1) CCND2, (2.2) FGFR3, WHSC1, CCND2, IRTA2, SELL, and MAGED4. Distribution of clinical parameters (i.e. β2M, Durie Salmon stages, ISS) was not significantly different between the groups. The distribution of del(13)(q14q14) was (1.1) 31.5%, (1.2) 37.5%, (2.1) 37.5% and (2.2) 100%. (p<0.01). I.e. HGF, DKK1, VCAM, CD163 are differentially expressed between all 4 groups and ND (adjusted p<0.001). The groups defined by the predictor show a significantly different EFS after autologous stem cell transplantation according to the GMMG-HD3 protocol (median: (1.1) 18 / (1.2) not reached (no event) / (2.1) 22 / (2.2) 6 months; log-rank-test: p=0.004). CONCLUSION. CCND1 or CCND2 overexpression is nearly ubiquitous in MM and attributable to defined cytogenetic aberrations. Gene expression and iFISH allow a molecular classification of MM which can be predicted by gene expression profiling alone. Groups in the classification show a distinctive pattern in gene expression as well as a different EFS interpretable as risk stratification and indicator of therapeutic targets.

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.

Ninety Percent Sustained Complete Response (CR) Rate Projected 4 Years after Onset of CR in Gene Expression Profiling (GEP)-Defined Low-Risk Multiple Myeloma (MM) Treated with Total Therapy 3 (TT3): Basis for GEP-Risk-Adapted TT4 and TT5

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 162-162 ◽  
Author(s):  
Bart Barlogie ◽  
Elias J. Anaissie ◽  
John D. Shaughnessy ◽  
Frits van Rhee ◽  
Mauricio Pineda-Roman ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Complete Response ◽  
Low Risk ◽  
Event Free Survival ◽  
Free Survival ◽  
Response Onset ◽  
Dose Dense

Abstract We have previously reported on the remarkable activity of the TT3 program that incorporated both bortezomib (V) and thalidomide (T) into the up-front management of 303 patients. TT3 consisted of 2 cycles each of induction prior to and of dose-reduced consolidation therapy with VTD-PACE (cisplatin, doxorubicin, cyclophosphamide, etoposide) after melphalan 200mg/m2 (M200)-based tandem transplants, followed by maintenance therapy for 3 years with VTD and, in later stages, VRD (substituting T for lenalidomide, R). Characteristics included a median age of 59yr (range, 33–75yr), B2M &gt;=4mg/L in 37%, albumin &lt;3.5g/dL in 26%, ISS stages II and III in 33% and 21%, cytogenetic abnormalities (CA) in 33% and gene expression profiling (GEP)-defined high-risk MM in 15% of the 275 patients with such data. With a median follow-up of 39 months, 4-yr overall survival (OS) and event-free survival (EFS) estimates were 78% and 71%, respectively, including 84% and 77% among the 85% with GEP-defined low-risk MM contrasting with 43% and 33% in the remainder with high-risk MM (both p&lt;0.0001). Near-CR and CR, attained in 86% and 63%, were sustained at 4 years from response onset in 78% and 87%, which pertained to 83% and 90% with low-risk MM but to only 44% and 57% with high-risk MM (all p &lt;0.0001). These results were corroborated in a TT3 extension trial (TT3E) that enrolled 175 additional patients, comprising higher proportions of CA (42%) and GEP-defined high-risk MM (21%). Two-year estimates of OS and EFS are 85% and 85%, with 94% and 92% in low-risk patients versus 61% and 62% in high-risk MM (p=0.0001, p=0.0003); the 2-yr estimate of remaining in CR is 93% including 100% in low-risk and 77% in high-risk MM (p=0.01). Multivariate analysis of features linked to OS in TT3 included GEP-defined high-risk, CA, B2M and LDH elevation, collectively accounting for 41% of outcome variability by R2 statistics; the corresponding R2 values for EFS and n-CR duration were 38% and 39%. Compared to the predecessor trial, TT2, that evaluated the role of T in a randomized trial design in 668 patients, TT3 data were superior for OS (p=0.08), EFS (&lt;0.0001), n-CR duration (p&lt;0.0001) and CR duration (p=0.0002). In the low-risk subgroup, EFS (p=0.0001), n-CR duration (p&lt;0.0001) and CR duration (Figure 1a; p=0.0002) all were superior in TT3 versus TT2; whereas, in the high-risk MM group, outcomes remained poor also with TT3 despite superior EFS (Figure 1b; p=0.03). Based on these data, we have now started a GEP-risk-based algorithm of assigning separate therapies to good-risk (TT4) and poor-risk MM (TT5). As the TT3 results for low-risk are difficult to improve upon, TT4 randomizes patients between standard TT3 and TT3-LITE that employs only 1 cycle each of induction and consolidation (with anticipated further improvement in compliance) and 4-day-fractionated M50×4 to enable the addition of VTD and thus exploit synergistic drug interactions to occur. In order to sustain tolerable effective therapies for at least 3 years and prevent recurrence from previous drug-free or insufficiently effective phases in TT3, TT5 for high-risk MM employs less dose-intense and more dose-dense highly synergistic combination therapy, utilizing M10-VTD-PACE for induction, M80 (in 4 daily fractions of M20) plus VRD-PACE tandem transplants, separated by 2 cycles of M20 (in 4 daily fractions of M5) plus VTD-PACE, and followed by 2 years of monthly alternating R-VD and M-VD. Figure 1a: Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1a:. Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1b: Superior event-free survival with TT3 v TT2 in GEP-high-risk MM: Figure 1b:. Superior event-free survival with TT3 v TT2 in GEP-high-risk MM:

scholarly journals Gene expression profiling of the Notch-AhR-IL22 axis at homeostasis and in response to tissue injury

2017 ◽  
Vol 37 (6) ◽  
Author(s):  
Marc Weidenbusch ◽  
Severin Rodler ◽  
Shangqing Song ◽  
Simone Romoli ◽  
Julian A. Marschner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Tissue Injury ◽  
Expression Profiles ◽  
Notch Pathway ◽  
Gene Expression Profiles ◽  
Sterile Inflammation ◽  
Specific Gene ◽  
Specific Gene Expression

Notch and interleukin-22 (IL-22) signaling are known to regulate tissue homeostasis and respond to injury in humans and mice, and the induction of endogenous aryl hydrocarbon receptor (Ahr) ligands through Notch links the two pathways in a hierarchical fashion. However in adults, the species-, organ- and injury-specific gene expression of the Notch-AhR-IL22 axis components is unknown. We therefore performed gene expression profiling of DLL1, DLL3, DLL4, DLK1, DLK2, JAG1, JAG2, Notch1, Notch2, Notch3, Notch4, ADAM17/TNF-α ADAM metalloprotease converting enzyme (TACE), PSEN1, basigin (BSG)/CD147, RBP-J, HES1, HES5, HEY1, HEYL, AHR, ARNT, ARNT2, CYP1A1, CYP24A1, IL-22, IL22RA1, IL22RA2, IL10RB, and STAT3 under homeostatic conditions in ten mature murine and human organs. Additionally, the expression of these genes was assessed in murine models of acute sterile inflammation and progressive fibrosis. We show that there are organ-specific gene expression profiles of the Notch-AhR-IL22 axis in humans and mice. Although there is an overall interspecies congruency, specific differences between human and murine expression signatures do exist. In murine tissues with AHR/ARNT expression CYP1A1 and IL-22 were correlated with HES5 and HEYL expression, while in human tissues no such correlation was found. Notch and AhR signaling are involved in renal inflammation and fibrosis with specific gene expression changes in each model. Despite the presence of all Notch pathway molecules in the kidney and a model-specific induction of Notch ligands, IL-22 was only up-regulated in acute inflammation, but rapidly down-regulated during regeneration. This implies that for targeting injury responses, e.g. via IL-22, species-specific differences, injury type and time points have to be considered.

Cancer/Testis Genes in Multiple Myeloma: Expression Patterns and Vaccination Strategies Determined by Microarray Analysis.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 3401-3401
Author(s):  
Maud Condomines ◽  
Dirk Hose ◽  
Thierry Reme ◽  
Michael Hundemer ◽  
John De Vos ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Tumor Escape ◽  
Event Free Survival ◽  
Chromosome X ◽  
Free Survival ◽  
Ct Antigens ◽  
Cancer Testis

Abstract Cancer-testis (CT) antigens are expressed in testis and malignant tumors, but rarely in non-gametogenic tissues. Due to this pattern, they represent attractive targets for cancer vaccination approaches. The aims of the present study were (1) to assess for the first time the expression of CT genes on a pangenomic basis in multiple myeloma (MM), (2) to provide selection strategies of CT antigens for clinical vaccination trials and (3) to assess the impact of CT gene expression on event-free survival. We report here the expression pattern of CT genes in purified MM cells (MMC) of 64 patients with newly-diagnosed MM, 12 patients with monoclonal gammopathy of unknown significance (MGUS), in normal plasma cell and B cell samples and in 20 MMC lines, using gene expression profiling (GEP). Out of 46 CT genes interrogated by the Affymetrix HG U133 Set arrays, 35 were expressed in MMC of at least one patient, according to the Affymetrix “present” call (frequency range: 2% – 66%). Of these, 24 CT genes were expressed in more than 5% of the MMC samples and 25 are located on chromosome X. MMC of 98% of the patients expressed at least one CT gene, 86% at least two, and 70% at least three CT genes. By using a set of 10 CT genes including KM-HN-1, MAGE-C1, MAGE-A3/6/12, MAGE-A5, MORC, DDX43, SPACA3, SSX-4, GAGE-1–8 and MAGE-C2, a combination of at least three CT genes - desirable to circumvent tumor escape mechanisms and immune tolerance - could be obtained in MMC of 67% of the patients. Thus, gene expression profiling can be used to select CT antigens as vaccination targets in individual patients. In a series of MMC from 111 patients treated with the same high-dose chemotherapy and autologous peripheral blood stem cell transplantation protocol and having a median two-year follow-up, we found that the expression of six CT genes, i.e. CTAG-1B, CTAG-2, MAGE-A1, MAGE-A2, MAGE-A3 and MAGE-A6 was associated with a shorter event-free survival (EFS). Furthermore, considering only the 25 CT genes encoded by chromosome X, a CT-Xhigh cluster comprising MMC of one third of the patients (35 of 111) could be defined using a binary hierarchical clustering based on Affymetrix call. Patients in the CT-Xhigh cluster had a shorter EFS (median 13 months) compared to patients in the CT-Xlow cluster (median 18 months, P = .003). The CT-Xhigh clsuter included more patients with a stage III disease (P = .004). These results confirm data from previous studies indicating that patients expressing some CT genes located on chromosome X have a poor outcome.

scholarly journals Prediction of cytogenetic abnormalities with gene expression profiles

Blood ◽  
2012 ◽  
Vol 119 (21) ◽  
pp. e148-e150 ◽  
Author(s):  
Yiming Zhou ◽  
Qing Zhang ◽  
Owen Stephens ◽  
Christoph J. Heuck ◽  
Erming Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Parameters ◽  
Proof Of Concept ◽  
Accuracy Rate ◽  
Cytogenetic Abnormalities

Abstract Cytogenetic abnormalities are important clinical parameters in various types of cancer, including multiple myeloma. We developed a model to predict cytogenetic abnormalities in patients with multiple myeloma using gene expression profiling and validated it by different cytogenetic techniques. The model has an accuracy rate up to 0.89. These results provide proof of concept for the hypothesis that gene expression profiling is a superior genomic method for clinical molecular diagnosis and/or prognosis.

Infant Acute Lymphoblastic Leukemias Are Pan-Sensitive to Obatoclax Across molecular/Cytogenetic Subtypes, Especially MLL-ENL, and gene Expression Profiles Determine Obatoclax IC50: A Report on the Children's Oncology Group (COG) P9407 Trial

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2757-2757 ◽  
Author(s):  
Karen A. Urtishak ◽  
Li-San Wang ◽  
Richard Harvey ◽  
Susan R Atlas ◽  
I-Ming L. Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Single Agent ◽  
Gene Expression Profiles ◽  
Poor Survival ◽  
Molecular Cytogenetic ◽  
Ic50 Values ◽  
Mtt Assays

Abstract Abstract 2757 Introduction: The outcome of infants with acute lymphoblastic leukemia (ALL) remains poor because of the association of frequently occurring MLL translocations with drug resistance and vulnerability of the very young to treatment complications. The two most common MLL partner genes in infant ALL, AF4 (AFF1) and ENL (MLLT1), are associated with particularly poor survival. Better therapies are urgent. One candidate is obatoclax (GeminX Biotechnologies, Inc.), which targets interactions of pan-anti-apoptotic BCL-2 family proteins with BH3 proteins and is now in a Phase I trial for relapsed/refractory pediatric cancers (COG ADVL0816). Previously we showed potent single agent in vitro activity of obatoclax against MLL-rearranged infant ALL (Zhang ASH 2008). Here we evaluate correlations of obatoclax activity with MLL translocation status and gene expression profiles in a large number of cases of infant ALL to define molecular determinants of sensitivity. Methods: Bone marrow, peripheral blood or apheresis samples from the time of diagnosis in 54 infants (age 1–365 d, median 168 d; WBC count 15–1230×103/μL, median 445×103/μL) with ALL (n=52) or bilineal acute leukemia (n=2) were examined, 48 of which were from the COG P9407 trial. By molecular/cytogenetic classification, the cases were MLL-AF4+ (n= 28), MLL-ENL+ (n= 11), other MLL rearrangement positive (other MLL+) (n= 8) or MLL germline (MLL-) (n= 7). Single agent IC50 values from MTT assays after 72 h obatoclax exposures were determined in all cases (including 13 previously tested; Zhang ASH 2008) by plotting the surviving fractions. IC50s in the MLL-AF4+ group were compared to those in each of the other 3 molecular/cytogenetic groups by Wilcoxon's test. Gene expression profiling was performed on Affymetrix HG_U133 Plus2.0 arrays in 47 of the 48 COG P9407 cases. Spearman test was used to identify correlation between log2 expression levels for each probeset and IC50 values across subjects. A heatmap of significant probesets (p≤0.001) was generated by transforming expression levels to z-scores and ordering rows and columns by complete linkage hierarchical clustering. Ingenuity pathway analysis was applied to all probesets with p≤0.01 to identify pathways significantly correlated with IC50. Additional MTT assays were initiated to test sensitivity to agents targeting these pathways. Results: Even though most cases in all 4 groups were sensitive to obatoclax as indicated by IC50s within a clinically achievable range, MLL translocation status still had a significant effect on IC50. MLL-AF4+ cases were least sensitive and MLL-ENL+ cases were most sensitive to obatoclax. Respective IC50 ranges across all 54 cases were: MLL-AF4+, 26–918 nM; MLL-ENL+, 13–294 nM; other MLL+ 10–356 nM; MLL−, 31–488. Compared to MLL-AF4+, the IC50s in MLL-ENL+ cases were significantly lower (p=0.047), IC50s in other MLL+ cases were lower but the difference did not achieve significance (p=0.10), and IC50s in MLL- cases were not significantly different (p=0.64). In the 47 COG P9407 cases studied by MTT assay and gene expression profiling, 450 probesets defined a cluster of 16 cases with higher IC50s, which were predominantly MLL-AF4+ (68.7%). Ingenuity analysis identified significant correlations of the following canonical pathways with the IC50 in the same 47 cases: glycolysis/gluconeogenesis, mTOR signaling, regulation of eIF4 and p70S6K signaling, EIF2 signaling, and fructose and mannose metabolism. In preliminary analyses, cell lines with t(4;11) exhibited time and dose-dependant sensitivity to the eIF4e inhibitor ribavirin. Conclusions: In infant ALL, obatoclax has broad-spectrum activity and there is pan-sensitivity across MLL translocation subtypes and MLL− cases. Still specific MLL partner genes have a strong effect on obatoclax IC50 and there is exquisite sensitivity in MLL-ENL+ cases. This result is important because MLL-ENL is associated with particularly poor survival when conventional therapies are used. The association of differentially expressed genes in canonical cell signaling and metabolism pathways with differences in obatoclax sensitivity forms the basis to combine obatoclax with targeted agents directed at restoring these pathways to enhance responsiveness even further. Disclosures: Felix: None: Patent not licensed.

scholarly journals Biological Threat Detection via Host Gene Expression Profiling

2003 ◽  
Vol 49 (7) ◽  
pp. 1045-1049 ◽  
Author(s):  
Baochuan Lin ◽  
Maryanne T Vahey ◽  
Dzung Thach ◽  
David A Stenger ◽  
Joseph J Pancrazio
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Dna Microarrays ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Host Gene ◽  
Threat Detection ◽  
Host Gene Expression ◽  
Detection Techniques

Abstract With the increased threat posed by biological weapons, detection techniques for biothreat pathogens are critically needed to monitor and assess the severity of the illness once exposure has occurred. Current approaches for detecting biological threats are either time-consuming or highly specific but provide little information regarding pathogenicity. Genotyping of pathogens by PCR provides a fast and definitive means for identifying pathogens, but reliance on pathogen genotypic endpoints has several limitations. Current progress in DNA microarrays technology provides an alternative way to address the issues faced by traditional detection systems through host gene expression profiles of peripheral blood cells. We discuss the advantages and critical issues facing the use of host gene expression profiling for biological threat detection.

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