An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia

Metzeler, Klaus H.; Hummel, Manuela; Bloomfield, Clara D.; Spiekermann, Karsten; Braess, Jan; Sauerland, Maria-Cristina; Heinecke, Achim; Radmacher, Michael D.; Marcucci, Guido; Whitman, Susan P.; Maharry, Kati; Paschka, Peter; Larson, Richard A.; Berdel, Wolfgang E.; Büchner, Thomas; Wörmann, Bernhard; Mansmann, Ulrich; Hiddemann, Wolfgang; Bohlander, Stefan K.; Buske, Christian

doi:10.1182/blood-2008-02-134411

Cited by 368 publications

(437 citation statements)

References 32 publications

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“…Importantly to note, our three identified target genes are not included in the previously described prognostically relevant sets of 133 genes 7 and 86 genes. 36 Even when considering all top 50 AML CD34 þ specific genes, only one gene was found to overlap with one of the previously identified prognostic signatures. FLT3 was identified previously by Bullinger et al 7 and is the first gene in our list of AML CD34 þ specific genes, suggesting that upregulation of FLT3 might be important in the biology of AML.…”

Section: Discussionmentioning

confidence: 99%

“…This was validated and confirmed in an independent cohort of 79 normal karyotype AML patients. 36 A limitation in applying these results to clinical practice is the number of genes that have to be studied. By using the more purified AML CD34 þ population and a large cohort of normal BM samples, we were able to identify a small gene set with strong prognostic significance.…”

Section: Discussionmentioning

confidence: 99%

“…To perform further analyses two publicly available cytogenetically normal AML data sets (GSE16891 (NCBI GEO); n ¼ 218) 6,35 and (GSE12417 (NCBI GEO); n ¼ 163) 36 were utilized. The selected data sets provided us with clinically annotated gene expression values from Affymetrix Human Genome U133A or U95 gene chip array (Affymetrix, Santa Clara, CA, USA).…”

Section: Gene Expression Profilingmentioning

confidence: 99%

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Gene expression profiling in the leukemic stem cell-enriched CD34+ fraction identifies target genes that predict prognosis in normal karyotype AML

et al. 2011

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In order to identify acute myeloid leukemia (AML) CD34 þ -specific gene expression profiles, mononuclear cells from AML patients (n ¼ 46) were sorted into CD34 þ and CD34 À subfractions, and genome-wide expression analysis was performed using Illumina BeadChip Arrays. AML CD34 þ and CD34 À gene expression was compared with a large group of normal CD34 þ bone marrow (BM) cells (n ¼ 31). Unsupervised hierarchical clustering analysis showed that CD34 þ AML samples belonged to a distinct cluster compared with normal BM and that in 61% of the cases the AML CD34 þ transcriptome did not cluster together with the paired CD34 À transcriptome. The top 50 of AML CD34 þ -specific genes was selected by comparing the AML CD34 þ transcriptome with the AML CD34 À and CD34 þ normal BM transcriptomes. Interestingly, for three of these genes, that is, ankyrin repeat domain 28 (ANKRD28), guanine nucleotide binding protein, alpha 15 (GNA15) and UDP-glucose pyrophosphorylase 2 (UGP2), a high transcript level was associated with a significant poorer overall survival (OS) in two independent cohorts (n ¼ 163 and n ¼ 218) of normal karyotype AML. Importantly, the prognostic value of the continuous transcript levels of ANKRD28 (OS hazard ratio (HR): 1.32, P ¼ 0.008), GNA15 (OS HR: 1.22, P ¼ 0.033) and UGP2 (OS HR: 1.86, P ¼ 0.009) was shown to be independent from the well-known risk factors FLT3-ITD, NPM1c þ and CEBPA mutation status.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Gene Expression Profilingmentioning

confidence: 99%

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Gene expression profiling in the leukemic stem cell-enriched CD34+ fraction identifies target genes that predict prognosis in normal karyotype AML

et al. 2011

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“…Metzeler et al,derived 86 probe-sets of gene expression to predict survival for leukemia (Metzeler et al, 2008). In breast cancer, Motakis et al, used a couple of genes for survival prediction (Motakis et al, 2009).…”

Section: Expression Profiles Of Loneliness-associated Genes For Survimentioning

confidence: 99%

“…Three cohorts of brain cancer (glioma) datasets came from the Gene Expression Omnibus GSE 4412 (Freije et al, 2004), GSE4271 (Phillips et al, 2006), and GSE13041 (Lee et al, 2008). And the bone cancer (osteosarcoma), lung cancer, ovarian cancer, leukemia, and lymphoma cohort came from Gene Expression Omnibus GSE16091 (Paoloni et al, 2009), GSE3141 (Bild et al, 2006), GSE26712 (Bonome et al, 2008), GSE12417 (Metzeler et al, 2008), and GSE4475 (Hummel et al, 2006), individually. The data sets of GEO databases were downloaded from the National Center for Biotechnology Information (NCBI) in the web site of http://www.ncbi.…”

Section: Affymetrix Microarraysmentioning

confidence: 99%

Expression Profiles of Loneliness-associated Genes for Survival Prediction in Cancer Patients

You

Yeh

Su³

2014

Asian Pacific Journal of Cancer Prevention

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Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for highlonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Lonelinessassociated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

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Association of a Leukemic Stem Cell Gene Expression Signature With Clinical Outcomes in Acute Myeloid Leukemia

Gentles

Plevritis²,

Majeti³

et al. 2010

JAMA

355

317

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CUTE MYELOID LEUKEMIA(AML) is an aggressive malignancy of the bone marrow characterized by accumulation of early myeloid blood cells that fail to mature and differentiate. The course of the disease is marked by poor prognosis, frequent relapse, and high disease-related mortality. 1,2 Recent clinical investigation has focused on the identification of prognostic subgroups in adult AML with the goal of guiding patients into risk-adapted therapies. Such investigation determined that cytogenetic abnormalities are prognostic, some favorable and others unfavorable, 3,4 yet up to 50% of patients have normal karyotype AML with a wide range of clinical outcomes. In these patients, the presence of specific molecular mutations can provide prognostic information, including internal tandem duplications within the FLT3 gene, partial tandem duplication of the MLL gene, mislocalizing mutations of the NPM1 gene, mutations in the CEBPA and RAS genes, and increased expression of the BAALC and ERG genes. 5,6 However, these parameters and others such as patient age are only partially successful at capturing risk of relapse and patient outcomes following treatment.A growing body of evidence suggests that specific cancer cell subpopu-Context In many cancers, specific subpopulations of cells appear to be uniquely capable of initiating and maintaining tumors. The strongest support for this cancer stem cell model comes from transplantation assays in immunodeficient mice, which indicate that human acute myeloid leukemia (AML) is driven by self-renewing leukemic stem cells (LSCs). This model has significant implications for the development of novel therapies, but its clinical relevance has yet to be determined.Objective To identify an LSC gene expression signature and test its association with clinical outcomes in AML. Design, Setting, and PatientsRetrospective study of global gene expression (microarray) profiles of LSC-enriched subpopulations from primary AML and normal patient samples, which were obtained at a US medical center between April 2005 and July 2007, and validation data sets of global transcriptional profiles of AML tumors from 4 independent cohorts (n=1047). Main Outcome MeasuresIdentification of genes discriminating LSC-enriched populations from other subpopulations in AML tumors; and association of LSCspecific genes with overall, event-free, and relapse-free survival and with therapeutic response.Results Expression levels of 52 genes distinguished LSC-enriched populations from other subpopulations in cell-sorted AML samples. An LSC score summarizing expression of these genes in bulk primary AML tumor samples was associated with clinical outcomes in the 4 independent patient cohorts. High LSC scores were associated with worse overall, event-free, and relapse-free survival among patients with either normal karyotypes or chromosomal abnormalities. For the largest cohort of patients with normal karyotypes (n=163), the LSC score was significantly associated with overall survival as a continuous variable (hazard ratio [HR], 1.15; ...

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An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia

Cited by 368 publications

References 32 publications

Gene expression profiling in the leukemic stem cell-enriched CD34+ fraction identifies target genes that predict prognosis in normal karyotype AML

Gene expression profiling in the leukemic stem cell-enriched CD34+ fraction identifies target genes that predict prognosis in normal karyotype AML

Expression Profiles of Loneliness-associated Genes for Survival Prediction in Cancer Patients

Association of a Leukemic Stem Cell Gene Expression Signature With Clinical Outcomes in Acute Myeloid Leukemia

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