Identification of novel molecular prognostic markers for paediatric T-cell acute lymphoblastic leukaemia

Division of Children's Leukaemia and Cancer Research, Telethon Institute for Child Health Research and Centre for Child Health Research, University of Western Australia, Perth, WA, Australia.
British Journal of Haematology (Impact Factor: 4.71). 06/2007; 137(4):319-28. DOI: 10.1111/j.1365-2141.2007.06576.x
Source: PubMed


In the last four decades the survival of patients with newly diagnosed childhood T-cell acute lymphoblastic leukaemia (T-ALL) has improved dramatically. In sharp contrast, relapsed T-ALL continues to confer a dismal prognosis. We sought to determine if gene expression profiling could uncover a signature of outcome for children with T-ALL. Using 12 patient specimens obtained before therapy started, we examined the gene expression profile by oligonucleotide microarrays. We identified three genes, CFLAR, NOTCH2 and BTG3, whose expression at the time of diagnosis accurately distinguished the patients according to disease outcome. These genes are involved in the regulation of apoptosis and cellular proliferation. The prognostic value of the three predictive genes was assessed in an independent cohort of 25 paediatric T-ALL patients using quantitative real-time reverse transcription polymerase chain reaction. Patients assigned to the adverse outcome group had a significantly higher cumulative incidence of relapse compared with patients assigned to the favourable outcome group (46% vs. 8%, P = 0.029). Five-year overall survival was also significantly worse in the patients assigned to the adverse outcome group (P = 0.0039). The independent influence of the 3-gene predictor was confirmed by multivariate analysis. Our study provides proof of principle that genome-wide expression profiling can detect novel molecular prognostic markers in paediatric T-ALL.

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Available from: Katrin Hoffmann, Mar 31, 2015
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    • "The underexpression of VEGFA in the T-ALL datasets examined may also be indicative of favorable prognosis in the T-ALL patients. Gottardo et al. [73] also reported downregulation of Notch2 in their analysis of T-ALL and they associate this lowered expression to adverse outcome in the patients. "
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    • "We have used two different approaches to identify gene signatures that can successfully discriminate relapse and CCR patients at the time of diagnosis across multiple patient cohorts and platforms. Defined gene classifiers (such as the 5-GC) containing a smaller number of genes may be useful to augment existing risk stratification regimens for patients diagnosed with ALL as they can easily be adapted to qRT-PCR technology [18,22]. The complementary method we present here uses larger, biologically defined genesets that provide important clues to the underlying mechanisms of relapse. "
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    • "Briefly, RNA was extracted from cell lines in exponential growth phase and hybridised to Affymetrix HG-U133A microarrays (Affymetrix, Santa Clara, CA, USA) in accordance with our previously published protocols (Beesley et al, 2005; Hoffmann et al, 2005; Gottardo et al, 2007). Microarray data were normalised using robust multiarray analysis (Irizarry et al, 2003) and all passed quality control criteria for noise, background, absent/ present calls and 3 0 /5 0 signal ratios for ACTB and GAPDH. "
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