Identification of genomic classifiers that distinguish induction failure in T-lineage acute lymphoblastic leukemia: a report from the Children's Oncology Group

Abstract

The clinical and cytogenetic features associated with T-cell acute lymphoblastic leukemia (T-ALL) are not predictive of early treatment failure. Based on the hypothesis that microarrays might identify patients who fail therapy, we used the Affymetrix U133 Plus 2.0 chip and prediction analysis of microarrays (PAM) to profile 50 newly diagnosed patients who were treated in the Children's Oncology Group (COG) T-ALL Study 9404. We identified a 116-member genomic classifier that could accurately distinguish all 6 induction failure (IF) cases from 44 patients who achieved remission; network analyses suggest a prominent role for genes mediating cellular quiescence. Seven genes were similarly upregulated in both the genomic classifier for IF patients and T-ALL cell lines having acquired resistance to neoplastic agents, identifying potential target genes for further study in drug resistance. We tested whether our classifier could predict IF IntroductionAcute lymphoblastic leukemia (ALL) is the most common form of cancer among children and young adults. Approximately 15% of patients express cellular and molecular features that are unique to T-lineage acute lymphoblastic leukemia (T-ALL). [1][2][3][4] Through the use of increasingly dose-intensive therapy, combined with an improved understanding of leukemic pathogenesis, disease-free survival for children with ALL has improved over the past 3 decades. 5 However, when matched for NCI-designated clinical risk features of age, initial white blood cell count, and evidence of extramedullary disease, patients with T-ALL are at an increased risk of relapse compared with children treated for precursor B-lineage acute lymphoblastic leukemia (B-ALL). 6 In addition, unlike many of the genetic biomarkers observed in patients with precursor B-ALL, the recurring karyotypic aberrations identified in T-ALL do not consistently correlate with outcome on modern treatment schemas. 2,7,8 For these reasons, the identification of prognostically relevant karyotypic and clinicopathologic abnormalities in T-ALL has been difficult to elucidate. The recent identification of T-ALL risk groups, as defined by minimal residual disease (MRD) status, 6,9,10 activating NOTCH1 mutations, 11-13 and response to induction therapy, 6,14,15 can be used to stratify treatment approaches. Nevertheless, the mechanisms of drug resistance that result in persistent disease and early treatment failure remain poorly understood.Gene expression microarrays are spotted with thousands of 25mer oligonucleotides, which correspond to transcripts of known and hypothetical genes within the human genome. By using microarrays for class discovery in hematopoietic malignancies, it has been possible to identify novel pathways in malignant transformation, 16,17 explore heterogeneities among study populations, 18-21 and segregate patients into prognostically relevant subsets. 18,22 While numerous genes and genetic signatures predicting disease course have been identified for patients with acute myelogenous leukemia, precursor B-ALL, and...

Glucocorticoid resistance in T-lineage acute lymphoblastic leukaemia is associated with a proliferative metabolism

“…Previous reports have indicated an elevated glycolytic rate in prednisolone-resistant leukaemia cell lines (Tissing et al, 2007), and the involvement of carbohydrate metabolism genes in GC response (Tonko et al, 2001;Schmidt et al, 2006) and GC resistance in primary ALL specimens (Holleman et al, 2004). In the present study, GC resistance was significantly correlated with expression of hexokinase II, the rate-limiting glycolytic enzyme that has recently been associated both with induction failure in ALL (Winter et al, 2007) and discrimination between early and late ALL relapse (Bhojwani et al, 2006). Inhibition of cholesterol synthesis (required in highly proliferative cell types for the synthesis of cellular membranes) has been shown to be one of the earliest parameters affected by GCs in ALL cells (Cutts and Melnykovych, 1987), and is a critical metabolic event given that lymphocytes appear to be dependent on cholesterol synthesised endogenously (Madden et al, 1986).…”

Absence of biallelic TCRγ deletion predicts induction failure and poorer outcomes in childhood T‐cell acute lymphoblastic leukemia

“…Information on the genetic development of T-cell ALL has been obtained from gene expression profiles, some of which is associated with clinical outcomes [19,20]. Some studies have constructed gene expression signatures to predict clinical outcomes for T-cell ALL [21][22][23]. With…”

Drug–Gene Modeling in Pediatric T-Cell Acute Lymphoblastic Leukemia Highlights Importance of 6-Mercaptopurine for Outcome

“…All patients achieved remission following induction therapy; those patients achieving complete continuous remission (CCR) had median followup times of 7.3 years, whereas 44% of the patients subsequently relapsed (R). Expression data from the 2 Winter and colleagues cohorts (microarray CEL files and patient details) were obtained from the authors (23) and normalized by robust multiarray analysis (RMA) as previously described (7). Induction failure cases were removed from these cohorts before analysis, resulting in cohort sizes of 44 patients for Pediatric Oncology Group (POG/COG) Protocol 9404 (30 CCR, 14R, measured on HG-U133 Plus 2.0 arrays) and 41 patients for POG-8704 (24 CCR, 17R, measured on HG-U133A arrays).…”