Abstract 2485

T-cell acute lymphoblastic leukemia (T-ALL) is caused by multiple lesions affecting genes involved in cell cycle control, proliferation, survival and differentiation. Type A abnormalities are driving events in the leukemogenic process; they are mutually exclusive genomic rearrangements, mainly translocations, which delineate specific T-ALL subgroups such as the TAL/LMO, TLX1, TLX3, and HOXA (MLL, CALM-AF10, and SET-NUP214). Type B abnormalities, on the other hand, are much greater in number and cooperate with different molecular lesions, as they are widespread in diverse genetic subgroups. They include genomic imbalances, chromosome translocations and mutations.

To confront the heterogeneity of T-ALL associated genomic lesions we used CI-FISH, SNP and GEP, explored their utility as potential diagnostic tools in pediatric T-ALL and correlated the genetic lesions at diagnosis with the Minimal Residual Disease (MRD) clinical stratification. We examined 51 children with T-ALL enrolled in Italy into the AIEOP-BFM ALL2000 protocol; MRD was performed by RQ-PCR monitoring of IG and TCR clonal rearrangements at days 33 and 78. Based on tumor load levels at both time points, patients were classified as MRD standard (MRD-SR), intermediate (MRD-IR) or high risk (MRD-HR)(Schrappe M, et al. Blood 2011;118:2077-84). Combined Interphase FISH (CI-FISH) was done using a panel of probes for 42 candidate genes. Cases with TCR-rearrangements were investigated for partners; aneuploidies were confirmed with probes for the centromeric alpha satellite regions. Single Nucleotide Polymorphism (SNP) arrays were done with Whole-Genome Cytogenetic 2.7M array (Affymetrix, Santa Clara, CA, USA) following the manufacturer's protocol. Data were analyzed by Chromosome Analysis Suite (ChAS) Software (Affymetrix) with hg19 genome built (http://genome.ucsc.edu/) as reference. Copy number (CN) filters were set at ≥ 20 markers and ≥ 30kb size for losses, ≥50kb for gains, and ≥ 2Mb for CNN-LOH. Gene expression profiles (GEP) (Affymetrix HU-133 Plus 2.0 arrays) were obtained following previously described protocols. Data were normalized with Robust Multi-array Avarage algorithm (RMA). Prediction was performed using the method Prediction Analysis of Microarrays (PAM): a threshold for the selection of predictive probe sets was established using cross validation. This procedure was used to predict and compare classification of 34 cases with CI-FISH and 6 samples for which CI-FISH was not available.

CI-FISH grouped 85% of patients according to Type A mutations with distribution in each category reflecting the estimated incidence in childhood T-ALL: 37.5% of cases in the TAL/LMO subgroup, 22.5% in the HOXA, 20% in the TLX3, and 5% in the TLX1. GEP class prediction was concordant with the CI-FISH results. PAM analysis identified 15 probe sets, 11 of which are part of the signature used by Homminga et al. (Cancer Cell 2011;19:484–497) to distinguish the three categories LMOTAL, TLX3 and HOX. SNPs complemented the findings by detecting Type B abnormalities in all cases, thus linking Type A and B lesions. CDKN2A/B abnormalities, as previously observed, were prevalently associated with TLX1 and TLX3(∼90% of TLX1/TLX3 positive cases vs 68% of TAL/LMO and 55.5% of HOXA); PTEN/10q23 deletions occurred in the TAL/LMO subgroup; monoallelic RB1 deletions were found only in the TLX3 subgroup. Interestingly, the TLX3 subgroup was also significantly associated with trisomies and/or tetrasomies of chromosomes 1, 7, 8, and 18 (Fisher exact test; p=0.01). Patients' stratification according to MRD showed most cases with TAL/LMO (15/18, 83.3%) and HOXA (6/9, 66.6%) fell within MRD-HR while TLX3 positive cases were mainly in MRD-SR (4/8) and MRD-IR (3/8). The 2 TLX1 positive cases were respectively assigned to MRD-SR and MRD-IR.

CI-FISH and SNP arrays provided us with an accurate and exhaustive genomic diagnosis of pediatric T-ALL. Based on CI-FISH results a successful predictive GEP test was elaborated. In a prospective design, dissection of type A/B abnormalities within MRD categories might represent a refined prognostic stratification at diagnosis for the majority of patients.

Disclosures:

No relevant conflicts of interest to declare.

Author notes

*

Asterisk with author names denotes non-ASH members.

Sign in via your Institution