Microarray Classification of Myelodysplastic Syndrome (MDS) Identifies Subgroups with Distinct Clinical Outcomes.

The MILE (Microarray Innovations in LEukemia) study has previously shown that gene expression signatures associated with initial leukaemia classifier (LCver7) give an overall cross-validation accuracy of >95% for distinct sub-classes of pediatric and adult leukemias. However, only 50% of the 174 MDS samples in the whole-genome microarray analysis (Stage 1) of the MILE study were correctly identified; the remainder showed AML-like or non-leukemia-like gene profiles. An external morphological review (DB & HL) according to FAB and WHO criteria, of the 174 slides was performed independently (blind) which resulted in 6 samples being reclassified as AML and 4 non-leukemia cases excluded from the study. A recently improved, hierarchical based algorithm correctly identified 100% of the confirmed MDS cases. In this study, using LCver7, the confirmed 164 samples had 50% MDS classifications (Class 17), 23.8% non-leukemia classifications (Class 18), and 22.6% AML classifications (Classes 13 or 14) with the remaining 3.7% having a classification tie between 2 or 3 Classes (due to low confidence). No 5q- syndrome patients had an AML call, whilst 68.3% of RAEB2 patients had an AML classification and none were Class 18. Similarly, 95.6% of Low IPSS patients were classified as Class 17 or 18, whilst all patients (n=5) with High IPSS had an AML call. The classification was independent of blast cells: 10.2% of Class 18 calls had >5% blasts; 28.2% of AML-like cases had <5% blasts. Outcome data (132 MDS patients) was correlated with Class: significant difference (p<0.028, (Kaplan-Meier)) was seen in overall survival; with p <0.004 if AML (Classes 13 & 14) was compared to “non AML” (Classes 17 & 18). Statistically significant differences were seen for time to transformation to AML between the classes (p<0.0001) and between AML and “non AML” (p<0.00007, Kaplan-Meier)) with a probability of transformation of 44% at 18 months for the AML group compared to <8% for the “non-AML” group. A further linear classifier has been used to discriminate patients who transform to AML within 18 months (poor prognosis) with patients with no transformation after >60 months (good prognostic group). Bioinformatic analysis of molecular mapped functions and canonical pathways showed that cell signalling processes were over-represented when comparing de novo AML (n=204) with MDS, from the MILE study, whilst signal transduction pathways were deregulated when comparing non-leukemia samples (n=71) with MDS. Similar pathways and functions were also deregulated when comparing the correctly classified MDS with Class 17 call against MDS with Class 18 call and MDS with AML Classes 13 or 14 calls. In conclusion, the use of microarrays within the initial study, solely intended for diagnostic purposes, has now evolved towards a position in which novel prognostic value may be gained from distinct gene expression signatures. This has also resulted in a better molecular understanding of the progression from non-leukemia, through MDS into full blown AML.