Abstract
Introduction:
Risk stratification and minimal residual disease (MRD) monitoring improved outcome for adult T-ALL patients, but a relevant percentage of adult patients, particularly high-risk subtypes, still relapse with then very limited therapeutic options. For improved individualized treatment strategies, better understanding of molecular inter-leukemic heterogeneity would be important. Increasing amounts of unbiased next generation sequencing study data are available for pediatric T-ALL patients, but comprehensive data for adult T-ALL patients are scarce.
Patients and methods:
Eighty-four adult T-ALL patients (age: median 32, range 17-59 years) with different immunophenotypes were studied: 19 early, 14 mature and 51 thymic T-ALL. For all samples, deep targeted DNA sequencing with a gene panel consisting of 206 genes was performed (HighSeq 1500, 100 bp, average ~800 reads/bp). We sequenced mRNA with ~30 million reads/sample (HighSeq 2000, 125 bp). DNA methylation status of all samples were addressed by Infinium 450k methylation bead arrays.
Results:
Unsupervised clustering of 600 most variant expressed genes in our cohort identified five stable clusters with aberrant expression of oncogenes: TLX1 - (n=21), TLX3 - (n=10), HOXA - (n=12), TAL / LMO - (n=21) deregulated subgroups and cases with an immature gene expression signature (n=16). While the TLX1 - (thymic), the TAL / LMO - (thymic/mature), and the immature (early/mature) clusters are highly correlated with immunophenotype, HOX-A- and TLX3-cases occurred in any immunophenotypically defined subgroup. Different gene fusions were found in respective subgroups: TAL1 / 2 (n=7, fusion partners (FP): STIL1, TRDC, TCF7), LMO1/2 (n=2, FP: CAPRIN, RIC3), TXL1 (n=7, FP: TCRA, TCRB), and in the HOXA-cluster SET-NUP214-fusions (n=7). Differential expression (DE) analysis revealed an enrichment of stem cell genes like MEF2C, MN1, IGFBP7, FLT3 in the immature subgroup (2879 DE genes, DEG). TLX1 (2198 DEGs) and LMO/TAL (2165 DEGs) clusters were associated with mature T cell development stage (FDR<0.0001). Interestingly, HOXA-cluster (422 DEGs) showed a marked enrichment for ribosomal proteins (FDR<.00001).
On genomic level, we found a slightly lower rate of mutations in the HOXA-cluster (median mutations/patient: TAL/LMO 8, TLX1 9, TLX3 8.5, HOXA 6, immature 9). Most frequently mutated genes included NOTCH1 (51%), PHF6 (32%), DNM2 (18%), PTEN (18%), FBXW7 (16%), and JAK3 (14%). Noteworthy, multiple NOTCH1 mutations were present in many patients and frequently on a subclonal level pointing to a late event in leukemogenesis. Mutations of epigenetic modifiers including KMT2D, DNMT3A, SUZ12, and EP300 were enriched in the TLX3 and immature cluster. JAK/STAT pathway was affected in all subgroups with frequently two hits in individual patients, e.g. 6/7 (86%) JAK1 mutations co-occurred with JAK3 mutations.
On level of epigenetics, principal component analysis of the most variable CG-sites revealed five distinct subgroups. These are highly concordant with the subgroups based on gene expression profiling, with the exception of the HOXA-cluster. The increase of genomic altered epigenetic modifiers in TLX3 and immature cluster is reflected by a common DNA methylation signature (cluster M1).
Conclusion:
We characterized molecular defined subgroups of adult T-ALL on a genomic, transcriptional and epigenetic level finding high concordance for all subgroups across the platforms. We identified subgroup specific mutations and fusion genes for adult T-ALL patients reflecting inter-leukemic heterogeneity with association of molecularly defined subgroups to enriched pathways. These results might build the basis for the identification of patients eligible for targeted therapy like JAK/STAT inhibitors or epigenetic modulators.
No relevant conflicts of interest to declare.
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