Simon V. van Reijmersdal

Diagnostic Genome Profiling in Mental Retardation

Mental retardation (MR) occurs in 2%-3% of the general population. Conventional karyotyping has a resolution of 5-10 million bases and detects chromosomal alterations in approximately 5% of individuals with unexplained MR. The frequency of smaller submicroscopic chromosomal alterations in these patients is unknown. Novel molecular karyotyping methods, such as array-based comparative genomic hybridization (array CGH), can detect submicroscopic chromosome alterations at a resolution of 100 kb. In this study, 100 patients with unexplained MR were analyzed using array CGH for DNA copy-number changes by use of a novel tiling-resolution genomewide microarray containing 32,447 bacterial artificial clones. Alterations were validated by fluorescence in situ hybridization and/or multiplex ligation-dependent probe amplification, and parents were tested to determine de novo occurrence. Reproducible DNA copy-number changes were present in 97% of patients. The majority of these alterations were inherited from phenotypically normal parents, which reflects normal large-scale copy-number variation. In 10% of the patients, de novo alterations considered to be clinically relevant were found: seven deletions and three duplications. These alterations varied in size from 540 kb to 12 Mb and were scattered throughout the genome. Our results indicate that the diagnostic yield of this approach in the general population of patients with MR is at least twice as high as that of standard GTG-banded karyotyping.

Independent prognostic value of BCR-ABL1-like signature and IKZF1 deletion, but not high CRLF2 expression, in children with B-cell precursor ALL

Most relapses in childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL) are not predicted using current prognostic features. Here, we determined the co-occurrence and independent prognostic relevance of 3 recently identified prognostic features: BCR-ABL1-like gene signature, deletions in IKZF1, and high CRLF2 messenger RNA expression (CRLF2-high). These features were determined in 4 trials representing 1128 children with ALL: DCOG ALL-8, ALL9, ALL10, and Cooperative ALL (COALL)-97/03. BCR-ABL1-like, IKZF1-deleted, and CRLF2-high cases constitute 33.7% of BCR-ABL1-negative, MLL wild-type BCP-ALL cases, of which BCR-ABL1-like and IKZF1 deletion (co)occurred most frequently. Higher cumulative incidence of relapse was found for BCR-ABL1-like and IKZF1-deleted, but not CRLF2-high, cases relative to remaining BCP-ALL cases, reflecting the observations in each of the cohorts analyzed separately. No relapses occurred among cases with CRLF2-high as single feature, whereas 62.9% of all relapses in BCR-ABL1-negative, MLL wild-type BCP-ALL occurred in cases with BCR-ABL1-like signature and/or IKZF1 deletion. Both the BCR-ABL1-like signature and IKZF1 deletions were prognostic features independent of conventional prognostic markers in a multivariate model, and both remained prognostic among cases with intermediate minimal residual disease. The BCR-ABL1-like signature and an IKZF1 deletion, but not CRLF2-high, are prognostic factors and are clinically of importance to identify high-risk patients who require more intensive and/or alternative therapies.

The Origin and Nature of Tightly Clustered BTG1 Deletions in Precursor B-Cell Acute Lymphoblastic Leukemia Support a Model of Multiclonal Evolution

Recurrent submicroscopic deletions in genes affecting key cellular pathways are a hallmark of pediatric acute lymphoblastic leukemia (ALL). To gain more insight into the mechanism underlying these deletions, we have studied the occurrence and nature of abnormalities in one of these genes, the B-cell translocation gene 1 (BTG1), in a large cohort of pediatric ALL cases. BTG1 was found to be exclusively affected by genomic deletions, which were detected in 65 out of 722 B-cell precursor ALL (BCP-ALL) patient samples (9%), but not in 109 T-ALL cases. Eight different deletion sizes were identified, which all clustered at the telomeric site in a hotspot region within the second (and last) exon of the BTG1 gene, resulting in the expression of truncated BTG1 read-through transcripts. The presence of V(D)J recombination signal sequences at both sites of virtually all deletions strongly suggests illegitimate RAG1/RAG2-mediated recombination as the responsible mechanism. Moreover, high levels of histone H3 lysine 4 trimethylation (H3K4me3), which is known to tether the RAG enzyme complex to DNA, were found within the BTG1 gene body in BCP-ALL cells, but not T-ALL cells. BTG1 deletions were rarely found in hyperdiploid BCP-ALLs, but were predominant in other cytogenetic subgroups, including the ETV6-RUNX1 and BCR-ABL1 positive BCP-ALL subgroups. Through sensitive PCR-based screening, we identified multiple additional BTG1 deletions at the subclonal level in BCP-ALL, with equal cytogenetic distribution which, in some cases, grew out into the major clone at relapse. Taken together, our results indicate that BTG1 deletions may act as “drivers” of leukemogenesis in specific BCP-ALL subgroups, in which they can arise independently in multiple subclones at sites that are prone to aberrant RAG1/RAG2-mediated recombination events. These findings provide further evidence for a complex and multiclonal evolution of ALL.

Validation Study of Existing Gene Expression Signatures for Anti-TNF Treatment in Patients with Rheumatoid Arthritis

So far, there are no means of identifying rheumatoid arthritis (RA) patients who will fail to respond to tumour necrosis factor blocking agents (anti-TNF), prior to treatment. We set out to validate eight previously reported gene expression signatures predicting therapy outcome. Genome-wide expression profiling using Affymetrix GeneChip Exon 1.0 ST arrays was performed on RNA isolated from whole blood of 42 RA patients starting treatment with infliximab or adalimumab. Clinical response according to EULAR criteria was determined at week 14 of therapy. Genes that have been reported to be associated with anti-TNF treatment were extracted from our dataset. K-means partition clustering was performed to assess the predictive value of the gene-sets. We performed a hypothesis-driven analysis of the dataset using eight existing gene sets predictive of anti-TNF treatment outcome. The set that performed best reached a sensitivity of 71% and a specificity of 61%, for classifying the patients in the current study. We successfully validated one of eight previously reported predictive expression profile. This replicated expression signature is a good starting point for developing a prediction model for anti-TNF treatment outcome that can be used in a daily clinical setting. Our results confirm that gene expression profiling prior to treatment is a useful tool to predict anti-TNF (non) response.

High-resolution genomic profiling of pediatric lymphoblastic lymphomas reveals subtle differences with pediatric acute lymphoblastic leukemias in the B-lineage

Lymphoblastic lymphoma (LBL) is one of the most frequent occurring pediatric non-Hodgkin lymphomas. In the WHO classification scheme, pediatric LBL is considered to be the same disease entity as pediatric acute lymphoblastic leukemia (ALL). However, it is unclear whether the genetic basis of pediatric LBL development is similar to that of pediatric ALL. We performed genome-wide analyses of copy number aberrations in 12 T-LBL and 7 precursor B-cell LBL pediatric cases using high-resolution SNP-based array CGH. Similar to what previously has been found in T-ALL, T-LBL exhibited recurrent deletions of the CDKN2A locus, occurring in 92% of the cases. Additionally, we detected deletions of RB1 (16%), duplications of MYB (16%), and an amplification of ABL1 in one case. These results show that, similar to T-ALL, the genomic alterations in T-LBL predominantly target genes involved in cell cycle progression. The majority of precursor B-cell LBL was characterized by high-hyperdiploidy (71%), and showed high resemblance with high-hyperdiploid precursor B-cell ALL. Taken together, our data suggest that pediatric LBL and ALL exhibit similar genomic abnormalities within confined immunophenotypic and cytogenetic subgroups, but that the representations of these subgroups differs between the two entities.

No evidence for large-scale germline genomic aberrations in hereditary bladder cancer patients with high-resolution array-based comparative genomic hybridization.

Linkage studies in high-risk families have led to the identification of several important susceptibility genes for hereditary cancer. Unfortunately, such studies offer limited possibilities in the search for high-penetrance bladder cancer genes, as extended bladder cancer families are very rare.

DNA copy number alterations mark disease progression in paediatric chronic myeloid leukaemia

Early recognition of children with chronic phase chronic myeloid leukaemia (CML‐CP) at risk for developing a lymphoid blast crisis (LyBC) is desirable, because therapy options in CML‐LyBC are limited. We used Multiplex Ligation‐dependent Probe Amplification to determine whether B‐cell lymphoid leukaemia‐specific copy number alterations (CNAs) (e.g. IKZF1, PAX5, CDKN2A deletions) could be detected in CML‐CP and may be used to predict disease progression to LyBC. CNAs were detected in all patients with CML‐LyBC, but in none of the 77 patients with CML‐CP. Based on this study we conclude that CNAs remain a hallmark of disease progression.

Accurate detection of low-level mosaic mutations in pediatric acute lymphoblastic leukemia using single molecule tagging and deep-sequencing

Abstract Pathogenic mutations in relapse-associated genes in pediatric acute lymphoblastic leukemia may improve risk stratification when detected at subclonal levels at primary diagnosis. However, to detect subclonal mutations upfront, a deep-sequencing approach with high specificity and sensitivity is required. Here, we performed a proof-of-principle study to detect low-level mosaic RAS pathway mutations by deep sequencing using random tagging-based single molecule Molecular Inversion Probes (smMIPs). The smMIP-based approach could sensitively detect variants with allele frequency as low as 0.4%, which could all be confirmed by other techniques. In comparison, with standard deep-sequencing techniques we reached a detection threshold of only 2.5%, which hampered detection of seven low-level mosaic mutations representing 24% of all detected mutations. We conclude that smMIP-based deep-sequencing outperforms standard deep-sequencing techniques by showing lower background noise and high specificity, and is the preferred technology for detecting mutations upfront, particularly in genes in which mutations show limited clustering in hotspots.