Schwannomas exhibit distinct size-dependent gene-expression patterns.

AIM: Neurofibromatosis type 2 (NF2)-associated vestibular schwannomas have variable size at presentation which presents a unique challenge in NF2 patient management. Therefore, we investigated the molecular signature characteristic of the differences in size for improved individualized precise therapy. MATERIALS & METHODS: RNA expression analysis was performed on 15 small and 27 large NF2-associated vestibular schwannoma tumors using a microarray analyzing over 47,000 transcripts. RESULTS: A signature of 11 genes was found to be correlated with NF2 tumor size. CONCLUSION: We have identified the genetic hallmark that differentiates large NF2-associated tumors from smaller tumors. This is the first time that these genes have been shown to be the hallmark for NF2 tumor size.

Significance Associated with Phenotype Score Aids in Variant Prioritization for Exome Sequencing Analysis.

Several in silico annotation-based methods have been developed to prioritize variants in exome sequencing analysis. This study introduced a novel metric Significance Associated with Phenotypes (SAP) score, which generates a statistical score by comparing an individual's observed phenotypes against existing gene-phenotype associations. To evaluate the SAP score, a retrospective analysis was performed on 219 exomes. Among them, 82 family-based and 35 singleton exomes had at least one disease-causing variant that explained the patient's clinical features. SAP scores were calculated, and the rank of the disease-causing variant was compared with a known method, Exomiser. Using the SAP score, the known causative variant was ranked in the top 10 retained variants for 94% (77 of 82) of the family-based exomes and in first place for 73% of these cases. For singleton exomes, the SAP score analysis ranked the known pathogenic variants within the top 10 for 80% (28 of 35) of cases. The SAP score, which is independent of detected variants, demonstrates comparable performance with Exomiser, which considers both phenotype and variant-level evidence simultaneously. Among 102 cases with negative results or variants of uncertain significance, SAP score analysis revealed two cases with a potential new diagnosis based on rank. The SAP score, a phenotypic quantitative metric, can be used in conjunction with standard variant filtration and annotation to enhance variant prioritization in exome analysis.

Diagnostic interpretation of array data using public databases and internet sources.

The range of commercially available array platforms and analysis software packages is expanding and their utility is improving, making reliable detection of copy-number variants (CNVs) relatively straightforward. Reliable interpretation of CNV data, however, is often difficult and requires expertise. With our knowledge of the human genome growing rapidly, applications for array testing continuously broadening, and the resolution of CNV detection increasing, this leads to great complexity in interpreting what can be daunting data. Correct CNV interpretation and optimal use of the genotype information provided by single-nucleotide polymorphism probes on an array depends largely on knowledge present in various resources. In addition to the availability of host laboratories' own datasets and national registries, there are several public databases and Internet resources with genotype and phenotype information that can be used for array data interpretation. With so many resources now available, it is important to know which are fit-for-purpose in a diagnostic setting. We summarize the characteristics of the most commonly used Internet databases and resources, and propose a general data interpretation strategy that can be used for comparative hybridization, comparative intensity, and genotype-based array data.

Association of Combined Focal 22q11.22 Deletion and IKZF1 Alterations With Outcomes in Childhood Acute Lymphoblastic Leukemia.

IMPORTANCE: Alterations in the IKZF1 gene drive B-cell acute lymphoblastic leukemia (B-ALL) but are not routinely used to stratify patients by risk because of inconsistent associations with outcomes. We describe a novel deletion in 22q11.22 that was consistently associated with very poor outcomes in patients with B-ALL with IKZF1 alterations. OBJECTIVE: To determine whether focal deletions within the λ variable chain region in chromosome 22q11.22 were associated with patients with B-ALL with IKZF1 alterations with the highest risk of relapse and/or death. DESIGN, SETTING, AND PARTICIPANTS: This cohort study included 1310 primarily high-risk pediatric patients with B-ALL who were taken from 6 independent clinical cohorts, consisting of 3 multicenter cohorts (AALL0232 [2004-2011], P9906 [2000-2003], and patients with Down syndrome who were pooled from national and international studies) and 3 single-institution cohorts (University of Utah [Salt Lake City], Children's Hospital of Philadelphia [Philadelphia, Pennsylvania], and St. Jude Children's Hospital [Memphis, Tennessee]). Data analysis began in 2011 using patients from the older studies first, and data analysis concluded in 2021. EXPOSURES: Focal 22q11.22 deletions. MAIN OUTCOMES AND MEASURES: Event-free and overall survival was investigated. The hypothesis that 22q11.22 deletions stratified the prognostic effect of IKZF1 alterations was formulated while investigating nearby deletions in VPREB1 in 2 initial cohorts (n = 270). Four additional cohorts were then obtained to further study this association (n = 1040). RESULTS: This study of 1310 patients with B-ALL (717 male [56.1%] and 562 female patients [43.9%]) found that focal 22q11.22 deletions are frequent (518 of 1310 [39.5%]) in B-ALL and inconsistent with physiologic V(D)J recombination. A total of 299 of 1310 patients with B-ALL had IKZF1 alterations. Among patients with IKZF1 alterations, more than half shared concomitant focal 22q11.22 deletions (159 of 299 [53.0%]). Patients with combined IKZF1 alterations and 22q11.22 deletions had worse outcomes compared with patients with IKZF1 alterations and wild-type 22q11.22 alleles in every cohort examined (combined cohorts: 5-year event-free survival rates, 43.3% vs 68.5%; hazard ratio [HR], 2.18; 95% CI, 1.54-3.07; P < .001; 5-year overall survival rates, 66.9% vs 83.9%; HR, 2.05; 95% CI, 1.32-3.21; P = .001). While 22q11.22 deletions were not prognostic in patients with wild-type IKZF1 , concomitant 22q11.22 deletions in patients with IKZF1 alterations stratified outcomes across additional risk groups, including patients who met the IKZF1plus criteria, and maintained independent significance in multivariate analysis for event-free survival (HR, 2.05; 95% CI, 1.27-3.29; P = .003) and overall survival (HR, 1.83; 95% CI, 1.01-3.34; P = .05). CONCLUSIONS AND RELEVANCE: This cohort study suggests that 22q11.22 deletions identify patients with B-ALL and IKZF1 alterations who have very poor outcomes and may offer a new genetic biomarker to further refine B-ALL risk stratification and treatment strategies.

Comparison of familial and sporadic chronic lymphocytic leukaemia using high resolution array comparative genomic hybridization.

Approximately 10% of patients with chronic lymphocytic leukaemia (CLL) have a family history of the disease or a related lymphoproliferative disorder, yet the relationship of familial CLL to genomic abnormalities has not been characterized in detail. We therefore studied 75 CLL patients, half familial and half sporadic, using high-resolution array comparative genomic hybridization (CGH), in order to better define the relationship of genomic abnormalities to familial disease and other biological prognostic factors. Our results showed that the most common high-risk deletion in CLL, deletion 11q, was significantly associated with sporadic disease. Comparison of familial to sporadic disease additionally identified a copy number variant region near the centromere on 14q, proximal to IGH@, in which gains were associated both with familial CLL, and with mutated IGHV and homozygous deletion of 13q. Homozygous deletion of 13q was also found to be associated with mutated IGHV and low expression of ZAP-70, and a significantly longer time to first treatment compared to heterozygous deletion or lack of alteration. This study is the first high resolution effort to investigate and report somatic genetic differences between familial and sporadic CLL.

Genomic landscape of meningiomas.

Meningiomas are one of the most common adult brain tumors. For most patients, surgical excision is curative. However, up to 20% recur. Currently, the molecular determinants predicting recurrence and malignant transformation are lacking. We performed retrospective global genetic and genomic analysis of 85 meningioma samples of various grades. Copy number alterations were assessed by 100K single-nucleotide polymorphism arrays and correlated with gene expression, proliferation indices and clinical outcome. In addition to chromosome 22q loss, which was detected in the majority of clinical samples, chromosome 6q and 14q loss was significantly more common in recurrent tumors and was associated with anaplastic histology. Five "classes" of meningiomas were detected by gene expression analysis that correlated with copy number alterations, recurrent status and malignant histology. These classes more accurately identified recurrent tumors relative to Ki-67 index and extent of surgical resection, and highlight substantial expression heterogeneity between meningiomas. These data offer the most complete description of the genomic landscape of meningiomas, and provide broad genomic information that may be used to further stratify meningioma patients into prognostic risk groups.

Noise sampling method: an ANOVA approach allowing robust selection of differentially regulated genes measured by DNA microarrays.

MOTIVATION: A crucial step in microarray data analysis is the selection of subsets of interesting genes from the initial set of genes. In many cases, especially when comparing a specific condition to a reference, the genes of interest are those which are differentially expressed. Two common methods for gene selection are: (a) selection by fold difference (at least n fold variation) and (b) selection by altered ratio (at least n standard deviations away from the mean ratio). RESULTS: The novel method proposed here is based on ANOVA and uses replicate spots to estimate an empirical distribution of the noise. The measured intensity range is divided in a number of intervals. A noise distribution is constructed for each such interval. Bootstrapping is used to map the desired confidence levels from the noise distribution corresponding to a given interval to the measured log ratios in that interval. If the method is applied on individual arrays having replicate spots, the method can calculate an overall width of the noise distribution which can be used as an indicator of the array quality. We compared this method with the fold change and unusual ratio method. We also discuss the relationship with an ANOVA model proposed by Churchill et al. In silico experiments were performed while controlling the degree of regulation as well as the amount of noise. Such experiments show the performance of the classical methods can be very unsatisfactory. We also compared the results of the 2-fold method with the results of the noise sampling method using pre and post immortalization cell lines derived from the MDAH041 fibroblasts hybridized on Affymetrix GeneChip arrays. The 2-fold method reported 198 genes as upregulated and 493 genes as downregulated. The noise sampling method reported 98 gene upregulated and 240 genes downregulated at the 99.99% confidence level. The methods agreed on 221 genes downregulated and 66 genes upregulated. Fourteen genes from the subset of genes reported by both methods were all confirmed by Q-RT-PCR. Alternative assays on various subsets of genes on which the two methods disagreed suggested that the noise sampling method is likely to provide fewer false positives.