Percutaneous biopsy for the diagnosis, risk stratification, and molecular profiling of neuroblastoma: A single-center retrospective study.

PURPOSE: To determine whether percutaneous core needle biopsy (PCNB) is adequate for the diagnosis and full molecular characterization of newly diagnosed neuroblastoma. MATERIALS AND METHODS: Patients with newly diagnosed neuroblastoma who underwent PCNB in interventional radiology at a single center over a 5-year period were included. Pre-procedure imaging and procedure details were reviewed. Rates of diagnostic success and sufficiency for International Neuroblastoma Pathology Classification (INPC), risk stratification, and evaluation of genomic markers utilized in the Children's Oncology Group risk stratification, and status of the anaplastic lymphoma kinase (ALK) gene were assessed. RESULTS: Thirty-five patients (13 females, median age 2.4 years [interquartile range, IQR: 0.9-4.4] and median weight 12.4 kg [IQR: 9.6-18]) were included. Most had International Neuroblastoma Risk Group Stage M disease (n = 22, 63%). Median longest axis of tumor target was 8.8 cm [IQR: 6.1-12]. A 16-gauge biopsy instrument was most often used (n = 20, 57%), with a median of 20 cores [IQR: 13-23] obtained. Twenty-five specimens were assessed for adequacy, and 14 procedures utilized contrast-enhanced ultrasound guidance. There were two post-procedure bleeds (5.7%). Thirty-four of 35 procedures (97%) were sufficient for histopathologic diagnosis and risk stratification, 94% (n = 32) were sufficient for INPC, and 85% (n = 29) were sufficient for complete molecular characterization, including ALK testing. Biologic information was otherwise obtained from bone marrow (4/34, 12%) or surgery (1/34, 2.9%). The number of cores did not differ between patients with sufficient versus insufficient biopsies. CONCLUSION: In this study, obtaining multiple cores with PCNB resulted in a high rate of diagnosis and successful molecular profiling for neuroblastoma.

Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation.

Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer genome atlases reveal that kinase domains, which consist of 300 amino acids, can harbor numerous (150 to 200) single-point mutations across different patients in the same disease. This preponderance of mutations-some activating, some silent-in a known target protein make clinical decisions for enrolling patients in drug trials challenging since the relevance of the target and its drug sensitivity often depend on the mutational status in a given patient. We show through computational studies using molecular dynamics (MD) as well as enhanced sampling simulations that the experimentally determined activation status of a mutated kinase can be predicted effectively by identifying a hydrogen bonding fingerprint in the activation loop and the αC-helix regions, despite the fact that mutations in cancer patients occur throughout the kinase domain. In our study, we find that the predictive power of MD is superior to a purely data-driven machine learning model involving biochemical features that we implemented, even though MD utilized far fewer features (in fact, just one) in an unsupervised setting. Moreover, the MD results provide key insights into convergent mechanisms of activation, primarily involving differential stabilization of a hydrogen bond network that engages residues of the activation loop and αC-helix in the active-like conformation (in >70% of the mutations studied, regardless of the location of the mutation).

A safety and feasibility trial of 131 I-MIBG in newly diagnosed high-risk neuroblastoma: A Children's Oncology Group study.

INTRODUCTION: 131 I-meta-iodobenzylguanidine (131 I-MIBG) is effective in relapsed neuroblastoma. The Children's Oncology Group (COG) conducted a pilot study (NCT01175356) to assess tolerability and feasibility of induction chemotherapy followed by 131 I- MIBG therapy and myeloablative busulfan/melphalan (Bu/Mel) in patients with newly diagnosed high-risk neuroblastoma. METHODS: Patients with MIBG-avid high-risk neuroblastoma were eligible. After the first two patients to receive protocol therapy developed severe sinusoidal obstruction syndrome (SOS), the trial was re-designed to include an 131 I-MIBG dose escalation (12, 15, and 18 mCi/kg), with a required 10-week gap before Bu/Mel administration. Patients who completed induction chemotherapy were evaluable for assessment of 131 I-MIBG feasibility; those who completed 131 I-MIBG therapy were evaluable for assessment of 131 I-MIBG + Bu/Mel feasibility. RESULTS: Fifty-nine of 68 patients (86.8%) who completed induction chemotherapy received 131 I-MIBG. Thirty-seven of 45 patients (82.2%) evaluable for 131 I-MIBG + Bu/Mel received this combination. Among those who received 131 I-MIBG after revision of the study design, one patient per dose level developed severe SOS. Rates of moderate to severe SOS at 12, 15, and 18 mCi/kg were 33.3%, 23.5%, and 25.0%, respectively. There was one toxic death. The 131 I-MIBG and 131 I-MIBG+Bu/Mel feasibility rates at the 15 mCi/kg dose level designated for further study were 96.7% (95% CI: 83.3%-99.4%) and 81.0% (95% CI: 60.0%-92.3%). CONCLUSION: This pilot trial demonstrated feasibility and tolerability of administering 131 I-MIBG followed by myeloablative therapy with Bu/Mel to newly diagnosed children with high-risk neuroblastoma in a cooperative group setting, laying the groundwork for a cooperative randomized trial (NCT03126916) testing the addition of 131 I-MIBG during induction therapy.

Preclinical evaluation of the combination of AZD1775 and irinotecan against selected pediatric solid tumors: A Pediatric Preclinical Testing Consortium report.

INTRODUCTION: WEE1 is a serine kinase central to the G2 checkpoint. Inhibition of WEE1 can lead to cell death by permitting cell-cycle progression despite unrepaired DNA damage. AZD1775 is a WEE1 inhibitor that is in clinical development for children and adults with cancer. METHODS: AZD1775 was tested using a dose of 120 mg/kg administered orally for days 1 to 5. Irinotecan was administered intraperitoneally at a dose of 2.5 mg/kg for days 1 to 5 (one hour after AZD1775 when used in combination). AZD1775 and irinotecan were studied alone and in combination in neuroblastoma (n = 3), osteosarcoma (n = 4), and Wilms tumor (n = 3) xenografts. RESULTS: AZD1775 as a single agent showed little activity. Irinotecan induced objective responses in two neuroblastoma lines (PRs), and two Wilms tumor models (CR and PR). The combination of AZD1775 + irinotecan-induced objective responses in two neuroblastoma lines (PR and CR) and all three Wilms tumor lines (CR and 2 PRs). The objective response measure improved compared with single-agent treatment for one neuroblastoma (PR to CR), two osteosarcoma (PD1 to PD2), and one Wilms tumor (PD2 to PR) xenograft lines. Of note, the combination yielded CR (n = 1) and PR (n = 2) in all the Wilms tumor lines. The event-free survival was significantly longer for the combination compared with single-agent irinotecan in all models tested. The magnitude of the increase was greatest in osteosarcoma and Wilms tumor xenografts. CONCLUSIONS: AZD1775 potentiates the effects of irinotecan across most of the xenograft lines tested, with effect size appearing to vary across tumor panels.

Computational algorithms for in silico profiling of activating mutations in cancer.

Methods to catalog and computationally assess the mutational landscape of proteins in human cancers are desirable. One approach is to adapt evolutionary or data-driven methods developed for predicting whether a single-nucleotide polymorphism (SNP) is deleterious to protein structure and function. In cases where understanding the mechanism of protein activation and regulation is desired, an alternative approach is to employ structure-based computational approaches to predict the effects of point mutations. Through a case study of mutations in kinase domains of three proteins, namely, the anaplastic lymphoma kinase (ALK) in pediatric neuroblastoma patients, serine/threonine-protein kinase B-Raf (BRAF) in melanoma patients, and erythroblastic oncogene B 2 (ErbB2 or HER2) in breast cancer patients, we compare the two approaches above. We find that the structure-based method is most appropriate for developing a binary classification of several different mutations, especially infrequently occurring ones, concerning the activation status of the given target protein. This approach is especially useful if the effects of mutations on the interactions of inhibitors with the target proteins are being sought. However, many patients will present with mutations spread across different target proteins, making structure-based models computationally demanding to implement and execute. In this situation, data-driven methods-including those based on machine learning techniques and evolutionary methods-are most appropriate for recognizing and illuminate mutational patterns. We show, however, that, in the present status of the field, the two methods have very different accuracies and confidence values, and hence, the optimal choice of their deployment is context-dependent.

Heterozygosity mapping for human dominant trait variants.

Homozygosity mapping is a well-known technique to identify runs of homozygous variants that are likely to harbor genes responsible for autosomal recessive disease, but a comparable method for autosomal dominant traits has been lacking. We developed an approach to map dominant disease genes based on heterozygosity frequencies of sequence variants in the immediate vicinity of a dominant trait. We demonstrate through theoretical analysis that DNA variants surrounding an inherited dominant disease variant tend to have increased heterozygosity compared with variants elsewhere in the genome. We confirm existence of this phenomenon in sequence data with known dominant pathogenic variants obtained on family members and in unrelated population controls. A computer-based approach to estimating empirical significance levels associated with our test statistics shows genome-wide p-values smaller than 0.05 for many but not all of the individuals carrying a pathogenic variant.

Enrichment of Targetable Mutations in the Relapsed Neuroblastoma Genome.

Neuroblastoma is characterized by a relative paucity of recurrent somatic mutations at diagnosis. However, recent studies have shown that the mutational burden increases at relapse, likely as a result of clonal evolution of mutation-carrying cells during primary treatment. To inform the development of personalized therapies, we sought to further define the frequency of potentially actionable mutations in neuroblastoma, both at diagnosis and after chemotherapy. We performed a retrospective study to determine mutation frequency, the only inclusion criterion being availability of cancer gene panel sequencing data from Foundation Medicine. We analyzed 151 neuroblastoma tumor samples: 44 obtained at diagnosis, 42 at second look surgery or biopsy for stable disease after chemotherapy, and 59 at relapse (6 were obtained at unknown time points). Nine patients had multiple tumor biopsies. ALK was the most commonly mutated gene in this cohort, and we observed a higher frequency of suspected oncogenic ALK mutations in relapsed disease than at diagnosis. Patients with relapsed disease had, on average, a greater number of mutations reported to be recurrent in cancer, and a greater number of mutations in genes that are potentially targetable with available therapeutics. We also observed an enrichment of reported recurrent RAS/MAPK pathway mutations in tumors obtained after chemotherapy. Our data support recent evidence suggesting that neuroblastomas undergo substantial mutational evolution during therapy, and that relapsed disease is more likely to be driven by a targetable oncogenic pathway, highlighting that it is critical to base treatment decisions on the molecular profile of the tumor at the time of treatment. However, it will be necessary to conduct prospective clinical trials that match sequencing results to targeted therapeutic intervention to determine if cancer genomic profiling improves patient outcomes.

Integrative genomics identifies LMO1 as a neuroblastoma oncogene.

Neuroblastoma is a childhood cancer of the sympathetic nervous system that accounts for approximately 10% of all paediatric oncology deaths. To identify genetic risk factors for neuroblastoma, we performed a genome-wide association study (GWAS) on 2,251 patients and 6,097 control subjects of European ancestry from four case series. Here we report a significant association within LIM domain only 1 (LMO1) at 11p15.4 (rs110419, combined P = 5.2 × 10(-16), odds ratio of risk allele = 1.34 (95% confidence interval 1.25-1.44)). The signal was enriched in the subset of patients with the most aggressive form of the disease. LMO1 encodes a cysteine-rich transcriptional regulator, and its paralogues (LMO2, LMO3 and LMO4) have each been previously implicated in cancer. In parallel, we analysed genome-wide DNA copy number alterations in 701 primary tumours. We found that the LMO1 locus was aberrant in 12.4% through a duplication event, and that this event was associated with more advanced disease (P < 0.0001) and survival (P = 0.041). The germline single nucleotide polymorphism (SNP) risk alleles and somatic copy number gains were associated with increased LMO1 expression in neuroblastoma cell lines and primary tumours, consistent with a gain-of-function role in tumorigenesis. Short hairpin RNA (shRNA)-mediated depletion of LMO1 inhibited growth of neuroblastoma cells with high LMO1 expression, whereas forced expression of LMO1 in neuroblastoma cells with low LMO1 expression enhanced proliferation. These data show that common polymorphisms at the LMO1 locus are strongly associated with susceptibility to developing neuroblastoma, but also may influence the likelihood of further somatic alterations at this locus, leading to malignant progression.

Copy number variation at 1q21.1 associated with neuroblastoma.

Common copy number variations (CNVs) represent a significant source of genetic diversity, yet their influence on phenotypic variability, including disease susceptibility, remains poorly understood. To address this problem in human cancer, we performed a genome-wide association study of CNVs in the childhood cancer neuroblastoma, a disease in which single nucleotide polymorphism variations are known to influence susceptibility. We first genotyped 846 Caucasian neuroblastoma patients and 803 healthy Caucasian controls at approximately 550,000 single nucleotide polymorphisms, and performed a CNV-based test for association. We then replicated significant observations in two independent sample sets comprised of a total of 595 cases and 3,357 controls. Here we describe the identification of a common CNV at chromosome 1q21.1 associated with neuroblastoma in the discovery set, which was confirmed in both replication sets. This CNV was validated by quantitative polymerase chain reaction, fluorescent in situ hybridization and analysis of matched tumour specimens, and was shown to be heritable in an independent set of 713 cancer-free parent-offspring trios. We identified a previously unknown transcript within the CNV that showed high sequence similarity to several neuroblastoma breakpoint family (NBPF) genes and represents a new member of this gene family (NBPF23). This transcript was preferentially expressed in fetal brain and fetal sympathetic nervous tissues, and the expression level was strictly correlated with CNV state in neuroblastoma cells. These data demonstrate that inherited copy number variation at 1q21.1 is associated with neuroblastoma and implicate a previously unknown neuroblastoma breakpoint family gene in early tumorigenesis of this childhood cancer.