The International Neuroblastoma Pathology Classification (the Shimada system)

Shimada, Hiroyuki; Ambros, Inge M.; Dehner, Louis P.; Hata, Junichi; Joshi, Vijay V.; Roald, Borghild; Stram, Daniel O.; Gerbing, Robert B.; Lukens, John N.; Matthay, Katherine K.; Castleberry, Robert P.

doi:10.1002/(sici)1097-0142(19990715)86:2<364::aid-cncr21>3.0.co;2-7

Cited by 906 publications

(377 citation statements)

References 16 publications

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“…The extent of differentiation in the tumour has prognostic significance. 19,161,170,171 Ganglioneuromas are comprised of individual ganglion cells or clusters surrounded by Schwannian stroma, but there is controversy concerning the origin of the Schwann cells in these tumours. Ambros et al 172 showed that the Schwann cells in ganglioneuromas had a normal DNA content, whereas the ganglionic cells were clonally aneuploid, suggesting the Schwann cells are normal, infiltrating host cells.…”

Section: Mechanisms Of Spontaneous Regressionmentioning

confidence: 99%

“…160 Indeed, the retinoid isotretinoin (13-cisretinoic acid) has been incorporated into frontline therapy for children with high-risk neuroblastoma in an effort to induce differentiation in vivo in states of minimal residual disease following intensive, multimodality therapy. 161 The precise mechanisms by which isotretinoin induces differentiation are unclear, but it seems that retinoids are associated with increased expression of Trk receptors. 160 …”

Section: Therapeutic Implications Of Regressionmentioning

confidence: 99%

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Mechanisms of neuroblastoma regression

2014

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Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches.

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Section: Mechanisms Of Spontaneous Regressionmentioning

confidence: 99%

Section: Therapeutic Implications Of Regressionmentioning

confidence: 99%

Mechanisms of neuroblastoma regression

2014

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“…However, very low- and low-risk patients were joined for the statistical analysis and were considered as low-risk group. Samples were centrally reviewed and classified according to the International Neuroblastoma Pathology Committee (INPC) system [5,34]. Biological studies included status of MYCN and 1p, both studied by FISH according to ENQUA guidelines [35,36].…”

Section: Methodsmentioning

confidence: 99%

“…This tumor exhibits contrasting patterns of clinical behavior ranging from spontaneous remission to rapid tumor progression and death. Prognosis classically depends on age at diagnosis [1], tumor stage [2], MYCN oncogene amplification status [3,4], and histology in a lesser extent [5]. Several well-characterized genetic abnormalities associated with neuroblastoma (NB) have been used to predict outcome, for example, DNA content [6], gain of chromosome arm 17q [7], or deletion of chromosome arm 1p [8] and 11q [9,10].…”

Section: Introductionmentioning

confidence: 99%

Two independent epigenetic biomarkers predict survival in neuroblastoma

et al. 2015

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BackgroundNeuroblastoma (NB) is the most common extracranial pediatric solid tumor with a highly variable clinical course, ranging from spontaneous regression to life-threatening disease. Survival rates for high-risk NB patients remain disappointingly low despite multimodal treatment. Thus, there is an urgent clinical need for additional biomarkers to improve risk stratification, treatment management, and survival rates in children with aggressive NB.ResultsUsing gene promoter methylation analysis in 48 neuroblastoma tumors with microarray technology, we found a strong association between survival and gene promoter hypermethylation (P = 0.036). Hypermethylation of 70 genes significantly differentiated high-risk survivor patients from those who died during follow-up time. Sixteen genes with relevant roles in cancer biology were further validated in an additional cohort of 83 neuroblastoma tumors by bisulfite pyrosequencing. High promoter methylation rates of these genes were found in patients with metastatic tumors (either stage metastatic (M) or metastatic special (MS)), 18 months or older at first diagnosis, MYCN amplification, relapsed, and dead. Notably, the degree of methylation of retinoblastoma 1 (RB1) and teratocarcinoma-derived growth factor 1 (TDGF1) predicts event-free and overall survival independently of the established risk factors. In addition, low RB1 mRNA expression levels associate with poor prognosis suggesting that promoter methylation could contribute to the transcriptional silencing of this gene in NB.ConclusionsWe found a new epigenetic signature predictive for NB patients’ outcome: the methylation status of RB1 and TDGF1 associate with poorer survival. This information is useful to assess prognosis and improve treatment selection.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-015-0054-8) contains supplementary material, which is available to authorized users.

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“…Since treatment strategies vary from surgery alone to intensive multimodal regimens, precise risk assessment is critical for therapeutic decisions. Currently, several clinical, biologic, and morphologic parameters, such as age at diagnosis, tumor stage, genomic amplification of MYCN oncogene, copy number alterations of the chromosomal regions 1p, 11q, and 17q, ploidy, and histologic features, are considered as markers of neuroblastoma outcome (1–4). However, despite elaborate risk stratification strategies, there remain cases where these markers have shown limited clinical use.…”

Section: Introductionmentioning

confidence: 99%

A Three-Gene Expression Signature Model for Risk Stratification of Patients with Neuroblastoma

García

Mayol

Ríos

et al. 2012

Clinical Cancer Research

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Purpose Neuroblastoma is an embryonal tumor with contrasting clinical courses. Despite elaborate stratification strategies, precise clinical risk assessment still remains a challenge. The purpose of this study was to develop a PCR-based predictor model to improve clinical risk assessment of patients with neuroblastoma. Experimental Design The model was developed using real-time PCR gene expression data from 96 samples and tested on separate expression data sets obtained from real-time PCR and microarray studies comprising 362 patients. Results On the basis of our prior study of differentially expressed genes in favorable and unfavorable neuroblastoma subgroups, we identified three genes, CHD5, PAFAH1B1, and NME1, strongly associated with patient outcome. The expression pattern of these genes was used to develop a PCR-based single-score predictor model. The model discriminated patients into two groups with significantly different clinical outcome [set 1: 5-year overall survival (OS): 0.93 ± 0.03 vs. 0.53 ± 0.06, 5-year event-free survival (EFS): 0.85 ± 0.04 vs. 0.042 ± 0.06, both P < 0.001; set 2 OS: 0.97 ± 0.02 vs. 0.61 ± 0.1, P = 0.005, EFS: 0.91 ± 0.8 vs. 0.56 ± 0.1, P = 0.005; and set 3 OS: 0.99 ± 0.01 vs. 0.56 ± 0.06, EFS: 0.96 ± 0.02 vs. 0.43 ± 0.05, both P < 0.001]. Multivariate analysis showed that the model was an independent marker for survival (P < 0.001, for all). In comparison with accepted risk stratification systems, the model robustly classified patients in the total cohort and in different clinically relevant risk subgroups. Conclusion We propose for the first time in neuroblastoma, a technically simple PCR-based predictor model that could help refine current risk stratification systems.

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The International Neuroblastoma Pathology Classification (the Shimada system)

Cited by 906 publications

References 16 publications

Mechanisms of neuroblastoma regression

Mechanisms of neuroblastoma regression

Two independent epigenetic biomarkers predict survival in neuroblastoma

A Three-Gene Expression Signature Model for Risk Stratification of Patients with Neuroblastoma

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