Dataset Information

An 18 gene expression-based score classifier predicts the clinical outcome in stage 4 neuroblastoma.

ABSTRACT:

Background

The prognosis of children with metastatic stage 4 neuroblastoma (NB) has remained poor in the past decade.

Patients and methods

Using microarray analyses of 342 primary tumors, we here developed and validated an easy to use gene expression-based risk score including 18 genes, which can robustly predict the outcome of stage 4 patients.

Results

This classifier was a significant predictor of overall survival in two independent validation cohorts [cohort 1 (n = 214): P = 6.3 × 10(-5); cohort 2 (n = 27): P = 3.1 × 10(-2)]. The prognostic value of the risk score was validated by multivariate analysis including the established markers age and MYCN status (P = 0.027). In the pooled validation cohorts (n = 241), integration of the risk score with the age and/or MYCN status identified subgroups with significantly differing overall survival (ranging from 35 to 100 %).

Conclusion

Together, the 18-gene risk score classifier can identify patients with stage 4 NB with favorable outcome and may therefore improve risk assessment and treatment stratification of NB patients with disseminated disease.

SUBMITTER: Formicola D

PROVIDER: S-EPMC4870777 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Publications

An 18 gene expression-based score classifier predicts the clinical outcome in stage 4 neuroblastoma.

Formicola Daniela D Petrosino Giuseppe G Lasorsa Vito Alessandro VA Pignataro Piero P Cimmino Flora F Vetrella Simona S Longo Luca L Tonini Gian Paolo GP Oberthuer André A Iolascon Achille A Fischer Matthias M Capasso Mario M

Journal of translational medicine 20160517 1

<h4>Background</h4>The prognosis of children with metastatic stage 4 neuroblastoma (NB) has remained poor in the past decade.<h4>Patients and methods</h4>Using microarray analyses of 342 primary tumors, we here developed and validated an easy to use gene expression-based risk score including 18 genes, which can robustly predict the outcome of stage 4 patients.<h4>Results</h4>This classifier was a significant predictor of overall survival in two independent validation cohorts [cohort 1 (n = 214): ...[more]

PMID: 27188717

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Project description:A gene expression signature indicative of activated wound responses is common to more than 90% of non-neoplastic tissues adjacent to breast cancer, but these tissues also exhibit substantial heterogeneity. We hypothesized that gene expression subtypes of breast cancer microenvironment can be defined and that these microenvironment subtypes have clinical relevance.Gene expression was evaluated in 72 patient-derived breast tissue samples adjacent to invasive breast cancer or ductal carcinoma in situ. Unsupervised clustering identified two distinct gene expression subgroups that differed in expression of genes involved in activation of fibrosis, cellular movement, cell adhesion and cell-cell contact. We evaluated the prognostic relevance of extratumoral subtype (comparing the Active group, defined by high expression of fibrosis and cellular movement genes, to the Inactive group, defined by high expression of claudins and other cellular adhesion and cell-cell contact genes) using clinical data. To establish the biological characteristics of these subtypes, gene expression profiles were compared against published and novel tumor and tumor stroma-derived signatures (Twist-related protein 1 (TWIST1) overexpression, transforming growth factor beta (TGF-?)-induced fibroblast activation, breast fibrosis, claudin-low tumor subtype and estrogen response). Histological and immunohistochemical analyses of tissues representing each microenvironment subtype were performed to evaluate protein expression and compositional differences between microenvironment subtypes.Extratumoral Active versus Inactive subtypes were not significantly associated with overall survival among all patients (hazard ratio (HR) = 1.4, 95% CI 0.6 to 2.8, P = 0.337), but there was a strong association with overall survival among estrogen receptor (ER) positive patients (HR = 2.5, 95% CI 0.9 to 6.7, P = 0.062) and hormone-treated patients (HR = 2.6, 95% CI 1.0 to 7.0, P = 0.045). The Active subtype of breast microenvironment is correlated with TWIST-overexpression signatures and shares features of claudin-low breast cancers. The Active subtype was also associated with expression of TGF-? induced fibroblast activation signatures, but there was no significant association between Active/Inactive microenvironment and desmoid type fibrosis or estrogen response gene expression signatures. Consistent with the RNA expression profiles, Active cancer-adjacent tissues exhibited higher density of TWIST nuclear staining, predominantly in epithelium, and no evidence of increased fibrosis.These results document the presence of two distinct subtypes of microenvironment, with Active versus Inactive cancer-adjacent extratumoral microenvironment influencing the aggressiveness and outcome of ER-positive human breast cancers.

Dataset Information

An 18 gene expression-based score classifier predicts the clinical outcome in stage 4 neuroblastoma.

Background

Patients and methods

Results

Conclusion

Publications

An 18 gene expression-based score classifier predicts the clinical outcome in stage 4 neuroblastoma.

Similar Datasets

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