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Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication

BACKGROUND: Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue dat...

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Autores principales: Wolf, Maija, Korja, Miikka, Karhu, Ritva, Edgren, Henrik, Kilpinen, Sami, Ojala, Kalle, Mousses, Spyro, Kallioniemi, Anne, Haapasalo, Hannu
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2873396/
https://www.ncbi.nlm.nih.gov/pubmed/20444257
http://dx.doi.org/10.1186/1471-2407-10-181
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author Wolf, Maija
Korja, Miikka
Karhu, Ritva
Edgren, Henrik
Kilpinen, Sami
Ojala, Kalle
Mousses, Spyro
Kallioniemi, Anne
Haapasalo, Hannu
author_facet Wolf, Maija
Korja, Miikka
Karhu, Ritva
Edgren, Henrik
Kilpinen, Sami
Ojala, Kalle
Mousses, Spyro
Kallioniemi, Anne
Haapasalo, Hannu
author_sort Wolf, Maija
collection PubMed
description BACKGROUND: Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. METHODS: A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumor tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s). RESULTS: In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42%) neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis) and to those with no MYCN amplification or 12q24.31 gain (good prognosis) (P = 0.001). Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC8, RSRC2, KNTC1 and MPHOSPH9). Among these, DIABLO showed the strongest activation suggesting a putative role in neuroblastoma progression. CONCLUSIONS: The presented systematic and rapid framework, which integrates aCGH, gene expression and tissue data to obtain novel targets and biomarkers for cancer, identified a low-level gain of the 12q24.31 as a potential new biomarker for neuroblastoma progression. Furthermore, results of in silico data mining suggest a new neuroblastoma target gene, DIABLO, within this region, whose functional and therapeutic role remains to be elucidated in follow-up studies.
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spelling pubmed-28733962010-05-20 Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication Wolf, Maija Korja, Miikka Karhu, Ritva Edgren, Henrik Kilpinen, Sami Ojala, Kalle Mousses, Spyro Kallioniemi, Anne Haapasalo, Hannu BMC Cancer Research Article BACKGROUND: Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. METHODS: A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumor tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s). RESULTS: In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42%) neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis) and to those with no MYCN amplification or 12q24.31 gain (good prognosis) (P = 0.001). Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC8, RSRC2, KNTC1 and MPHOSPH9). Among these, DIABLO showed the strongest activation suggesting a putative role in neuroblastoma progression. CONCLUSIONS: The presented systematic and rapid framework, which integrates aCGH, gene expression and tissue data to obtain novel targets and biomarkers for cancer, identified a low-level gain of the 12q24.31 as a potential new biomarker for neuroblastoma progression. Furthermore, results of in silico data mining suggest a new neuroblastoma target gene, DIABLO, within this region, whose functional and therapeutic role remains to be elucidated in follow-up studies. BioMed Central 2010-05-05 /pmc/articles/PMC2873396/ /pubmed/20444257 http://dx.doi.org/10.1186/1471-2407-10-181 Text en Copyright ©2010 Wolf et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wolf, Maija
Korja, Miikka
Karhu, Ritva
Edgren, Henrik
Kilpinen, Sami
Ojala, Kalle
Mousses, Spyro
Kallioniemi, Anne
Haapasalo, Hannu
Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication
title Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication
title_full Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication
title_fullStr Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication
title_full_unstemmed Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication
title_short Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication
title_sort array-based gene expression, cgh and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2873396/
https://www.ncbi.nlm.nih.gov/pubmed/20444257
http://dx.doi.org/10.1186/1471-2407-10-181
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