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Cited by 155Neuroblastoma Research and TreatmentsGene expression and cancer classificationBreast Cancer Treatment Studies

Expression profiling using a tumor-specific cDNA microarray predicts the prognosis of intermediate risk neuroblastomas

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Ohira, Miki, Oba, Shigeyuki, Nakamura, Yohko, Isogai, Eriko, Kaneko, Setsuko, Nakagawa, Atsuko, Hirata, Takahiro, Kubo, Hiroyuki +6 more·2005·Cancer Cell
DOI 10.1016/j.ccr.2005.03.019
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Abstract

To predict the prognosis of neuroblastoma patients and choose a better therapeutic protocol, we developed a cDNA microarray carrying 5340 genes obtained from primary neuroblastomas and examined 136 tumor samples. We made a probabilistic output statistical classifier that provided a high accuracy in prognosis prediction (89% at 5 years) and a highly reliable method to validate it. Kaplan-Meier analysis indicated that the patients in an intermediate group defined by existing markers are divided by microarray into two further groups with 5 year survivals for 36% and 89% of patients (p < 10(-4)), i.e., with unfavorably and favorably predicted neuroblastomas, respectively. According to these results, we developed a gene subset chip for a clinical tool, for which our classifier exhibited 88% prediction accuracy.

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Crossref · 10.1016/j.ccr.2005.03.019

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  • A number of microarray-based gene expression models have been proposed to predict neuroblastoma patient outcome.

    “In addition, a number of microarray-based gene expression models have been proposed to predict neuroblastoma patient outcome [16, 17].”

    From Comparison of RNA-seq and microarray-based models for clinical endpoint prediction (2015) · cites this paper as [17]

  • The best performing models significantly discriminated patients with favorable and unfavorable outcome in the entire cohort and in the class labeled cohort.

    “The models significantly discriminated patients with favorable and unfavorable outcome in the entire cohort and in the class labeled cohort (Additional file 1: Figure S9a-d, Table S3 and S4), which is consistent with previous observations made by us and others [16–18, 20].”

    From Comparison of RNA-seq and microarray-based models for clinical endpoint prediction (2015) · cites this paper as [17]

  • Both gene expression-based models derived from RNA-seq and microarray analyses were capable of predicting patient outcome in the entire neuroblastoma cohort accurately.

    “Both gene expression-based models derived from RNA-seq and microarray analyses were capable of predicting patient outcome in the entire neuroblastoma cohort accurately, thereby validating results from previous studies and underscoring their potential clinical utility for risk estimation in neuroblastoma [16–18, 20].”

    From Comparison of RNA-seq and microarray-based models for clinical endpoint prediction (2015) · cites this paper as [17]

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Authors
Ohira, M., Oba, S., Nakamura, Y., Isogai, E., Kaneko, S., Nakagawa, A., Hirata, T., Kubo, H., Goto, T., Yamada, S., Yoshida, Y., Fuchioka, M., Ishii, S., & Nakagawara, A.
Affiliations
  • Chiba Cancer Center (JP)
  • Nara Institute of Science and Technology (JP)
  • University of Tsukuba (JP)
  • Aichi Medical University (JP)
  • Hisamitsu Pharmaceutical (Japan) (JP)
  • NGK Insulators (Japan) (JP)
  • SRL (Japan) (JP)
Corresponding author
Nakagawara, Akira
ORCID
Venue
Cancer Cell
Publisher
Elsevier BV
Published
2005-04
Volume
7
Issue
4
Pages
337-350
ISSN
1535-6108 (ISSN-L)
DOI
10.1016/j.ccr.2005.03.019
OpenAlex
W2110417418
Cited by
155
References
51
Citations by year
2025: 2 · 2024: 4 · 2023: 7 · 2022: 4 · 2021: 3 · 2020: 2 · 2018: 5 · 2017: 1 · 2016: 5 · 2015: 5 · 2014: 8 · 2013: 10 · 2012: 16
FWCI
8.85
Type
journal article
Language
en
Open access
Licence
Locations
  • Cancer Cell (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Ministry of Health, Labour and Welfare
  • Ministry of Education, Culture, Sports, Science and Technology
Topics
  • Health Sciences › Medicine › Neurology › Neuroblastoma Research and Treatments
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
Keywords
neuroblastoma, intermediate-risk neuroblastoma, outcome prediction, gene expression profiling, probabilistic classifiers, clinical decision support, survival prediction
MeSH terms
Algorithms, Artificial Intelligence, Humans, Neoplasm Staging, Neoplasms, Neuroblastoma, Prognosis, Sensitivity and Specificity, Reproducibility of Results, Models, Statistical, Survival Analysis, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling

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