MALDI imaging-based identification of prognostically relevant signals in bladder cancer using large-scale tissue microarrays.
Urol Oncol
; 32(8): 1225-33, 2014 Nov.
Article
em En
| MEDLINE
| ID: mdl-25131659
ABSTRACT
OBJECTIVE:
Although most patients with urinary bladder cancer present with noninvasive and low-malignant stages of the disease, about 20% eventually develop life-threatening metastatic tumors. This study was designed to evaluate the potential of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to identify molecular markers predicting the clinical course of bladder cancer. MATERIALS ANDMETHODS:
We employed MALDI-MSI to a bladder cancer tissue microarray including paraffin-embedded tissue samples from 697 patients with clinical follow-up data to search for prognostically relevant associations.RESULTS:
Analysis of our MALDI imaging data revealed 40 signals in the mass spectra (m/z signals) associated with epithelial structures. The presence of numerous m/z signals was statistically related to one or several phenotypical findings including tumor aggressiveness (stage, grade, or nodal status; 30 signals), solid (5 signals) or papillary (3 signals) growth patterns, and increased (6 signals) or decreased (12 signals) cell proliferation, as determined by Ki-67 immunohistochemistry. Two signals were linked with tumor recurrence in noninvasive (pTa category) tumors, of which one was also related to progression from pTa-category to pT1-category disease. The absence of one m/z signal was linked with decreased survival in the subset of 102 muscle-invasive cancers.CONCLUSION:
Our data demonstrate the suitability of combining MSI and large-scale tissue microarrays to simultaneously identify and validate clinically useful molecular markers in urinary bladder cancer.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Bexiga Urinária
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Diagnóstico por Imagem
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Espectrometria de Massas por Ionização e Dessorção a Laser Assistida por Matriz
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Análise Serial de Tecidos
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article