Abstract | PURPOSE: There is an increasing need to identify molecular markers, which can be used to prognosticate patient populations in gastric cancer. Whereas a significant number have been identified, very few have been characterized in the context of their ability to discriminate between young and old age groups in which a survival difference clearly exists. MATERIAL/METHODS: RESULTS: After adjustments for TNM stage, tumor grade, histopathological characteristics (Lauren classification), we found significant differences in the expression of these proteins, particularly E-cadherin and CDX2 between young and elderly patients. However, these differences did not amount to a significant difference in survival. CONCLUSIONS: This study demonstrates that the protein expression of p53, CDH1 and CDX2 significantly discriminates young patients with gastric cancer who have a better prognostic outlook from older patients, but this difference in expression does not contribute to a survival benefit.
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Authors | Claus Wilhelm Schildberg, Mohammed Abba, Susanne Merkel, Abbas Agaimy, Arno Dimmler, Anne Schlabrakowski, Roland Croner, Jörg Hendrik Leupold, Werner Hohenberger, Heike Allgayer |
Journal | Advances in medical sciences
(Adv Med Sci)
Vol. 59
Issue 1
Pg. 142-6
(Mar 2014)
ISSN: 1898-4002 [Electronic] Netherlands |
PMID | 24797991
(Publication Type: Comparative Study, Journal Article)
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Copyright | Copyright © 2014 Medical University of Bialystok. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved. |
Chemical References |
- Biomarkers, Tumor
- CDX2 Transcription Factor
- CDX2 protein, human
- Cadherins
- Homeodomain Proteins
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Topics |
- Biomarkers, Tumor
(metabolism)
- CDX2 Transcription Factor
- Cadherins
(metabolism)
- Combined Modality Therapy
- Female
- Follow-Up Studies
- Germany
(epidemiology)
- Homeodomain Proteins
(metabolism)
- Humans
- Immunoenzyme Techniques
- Male
- Middle Aged
- Neoplasm Staging
- Prognosis
- Reference Values
- Retrospective Studies
- Stomach Neoplasms
(epidemiology, metabolism, mortality)
- Survival Rate
- Tissue Array Analysis
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