Associations between Selected Biomarkers and Prognosis in a Population-Based Pancreatic Cancer Tissue Microarray
Open Access
- 1 April 2009
- journal article
- research article
- Published by American Association for Cancer Research (AACR) in Cancer Research
- Vol. 69 (7), 2950-2955
- https://doi.org/10.1158/0008-5472.can-08-3879
Abstract
Pancreatic cancer is the fourth leading cause of cancer death in the United States. Prognostic biomarkers are lacking, and treatment has limited effect on survival. Tissues from Surveillance, Epidemiology, and End Results registries (Iowa, Hawaii, and Los Angeles) were used to build a tissue microarray of 161 pancreatic tumors (113 resections and 48 biopsies). Proportional hazard models adjusted for age, race, sex, stage, time-period of diagnosis, and treatment. Associations were examined between markers (MUC1, MUC2, MUC5AC, synaptophysin, chromogranin, neuron specific enolase, epidermal growth factor receptor, HER2, CD5, CD138, CK5/6, CK19, CK20, and p53) and survival time from diagnosis. After adjusting for covariates, borderline statistically significant associations were seen between expression of each of the three mucins (MUC1, MUC2, and MUC5AC) and shorter survival time. The associations strengthened for 154 (96%) adenocarcinomas, particularly the 120 (75%) well-differentiated to moderately differentiated ductal adenocarcinomas, a tumor type that occurred more often in the cohort among White cases than cases of other racial origin (P < 0.01). For differentiated ductal adenocarcinomas, associations with shorter survival time were seen for expression of all three mucins combined versus other mucin expression patterns (adjusted hazard ratio, 1.8; 95% confidence interval, 1.2–2.6) and for MUC2(+) versus MUC2(−) expression (adjusted hazard ratio, 1.6; 95% confidence interval, 1.1–2.4). Mucin gene expression, particularly MUC2 expression, may have prognostic value for differentiated adenocarcinomas. Tumor histologies differed in this and Japanese cohorts. The tissue microarray is available to evaluate other biomarkers. Tissue-based surveillance can be used to monitor tumor histology in populations and facilitate applied research. [Cancer Res 2009;69(7):2950–5]Keywords
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