Identification of a Gene Expression Signature for Survival Prediction in Type I Endometrial Carcinoma
Endometrial cancer is the most common malignancy of the female reproductive tract. In many cases the prognosis is favorable, but 22% of affected women die from the disease. We aimed to study potential differences in gene expression between endometrioid adenocarcinomas from survivors (5-year survival...
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Veröffentlicht in: | Gene expression 2010-01, Vol.14 (6), p.361-370 |
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Zusammenfassung: | Endometrial cancer is the most common malignancy of the female reproductive tract. In many cases the prognosis is favorable, but 22% of affected women die from the disease. We aimed to study potential differences in gene expression between endometrioid adenocarcinomas from survivors
(5-year survival) and nonsurvivors. Forty-five patients were included in the investigation, of which 21 were survivors and 24 were nonsurvivors. The tumors were analyzed with genome-wide expression array analysis, represented by 13,526 genes. Distinct differences in gene expression were found
between the groups. A t-test established that 218 genes were significantly differentially expressed (p < 0.001) between the two survival groups, and in a cross-validation test 40 of the 45 (89%) tumors were classified correctly. The 218 differentially expressed genes were
subjected to hierachical clustering analysis, which yielded two clusters both exhibiting over 80% homogeneity with respect to survival. When the additional constraint of fold change (FC > 2) was added the hierachical clustering yielded similar results. Stage I tumors are expected to have
a favorable prognosis. However, in our tumor material there were six nonsurvivors with stage I tumors. Five out of six stage I nonsurvivors clustered in the nonsurvival fraction. Our findings suggest that a subgroup of early stage endometroid adenocarcinomas can be correctly classified as
potentially aggressive by using molecular biology in combination with conventional markers, thereby providing a tool for a more accurate classification and risk evaluation of the individual patient. |
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ISSN: | 1052-2166 1555-3884 1555-3884 |
DOI: | 10.3727/105221610X12735213181242 |