Gene expression profiling has been widely used in understanding global gene expression alterations in endometrial cancer vs. normal cells. In many microarray-based endometrial cancer studies, comparisons of cancer with normal cells were generally made using heterogeneous samples in terms of menstrual cycle phases, or status of hormonal therapies, etc, which may confound the search for differentially expressed genes playing roles in the progression of endometrial cancer. These studies will consequently fail to uncover genes that are important in endometrial cancer biology. Thus it is fundamentally important to identify a gene signature for discriminating normal endometrial cyclic phases. To this end, gene expression analysis was performed on 29 normal endometrium specimens. Unsupervised analysis demonstrated that gene expression profiles common to secretory endometrium were distinctively different from those of proliferative and atrophic endometrium. Pairwise comparisons further revealed no significant difference in gene expression between proliferative and atrophic endometrium. In addition, using a normal mixture model-based clustering algorithm we were able to identify a gene signature consisting of 35 unique annotated genes that display a switch-like or bimodal expression pattern across all samples. Functional annotation of this gene signature revealed that complement and coagulation cascades and Wnt signaling pathway were significantly enriched. Utility of this gene signature was validated in an independent gene expression data set, where clustered proliferative samples from clustered early, mid, and late-secretory samples were successfully separated. These data suggest that the bimodal gene signature identified in this study could potentially be used to distinguish cyclic phases of the menstrual cycle. Our findings will facilitate future work in understanding the molecular characteristics of endometrial cancers in comparison to normal endometrium.
University of Minnesota M.S. thesis. December 2014. Major: Biomedical Informatics and Computational Biology. Advisors: Adviser: George Vasmatzis
Claudia Neuhauser. 1 computer file (PDF); vii, 58 pages.
Gene expression signature of menstrual cyclic phase in normal cycling endometrium.
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