Heirarchical Clustering and Beyond in PCOS Endometrium : Brave New World

What is a clinician to make of microarrays? We accepted the adage of one gene one protein in our school years, and now we are blessed with the ability to measure the relative expression of 22,000 genes at once, creating enough data from one experiment to last a lifetime. The models used to analyze such data are beyond our comprehension, and even the culled results are dizzying in their complexity. The article by Kim et al. (1) weaves together microarray, expression, and protein data to tell an intriguing story about PCOS endometrium and ultimately PCOS. Should we gaze upon this “brave new world” of science with the wonder of Miranda in Shakespeare’s Tempest (our naivete and optimism may be similar) or with the irony Aldous Huxley intended in his antiutopian novel of the same name (we are also older and worldly wise and still waiting for the bounty of the genetic revolution to trickle down)? A complex syndrome like polycystic ovary syndrome (PCOS) with myriad reproductive and metabolic abnormalities calls for complex solutions. The investigators designed a study to examine dysregulated signaling pathways in the endometrium of women with PCOS (1) that is both tantalizing and frustrating. The authors have performed an enormous amount of work proceeding from microarray to pathway mapping to protein detection. They present a consistent, well-documented, if not counterintuitive story about a down-regulated, quiescent endometrium (at least the stroma) in PCOS. But how is the systemic down-regulation of signaling pathways and diminished cellular proliferation of the stromal endometrium consistent with an increased risk for endometrial hyperplasia and cancer in women with PCOS? The endometrium is a remarkably understudied and comparatively easily accessible tissue, and its choice is one of the many strengths of the study. It is a pathological tissue target in women with PCOS, from implantation failure to hyperplasia to cancer. The authors used a case-control study of 12 women with PCOS compared with a control population of 12 women with regular menses and biopsied the endometrium in a progestin-free environment, i.e. chronic anovulation for PCOS and the early follicular phase for controls. They were matched for endometrial thickness (all 6–9 mm), a potential weakness of the study given that a thicker PCOS endometrium might have yielded a more proliferative result. Another confounder is the difficulty in comparing a dynamic state of flux, i.e. the cycling women with evolving endometrium vs. the PCOS state of chronic unopposed estrogen/androgen. (Is endometrial torpor the correct term?) They chose a relatively thin endometrium to study, perhaps limited by the thickness in the early proliferative phase in cycling control women. What about the women with PCOS with thick endometriums? Aren’t they the ones we worry about clinically? A portion of tissue was snap-frozen for RNA analysis, and another portion was fixed for histology and eventual immunohistochemistry. These samples were then divided into three groups; one third (n = 4 from each group) was randomly selected for microarray hybridization with the Affymetrix GeneChip (with ∼22,000 genes) and two thirds for further validation of findings with real time RT-PCR. The data were then analyzed with a computational method (Gene Set Enrichment Analysis-GSEA) developed by researchers at the Broad Institute at the Massachusetts Institute of Technology in Cambridge, Massachusetts. This program determines whether an a priori defined set of genes (involved in a certain biological pathway and/or signaling process) shows statistically significant, concordant differences between two biological states (i.e. phenotypes such as PCOS and normally cycling women). They noted that 44 gene sets were enriched in normal endometrium vs. only two in women with PCOS (these were Hox_List and Glycerolipid metabolism). Of note, in comparison to findings in theca cells and oocytes of women with PCOS (2,3,4), no changes were noted in androgen-regulated pathways. The authors then validated expression of specific genes in select pathways using real time RT-PCR and demonstrated convincingly that genes encoding enzymes involved in glycolysis and integrin-mediated cell adhesion are down-regulated in PCOS endometrium. It is tempting to speculate that these changes mirror systemic problems such as a predisposition to diabetes and increased risks of miscarriage noted in women with PCOS. Finally, the authors performed immunohistochemical studies of a proliferation marker (Ki-67) with laser capture microdissection to identify specific cell types with evidence of impaired cell cycling in the stroma of PCOS endometrium. Oh, it’s a brave new world that has such a Prospero in it to order the genes into pathways that can be ranked in importance, so that a tiny fraction of them can be tested for expression, and then even fewer proteins selected such that a clear story of a relatively silent endometrium unfolds! But Prospero had his own agenda (which, for example, markedly conflicted with Caliban’s). Similarly both the statistical methods and the pathways chosen for further study (as well as the type and extent of further study of gene expression and protein) are subject to a certain amount of investigative license. We would have chosen other pathways for confirmation by laser capture, for example the kinesins, which are not only motoring proteins but can regulate a variety of cell signaling pathways and functional pathways such as androgen and insulin action, cell growth, and proliferation. There are multiple unsupervised modeling methods that they could have selected for analyzing the microarray data, beyond the hierarchical method done here, including partitional, graph-based, model-based, and biclustering methods that may have yielded varying results (5). Inevitably, claims of better and newer methods of hierarchical clustering than the ones used in this study have emerged (6,7). Each of these analysis methods makes certain assumptions; for example, in this paper the enrichment method looks for genes within a pathway that are highly correlated or anticorrelated between phenotypes (7). What if the pathways are grayer and the changes in genes in a certain pathway are not coexpressed (8)? What if there is discrepant expression and protein data, i.e. message is down-regulated because protein is up? Certainly more extensive characterization of proteins would shore up the story. We confess perhaps greater knowledge of Shakespeare and Huxley than the computational methods used. But we do understand some numbers. Can a meaningful analysis be performed in a case-control study when the number in each group is 4? If we were measuring sex steroids, ultrasound parameters of the ovary, or bumps on the head with a n of 4, the study would not see the light of day. With such numbers, the chance for a false-positive is large, reflected in the unacceptably high false discovery rate of many of the highlighted pathways in the analysis. But every new technology has its grace period. An adequate ample size and replication, as genomewide genetic association studies indicate, are the “gold standard”; thus, it is unfortunate that two thirds of such a small starting sample size went toward confirmatory studies, but we acknowledge that the extensive postarray studies are also a significant strength of this study. Although it is too soon to expect such exploratory studies of the endometrium to have sample sizes in the thousands, we await confirmation of the key finding of systemic down-regulation of signaling pathways in the endometrium of women with PCOS by other groups with larger sample sizes. In the meantime, we will continue to express some Huxleyian skepticism about the ability of a mathematical construct to herd such extensive and diverse data from so few individuals into meaningful patterns, while marveling at the pageant presented.