(HealthDay News) – Bimodal genes, or molecular on/off switches, can distinguish clinically relevant subtypes of ovarian cancer and provide ideal targets for diagnostic and prognostic testing.

Dawn N. Kernagis, from Duke University in Durham, NC, and colleagues used a bimodal discovery algorithm in conjunction with a publicly available ovarian cancer expression microarray data set on 285 ovarian tumors (246 malignant serous [MS] tumors, 20 endometrioid [EM] tumors, 18 low malignant potential [LMP] tumors, and one malignant adenocarcinoma).

The researchers found that robust bimodal expression patterns were identified in genes across all ovarian tumor types and within selected subtypes. Differential expression between LMP versus MS and EM was shown in 73 bimodal genes; 22 bimodal genes distinguished MS from EM; and 14 genes were significantly associated with survival among MS tumors. For patients with a favorable survival score, derived from a combination of these genes, median survival was significantly longer, 65 vs. 29 months (hazard ratio, 0.4221). The survival score was validated using two independent data sets [high-grade, advanced-stage serous and advanced-stage ovarian tumors].

“We conclude that genes with bimodal expression patterns not only define clinically relevant molecular subtypes of ovarian carcinoma but also provide ideal targets for translation into the clinical laboratory,” write the authors.

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