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Ovarian clear cell carcinoma (CCC) is generally associated with chemoresistance and poor clinical outcome, even with early diagnosis; whereas high-grade serous carcinomas (SCs) and endometrioid carcinomas (ECs) are commonly chemosensitive at advanced stages. Although an integrated genomic analysis of SC has been performed, conclusive views on copy number and expression profiles for CCC are still limited. In this study, we performed single nucleotide polymorphism analysis with 57 epithelial ovarian cancers (31 CCCs, 14 SCs, and 12 ECs) and microarray expression analysis with 55 cancers (25 CCCs, 16 SCs, and 14 ECs). We then evaluated PIK3CA mutations and ARID1A expression in CCCs. SNP array analysis classified 13% of CCCs into a cluster with high frequency and focal range of copy number alterations (CNAs), significantly lower than for SCs (93%, P < 0.01) and ECs (50%, P = 0.017). The ratio of whole-arm to all CNAs was higher in CCCs (46.9%) than SCs (21.7%; P < 0.0001). SCs with loss of heterozygosity (LOH) of BRCA1 (85%) also had LOH of NF1 and TP53, and LOH of BRCA2 (62%) coexisted with LOH of RB1 and TP53. Microarray analysis classified CCCs into three clusters. One cluster (CCC-2, n = 10) showed more favorable prognosis than the CCC-1 and CCC-3 clusters (P = 0.041). Coexistent alterations of PIK3CA and ARID1A were more common in CCC-1 and CCC-3 (7/11, 64%) than in CCC-2 (0/10, 0%; P < 0.01). Being in cluster CCC-2 was an independent favorable prognostic factor in CCC. In conclusion, CCC was characterized by a high ratio of whole-arm CNAs; whereas CNAs in SC were mainly focal, but preferentially caused LOH of well-known tumor suppressor genes. As such, expression profiles might be useful for sub-classification of CCC, and might provide useful information on prognosis.

Cell surface glycans show dynamic changes during cell differentiation. Several glycans are useful biomarkers of tumors, stem cells, and embryogenesis. Glycomic studies have been performed using liquid chromatography and mass spectrometry, which are powerful tools for glycan structural analysis but are difficult to use for small sample sizes. Recently, a lectin microarray system was developed for profiling cell surface glycome changes to terminal carbohydrate chains and branch types, using sample sizes of a few micrograms. In this study, we used the lectin microarray system for the first time to investigate stage-specific glycomes in Xenopus laevis embryos. Unsupervised cluster analysis of lectin microarray data indicated that glycan profiles changed sequentially during development. Nine lectin probes showed significantly different signals between early and the late-stage embryos: 4 showed higher signals in the early stages, and 5 exhibited higher signals in the late stages. The gene expression profiles of relevant glycosyltransferase genes support the lectin microarray data. Therefore, we have shown that lectin microarray is an effective tool for high-throughput glycan analysis in Xenopus embryogenesis, allowing glycan profiling of early embryos and small biopsy specimens.