Transcriptome Analysis of Ovarian and Uterine Clear Cell Malignancies

Abstract

PurposeOvarian and uterine clear cell carcinomas (CCCs) are rare but associated with poor prognosis. This study explored RNA transcription patterns characteristic of these tumors.Experimental DesignRNA sequencing (RNA-seq) of 11 ovarian CCCs and five uterine CCCs was performed and compared to publicly available data from high grade serous ovarian cancers (HGSOCs). Ingenuity Pathway Analyses were performed. CIBERSORT analyses estimated relative fractions of 22 immune cell types in each RNA-seq sample. Sequencing data was correlated with PD-L1 immunohistochemical expression.ResultsRNA-seq revealed 1,613 downregulated and 1,212 upregulated genes (corrected p < 0.05, |FC |≥10) in ovarian CCC versus HGSOC. Two subgroups were identified in the ovarian CCC, characterized by ethnicity and expression differences in ARID1A. There were 3,252 differentially expressed genes between PD-L1+/− ovarian CCCs, revealing immune response, cell death, and DNA repair networks, negatively correlated with PD-L1 expression, whereas cellular proliferation networks positively correlated with expression. In clear cell ovarian versus clear cell uterine cancer, 1,607 genes were significantly upregulated, and 109 genes were significantly downregulated (corrected p < 0.05, |FC|≥10). Comparative pathway analysis of late and early stage ovarian CCCs revealed unique metabolic and PTEN pathways, whereas uterine CCCs had unique Wnt/Ca+, estrogen receptor, and CCR5 signaling. CIBERSORT analysis revealed that activated mast cells and regulatory T cell populations were relatively enriched in uterine CCCs. The PD-L1+ ovarian CCCs had enriched resting NK cells and memory B cell populations, while PD-L1− had enriched CD8 T-cells, monocytes, eosinophils, and activated dendritic cells.ConclusionsUnique transcriptional expression profiles distinguish clear cell uterine and ovarian cancers from each other and from other more common histologic subtypes. These insights may aid in devising novel therapeutics.

Vitamin C Enhances Antiviral Functions of Lung Epithelial Cells

“…Pooled analysis was performed using the Audic-Claverie (AC) test, which pools together raw counts across three sets of vitamin-C-treated and untreated BEAS-2B cells, separately, and tests the differences between them based on a Poisson assumption of the distribution of counts. A multiple testing correction, Benjamini-Hochberg FDR (false discovery rate) of 0.05, and a maximum p-value cutoff of 0.05 were used as described previously [14,17]. The genes of the AC test were ranked based on adjusted p-value (FDR corrected), and cutoff was set at p adj < 0.05 to select for statistically significant differentially expressed genes between the vitamin-C-treated and untreated BEAS-2B cells.…”

RNA expression differences in prostate tumors and tumor-adjacent stroma between Black and White Americans

“…RNA quality and quantity were assessed using an Agilent 2100 Bioanalyzer and a Qubit fluorimeter, respectively. All samples exhibited a DV200 metric of over 30% of RNA with fragment sizes over 200 nucleotides, as previously described [52][53][54]. RNA expression profiling Oncotarget 10 www.oncotarget.com was performed using the Illumina Truseq RNA Access library preparation kit.…”

The Role of Omics Approaches to Characterize Molecular Mechanisms of Rare Ovarian Cancers: Recent Advances and Future Perspectives

“…Several studies have used RNA-Seq to differentiate between OCCC and other cancer types. For example, A previous study exploring differences between OCCC and uterine clear cell carcinomas (UCCC) found that 1607 genes were significantly upregulated and 109 genes were significantly downregulated in OCCC compared to UCCC [52]. Another study by Nagasawa and colleagues employed RNA-sequencing to identify fundamental differences between HGSOC, a common ovarian cancer subtype, with clear cell carcinoma [37].…”