Histological and Molecular Heterogeneity in Epithelial Ovarian Cancers

<p>Common genetic alterations vary between different epithelial ovarian cancer sub-types. Highlighted in red are genes/pathways commonly inactivated in tumours; highlighted in green are genes commonly activated or amplified in epithelial ovarian cancer tumour specimens. Hematoxylin and eosin stained sections show typical histological and architectural appearance of the high-grade serous, borderline serous, mucinous, clear cell, and endometrioid sub-types. Biomarkers listed are those found in the study by Huntsman and colleagues to be highly expressed (i.e., samples positive in over 60% of tumours, green arrow), or lowly expressed (red arrow) in each histological sub-type. Median Ki67 labelling indices (a measure of the proportion of proliferating cells in a tumour sample) are given in bold type.</p

Validation of exosome enrichment from human cell-free sera.

<p>(A) TEM micrographs of exosomes in ultracentrifugation (UC) and ExoQuick (EQ) preparations. Data for 6 independent patient samples are shown (P1-6). Exosomes confirmed by size (30-100nm) and appearance. Scale bar in each image represents 100 nm. (B) Immunoblot of CD63 in unprocessed cell-free serum alone (-), UC, and EQ exosomal preparations.</p

Comparison of sera exosomal RNA using four different RNA extraction methods.

<p>(A) Total RNA yield from ultracentrifugation (UC) and ExoQuick (EQ) treated samples using the RNeasy Mini Kit combined with TRIzol LS, the RNeasy Mini Kit alone, conventional RNA precipitation, and AllPrep DNA/RNA Mini Kit. (B) Demonstration of RNA quality measured by OD₂₆₀/OD₂₈₀ in EQ and UC treated samples. Data are shown as the mean ± SD from six independent patient samples. ***<i>P</i><0.001, **<i>P</i><0.01, *<i>P</i><0.05, ns, not significant, student’s <i>t</i> test. Note: RNA could not be extracted from some samples using the AllPrep kit due to clogging.</p

Flow chart for evaluation of exosomal RNAs from cell-free sera as biomarkers for human diseases.

<p>Graphic summary of the workflow including time allotment for preparation for cell-free serum (steps ①-③), comparison of methods for exosome enrichment (step ④), validation by transmission electron microscopy (TEM) and immunoblotting for CD63 or other exosomal markers (step ⑤), RNA extraction (step ⑥), and preparation of RNA-Seq libraries (step ⑦). 10–100 nanograms RNA can be used for library preparation with the NEBNext Ultra Directional RNA Library Prep Kit. Step ② is an optional centrifugation step that can be included to ensure the most efficient removal of trace amounts of cell debris and shedding microvesicles. A validation step can be performed with RT-qPCR for specific candidate RNA following RNA-Seq analysis (step ⑧).</p

Exosomal RNAs are stable over two decades.

<p>Dot plots of total RNA yield and OD₂₆₀/OD₂₈₀ from 105 EQ-treated archival patient samples using the RNeasy Mini Kit combined with TRIzol LS. Storage time for each sample is indicated on the x-axis. The Spearman’s rank correlations for RNA yield <i>versus</i> storing time and OD₂₆₀/OD₂₈₀ <i>versus</i> storage time are 0.185 (<i>P</i> = 0.06) and 0.04 (<i>P</i> = 0.70), respectively.</p

Minimal sera volume for exosome detection and RNA extraction.

<p>(A) Representative immunoblots for CD63 comparing exosome enrichment using ultracentrifugation (UC) and ExoQuick (EQ) among samples of varying volumes. (B) Scatter dot plots depict total exosomal RNA recovered per sample volume using EQ. (C) Scatter dot plots show RNA quality measured by OD₂₆₀/OD₂₈₀ per sample volume. Data are shown as the mean ± standard deviation (SD) from six independent patient samples. <i>P</i>-values were calculated using one-way ANOVA.</p

The most significantly differentially expressed genes between EAC G1 and USC G3.

<p>Performed using data from The Cancer Genome Atlas, listed in order of log2 fold change. The top 10 upregulated and downregulated genes are shown. Log₂ FC, log2 fold-change in gene expression for USC G3 relative to EAC G1; SE, standard error; BH, Benjamini & Hochberg adjusted p-values. ‘Mean’ denotes mean expression for each group based as normalized RNAseq reads.</p

Comparison of p16 gene and protein expression.

<p>(A) Linear regression shows p16 gene and protein expression are highly correlated in USC and EAC components of MT-ECs. Protein expression is denoted at the percentage of cells staining positive plotted against relative, normalized gene expression. (B) P16 protein expression in USC and EAC components of a mixed tumor. 400X magnification.</p

<i>PAX8</i> is differentially expressed between pure and mixed-type tumors.

<p>Normalized relative gene expression, the horizontal line indicates median expression, the box indicates the 25^th and 75^th percentiles of the data and dots represent outlier datapoints.</p

Patient information for samples used in this study.

<p>W, white; H, Hispanic.</p