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Ovarian cancer Ovarian cancerOvarian cancer is a cancer that forms in or on an ovary. Over 95% of cases consist of ovarian carcinomas which develop in the epithelial tissue, a thin lining that covers the outside of an ovary. In the remaining cases, ovarian cancer develops from stromal or germ cells (Arora T et al. (2024)). More than 70% of ovarian cancer cases are diagnosed at a late stage, leading to a poor prognosis. Currently, diagnosis is based on histopathological examination. The best biomarker is serum glycoprotein CA125 which is overexpressed in more than 80% of ovarian cancer patients (Zhang R et al. (2022)). It may occur at any age but is more common in patients older than 50 years. Ovarian cancer is the fifth most common cause of cancer death in women (Penny SM. (2020)). Differential Abundance Analysis ResultsThis section presents the results of the differential protein abundance analysis, visualized through a volcano plot and summarized in the accompanying table for all three comparisons: 1) disease vs. healthy samples, 2) disease vs. diseases from the same class, and 3) disease vs. all other diseases. Disease vs Healthy
Disease vs Class
Disease vs All other
Figure 1: In the volcano plot, proteins are plotted based on their fold change (logFC) on the x-axis and the statistical significance of the change (-log10 adjusted p-value) on the y-axis. Proteins considered differentially abundant are highlighted, defined by an adjusted p-value < 0.05 and an absolute logFC > 0.5.
Table 1: The summary table lists the results for all comparisons, sorted by p-value by default. It includes key metrics such as fold change and adjusted p-value, to allow exploration of the most significant proteins for each comparison.
Figure 1: In the volcano plot, proteins are plotted based on their fold change (logFC) on the x-axis and the statistical significance of the change (-log10 adjusted p-value) on the y-axis. Proteins considered differentially abundant are highlighted, defined by an adjusted p-value < 0.05 and an absolute logFC > 0.5.
Table 1: The summary table lists the results for all comparisons, sorted by p-value by default. It includes key metrics such as fold change and adjusted p-value, to allow exploration of the most significant proteins for each comparison.
Figure 1: In the volcano plot, proteins are plotted based on their fold change (logFC) on the x-axis and the statistical significance of the change (-log10 adjusted p-value) on the y-axis. Proteins considered differentially abundant are highlighted, defined by an adjusted p-value < 0.05 and an absolute logFC > 0.5.
Table 1: The summary table lists the results for all comparisons, sorted by p-value by default. It includes key metrics such as fold change and adjusted p-value, to allow exploration of the most significant proteins for each comparison.
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The Project
The Human Protein Atlas
The Human Protein Atlas project is funded
