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Pancreatic cancer Pancreatic cancerPancreatic cancer is a disease where abnormal cells grow in the pancreas, often leading to symptoms like abdominal pain, weight loss, and jaundice. The most common form is pancreatic ductal adenocarcinoma, which originates in the cells lining the ducts that transport digestive enzymes. Pancreatic cancer is a major cause of cancer mortality, being the seventh leading cause of cancer death worldwide (Ilic M et al. (2016)). It is an aggressive cancer that is resistant to traditional therapeutics such as chemotherapy and radiotherapy. Pancreatic cancer in particular is difficult to treat because it is often diagnosed at later stages of disease and presents few to no symptoms. However, there is a large window for early diagnosis because it can take up to 10 years for malignancies to metastasize. Some of the risk factors include smoking, alcohol consumption, obesity, age, and genetic history. Pancreatic cancer is identified through a multidetector CT scan, and progression of disease can be measured by CA19-9 for the majority of the population (MayoClinic). 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
