Pancreatic cancer belongs among the most lethal tumors with the lowest survival rate of all cancers. It is expected to become the second leading cause of cancer-related death in the US as well as Europe by the year 2020. Pancreatic cancer is very hard to be diagnosed at early stages. Screening tests or examinations may be used to look for a disease in people who have no symptoms. However, neither the imaging tests (CT, MRI, etc) nor the invasive methods (percutaneous, endoscopic, or surgical biopsy) are applicable for larger-scale population screening and demonstrate limitations in the sensitivity of detection of tumors at an early stage. There is an urgent need for an effective non-invasive method with a sufficiently high sensitivity and specificity.
The mass spectrometry (MS) based analysis of the lipids dysregulation of non-invasively collected samples of pancreatic cancer patients and healthy volunteers allows the build up of the statistical models, which may be used to determine the probability of an individual suffering from pancreatic cancer. The whole methodology is based on accurate performance of multiple steps; including mainly the sample collection, storage, transport and processing, followed by analytical qualitative and quantitative analysis using one of three mass spectrometry based methods and then multivariate data analysis (MDA) of obtained absolute quantitative data. The sensitivity and specificity through this method of determination is very high, typically 95-100%. The method can be used for population screening, specifically selected population groups based on risk factors such as family history, age, gender, body-mass-index, genetic predispositions, risk behaviour etc.
We understand that early diagnosis of pancreatic cancer in stage T1 and T2 is the only chance to increase patients´ survival rate. 91% of pancreatic cancer patients die within a few months, because they are diagnosed in an advanced and incurable stage. Selective screening of high risk individuals is essential.
The sample throughput of our methodology is 10,000 samples per year per one MS system with possible improvements using automation and multiplexing. The methodology is validated in line with recommendations from authoritative organizations, such as The Food and Drug Administration (FDA) or European Medicines Agency (EMEA). The bigger validation studies with 1000 samples (healthy controls vs pancreatic ductal adenocarcinoma (PDAC) patients and first-degree relatives (FDR) of pancreatic cancer patients) were performed in the Czech Republic in cooperation with University Hospital in Olomouc, Czech Republic. From this study, the technology discriminated patients in stage I to IV pancreatic cancer from healthy controls with an accuracy of ≥ 95%.