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MS lipidomics for early diagnosis of pancreatic cancer

Technology Overview

The mass spectrometry (MS) based analysis of the lipid dysregulation of body fluid samples of pancreatic cancer patients and healthy volunteers enables to build up the statistical models, which may be used to determine the level of probability of the patient 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 analysis using ultrahighperformance supercritical fluid chromatography - mass spectrometry (UHPSFC/MS), shotgun MS and matrix assisted laser desorption/ionization (MALDI), followed by multivariate data analysis (MDA) of obtained absolute quantitative data. The method is suitable for high-throughput screening of the high-risk individuals. 10,000 samples can be analyzed per year per 1 MS system and 1 operator. The validation study with 400 samples was performed in the Czech Republic and discriminated patients in stage I to IV from healthy controls with an accuracy ≥ 95%.

Technology Features & Specifications

Changes in the lipid glycosylation occur quickly and dramatically at various stages of development, differentiation and oncogenesis. Large number of glycosylation patterns have been detected for lipids in the human cancer samples.  The main advantage of the lipidomic approach over the conventional proteomic based Healthcare - Diagonostics is the fact that the lipidomic plasma analysis using MS is ideally suited for screening purposes due to very high sensitivity (current front-end mass spectrometry instrumentation), specificity (advanced multivariate data analysis methods) and robustness (internal standards with odd number of carbon atoms in fatty acyl chains). Advantages : • biological fluid, sample volume 10-25μl • the sample throughput is 10,000 samples per year and one MS system • specific signaling lipids dysregulation – up to 400 species – cancer fingerprint • early stage dysregulation - detection of curable stages T1, T2 • advanced bioinformatics, evaluation software • YES/NO answer about the patient status • T1, T2 accuracy = 95-100% • validation studies - 400 samples (healthy controls vs PDAC patients), Czech patient cohorts • validated in line with recommendations of FDA and EMEA

Potential Applications

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, and no genetic predispositions. However, neither the imaging tests (CT, MRI, etc.) nor the invasive methods (percutaneous, endoscopic, or surgical biopsy) are applicable for large-scale population screening and demonstrate sensitivity limitations in the 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 sensitivity and specificity is very high, typically 95-100%. The method can be used for population screening of the whole population or selected population groups based on risk factors. 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. It is also suitable for monitoring of treatment progress.

Customer Benefits

Total addressable market for pancreatic cancer will include high risk individuals (to examine 2-3 times a year) and it represents approx. 4 000 000 individuals in EU and US per year – price per 1 sample MS analysis is expected below 40 EUR. Current throughput approx. 10,000 subjects/year/system could be improved using multiplexing and other optimization. The overall addressable market will be expanded by further cancers – prostate, lungs, breast, kidney. Many cancer types have no or only minor symptoms at early stages, so the common situation is that the patient is diagnosed too late. The prognosis is much better when the disease is recognized earlier, but the currently available diagnostic methods are expensive, and laborious, which is unsuitable for routine population screening. The screening methods have to fulfil several requirements, such as available treatment for early diagnosed disease with significantly better prognosis compared to late diagnosis, sufficiently high sample throughput to be able to perform at least a partial population screening of individuals at higher risk, the screening price has to be acceptable for the healthcare system in relation to the benefits obtained by early diagnosis, etc.

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