Research - Prolytic GmbH Quantifiizierung von miRNA unter GLP

Our research projects

After many years of experience in the development of bioanalytical methods for small and large molecules, we have turned to smaller structures: miRNAs.

Micro-RNAs (miRNAs) are a variation of RNA that play an important role in the development of cancer. miRNAs are specifically detectable in blood and can thus be used for the diagnosis and prognosis of various tumor diseases. Such so-called “biomarker” studies can help to identify a specific course of disease and to tailor therapy to the individual patient. Furthermore, specific RNA drugs that can block miRNAs represent a new class of drugs that can revolutionize the treatment of cancer. However, the advantages of these two therapeutic approaches can only be exploited if suitable analytics are available that have been validated under GLP conditions.

Our two research projects result from this problem

Determination of micro-RNAs and RNA therapeutics in human serum and plasma under Good Laboratory Practice (GLP) conditions

Essential basics for personalized miRNA diagnostics and prognostics

The basis of personalized medicine lies in the determination and analysis of biomarkers. Biomarkers represent natural parameters of biological processes in the body that have diagnostic or prognostic significance. Due to their high stability in blood or urine, microRNAs (miRNAs) are promising biomarkers for the diagnosis or prognosis of cancer and chronic inflammatory diseases. Despite the high number of miRNA biomarker studies, there is a problem with reproducibility because the results of many studies contradict each other. This results from the lack of standardization of the analysis of miRNAs in blood. With the validation of the method for miRNA isolation from plasma and the quantification by quantitative PCR under Good Laboratory Practice (GLP), we want to provide a basis for a standardized method for the analysis of miRNAs and thus enable the reproducible determination of miRNA biomarkers.

A cooperation project with Technical University Darmstadt since 2016; funded by the Central Innovation Programme for Small and Medium-Sized Enterprises (ZIM) of the Federal Ministry of Economics and Energy (BMWi).

Development of a diagnostic test based on miRNA-574-5p as a predictive biomarker for prostaglandin E2-mediated tumors

The future of successful therapies lies in personalized medicine

Using a previously standardized and GLP validated analytical method for the quantification of miRNAs from plasma, we will conduct an explorative biomarker study to determine miRNA-574-5p as a non-small cell lung cancer (NSCLC) stratification marker. MiRNA-574-5p increases the synthesis of prostaglandin E2 (PGE2), an important lipid mediator in the development of lung cancer. Consequently, PGE2 inhibition would be beneficial for the treatment of lung cancer. However, the use of PGE2 inhibitors is controversially discussed because success is not observed in all lung cancer patients. The suitability of therapy with PGE2 inhibitors depends on the type of lung cancer, as there are PGE2-dependent and PGE2-independent lung carcinomas. With the establishment of miRNA-574-5p as a biomarker, we hope to establish a threshold value in the blood from which a PGE2-dependent lung cancer can be predicted, and thus also the therapeutic outcome with PGE2 inhibitors. Such personalized therapy approaches can lead to a better therapy outcome and thus also to the avoidance of potentially ineffective therapies.

A research project in cooperation with Technical University Darmstadt and University of Gie├čen since 2019; funded by KMU-innovativ of the Federal Ministry of Education and Research (BMBF).

Find out more about our cooperation on the webpage of TU Darmstadt

Poster: Validated Analysis of miRNA according to GLP

At several congresses we presented our research results as posters in cooperation with TU Darmstadt.
You are welcome to download our poster “First validated extracellular miRNA quantification in blood samples using RT-qPCR” here.

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