Hummingbird Diagnostics & Saarland University Cooperate on Cancer Detection

Hummingbird Diagnostics & Saarland University cooperate on the early detection of cancer by liquid biopsy employing miRNA fingerprints

Early detection as key for improved outcome

The maybe best strategy in the daily fight against cancer – besides preventive actions such as anti-smoking campaigns – is the in-time detection of malignant tumors. There is an undisputed clinical need for minimally or non-invasive diagnostics that facilitate sensitive and specific discovery of cancers. The panel of possible approaches that is currently explored by research groups and companies worldwide includes different molecular diagnostic options, including protein patterns, gene expression profiles, epigenetics or metabolic marker sets.

One of the most severe cases is lung cancer: despite the many different options, more than 60% of lung cancer patients are diagnosed in late stages with a five-year survival rate of 10%. In contrast, detection at stage I means a five-year survival rate that is 7-fold higher. But still, the clinical reality – admittedly leading to lung improved cancer detection – is low dose computer tomography (LD-CT). One challenge of LD-CT is however a limited positive predictive value of 4%. This means, of 100 individuals predicted to have lung cancer finally four have indeed a cancer.

Hummingbird Diagnostics (HBDx) pursues a unique approach. As molecular markers small-non-coding RNAs are measured. These are known as master regulators in many pathological and pathophysiological conditions. In contrast to other diagnostic strategies, HBDx does not aim at measuring molecules secreted by the tumor. The key to success is to profile cells of the immune system – the first line of defense against aggressors such as cancer cells.

The optimal combination: the right molecules and the right bio-specimens – miRNAs and immune cells

The innovation goes back to Professor Andreas Keller and Professor Eckart Meese, both from Saarland University. Keller is convinced that for a highly specific and sensitive diagnosis not only the right molecule class has to be identified. The right specimens that carries the diagnostic information in combination with the respective molecule class is key to success. As it seems, the team consisting of Human Genetics and Bioinformatics specialists has discovered an optimal combination: small non-coding RNAs that are measured from cells of the immune system, such as T- and B-cells facilitate minimally-invasive  an optimal combination. Over the past 8 years Keller and Meese, supported by various research grants and companies, increased the cohort sizes for different cancers – most importantly lung cancer – step by step to some hundred samples (1-5). At the same time the two groups systematically explored the influence of environmental conditions on blood-borne miRNA profiles. A broad understanding of the distribution and behavior of miRNAs was essential to select the right biomarkers. Factors include the age and gender (6), fitness conditions (7), bias by different high-throughput profiling approaches (8), coagulants such as EDTA (9) expression in different tissues of origin (10) and many others. The group was even the first to demonstrate stability of miRNAs in one of the most famous mummies in the world, the Tyrolean iceman, better known as Ötzi (11). Thereby, not only microarray based technique but also Next-Generation sequencing was applied, e.g. by using the new BGISEQ technology (12). From over 2,000 sequencing samples, HbDx and Saarland University jointly developed a custom array containing over 2,500 human (candidate) miRNAs that are expressed in blood. These contain in addition to 800 miRNAs from the current reference database miRBase, 1,300 new candidates and validated miRNAs. The microarray will be commercialy available in fall 2017.

It was also the cooperation with HBDx that allowed to prepare the next step in lung cancer diagnosis: translation from bench to bedside. The experience of HBDx in assay design and the use of the highly standardized SoPs increased the stability of the measurements. At the same time, the throughput could be drastically increased. Meese said that the transfer of the workflow from the university lab to the ISO certified lab and processes at HBDx resulted in significantly higher throughput. This year, the cohort sizes have been increased to above 1,000 lung cancer samples (predominantly non-small cell lung carcinoma) and controls. According to Keller, the results of the previous studies were basically confirmed by this large cohort collected in three German clinics: accuracy, specificity and sensitivity in the range of 90%. Publication of the results is expected later this year. Likewise promising results were obtained in measuring the diagnostic profiles not from blood tubes but from dried blood spots – as used in newborn screening programs. Respective results have recently been published in Clinical Chemistry. Also in this direction more results on similar blood collection devices will be published soon.

Lung cancer – but what’s next?

During their studies, the researchers recognized that many miRNAs are altered independent of the disease (13). This means that multiple diseases can be tackled with the proposed approach. Jochen Kohlhaas, CEO of HBDx sais that the ongoing lung cancer study has prototype character and that he considers the method as a diagnostic framework: with the same workflows different cancer and non-cancer diseases can be detected. Only one further example is the promising results in Alzheimer’s Disease (14,15). Keller warns that the consequence usually is a lack of specificity of single miRNAs, calling for complex diagnostic signatures and appropriate biostatistical tools (16). Having those, the power of miRNAs from blood cells seems to be very promising: in a Nature Methods article the group was able to separate 15 human pathologies by using different combinations of miRNAs (17).

  1. Keller, A., Leidinger, P., Borries, A., Wendschlag, A., Wucherpfennig, F., Scheffler, M., Huwer, H., Lenhof, H.P. and Meese, E. (2009) miRNAs in lung cancer – studying complex fingerprints in patient’s blood cells by microarray experiments. BMC Cancer, 9, 353.
  2. Keller, A., Backes, C., Leidinger, P., Kefer, N., Boisguerin, V., Barbacioru, C., Vogel, B., Matzas, M., Huwer, H., Katus, H.A. et al. (2011) Next-generation sequencing identifies novel microRNAs in peripheral blood of lung cancer patients. Mol Biosyst, 7, 3187-3199.
  3. Leidinger, P., Keller, A., Borries, A., Huwer, H., Rohling, M., Huebers, J., Lenhof, H.P. and Meese, E. (2011) Specific peripheral miRNA profiles for distinguishing lung cancer from COPD. Lung Cancer, 74, 41-47.
  4. Leidinger, P., Backes, C., Blatt, M., Keller, A., Huwer, H., Lepper, P., Bals, R. and Meese, E. (2014) The blood-borne miRNA signature of lung cancer patients is independent of histology but influenced by metastases. Mol Cancer, 13, 202.
  5. Leidinger, P., Brefort, T., Backes, C., Krapp, M., Galata, V., Beier, M., Kohlhaas, J., Huwer, H., Meese, E. and Keller, A. (2016) High-throughput qRT-PCR validation of blood microRNAs in non-small cell lung cancer. Oncotarget, 7, 4611-4623.
  6. Meder, B., Backes, C., Haas, J., Leidinger, P., Stahler, C., Grossmann, T., Vogel, B., Frese, K., Giannitsis, E., Katus, H.A. et al. (2014) Influence of the confounding factors age and sex on microRNA profiles from peripheral blood. Clin Chem, 60, 1200-1208.
  7. Backes, C., Leidinger, P., Keller, A., Hart, M., Meyer, T., Meese, E. and Hecksteden, A. (2014) Blood born miRNAs signatures that can serve as disease specific biomarkers are not significantly affected by overall fitness and exercise. PLoS One, 9, e102183.
  8. Backes, C., Sedaghat-Hamedani, F., Frese, K., Hart, M., Ludwig, N., Meder, B., Meese, E. and Keller, A. (2016) Bias in High-Throughput Analysis of miRNAs and Implications for Biomarker Studies. Anal Chem, 88, 2088-2095.
  9. Leidinger, P., Backes, C., Rheinheimer, S., Keller, A. and Meese, E. (2015) Towards Clinical Applications of Blood-Borne miRNA Signatures: The Influence of the Anticoagulant EDTA on miRNA Abundance. PLoS One, 10, e0143321.
  10. Ludwig, N., Leidinger, P., Becker, K., Backes, C., Fehlmann, T., Pallasch, C., Rheinheimer, S., Meder, B., Stahler, C., Meese, E. et al. (2016) Distribution of miRNA expression across human tissues. Nucleic Acids Res, 44, 3865-3877.
  11. Keller, A., Kreis, S., Leidinger, P., Maixner, F., Ludwig, N., Backes, C., Galata, V., Guerriero, G., Fehlmann, T., Franke, A. et al. (2017) miRNAs in Ancient Tissue Specimens of the Tyrolean Iceman. Mol Biol Evol, 34, 793-801.
  12. Fehlmann, T., Reinheimer, S., Geng, C., Su, X., Drmanac, S., Alexeev, A., Zhang, C., Backes, C., Ludwig, N., Hart, M. et al. (2016) cPAS-based sequencing on the BGISEQ-500 to explore small non-coding RNAs. Clin Epigenetics, 8, 123.
  13. Keller, A., Leidinger, P., Vogel, B., Backes, C., ElSharawy, A., Galata, V., Mueller, S.C., Marquart, S., Schrauder, M.G., Strick, R. et al. (2014) miRNAs can be generally associated with human pathologies as exemplified for miR-144. BMC Med, 12, 224.
  14. Leidinger, P., Backes, C., Deutscher, S., Schmitt, K., Mueller, S.C., Frese, K., Haas, J., Ruprecht, K., Paul, F., Stahler, C. et al. (2013) A blood based 12-miRNA signature of Alzheimer disease patients. Genome Biol, 14, R78.
  15. Keller, A., Backes, C., Haas, J., Leidinger, P., Maetzler, W., Deuschle, C., Berg, D., Ruschil, C., Galata, V., Ruprecht, K. et al. (2016) Validating Alzheimer’s disease micro RNAs using next-generation sequencing. Alzheimers Dement, 12, 565-576.
  16. Backes, C., Meese, E. and Keller, A. (2016) Specific miRNA Disease Biomarkers in Blood, Serum and Plasma: Challenges and Prospects. Mol Diagn Ther, 20, 509-518.
  17. Keller, A., Leidinger, P., Bauer, A., Elsharawy, A., Haas, J., Backes, C., Wendschlag, A., Giese, N., Tjaden, C., Ott, K. et al. (2011) Toward the blood-borne miRNome of human diseases. Nat Methods, 8, 841-843.