D. Michiel Pegtel,
Associate Professor,
Amsterdam University Medical Center
Michiel Pegtel conducted practical training as an undergraduate student at the National Cancer Institute (Bethesda,USA) and obtained a PhD in Immunology at Tufts University Medical School (Boston,USA) working on Epstein virus-induced cancers in collaboration with the MIT/Harvard Broad Institute (Cambridge,USA). After postdoctoral training at the Netherlands Cancer Institute (Amsterdam, Netherlands) working on tumor cell biology, he started the ERG at the Amsterdam UMC working on virus-modified EVs. Michiel was recognized by Clarivate in 2021 as one of the world’s highly cited researchers. Current members of his group investigate i) the molecular dynamics of EV biogenesis and release ii) small RNA sorting into EVs and iii) exploiting exosomes for drug delivery. For his early discovery of functional miRNA transfer via exosomes Michiel was awarded the Beijerinck Virology Premium from the Royal Dutch Academy of Sciences. He is an inventor of multiple patents and cofounder of ExBiome a molecular diagnostics start-up aimed at developing liquid biopsy tests focusing on hematological cancers.
Plasma Extracellular Vesicle-Associated microRNAs for On-Treatment Response Monitoring and Prediction
Tuesday, 20 June 2023 at 12:30
Add to Calendar ▼2023-06-20 12:30:002023-06-20 13:30:00Europe/LondonPlasma Extracellular Vesicle-Associated microRNAs for On-Treatment Response Monitoring and PredictionCirculating Biomarkers and Extracellular Vesicles Europe 2023 in Rotterdam, The NetherlandsRotterdam, The NetherlandsSELECTBIOenquiries@selectbiosciences.com
Response monitoring and outcome prediction is essential in the clinical management of hematological malignancies. Extracellular Vesicle associated microRNAs (EV-miRNAs) are considered promising liquid biopsy-based biomarkers for hematological malignancies. We performed small RNA sequencing of plasma samples collected during therapy and applied machine learning to build signatures for response prediction in Multiple Myeloma (MM) and patients with high grade B-cell lymphoma (HGBL). We collected plasma samples from multiple clinical trials and obtained 'real-world' samples. In HGBL, response was assessed by an end-of-treatment (EOT) PET/CT while in MM we defined response based in part on M protein levels. We isolated plasma EVs with size exclusion chromatography as confirmed with transmission electron microscopy (TEM), tunable resistive pulse sensing (TRPS), and western blotting. Library preparation was done according to our IsoSeek method. We applied machine learning to build models with EV-miRNAs for early response prediction (HGBL) and monitoring (MM). We could generate robust signatures for HGBL that can predict EOT response after one cycle of R-CHOP. If validated in independent cohorts, this novel approach could potentially, in combination with other modalities, guide early risk-adapted treatment strategies. In addition, we show that EV-miRNAs distinguish MM patients with active disease from those in remission. Together our data suggests plasma EV-miRNA sequencing is a versatile platform technology for minimally invasive response evaluation and prediction.
Add to Calendar ▼2023-06-19 00:00:002023-06-20 00:00:00Europe/LondonCirculating Biomarkers and Extracellular Vesicles Europe 2023Circulating Biomarkers and Extracellular Vesicles Europe 2023 in Rotterdam, The NetherlandsRotterdam, The NetherlandsSELECTBIOenquiries@selectbiosciences.com
Add to Calendar ▼2023-06-20 12:30:002023-06-20 13:30:00Europe/LondonPlasma Extracellular Vesicle-Associated microRNAs for On-Treatment Response Monitoring and PredictionCirculating Biomarkers and Extracellular Vesicles Europe 2023 in Rotterdam, The NetherlandsRotterdam, The NetherlandsSELECTBIOenquiries@selectbiosciences.com
