Webinar: Targeted Detection of MET and NTRK Oncogenic Variants in Routine Molecular Analysis

Cancer Tumor
Cancer Tumor

Date: November 13, 2019

Time: 7:00 am Pacific Time / 10:00 am Eastern Time

Location: Online

This webinar will discuss advances in detecting MET and NTRK variants in tumor samples, which holds significant potential for diagnostic and research applications.

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MET oncogenic variants leading to diverse exon 14 splicing alterations are emerging as a new predictive biomarker that would be sensitizing to MET-targeted tyrosine kinase inhibitors. The splice site DNA somatic variants result in RNA splicing-based skipping of MET exon 14, which supports targeted therapies.

Fusions in the NTRK1, NTRK2 and NTRK3 genes, which encode neurotrophin receptors TRKA, TRKB and TRKC, result in overexpressed kinase function, leading to oncogenesis in a wide variety of adult and pediatric solid tumors. Novel compounds have recently been developed that selectively inhibit TRK fusion proteins. As these alterations affect multiple histologies, detecting the presence of fusions across these genes greatly advances clinical cancer research.

In this webinar, Prof. Hans-Ulrich Schildhaus will present results from a study using a targeted, MALDI-TOF based method for the detection of MET exon 14 alterations and fusions across NTRK1, NTRK2 and NTRK3, and its applicability for routine screening.

Speaker:

Prof. Dr. Med. Hans-Ulrich SchildhausProf. Dr. Med. Hans-Ulrich Schildhaus
Professor of Tumor Pathology & Head of the Molecular Pathology Laboratory
Center for Pathology, Neuropathology and Forensic Medicine, University Medical Center Essen, University Duisburg-Essen

Dr. Hans-Ulrich Schildhaus is Professor of Tumor Pathology and Head of the Molecular Pathology Laboratory at the Center for Pathology, Neuropathology and Forensic Medicine at University Medical Center Essen, Germany. He has longstanding experience in diagnostic molecular pathology and lung cancer diagnostics. His main scientific focus is on developing methods for predictive biomarkers in solid cancers.

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