Automated RNA Extraction from Plasma Analytically Validated
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By LabMedica International staff writers Posted on 28 Nov 2017 |
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Image: Sample application for a VeriStrat assay. The assay provides highly sensitive results in 72 hours for non-small cell lung cancer (NSCLC) patients (Photo courtesy of Biodesix).
A novel, automated method for extracting circulating RNA from plasma has been demonstrated and the method performed equivalently or better than the established manual method that is currently used.
A team of scientists utilized a commercially-available laboratory developed test (LDT) for echinoderm microtubule-associated protein-like 4 (EML4-ALK) messenger ribonucleic acid (mRNA) fusion variants as a reference assay to assess the performance of an automated solution for RNA extraction that was developed and optimized by Norgen Biotek Corporation (Thorold, ON, Canada). Results suggest that the automated method performed at least equivalently to the established manual method on all measures in the study, including quality and yield of mRNA from analytic blood samples.
The GeneStrat test (Biodesix, Boulder, CO, USA) is a blood-based genomic test for patients with lung cancer that can inform the use of targeted therapies; test results are available within 72 hours. The test delivers results for EGFR sensitizing; EGFR resistance (T790M), KRAS, and BRAF mutations; and EML4-ALK, ROS1 and RETS fusion variants. The liquid biopsy test measures circulating tumor DNA and RNA with a highly-sensitive droplet digital PCR (ddPCR) platform.
Gary Pestano, PhD, Vice President of Development and Operations at Biodesix, said, “As molecular testing becomes the standard in oncology, automation will be increasingly important to help us maintain the high quality of our test results and continue to meet our industry-leading 72-hour turnaround time. The data presented suggest that it is possible to automate testing without sacrificing performance. They represent one of many evaluations we are conducting to assess potential automation methods for the Biodesix Lung Reflex with both our GeneStrat and VeriStrat tests.” The study was presented at the Association for Molecular Pathology Annual Meeting held November 16-18, 2017, in Salt Lake City, UT, USA.
Related Links:
Norgen Biotek
Biodesix
A team of scientists utilized a commercially-available laboratory developed test (LDT) for echinoderm microtubule-associated protein-like 4 (EML4-ALK) messenger ribonucleic acid (mRNA) fusion variants as a reference assay to assess the performance of an automated solution for RNA extraction that was developed and optimized by Norgen Biotek Corporation (Thorold, ON, Canada). Results suggest that the automated method performed at least equivalently to the established manual method on all measures in the study, including quality and yield of mRNA from analytic blood samples.
The GeneStrat test (Biodesix, Boulder, CO, USA) is a blood-based genomic test for patients with lung cancer that can inform the use of targeted therapies; test results are available within 72 hours. The test delivers results for EGFR sensitizing; EGFR resistance (T790M), KRAS, and BRAF mutations; and EML4-ALK, ROS1 and RETS fusion variants. The liquid biopsy test measures circulating tumor DNA and RNA with a highly-sensitive droplet digital PCR (ddPCR) platform.
Gary Pestano, PhD, Vice President of Development and Operations at Biodesix, said, “As molecular testing becomes the standard in oncology, automation will be increasingly important to help us maintain the high quality of our test results and continue to meet our industry-leading 72-hour turnaround time. The data presented suggest that it is possible to automate testing without sacrificing performance. They represent one of many evaluations we are conducting to assess potential automation methods for the Biodesix Lung Reflex with both our GeneStrat and VeriStrat tests.” The study was presented at the Association for Molecular Pathology Annual Meeting held November 16-18, 2017, in Salt Lake City, UT, USA.
Related Links:
Norgen Biotek
Biodesix
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