Скачать или смотреть Webinar Leveraging transcriptomics for Cancer Research 2

Transcriptomics represents a critical discipline in cancer research, enabling comprehensive mapping of gene expression profiles and the identification of fusion genes implicated in tumor development. Achieving robust and reliable transcriptomic data depends on the extraction of high-quality RNA—a process that is highly sensitive to pre-analytical factors, such as the choice of blood collection tubes and extraction chemistries.

This webinar highlights the impact of RNA integrity achieved from blood-derived samples using various collection and preservation systems, with a focus on how these variables directly affect downstream analytical quality and interpretation in cancer transcriptomics. Emphasis is also placed on formalin-fixed paraffin-embedded (FFPE) tissue samples, which remain a mainstay in clinical research and archival studies despite the intrinsic challenges of RNA degradation and chemical modification.

Our data suggests that variations in extraction chemistry for FFPE tissues can lead to inconsistent fusion gene detection, highlighting the risk of overlooking critical genetic information crucial for cancer biomarker discovery and therapeutic targeting. Insights gained from workflow analyses of FFPE-derived RNA highlight the importance of optimizing extraction to improve sensitivity and specificity in fusion gene identification. This session advocates the best practices in sample extraction and handling, reinforcing the foundational role of RNA quality in advancing the reliability and translational value of cancer transcriptomics.


Learning Objectives
Critical pre-analytical factors, such as blood collection tubes and extraction chemistries, that significantly influence RNA integrity and subsequent analytical quality in cancer transcriptomics
How variations in RNA extraction methods from formalin-fixed paraffin-embedded (FFPE) tissue samples can lead to inconsistent fusion gene detection and impact the reliability of cancer biomarker discovery.
Best practices and optimized workflows for sample extraction and handling from both blood-derived and FFPE tissues to improve the sensitivity, specificity, and translational value of cancer transcriptomic data.