This online seminar focused on recent advances in gene expression profiling of challenging formalin-fixed, paraffin-embedded tissue samples for cancer research and clinical practice. Presentations covered studies in non-small cell lung cancer and pancreatic cancer.
Our first speakers, Adi Gazdar and Luc Girard from UT Southwestern Medical Center, discussed an expression-based assay for the pathological classification of non-small cell lung cancer.
Most NSCLCs are diagnosed from small specimens, and classification using standard pathology methods can be difficult. This is of clinical relevance as many therapy regimens and clinical trials are histology-dependent. Dr. Gazdar and Dr. Girard developed a 62-gene mRNA expression signature as an adjunct test for routine histopathological classification of NSCLCs, which includes many genes used in immunostains for NSCLC typing.
In order to demonstrate the clinical practicality and cost-effectiveness of the classifier, they developed a research-use, custom assay based on the HTG EdgeSeq technology. The classifier can be applied to small FFPE samples and core-needle biopsies, demonstrating the potential for deployment of routine RNA testing in standard clinical practice.
Next, Bryan Lo of the Ottawa Hospital discussed a method for gene expression profiling of pancreatic cancer precursors directly from FFPE tissues without nucleic acid extraction.
Gene expression analysis of pancreatic intraepithelial neoplasia’s (PanINs), the classical pancreatic cancer precursor, has been challenging because extracting and purifying RNA from pancreatic tissue is difficult. Since the pancreas is rich in ribonucleases and PanINs are typically very small lesions, attempts to purify RNA of sufficient quality and quantity for microarray or RNAseq are usually unsuccessful. This is especially true if the starting material is FFPE tissue, where the fixation process introduces further degradation of the RNA.
Dr. Lo and colleagues have shown in a pilot study that they can use the HTG EdgeSeq Oncology Biomarker Panel to profile approximately 2,500 genes from a cohort of microdissected low- and high-grade PanIN lesions from human pancreatic cancer resections that have been archived as FFPE tissue blocks.
Dr. Lo and colleagues believe that most of these PanIN lesions would not have been amenable to other gene expression methodologies and that the PanIN data collected using the HTG EdgeSeq technology will contribute to a better understanding of the molecular pathways that underlie pancreatic cancer.