Abstract


Performance of genome-wide targeted RNA expression technology based on multiplex RT-PCR-NGS for discovery of novel biomarkers in whole blood, and tumorigenesis mechanisms in xenograft mouse model

Dr Alex Chenchik, Ph.D

President & CEO Cellecta

Inc. USA

Aim : Application of targeted RNA expression for profiling infiltrating immune cells and cellular composition in tumor biopsy samples.

New rapid and robust transcriptome-based methods for cellular characterization of the tumor microenvironment and biomarker discovery are required to improve prognosis and treatment of cancer and other diseases. However, challenges with current approaches for the above applications include high sample requirements, poor sensitivity, low dynamic range, and limited throughput. To address these limitations, we have developed the Driver-Map targeted RNA expression profiling assay using a genome-wide set of 19,000 validated primer pairs that leverages the sensitivity of multiplex RT-PCR with the throughput and digital readout depth of Next-Generation Sequencing (NGS). Starting from just 10pg (single-cell) to 100ng (10,000 cells) of total RNA is sufficient to quantify over 5 orders of magnitude variation in gene expression levels with performance similar to conventional qRT-PCR. Further, the use of gene-specific primers enables direct analysis of total RNA isolate and obviates the need for globin and rRNA depletion from whole blood samples. In this study, we present the performance of the assay for immunophenotyping of immune cells in whole blood samples from sepsis patients and assess the immune responses to complex immunomodulatory stimuli in ex vivo model system. We will also present profiling results that demonstrate how this assay can be used to analyze the level of immune cell infiltration in tumor samples, and identify active pathways in tumor and xenograft samples. Preliminary studies demonstrate the assay’s unparalleled specificity and sensitivity resulting in better detection of low abundance mRNA transcripts as well as an improved cost-effectiveness for high-throughput clinical applications.