Our multi-omic results quantify the benefit of combining DNA and RNA profiles from GenMineTOP to classify tumor-of-origin from unknown primaries reduces classification error by approximately 50%. Additionally, our expression-based MSI status prediction model not only significantly improves NGS DNA (MSI-sensor) based MSI prediction (log-ratio test, pval < 1e-7) but also strongly suggests that nonlinear differential expression drives the improvement in MSI prediction. Our multi-modality results demonstrate that mining the spatial context of endogenous tumor immune response has nontrivial prognostic utility (p < .05).
"REALM IDx, Inc...announced...that GenMineTOP Cancer Genome Profiling System...has been awarded national health coverage in Japan and will begin full commercial launch of contract testing with strategic partner, LSI Medicine Corporation...In the United States and global regions outside of Japan, the company will offer a research-use version of GenMineTOP for clinical research and the investigation of new targeted therapies for cancer treatment."