The study presents the development of an RNA-based diagnostic platform, TME Panel-1, which classifies tumor microenvironment (TME) phenotypes using an artificial neural network model. TME Panel-1 was validated with data from gastric cancer patients treated with checkpoint inhibitors and tested on additional datasets, including bavituximab and navicixizumab clinical trials. The panel accurately stratified patients by their dominant TME biology, predicting therapeutic responses and outperforming standard biomarkers. This platform offers potential for precision medicine, enhancing treatment selection and outcomes for various cancers by targeting specific TME characteristics.
Published at SITC 2020.
Kristen Strand-Tibbitts1, Kerry Culm-Merdek1, Luka Ausec2, Matjaž Žganec2, Miha Štajdohar2, Jeeyun Lee3, Laura Benjamin1 and Rafael Rosengarten2
1 OncXerna Therapeutics, Inc., Waltham, MA
2 Genialis, Inc., Boston, MA 02115
3 Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
