Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration
Wenyi Wang, MD, Anderson Cancer Center
Friday, 21 July 2017, 11am to 12pm
Big Data Institute Seminar Room 0
We develop a novel method DeMixT for the gene expression deconvolution of three compartments in cancer patient samples: tumor, immune and surrounding stromal cells. In validation studies using mixed cell line and laser-capture microdissection data, DeMixT yielded accurate estimates for both cell proportions and compartment-specific expression profiles. Application to the head and neck cancer data shows DeMixT-based deconvolution provides an important step to link tumor transcriptome data with clinical outcomes.