Robust enumeration of cell subsets from tissue expression profiles (HGU133Plus2)

We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen, and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content, and closely related cell types. CIBERSORT should enable large-scale analysis of RNA specimens for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu). To evaluate the performance of CIBERSORT, RNA was extracted from the following primary human samples: (i) 14 disaggregated lymph node biopsies from patients with follicular lymphoma (FL), (ii) pre- and/or post-immunotherapy PBMC samples from 3 patients with extranodal marginal zone lymphoma (EMZL) or diffuse large B cell lymphoma (DLBCL), and (iii) B or T cells purified from the tonsils of 5 healthy normal controls.