easier: interpretable predictions of antitumor immune response from bulk RNA-seq data

Abstract

Immunotherapy with immune checkpoint blockers (ICB) is associated with striking clinical success, but only in a small fraction of patients. Thus, we need computational biomarker-based methods that can anticipate which patients will respond to treatment. Current established biomarkers are imperfect due to their incomplete view of the tumor and its microenvironment. We have recently presented a novel approach that integrates transcriptomics data with biological knowledge to study tumors at a more holistic level. Validated in four different solid cancers, our approach outperformed the state-of-the-art methods to predict response to ICB. Here, we introduce estimate systems immune response (easier), an R/Bioconductor package that applies our approach to quantify biomarkers and assess patients’ likelihood to respond to immunotherapy, providing just the patients’ baseline bulk-tumor RNA-sequencing (RNA-seq) data as input.

Mathematically mapping the network of cells in the tumor microenvironment

“…We used our "easier" R/Bioconductor package 26,88 to compute a score of immune response based on the median of the z-score values of 10 published transcriptomics signatures of the immune response. All these signatures were calculated according to the methodology reported by the original studies.…”