IOBR: Multi-Omics Immuno-Oncology Biological Research to Decode Tumor Microenvironment and Signatures

TLDR

Rapid growth of publicly available multi‑omics datasets from next‑generation sequencing has highlighted the need for tools that can comprehensively interpret these data to uncover mechanisms of oncogenesis and immunotherapeutic sensitivity, especially given the clinical success of immune checkpoint blockade. The authors developed IOBR to enable comprehensive investigation of signatures, tumor microenvironment deconvolution, and signature construction from multi‑omics data. IOBR integrates existing microenvironment deconvolution methods and signature construction tools, allowing users to estimate, deconvolve, and build signatures from multi‑omics data. IOBR facilitates batch analysis of signatures and their correlations with clinical phenotypes, lncRNA profiles, genomic features, and scRNA‑seq signatures across cancers, thereby accelerating precision immunotherapy.

Abstract

Recent advances in next-generation sequencing (NGS) technologies have triggered the rapid accumulation of publicly available multi-omics datasets. The application of integrated omics to explore robust signatures for clinical translation is increasingly emphasized, and this is attributed to the clinical success of immune checkpoint blockades in diverse malignancies. However, effective tools for comprehensively interpreting multi-omics data are still warranted to provide increased granularity into the intrinsic mechanism of oncogenesis and immunotherapeutic sensitivity. Therefore, we developed a computational tool for effective Immuno-Oncology Biological Research (IOBR), providing a comprehensive investigation of the estimation of reported or user-built signatures, TME deconvolution, and signature construction based on multi-omics data. Notably, IOBR offers batch analyses of these signatures and their correlations with clinical phenotypes, long non-coding RNA (lncRNA) profiling, genomic characteristics, and signatures generated from single-cell RNA sequencing (scRNA-seq) data in different cancer settings. Additionally, IOBR integrates multiple existing microenvironmental deconvolution methodologies and signature construction tools for convenient comparison and selection. Collectively, IOBR is a user-friendly tool for leveraging multi-omics data to facilitate immuno-oncology exploration and to unveil tumor-immune interactions and accelerating precision immunotherapy.