Upfront whole blood transcriptional patterns in patients receiving immune checkpoint inhibitors associate with clinical outcome.

Whole blood (WB) transcriptomics offers a minimal-invasive method to assess patients' immune system. This study aimed to identify transcriptional patterns in WB associated with clinical outcomes in patients treated with immune checkpoint inhibitors (ICIs). We performed RNA-sequencing on pre-treatment WB samples from 145 patients with advanced cancer. Additionally, we compiled a separate dataset of 14,085 WB transcriptomes from diverse health backgrounds from public repositories and applied consensus-independent component analysis (c-ICA) to identify transcriptional components (TCs). The biological processes represented by these TCs were elucidated using gene set enrichment analysis. The activity of the TCs was then quantified in the 145 WB profiles and analyzed for associations with tumor response, progression-free survival, and overall survival using univariate and multivariate analyses in a permutation framework. RNA-sequencing variant calling was performed, and the activity of the TCs was assessed in specific cell lineages using a single-cell immune cell atlas of the human hematopoietic system. c-ICA on 14,085 WB transcriptomes identified 1262 distinct TCs representing various cellular processes. Of these, 18 TCs were associated with ≥ 1 outcome parameter, with three specifically linked to tumor response. Top genes in these three TCs included CCHCR1, TCF19, LTA, DDX39B, and PPP1R18. RNA-sequencing variant calling and single-cell transcriptome projections revealed associations between these four TCs and germline variants. These findings support the potential of the identified WB-based transcriptional patterns to complement tumor characteristics in predictive and prognostic models for improved patient stratification.