Lung cancer is one of the major causes of cancer-related mortality worldwide. High-throughput RNA sequencing (RNA-seq) of surgically removed tumors has been used to identify new biomarkers of lung cancer; however, contamination by non-tumor cells in the tumor microenvironment significantly interferes with the search for novel biomarkers. Tumor organoids, as a pre-clinical cancer model, exhibit similar molecular characteristics with tumor samples while minimizing the interference from other cells.
Here we analyzed six RNA-seq datasets collected from different organoid models, in which cells with oncogenic mutations were reprogrammed to mimic lung adenocarcinoma (LUAD) tumorigenesis. We uncovered 9 LUAD-specific biomarker genes by integrating transcriptomic data from multiple sources, and identified IRAK1BP1 as a novel predictor of LUAD disease outcome. Validation with RNA-seq and microarray data collected from multiple patient cohorts, as well as patient-derived xenograft (PDX) and lung cancer cell line models confirmed that IRAK1BP1 expression was significantly lower in tumor cells, and had no correlation with known markers oflung cancer prognosis. In addition, loss of IRAK1BP1 correlated with the group of LUAD patients with worse survival; and gene-set enrichment analysis using tumor and cell line data implicated that high IRAK1BP1 expression was associated with suppression of oncogenic pathways.
In conclusion, we demonstrate that IRAK1BP1 is a promising biomarker of LUAD prognosis.