Gene expression estimates detected by RNA-sequencing technology vary with the updates of reference genome and gene annotation, which might confound existing expression-based prognostic signatures, making them inapplicable to clinical practice. In this study, we proposed a method to decrease these effects and developed a qualitative signature for stage I lung adenocarcinoma, whose classification was based on within-sample relative expression orderings (REOs) of gene pairs. The signature was validated in 471 stage I samples derived from public RNA-sequencing and microarray data (both log-rank p < 0.001). Notably, our signature could effectively predict prognosis for 30 stage I patients with severely degraded FFPE tissues (log-rank p = 0.0177). More important, the risk classification was stable in the latest annotation. In summary, our signature would be a promising signature for clinical individualized application because of its excellent prognostic performance and classification robustness. SOURCE: Lishuang Qi (qilishuang7@ems.hrbmu.edu.cn) -  Harbin Medical University

Pluto Bioinformatics

GSE143486: Contradictory of gene expression signatures for clinical prognostic prediction caused by update of reference genome and annotation