Reference genome and annotation updates lead to contradictory prognostic predictions in gene expression signatures: a case study of resected stage I lung adenocarcinoma. Issue 3 (8th May 2020)

• Record Type: Journal Article
• Authors: Zhang, Zheyang; Zhang, Sainan; Li, Xin; Zhao, Zhangxiang; Chen, Changjing; Zhang, Juxuan; Li, Mengyue; Wei, Zixin; Jiang, Wenbin; Pan, Bo; Li, Ying; Liu, Yixin; Cao, Yingyue; Zhao, Wenyuan; Gu, Yunyan; Yu, Yan; Meng, Qingwei; Qi, Lishuang
• Is Part Of: Briefings in bioinformatics. Volume 22:Issue 3(2021)
• Publication Date: 2020-05-08
• Subjects: conflicting annotation -- discordant risk classification -- lung adenocarcinoma -- relative expression order -- RNA-sequencing; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbaa081
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: RNA-sequencing enables accurate and low-cost transcriptome-wide detection. However, expression estimates vary as reference genomes and gene annotations are updated, confounding existing expression-based prognostic signatures. Herein, prognostic 9-gene pair signature (GPS) was applied to 197 patients with stage I lung adenocarcinoma derived from previous and latest data from The Cancer Genome Atlas (TCGA) processed with different reference genomes and annotations. For 9-GPS, 6.6% of patients exhibited discordant risk classifications between the two TCGA versions. Similar results were observed for other prognostic signatures, including IRGPI, 15-gene and ORACLE. We found that conflicting annotations for gene length and overlap were the major cause of their discordant risk classification. Therefore, we constructed a prognostic 40-GPS based on stable genes across GENCODE v20-v30 and validated it using public data of 471 stage I samples (log-rank P < 0.0010). Risk classification was still stable in RNA-sequencing data processed with the newest GENCODE v32 versus GENCODE v20–v30. Specifically, 40-GPS could predict survival for 30 stage I samples with formalin-fixed paraffin-embedded tissues (log-rank P = 0.0177). In conclusion, this method overcomes the vulnerability of existing prognostic signatures due to reference genome and annotation updates. 40-GPS may offer individualized clinical applications due to its prognostic accuracy and classification stability.