基因组
计算生物学
1000基因组计划
注释
基因
肺癌
癌症基因组测序
生物
基因签名
基因表达谱
阶段(地层学)
计算机科学
癌症研究
肿瘤科
转录组
微阵列分析技术
生物信息学
小桶
腺癌
作者
Zheyang Zhang,Sainan Zhang,Xin Li,Zhangxiang Zhao,Changjing Chen,Ju-Xuan Zhang,Mengyue Li,Zixin Wei,Wenbin Jiang,Bo Pan,Ying Li,Yixin Liu,Yingyue Cao,Wenyuan Zhao,Yunyan Gu,Yan Yu,Qingwei Meng,Lishuang Qi
摘要
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.
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