A multi-omic study reveals BTG2 as a reliable prognostic marker for early-stage non-small cell lung cancer.
Sipeng ShenRuyang ZhangYichen GuoElizabeth LoehrerYongyue WeiYing ZhuQianyu YuanSebastian MoranThomas FleischerMaria M BjaanaesAnna KarlssonMaria PlanckJohan StaafÅslaug HellandManel EstellerLi SuFeng ChenDavid C ChristianiPublished in: Molecular oncology (2018)
B-cell translocation gene 2 (BTG2) is a tumour suppressor protein known to be downregulated in several types of cancer. In this study, we investigated a potential role for BTG2 in early-stage non-small cell lung cancer (NSCLC) survival. We analysed BTG2 methylation data from 1230 early-stage NSCLC patients from five international cohorts, as well as gene expression data from 3038 lung cancer cases from multiple cohorts. Three CpG probes (cg01798157, cg06373167, cg23371584) that detected BTG2 hypermethylation in tumour tissues were associated with lower overall survival. The prognostic model based on methylation could distinguish patient survival in the four cohorts [hazard ratio (HR) range, 1.51-2.21] and the independent validation set (HR = 1.85). In the expression analysis, BTG2 expression was positively correlated with survival in each cohort (HR range, 0.28-0.68), which we confirmed with meta-analysis (HR = 0.61, 95% CI 0.54-0.68). The three CpG probes were all negatively correlated with BTG2 expression. Importantly, an integrative model of BTG2 methylation, expression and clinical information showed better predictive ability in the training set and validation set. In conclusion, the methylation and integrated prognostic signatures based on BTG2 are stable and reliable biomarkers for early-stage NSCLC. They may have new applications for appropriate clinical adjuvant trials and personalized treatments in the future.
Keyphrases
- early stage
- dna methylation
- genome wide
- gene expression
- poor prognosis
- small cell lung cancer
- systematic review
- advanced non small cell lung cancer
- free survival
- binding protein
- small molecule
- end stage renal disease
- single molecule
- randomized controlled trial
- healthcare
- newly diagnosed
- machine learning
- case report
- deep learning
- transcription factor
- prognostic factors
- amino acid
- nucleic acid
- squamous cell
- atomic force microscopy
- virtual reality