PDF(Pubmed)
Abstract：
Biomarker screening is critical for precision oncology. However, one of the main challenges in precision oncology is that the screened biomarkers often fail to achieve the expected clinical effects and are rarely approved by regulatory authorities. Considering the close association between cancer pathogenesis and the evolutionary events of organisms, we first explored the evolutionary feature underlying clinically approved biomarkers, and two evolutionary features of approved biomarkers (Ohnologs and specific evolutionary stages of genes) were identified. Subsequently, we utilized evolutionary features for screening potential prognostic biomarkers in four common cancers: head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. Finally, we constructed an evolution-strengthened prognostic model (ESPM) for cancers. These models can predict cancer patients\' survival time across different cancer cohorts effectively and perform better than conventional models. In summary, our study highlights the application potentials of evolutionary information in precision oncology biomarker screening.
摘要：
生物标志物筛选对于精确肿瘤学至关重要。然而,精准肿瘤学的主要挑战之一是筛选的生物标志物往往无法达到预期的临床效果,而且很少获得监管部门的批准.考虑到癌症的发病机制和生物体的进化事件之间的密切关系，我们首先探索了临床批准的生物标志物的进化特征，并确定了两个已批准的生物标志物的进化特征（Ohnologs和特定的基因进化阶段）。随后，我们利用进化特征筛选四种常见癌症的潜在预后生物标志物：头颈部鳞状细胞癌，肝细胞癌，肺腺癌,和肺鳞状细胞癌。最后,我们构建了一个进化强化的癌症预后模型(ESPM).这些模型可以有效地预测癌症患者在不同癌症队列中的生存时间，并且比传统模型表现更好。总之,我们的研究强调了进化信息在精准肿瘤生物标志物筛查中的应用潜力.
