肺癌仍然是全球癌症相关死亡的主要原因。转录融合在多种癌症的发生和发展中起着关键作用。基于对EGFR基因突变和NTRK、ROS1和ALK基因融合等驱动事件的具体靶向治疗方法，显著改善了临床预后。由基因组重排或转录后水平引起的嵌合蛋白质的形成广泛存在，并在肿瘤发生和发展中起到关键作用。但是，肺癌的融合谱景仍然未被充分探索。我们使用JAFFA流程在早期非小细胞肺癌(NSCLC)中发现转录融合。进一步分析检测到的融合事件，以识别复发事件、具有多个伙伴和具有高预测致癌潜力的融合。最后，我们使用广义线性模型(GLM)建立融合事件发生与临床病理变量之间的统计关联。我们使用RNA测序在选自Glans-Look标本库的270个早期NSCLC样本中发现和特征化转录融合。在化疗或放疗开始前的疾病早期获取这些样本。我们识别出792个融合，其中751个是新发现的，33个是复发性的。其中4个复发性融合与临床病理变量显著相关。一些融合伙伴由已建立的癌基因ERBB4、BRAF、FGFR2和MET代表。本研究所提供的数据可帮助研究人员确定、选择和验证有前途的靶向临床干预候选者(Copyright © 2023, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved)。

Lung cancer remains the main culprit in cancer-related mortality worldwide. Transcript fusions play a critical role in the initiation and progression of multiple cancers. Treatment approaches based on specific targeting of discovered driver events, such as mutations in EGFR, and fusions in NTRK, ROS1, and ALK genes led to profound improvements in clinical outcomes. The formation of chimeric proteins due to genomic rearrangements or at the post-transcriptional level is widespread and plays a critical role in tumor initiation and progression. Yet, the fusion landscape of lung cancer remains underexplored.We used the JAFFA pipeline to discover transcript fusions in early-stage non-small cell lung cancer (NSCLC). The set of detected fusions was further analyzed to identify recurrent events, genes with multiple partners and fusions with high predicted oncogenic potential. Finally, we used a generalized linear model (GLM) to establish statistical associations between fusion occurrences and clinicopathological variables. RNA sequencing was used to discover and characterize transcript fusions in 270 NSCLC samples selected from the Glans-Look specimen repository. The samples were obtained during the early stages of disease prior to the initiation of chemo- or radiotherapy.We identified a set of 792 fusions where 751 were novel, and 33 were recurrent. Four of the 33 recurrent fusions were significantly associated with clinicopathological variables. Several of the fusion partners were represented by well-established oncogenes ERBB4, BRAF, FGFR2, and MET.The data presented in this study allow researchers to identify, select, and validate promising candidates for targeted clinical interventions.Copyright © 2023, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.