Genome-wide Detection of Chimeric Transcripts in Early-stage Non-small Cell Lung Cancer

Abstract

Background/aim: 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.

Materials and methods: 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.

Results: 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.

Conclusion: The data presented in this study allow researchers to identify, select, and validate promising candidates for targeted clinical interventions.

Keywords: JAFFA; Non-small cell lung cancer; RNA sequencing; fusion; transcript.