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

Area of Science:

• Oncology
• Genomics
• Molecular Biology

Background:

• Lung cancer is a leading cause of cancer mortality globally.
• Transcript fusions are key drivers in cancer initiation and progression.
• Targeted therapies for specific gene alterations have improved lung cancer outcomes, yet the full fusion landscape remains unclear.

Purpose of the Study:

• To explore the underexplored fusion landscape in early-stage non-small cell lung cancer (NSCLC).
• To identify recurrent transcript fusions and those with potential oncogenic roles.
• To associate fusion events with clinicopathological variables for potential therapeutic targeting.

Main Methods:

• Utilized the JAFFA pipeline for transcript fusion discovery in 270 NSCLC samples.
• Analyzed fusions to identify recurrent events, multi-partner genes, and high-oncogenic-potential candidates.
• Employed RNA sequencing and generalized linear models (GLM) for statistical association analysis.

Main Results:

• Identified 792 transcript fusions, with 751 being novel and 33 recurrent.
• Found four recurrent fusions significantly associated with clinicopathological variables.
• Detected fusion partners including known oncogenes like ERBB4, BRAF, FGFR2, and MET.

Conclusions:

• This study provides a valuable resource of novel and recurrent transcript fusions in NSCLC.
• The findings enable the identification and validation of promising candidates for targeted clinical interventions.
• The identified fusion landscape offers new avenues for developing precision therapies in lung cancer.