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Published on: September 25, 2018
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Driver Mutation Analysis and PD-L1 Expression in Synchronous Double Primary Lung Cancer
Xiaoli Jia1,2, Liping Zhang1, Wei Wu1
1Department of Pathology, Shanghai Pulmonary Hospital, TongJi University School of Medicine.
Summary
Synchronous double primary lung cancer (SDPLC) genetic analysis reveals EGFR mutations in 50% of tumors. Clonality and PD-L1 expression offer insights for diagnosis and targeted treatment in SDPLC patients.
Area of Science:
- Oncology
- Genetics
- Thoracic Surgery
Background:
- Synchronous double primary lung cancer (SDPLC) is increasingly detected.
- Limited understanding of SDPLC's genetic landscape, diagnostic markers, and prognostic factors hinders effective management.
- Comprehensive analysis of driver mutations and PD-L1 expression is crucial for advancing SDPLC care.
Purpose of the Study:
- To investigate the genetic profiles, including driver mutations (EGFR, KRAS, BRAF, EML4-ALK, ROS1) and PD-L1 expression, in SDPLC.
- To analyze clonality patterns among synchronous primary lung tumors.
- To correlate genetic findings and clinical factors with patient outcomes and guide targeted therapy decisions.
Main Methods:
- Analysis of 110 lesions from 55 surgically resected SDPLC patients.
- Detection of 5 known driver mutations (EGFR, KRAS, BRAF, EML4-ALK, ROS1) and PD-L1 expression.
- Assessment of tumor clonality and correlation with clinical parameters and survival data.
Main Results:
- EGFR mutations were present in 50% of tumors; EML4-ALK fusions in 4.55%; KRAS mutations in 8.18%. BRAF and ROS1 aberrations were not detected.
- 47 patients (85.5%) exhibited different clonality between primary tumors, while 4 (7.27%) showed the same clonality.
- EGFR mutations with same clonality were more frequent in patients over 65 (P=0.021). PD-L1 expression (14.54%) was higher in males, squamous cell carcinoma, and tumors >3 cm.
Conclusions:
- Evaluation of EGFR/KRAS mutations and EML4-ALK fusions is vital for SDPLC diagnosis and classification.
- Tumor clonality and specific mutations can inform prognosis and guide personalized treatment strategies.
- Identifying genetic markers and PD-L1 status aids in selecting appropriate targeted therapies for SDPLC patients.

