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Updated: Dec 22, 2025
Simple and Rapid Method to Obtain High-quality Tumor DNA from Clinical-pathological Specimens Using Touch Imprint Cytology
Published on: March 21, 2018
Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer
Kei Kunimasa1,2, Yosuke Hirotsu2, Kenji Amemiya2
1Department of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan.
Introductions:
When tumor tissue samples are unavailable to search for actionable driver mutations, archival cytology samples can be useful. We investigate whether archival cytology samples can yield reliable genomic information compared to corresponding formalin-fixed paraffin-embedded (FFPE) tumor samples.
Patients And Methods:
Pretreatment class V archival cytology samples with adequate tumor cells were selected from 172 lung cancer patients. The genomic profiles of the primary lung tumors have been analyzed through whole-exome regions of 53 genes. We compared the genomic profiles based on the oncogenicity and variant allele frequency (VAF) between the archival cytology and the corresponding primary tumors. We also analyzed the genomic profiles of serial cytological samples during the treatment of EGFR-TKI.
Results:
A total of 43 patients were analyzed with the paired samples for DNA mutations and other three patients were analyzed for their fusion genes. A total of 672 mutations were detected. Of those, 106 mutations (15.8%) were shared with both samples. Sixty of seventy-seven (77.9%) shared mutations were oncogenic or likely oncogenic mutations with VAF ≧10%. As high as 90% (9/10) actionable driver mutations and ALK and ROS1 fusion genes were successfully detected from archival cytology samples. Sequential analysis revealed the dynamic changes in EGFR-TKI-resistant mutation (EGFR p.T790M) during the course of treatment.
Conclusion:
Archival cytology sample with adequate tumor cells can yield genetic information compared to the primary tumors. If tumor tissue samples are unavailable, we can use archival cytology samples to search for actionable driver mutations.
