ArticleCancer medicine2020
Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer.
Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Article
- Nucleic Acid Quality Assessment is Critical to the Success of the Oncomine Dx Target Test for Lung Cancer.Molecular diagnosis & therapy · 2023Article
- The Diagnostic Utility of Cell-Free DNA from Ex Vivo Bronchoalveolar Lavage Fluid in Lung Cancer.Cancers · 2022Article
- Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer.BioMed research international · 2022Article
- Association of Mutation Profiles with Postoperative Survival in Patients with Non-Small Cell Lung Cancer.Cancers · 2020Article
- Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer.Cancer medicine · 2020Article
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Authors and funding
21 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionsWhen 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
methodsPretreatment 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.
resultsA 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.
conclusionArchival 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.
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