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Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer

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...

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Autores principales: Kunimasa, Kei, Hirotsu, Yosuke, Amemiya, Kenji, Nagakubo, Yuki, Goto, Taichiro, Miyashita, Yoshihiro, Kakizaki, Yumiko, Tsutsui, Toshiharu, Otake, Sotaro, Kobayashi, Hiroaki, Higuchi, Rumi, Inomata, Kie, Kumagai, Takashi, Mochizuki, Hitoshi, Nakamura, Harumi, Nakatsuka, Shin‐ichi, Nishino, Kazumi, Imamura, Fumio, Kumagai, Toru, Oyama, Toshio, Omata, Masao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333826/
https://www.ncbi.nlm.nih.gov/pubmed/32351019
http://dx.doi.org/10.1002/cam4.3089
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author Kunimasa, Kei
Hirotsu, Yosuke
Amemiya, Kenji
Nagakubo, Yuki
Goto, Taichiro
Miyashita, Yoshihiro
Kakizaki, Yumiko
Tsutsui, Toshiharu
Otake, Sotaro
Kobayashi, Hiroaki
Higuchi, Rumi
Inomata, Kie
Kumagai, Takashi
Mochizuki, Hitoshi
Nakamura, Harumi
Nakatsuka, Shin‐ichi
Nishino, Kazumi
Imamura, Fumio
Kumagai, Toru
Oyama, Toshio
Omata, Masao
author_facet Kunimasa, Kei
Hirotsu, Yosuke
Amemiya, Kenji
Nagakubo, Yuki
Goto, Taichiro
Miyashita, Yoshihiro
Kakizaki, Yumiko
Tsutsui, Toshiharu
Otake, Sotaro
Kobayashi, Hiroaki
Higuchi, Rumi
Inomata, Kie
Kumagai, Takashi
Mochizuki, Hitoshi
Nakamura, Harumi
Nakatsuka, Shin‐ichi
Nishino, Kazumi
Imamura, Fumio
Kumagai, Toru
Oyama, Toshio
Omata, Masao
author_sort Kunimasa, Kei
collection PubMed
description 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.
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spelling pubmed-73338262020-07-07 Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer Kunimasa, Kei Hirotsu, Yosuke Amemiya, Kenji Nagakubo, Yuki Goto, Taichiro Miyashita, Yoshihiro Kakizaki, Yumiko Tsutsui, Toshiharu Otake, Sotaro Kobayashi, Hiroaki Higuchi, Rumi Inomata, Kie Kumagai, Takashi Mochizuki, Hitoshi Nakamura, Harumi Nakatsuka, Shin‐ichi Nishino, Kazumi Imamura, Fumio Kumagai, Toru Oyama, Toshio Omata, Masao Cancer Med Clinical Cancer Research 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. John Wiley and Sons Inc. 2020-04-29 /pmc/articles/PMC7333826/ /pubmed/32351019 http://dx.doi.org/10.1002/cam4.3089 Text en © 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Clinical Cancer Research
Kunimasa, Kei
Hirotsu, Yosuke
Amemiya, Kenji
Nagakubo, Yuki
Goto, Taichiro
Miyashita, Yoshihiro
Kakizaki, Yumiko
Tsutsui, Toshiharu
Otake, Sotaro
Kobayashi, Hiroaki
Higuchi, Rumi
Inomata, Kie
Kumagai, Takashi
Mochizuki, Hitoshi
Nakamura, Harumi
Nakatsuka, Shin‐ichi
Nishino, Kazumi
Imamura, Fumio
Kumagai, Toru
Oyama, Toshio
Omata, Masao
Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer
title Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer
title_full Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer
title_fullStr Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer
title_full_unstemmed Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer
title_short Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer
title_sort genome analysis of peeling archival cytology samples detects driver mutations in lung cancer
topic Clinical Cancer Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333826/
https://www.ncbi.nlm.nih.gov/pubmed/32351019
http://dx.doi.org/10.1002/cam4.3089
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