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Development of prediction models for the sensitivity of oral squamous cell carcinomas to preoperative S-1 administration
S-1 is an anticancer agent that is comprised of tegafur, gimeracil, and oteracil potassium, and is widely used in various carcinomas including oral squamous cell carcinoma (OSCC). Although an established prediction tool is not available, we aimed to develop prediction models for the sensitivity of p...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408317/ https://www.ncbi.nlm.nih.gov/pubmed/32793829 http://dx.doi.org/10.1016/j.heliyon.2020.e04601 |
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author | Shiiba, Masashi Yamagami, Hitomi Sudo, Tadashi Tomokuni, Yosuke Kashiwabara, Daisuke Kirita, Tadaaki Kusukawa, Jingo Komiya, Masamichi Tei, Kanchu Kitagawa, Yoshimasa Imai, Yutaka Kawamata, Hitoshi Bukawa, Hiroki Satomura, Kazuhito Oki, Hidero Shinozuka, Keiji Sugihara, Kazumasa Sugiura, Tsuyoshi Sekine, Joji Yokoe, Hidetaka Saito, Kengo Tanzawa, Hideki |
author_facet | Shiiba, Masashi Yamagami, Hitomi Sudo, Tadashi Tomokuni, Yosuke Kashiwabara, Daisuke Kirita, Tadaaki Kusukawa, Jingo Komiya, Masamichi Tei, Kanchu Kitagawa, Yoshimasa Imai, Yutaka Kawamata, Hitoshi Bukawa, Hiroki Satomura, Kazuhito Oki, Hidero Shinozuka, Keiji Sugihara, Kazumasa Sugiura, Tsuyoshi Sekine, Joji Yokoe, Hidetaka Saito, Kengo Tanzawa, Hideki |
author_sort | Shiiba, Masashi |
collection | PubMed |
description | S-1 is an anticancer agent that is comprised of tegafur, gimeracil, and oteracil potassium, and is widely used in various carcinomas including oral squamous cell carcinoma (OSCC). Although an established prediction tool is not available, we aimed to develop prediction models for the sensitivity of primary OSCC cases to the preoperative administration of S-1. We performed DNA microarray analysis of 95 cases with OSCC. Using global gene expression data and the clinical data, we developed two different prediction models, namely, model 1 that comprised the complete response (CR) + the partial response (PR) versus stable disease (SD) + progressive disease (PD), and model 2 that comprised responders versus non-responders. Twelve and 18 genes were designated as feature genes (FGs) in models 1 and 2, respectively, and, of these, six genes were common to both models. The sensitivity was 96.3%, the specificity was 91.2%, and the accuracy was 92.6% for model 1, and the sensitivity was 95.6%, the specificity was 85.2%, and the accuracy was 92.6% for model 2. These models were validated using receiver operating characteristic analysis, and the areas under the curves were 0.967 and 0.949 in models 1 and 2, respectively. The data led to the development of models that can reliably predict the sensitivity of patients with OSCC to the preoperative administration of S-1. The mechanism that regulates S-1 sensitivity remains unclear; however, the prediction models developed provide hope that further functional investigations into the FGs will lead to a greater understanding of drug resistance. |
format | Online Article Text |
id | pubmed-7408317 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-74083172020-08-12 Development of prediction models for the sensitivity of oral squamous cell carcinomas to preoperative S-1 administration Shiiba, Masashi Yamagami, Hitomi Sudo, Tadashi Tomokuni, Yosuke Kashiwabara, Daisuke Kirita, Tadaaki Kusukawa, Jingo Komiya, Masamichi Tei, Kanchu Kitagawa, Yoshimasa Imai, Yutaka Kawamata, Hitoshi Bukawa, Hiroki Satomura, Kazuhito Oki, Hidero Shinozuka, Keiji Sugihara, Kazumasa Sugiura, Tsuyoshi Sekine, Joji Yokoe, Hidetaka Saito, Kengo Tanzawa, Hideki Heliyon Article S-1 is an anticancer agent that is comprised of tegafur, gimeracil, and oteracil potassium, and is widely used in various carcinomas including oral squamous cell carcinoma (OSCC). Although an established prediction tool is not available, we aimed to develop prediction models for the sensitivity of primary OSCC cases to the preoperative administration of S-1. We performed DNA microarray analysis of 95 cases with OSCC. Using global gene expression data and the clinical data, we developed two different prediction models, namely, model 1 that comprised the complete response (CR) + the partial response (PR) versus stable disease (SD) + progressive disease (PD), and model 2 that comprised responders versus non-responders. Twelve and 18 genes were designated as feature genes (FGs) in models 1 and 2, respectively, and, of these, six genes were common to both models. The sensitivity was 96.3%, the specificity was 91.2%, and the accuracy was 92.6% for model 1, and the sensitivity was 95.6%, the specificity was 85.2%, and the accuracy was 92.6% for model 2. These models were validated using receiver operating characteristic analysis, and the areas under the curves were 0.967 and 0.949 in models 1 and 2, respectively. The data led to the development of models that can reliably predict the sensitivity of patients with OSCC to the preoperative administration of S-1. The mechanism that regulates S-1 sensitivity remains unclear; however, the prediction models developed provide hope that further functional investigations into the FGs will lead to a greater understanding of drug resistance. Elsevier 2020-08-05 /pmc/articles/PMC7408317/ /pubmed/32793829 http://dx.doi.org/10.1016/j.heliyon.2020.e04601 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Shiiba, Masashi Yamagami, Hitomi Sudo, Tadashi Tomokuni, Yosuke Kashiwabara, Daisuke Kirita, Tadaaki Kusukawa, Jingo Komiya, Masamichi Tei, Kanchu Kitagawa, Yoshimasa Imai, Yutaka Kawamata, Hitoshi Bukawa, Hiroki Satomura, Kazuhito Oki, Hidero Shinozuka, Keiji Sugihara, Kazumasa Sugiura, Tsuyoshi Sekine, Joji Yokoe, Hidetaka Saito, Kengo Tanzawa, Hideki Development of prediction models for the sensitivity of oral squamous cell carcinomas to preoperative S-1 administration |
title | Development of prediction models for the sensitivity of oral squamous cell carcinomas to preoperative S-1 administration |
title_full | Development of prediction models for the sensitivity of oral squamous cell carcinomas to preoperative S-1 administration |
title_fullStr | Development of prediction models for the sensitivity of oral squamous cell carcinomas to preoperative S-1 administration |
title_full_unstemmed | Development of prediction models for the sensitivity of oral squamous cell carcinomas to preoperative S-1 administration |
title_short | Development of prediction models for the sensitivity of oral squamous cell carcinomas to preoperative S-1 administration |
title_sort | development of prediction models for the sensitivity of oral squamous cell carcinomas to preoperative s-1 administration |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408317/ https://www.ncbi.nlm.nih.gov/pubmed/32793829 http://dx.doi.org/10.1016/j.heliyon.2020.e04601 |
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