Cargando…
Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer
BACKGROUND: Immune checkpoint inhibitors prolong the survival of non-small cell lung cancer (NSCLC) patients. Although it has been acknowledged that there is some correlation between the efficacy of anti-programmed cell death-1 (PD-1) antibody therapy and immunohistochemical analysis, this technique...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8822674/ https://www.ncbi.nlm.nih.gov/pubmed/35135489 http://dx.doi.org/10.1186/s12885-022-09264-2 |
_version_ | 1784646645413052416 |
---|---|
author | Kaneda, Toshihiko Kurata, Takayasu Yoshida, Tomoko Kibata, Kayoko Yoshioka, Hiroshige Yanagimoto, Hiroaki Takeda, Kazuhiko Yoshida, Takao Tsuta, Koji |
author_facet | Kaneda, Toshihiko Kurata, Takayasu Yoshida, Tomoko Kibata, Kayoko Yoshioka, Hiroshige Yanagimoto, Hiroaki Takeda, Kazuhiko Yoshida, Takao Tsuta, Koji |
author_sort | Kaneda, Toshihiko |
collection | PubMed |
description | BACKGROUND: Immune checkpoint inhibitors prolong the survival of non-small cell lung cancer (NSCLC) patients. Although it has been acknowledged that there is some correlation between the efficacy of anti-programmed cell death-1 (PD-1) antibody therapy and immunohistochemical analysis, this technique is not yet considered foolproof for predicting a favorable outcome of PD-1 antibody therapy. We aimed to predict the efficacy of nivolumab based on a comprehensive analysis of RNA expression at the gene level in advanced NSCLC. METHODS: This was a retrospective study on patients with NSCLC who were administered nivolumab at the Kansai Medical University Hospital. To identify genes associated with response to anti-PD-1 antibodies, we grouped patients into responders (complete and partial response) and non-responders (stable and progressive disease) to nivolumab therapy. Significant genes were then identified for these groups using Welch’s t-test. RESULTS: Among 42 analyzed cases (20 adenocarcinomas and 22 squamous cell carcinomas), enhanced expression of MAGE-A4, BBC3, and OTOA genes was observed in responders with adenocarcinoma, and enhanced expression of DAB2, HLA-DPB,1 and CDH2 genes was observed in responders with squamous cell carcinoma. CONCLUSIONS: This study predicted the efficacy of nivolumab based on a comprehensive analysis of mRNA expression at the gene level in advanced NSCLC. We also revealed different gene expression patterns as predictors of the effectiveness of anti PD-1 antibody therapy in adenocarcinoma and squamous cell carcinoma. |
format | Online Article Text |
id | pubmed-8822674 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88226742022-02-08 Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer Kaneda, Toshihiko Kurata, Takayasu Yoshida, Tomoko Kibata, Kayoko Yoshioka, Hiroshige Yanagimoto, Hiroaki Takeda, Kazuhiko Yoshida, Takao Tsuta, Koji BMC Cancer Research BACKGROUND: Immune checkpoint inhibitors prolong the survival of non-small cell lung cancer (NSCLC) patients. Although it has been acknowledged that there is some correlation between the efficacy of anti-programmed cell death-1 (PD-1) antibody therapy and immunohistochemical analysis, this technique is not yet considered foolproof for predicting a favorable outcome of PD-1 antibody therapy. We aimed to predict the efficacy of nivolumab based on a comprehensive analysis of RNA expression at the gene level in advanced NSCLC. METHODS: This was a retrospective study on patients with NSCLC who were administered nivolumab at the Kansai Medical University Hospital. To identify genes associated with response to anti-PD-1 antibodies, we grouped patients into responders (complete and partial response) and non-responders (stable and progressive disease) to nivolumab therapy. Significant genes were then identified for these groups using Welch’s t-test. RESULTS: Among 42 analyzed cases (20 adenocarcinomas and 22 squamous cell carcinomas), enhanced expression of MAGE-A4, BBC3, and OTOA genes was observed in responders with adenocarcinoma, and enhanced expression of DAB2, HLA-DPB,1 and CDH2 genes was observed in responders with squamous cell carcinoma. CONCLUSIONS: This study predicted the efficacy of nivolumab based on a comprehensive analysis of mRNA expression at the gene level in advanced NSCLC. We also revealed different gene expression patterns as predictors of the effectiveness of anti PD-1 antibody therapy in adenocarcinoma and squamous cell carcinoma. BioMed Central 2022-02-08 /pmc/articles/PMC8822674/ /pubmed/35135489 http://dx.doi.org/10.1186/s12885-022-09264-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Kaneda, Toshihiko Kurata, Takayasu Yoshida, Tomoko Kibata, Kayoko Yoshioka, Hiroshige Yanagimoto, Hiroaki Takeda, Kazuhiko Yoshida, Takao Tsuta, Koji Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer |
title | Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer |
title_full | Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer |
title_fullStr | Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer |
title_full_unstemmed | Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer |
title_short | Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer |
title_sort | massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8822674/ https://www.ncbi.nlm.nih.gov/pubmed/35135489 http://dx.doi.org/10.1186/s12885-022-09264-2 |
work_keys_str_mv | AT kanedatoshihiko massivedigitalgeneexpressionanalysisrevealsdifferentpredictiveprofilesforimmunecheckpointinhibitortherapybetweenadenocarcinomaandsquamouscellcarcinomaofadvancedlungcancer AT kuratatakayasu massivedigitalgeneexpressionanalysisrevealsdifferentpredictiveprofilesforimmunecheckpointinhibitortherapybetweenadenocarcinomaandsquamouscellcarcinomaofadvancedlungcancer AT yoshidatomoko massivedigitalgeneexpressionanalysisrevealsdifferentpredictiveprofilesforimmunecheckpointinhibitortherapybetweenadenocarcinomaandsquamouscellcarcinomaofadvancedlungcancer AT kibatakayoko massivedigitalgeneexpressionanalysisrevealsdifferentpredictiveprofilesforimmunecheckpointinhibitortherapybetweenadenocarcinomaandsquamouscellcarcinomaofadvancedlungcancer AT yoshiokahiroshige massivedigitalgeneexpressionanalysisrevealsdifferentpredictiveprofilesforimmunecheckpointinhibitortherapybetweenadenocarcinomaandsquamouscellcarcinomaofadvancedlungcancer AT yanagimotohiroaki massivedigitalgeneexpressionanalysisrevealsdifferentpredictiveprofilesforimmunecheckpointinhibitortherapybetweenadenocarcinomaandsquamouscellcarcinomaofadvancedlungcancer AT takedakazuhiko massivedigitalgeneexpressionanalysisrevealsdifferentpredictiveprofilesforimmunecheckpointinhibitortherapybetweenadenocarcinomaandsquamouscellcarcinomaofadvancedlungcancer AT yoshidatakao massivedigitalgeneexpressionanalysisrevealsdifferentpredictiveprofilesforimmunecheckpointinhibitortherapybetweenadenocarcinomaandsquamouscellcarcinomaofadvancedlungcancer AT tsutakoji massivedigitalgeneexpressionanalysisrevealsdifferentpredictiveprofilesforimmunecheckpointinhibitortherapybetweenadenocarcinomaandsquamouscellcarcinomaofadvancedlungcancer |