NDLI: Massive digital gene expression analysis reveals different predictive profiles for immune checkpoint inhibitor therapy between adenocarcinoma and squamous cell carcinoma of advanced lung cancer

Content Provider	Springer Nature : BioMed Central
Author	Kaneda, Toshihiko Kurata, Takayasu Yoshida, Tomoko Kibata, Kayoko Yoshioka, Hiroshige Yanagimoto, Hiroaki Takeda, Kazuhiko Yoshida, Takao Tsuta, Koji
Abstract	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.
Related Links	https://bmccancer.biomedcentral.com/counter/pdf/10.1186/s12885-022-09264-2.pdf
Ending Page	10
Page Count	10
Starting Page	1
File Format	HTM / HTML
ISSN	14712407
DOI	10.1186/s12885-022-09264-2
Journal	BMC Cancer
Issue Number	1
Volume Number	22
Language	English
Publisher	BioMed Central
Publisher Date	2022-02-08
Access Restriction	Open
Subject Keyword	Cancer Research Oncology Surgical Oncology Health Promotion and Disease Prevention Biomedicine Medicine Public Health Advanced non-small cell lung cancer Nivolumab Anti PD-1 antibody Transcriptome Medicine/Public Health
Content Type	Text
Resource Type	Article
Subject	Cancer Research Oncology Genetics
Journal Impact Factor	3.4/2023
5-Year Journal Impact Factor	3.8/2023

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