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COX-2-related tumor immune microenvironment in non-small cell lung cancer: a novel signature to predict hot and cold tumor
BACKGROUND: At present, non-small cell lung cancer (NSCLC) remains a great threat to the health of people worldwide. Immune checkpoint inhibitors (ICIs) have shown positive results in the treatment of advanced NSCLC. However, the treatment response of ICIs is not stable and unpredictable. We used a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987815/ https://www.ncbi.nlm.nih.gov/pubmed/35399232 http://dx.doi.org/10.21037/jtd-22-257 |
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author | Wang, Tiangong Luo, Ying Zhang, Qi Shen, Yanping Peng, Min Huang, Ping Zhou, Zijian Wu, Xinyi Chen, Ke |
author_facet | Wang, Tiangong Luo, Ying Zhang, Qi Shen, Yanping Peng, Min Huang, Ping Zhou, Zijian Wu, Xinyi Chen, Ke |
author_sort | Wang, Tiangong |
collection | PubMed |
description | BACKGROUND: At present, non-small cell lung cancer (NSCLC) remains a great threat to the health of people worldwide. Immune checkpoint inhibitors (ICIs) have shown positive results in the treatment of advanced NSCLC. However, the treatment response of ICIs is not stable and unpredictable. We used a bioinformatics analysis to determine a novel signature to diagnose the hot and cold tumor in NSCLC which may guide the programmed cell death protein 1/programmed cell death 1 ligand 1 (PD-1/PD-L1) therapeutic strategy. METHODS: The RNA-seq dataset and clinical data of 485 lung adenocarcinoma (LUAD) and 473 lung squamous cell carcinoma (LUSC) samples from The Cancer Genome Atlas (TCGA) database. Tumor infiltrating immune cells was calculated by CIBERSORT algorithm and ConsensusClusterPlus was used to classify the hot and cold tumor. Least absolute shrinkage and selection operator (LASSO) regression, Support Vector Machine (SVM) and Gaussian Mixture Model (GMM) were performed to determine the diagnostic area under curve (AUC) of novel signature of ICIs treatment. Overall survival (OS) analysis was based on the Kaplan-Meier statistical method. RESULTS: In this study, we found that the expression of PD-1/PD-L1 is associated with COX2 (PTGS2) expression. We identified novel signatures [STMN3, KIRREL1, SH2D3C, VCL, PDCD1, CD274, PTGS2, combined diagnostic (AUC) =0.838], in order to diagnose the hot and cold tumor subtype to indicate the treatment response of PD-1/PD-L1 inhibitor in NSCLC. Furthermore, we found that in hot tumor subtype, high PDCD1 expression group had worse OS than low PDCD1 expression group (P=0.047); high SH2D3C expression group had worse OS than low SH2D3C expression group either (P=0.003). SH2D3C was correlated to PD-1 expression in NSCLC samples (R=0.49, P<0.001). We speculated that SH2D3C likely plays a crucial role in PD-1-related immunotherapy in NSCLC patients. Pathway enrichment showed that the focal adhesion (P=0.005) and actin cytoskeleton (P=0.022) pathways were associated with OS. CONCLUSIONS: This study aimed to identify the classification of hot and cold tumors, and develop a novel signature to predict the ICI treatments response for PD-1/PD-L1 high expression NSCLC patients. |
format | Online Article Text |
id | pubmed-8987815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-89878152022-04-08 COX-2-related tumor immune microenvironment in non-small cell lung cancer: a novel signature to predict hot and cold tumor Wang, Tiangong Luo, Ying Zhang, Qi Shen, Yanping Peng, Min Huang, Ping Zhou, Zijian Wu, Xinyi Chen, Ke J Thorac Dis Original Article BACKGROUND: At present, non-small cell lung cancer (NSCLC) remains a great threat to the health of people worldwide. Immune checkpoint inhibitors (ICIs) have shown positive results in the treatment of advanced NSCLC. However, the treatment response of ICIs is not stable and unpredictable. We used a bioinformatics analysis to determine a novel signature to diagnose the hot and cold tumor in NSCLC which may guide the programmed cell death protein 1/programmed cell death 1 ligand 1 (PD-1/PD-L1) therapeutic strategy. METHODS: The RNA-seq dataset and clinical data of 485 lung adenocarcinoma (LUAD) and 473 lung squamous cell carcinoma (LUSC) samples from The Cancer Genome Atlas (TCGA) database. Tumor infiltrating immune cells was calculated by CIBERSORT algorithm and ConsensusClusterPlus was used to classify the hot and cold tumor. Least absolute shrinkage and selection operator (LASSO) regression, Support Vector Machine (SVM) and Gaussian Mixture Model (GMM) were performed to determine the diagnostic area under curve (AUC) of novel signature of ICIs treatment. Overall survival (OS) analysis was based on the Kaplan-Meier statistical method. RESULTS: In this study, we found that the expression of PD-1/PD-L1 is associated with COX2 (PTGS2) expression. We identified novel signatures [STMN3, KIRREL1, SH2D3C, VCL, PDCD1, CD274, PTGS2, combined diagnostic (AUC) =0.838], in order to diagnose the hot and cold tumor subtype to indicate the treatment response of PD-1/PD-L1 inhibitor in NSCLC. Furthermore, we found that in hot tumor subtype, high PDCD1 expression group had worse OS than low PDCD1 expression group (P=0.047); high SH2D3C expression group had worse OS than low SH2D3C expression group either (P=0.003). SH2D3C was correlated to PD-1 expression in NSCLC samples (R=0.49, P<0.001). We speculated that SH2D3C likely plays a crucial role in PD-1-related immunotherapy in NSCLC patients. Pathway enrichment showed that the focal adhesion (P=0.005) and actin cytoskeleton (P=0.022) pathways were associated with OS. CONCLUSIONS: This study aimed to identify the classification of hot and cold tumors, and develop a novel signature to predict the ICI treatments response for PD-1/PD-L1 high expression NSCLC patients. AME Publishing Company 2022-03 /pmc/articles/PMC8987815/ /pubmed/35399232 http://dx.doi.org/10.21037/jtd-22-257 Text en 2022 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Wang, Tiangong Luo, Ying Zhang, Qi Shen, Yanping Peng, Min Huang, Ping Zhou, Zijian Wu, Xinyi Chen, Ke COX-2-related tumor immune microenvironment in non-small cell lung cancer: a novel signature to predict hot and cold tumor |
title | COX-2-related tumor immune microenvironment in non-small cell lung cancer: a novel signature to predict hot and cold tumor |
title_full | COX-2-related tumor immune microenvironment in non-small cell lung cancer: a novel signature to predict hot and cold tumor |
title_fullStr | COX-2-related tumor immune microenvironment in non-small cell lung cancer: a novel signature to predict hot and cold tumor |
title_full_unstemmed | COX-2-related tumor immune microenvironment in non-small cell lung cancer: a novel signature to predict hot and cold tumor |
title_short | COX-2-related tumor immune microenvironment in non-small cell lung cancer: a novel signature to predict hot and cold tumor |
title_sort | cox-2-related tumor immune microenvironment in non-small cell lung cancer: a novel signature to predict hot and cold tumor |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987815/ https://www.ncbi.nlm.nih.gov/pubmed/35399232 http://dx.doi.org/10.21037/jtd-22-257 |
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