Cargando…

Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy

BACKGROUND: Non-small cell lung cancer (NSCLC) was usually associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. It is urgent to screen reliable biomarkers, especially immunotherapy-associated biomarkers, that can predict outcomes of thes...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Chenlu, Pan, Jingjing, Luo, Jing, Chen, Xupeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628446/
https://www.ncbi.nlm.nih.gov/pubmed/34844602
http://dx.doi.org/10.1186/s12890-021-01765-3
_version_ 1784607007144148992
author Li, Chenlu
Pan, Jingjing
Luo, Jing
Chen, Xupeng
author_facet Li, Chenlu
Pan, Jingjing
Luo, Jing
Chen, Xupeng
author_sort Li, Chenlu
collection PubMed
description BACKGROUND: Non-small cell lung cancer (NSCLC) was usually associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. It is urgent to screen reliable biomarkers, especially immunotherapy-associated biomarkers, that can predict outcomes of these patients. METHODS: Gene expression profiles of 1026 NSCLC patients were collected from The Cancer Genome Atlas (TCGA) datasets with their corresponding clinical and somatic mutation data. Based on immune infiltration scores, molecular clustering classification was performed to identify immune subtypes in NSCLC. After the functional enrichment analysis of subtypes, hub genes were further screened using univariate Cox, Lasso, and multivariate Cox regression analysis, and the risk score was defined to construct the prognostic model. Other microarray data and corresponding clinical information of 603 NSCLC patients from the GEO datasets were applied to conduct random forest models for the prognosis of NSCLC with 100 runs of cross-validation. Finally, external datasets with immunotherapy and chemotherapy were further applied to explore the significance of risk-scores in clinical immunotherapy response for NSCLC patients. RESULTS: Compared with Subtype-B, the Subtype-A, associated with better outcomes, was characterized by significantly higher stromal and immune scores, T lymphocytes infiltration scores and up-regulation of immunotherapy markers. In addition, we found and validated an eleven -gene signatures for better application of distinguishing high- and low-risk NSCLC patients and predict patients’ prognosis and therapeutical response to immunotherapy. Furthermore, combined with other clinical characteristics based on multivariate Cox regression analysis, we successfully constructed and validated a nomogram to effectively predict the survival rate of NSCLC patients. External immunotherapy and chemotherapy cohorts validated the patients with higher risk-scores exhibited significant therapeutic response and clinical benefits. CONCLUSION: These results demonstrated the immunological and prognostic heterogeneity within NSCLC and provided a new clinical application in predicting the prognosis and benefits of immunotherapy for the disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-021-01765-3.
format Online
Article
Text
id pubmed-8628446
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-86284462021-12-01 Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy Li, Chenlu Pan, Jingjing Luo, Jing Chen, Xupeng BMC Pulm Med Research BACKGROUND: Non-small cell lung cancer (NSCLC) was usually associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. It is urgent to screen reliable biomarkers, especially immunotherapy-associated biomarkers, that can predict outcomes of these patients. METHODS: Gene expression profiles of 1026 NSCLC patients were collected from The Cancer Genome Atlas (TCGA) datasets with their corresponding clinical and somatic mutation data. Based on immune infiltration scores, molecular clustering classification was performed to identify immune subtypes in NSCLC. After the functional enrichment analysis of subtypes, hub genes were further screened using univariate Cox, Lasso, and multivariate Cox regression analysis, and the risk score was defined to construct the prognostic model. Other microarray data and corresponding clinical information of 603 NSCLC patients from the GEO datasets were applied to conduct random forest models for the prognosis of NSCLC with 100 runs of cross-validation. Finally, external datasets with immunotherapy and chemotherapy were further applied to explore the significance of risk-scores in clinical immunotherapy response for NSCLC patients. RESULTS: Compared with Subtype-B, the Subtype-A, associated with better outcomes, was characterized by significantly higher stromal and immune scores, T lymphocytes infiltration scores and up-regulation of immunotherapy markers. In addition, we found and validated an eleven -gene signatures for better application of distinguishing high- and low-risk NSCLC patients and predict patients’ prognosis and therapeutical response to immunotherapy. Furthermore, combined with other clinical characteristics based on multivariate Cox regression analysis, we successfully constructed and validated a nomogram to effectively predict the survival rate of NSCLC patients. External immunotherapy and chemotherapy cohorts validated the patients with higher risk-scores exhibited significant therapeutic response and clinical benefits. CONCLUSION: These results demonstrated the immunological and prognostic heterogeneity within NSCLC and provided a new clinical application in predicting the prognosis and benefits of immunotherapy for the disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-021-01765-3. BioMed Central 2021-11-29 /pmc/articles/PMC8628446/ /pubmed/34844602 http://dx.doi.org/10.1186/s12890-021-01765-3 Text en © The Author(s) 2021 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
Li, Chenlu
Pan, Jingjing
Luo, Jing
Chen, Xupeng
Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy
title Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy
title_full Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy
title_fullStr Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy
title_full_unstemmed Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy
title_short Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy
title_sort prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628446/
https://www.ncbi.nlm.nih.gov/pubmed/34844602
http://dx.doi.org/10.1186/s12890-021-01765-3
work_keys_str_mv AT lichenlu prognosticcharacterizationofimmunemolecularsubtypesinnonsmallcelllungcancertoimmunotherapy
AT panjingjing prognosticcharacterizationofimmunemolecularsubtypesinnonsmallcelllungcancertoimmunotherapy
AT luojing prognosticcharacterizationofimmunemolecularsubtypesinnonsmallcelllungcancertoimmunotherapy
AT chenxupeng prognosticcharacterizationofimmunemolecularsubtypesinnonsmallcelllungcancertoimmunotherapy