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

Abstract 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...

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Autores principales:	Chenlu Li, Jingjing Pan, Jing Luo, Xupeng Chen
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Non-small cell lung cancer Immune molecular subtype Risk stratification Immunotherapy Prognosis Diseases of the respiratory system RC705-779
Acceso en línea:	https://doaj.org/article/22ade93edf0944fea407007df5cc0fcb
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spelling	oai:doaj.org-article:22ade93edf0944fea407007df5cc0fcb2021-12-05T12:23:28ZPrognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy10.1186/s12890-021-01765-31471-2466https://doaj.org/article/22ade93edf0944fea407007df5cc0fcb2021-11-01T00:00:00Zhttps://doi.org/10.1186/s12890-021-01765-3https://doaj.org/toc/1471-2466Abstract 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.Chenlu LiJingjing PanJing LuoXupeng ChenBMCarticleNon-small cell lung cancerImmune molecular subtypeRisk stratificationImmunotherapyPrognosisDiseases of the respiratory systemRC705-779ENBMC Pulmonary Medicine, Vol 21, Iss 1, Pp 1-17 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Non-small cell lung cancer Immune molecular subtype Risk stratification Immunotherapy Prognosis Diseases of the respiratory system RC705-779
spellingShingle	Non-small cell lung cancer Immune molecular subtype Risk stratification Immunotherapy Prognosis Diseases of the respiratory system RC705-779 Chenlu Li Jingjing Pan Jing Luo Xupeng Chen Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy
description	Abstract 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.
format	article
author	Chenlu Li Jingjing Pan Jing Luo Xupeng Chen
author_facet	Chenlu Li Jingjing Pan Jing Luo Xupeng Chen
author_sort	Chenlu Li
title	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_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_sort	prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy
publisher	BMC
publishDate	2021
url	https://doaj.org/article/22ade93edf0944fea407007df5cc0fcb
work_keys_str_mv	AT chenluli prognosticcharacterizationofimmunemolecularsubtypesinnonsmallcelllungcancertoimmunotherapy AT jingjingpan prognosticcharacterizationofimmunemolecularsubtypesinnonsmallcelllungcancertoimmunotherapy AT jingluo prognosticcharacterizationofimmunemolecularsubtypesinnonsmallcelllungcancertoimmunotherapy AT xupengchen prognosticcharacterizationofimmunemolecularsubtypesinnonsmallcelllungcancertoimmunotherapy
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Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy

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