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mTOR pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers

BACKGROUND: mTOR pathway is known to promote cancer malignancy and influence cancer immunity but is unknown for its role in immune checkpoint inhibitors (ICI) therapy. METHODS: Using Memorial Sloan-Kettering Cancer Center dataset (MSKCC), we extracted mTOR pathway gene mutations for stepwise Cox reg...

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Autores principales: Cheng, Lei, Wang, Yanan, Qiu, Lixin, Chang, Yuanyuan, Lu, Haijiao, Liu, Chenchen, Zhang, Bo, Zhou, Yan, Bai, Hao, Xiong, Liwen, Zhong, Hua, Nie, Wei, Han, Baohui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9153162/
https://www.ncbi.nlm.nih.gov/pubmed/35642038
http://dx.doi.org/10.1186/s12967-022-03436-1
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author Cheng, Lei
Wang, Yanan
Qiu, Lixin
Chang, Yuanyuan
Lu, Haijiao
Liu, Chenchen
Zhang, Bo
Zhou, Yan
Bai, Hao
Xiong, Liwen
Zhong, Hua
Nie, Wei
Han, Baohui
author_facet Cheng, Lei
Wang, Yanan
Qiu, Lixin
Chang, Yuanyuan
Lu, Haijiao
Liu, Chenchen
Zhang, Bo
Zhou, Yan
Bai, Hao
Xiong, Liwen
Zhong, Hua
Nie, Wei
Han, Baohui
author_sort Cheng, Lei
collection PubMed
description BACKGROUND: mTOR pathway is known to promote cancer malignancy and influence cancer immunity but is unknown for its role in immune checkpoint inhibitors (ICI) therapy. METHODS: Using Memorial Sloan-Kettering Cancer Center dataset (MSKCC), we extracted mTOR pathway gene mutations for stepwise Cox regression in 1661 cancer patients received ICI. We associated the mutation of the gene signature resulted from the stepwise Cox regression with the 1661 patients’ survival. Other 553 ICI-treated patients were collected from 6 cohorts for validation. We also performed this survival association in patients without ICI treatment from MSKCC as discovery (n = 2244) and The Cancer Genome Atlas (TCGA) as validation (n = 763). Pathway enrichment analysis were performed using transcriptome profiles from TCGA and IMvigor210 trial to investigate the potential mechanism. RESULTS: We identified 8 genes involved in mTOR pathway, including FGFR2, PIK3C3, FGFR4, FGFR1, FGF3, AKT1, mTOR, and RPTOR, resulted from stepwise Cox regression in discovery (n = 1661). In both discovery (n = 1661) and validation (n = 553), the mutation of the 8-gene signature was associated with better survival of the patients treated with ICI, which was independent of tumor mutation burden (TMB) and mainly attributed to the missense mutations. This survival association was not observed in patients without ICI therapy. Intriguingly, the mutation of the 8-gene signature was associated with increased TMB and PD1/PD-L1 expression. Immunologically, pathways involved in anti-tumor immune response were enriched in presence of this mutational signature in mTOR pathway, leading to increased infiltration of immune effector cells (e.g., CD8 + T cells, NK cells, and M1 macrophages), but decreased infiltration of immune inhibitory M2 macrophages. CONCLUSIONS: These results suggested that mTOR pathway gene mutations were predictive of better survival upon ICI treatment in multiple cancers, likely by its association with enhanced anti-tumor immunity. Larger studies are warranted to validate our findings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03436-1.
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spelling pubmed-91531622022-06-01 mTOR pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers Cheng, Lei Wang, Yanan Qiu, Lixin Chang, Yuanyuan Lu, Haijiao Liu, Chenchen Zhang, Bo Zhou, Yan Bai, Hao Xiong, Liwen Zhong, Hua Nie, Wei Han, Baohui J Transl Med Research BACKGROUND: mTOR pathway is known to promote cancer malignancy and influence cancer immunity but is unknown for its role in immune checkpoint inhibitors (ICI) therapy. METHODS: Using Memorial Sloan-Kettering Cancer Center dataset (MSKCC), we extracted mTOR pathway gene mutations for stepwise Cox regression in 1661 cancer patients received ICI. We associated the mutation of the gene signature resulted from the stepwise Cox regression with the 1661 patients’ survival. Other 553 ICI-treated patients were collected from 6 cohorts for validation. We also performed this survival association in patients without ICI treatment from MSKCC as discovery (n = 2244) and The Cancer Genome Atlas (TCGA) as validation (n = 763). Pathway enrichment analysis were performed using transcriptome profiles from TCGA and IMvigor210 trial to investigate the potential mechanism. RESULTS: We identified 8 genes involved in mTOR pathway, including FGFR2, PIK3C3, FGFR4, FGFR1, FGF3, AKT1, mTOR, and RPTOR, resulted from stepwise Cox regression in discovery (n = 1661). In both discovery (n = 1661) and validation (n = 553), the mutation of the 8-gene signature was associated with better survival of the patients treated with ICI, which was independent of tumor mutation burden (TMB) and mainly attributed to the missense mutations. This survival association was not observed in patients without ICI therapy. Intriguingly, the mutation of the 8-gene signature was associated with increased TMB and PD1/PD-L1 expression. Immunologically, pathways involved in anti-tumor immune response were enriched in presence of this mutational signature in mTOR pathway, leading to increased infiltration of immune effector cells (e.g., CD8 + T cells, NK cells, and M1 macrophages), but decreased infiltration of immune inhibitory M2 macrophages. CONCLUSIONS: These results suggested that mTOR pathway gene mutations were predictive of better survival upon ICI treatment in multiple cancers, likely by its association with enhanced anti-tumor immunity. Larger studies are warranted to validate our findings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03436-1. BioMed Central 2022-05-31 /pmc/articles/PMC9153162/ /pubmed/35642038 http://dx.doi.org/10.1186/s12967-022-03436-1 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
Cheng, Lei
Wang, Yanan
Qiu, Lixin
Chang, Yuanyuan
Lu, Haijiao
Liu, Chenchen
Zhang, Bo
Zhou, Yan
Bai, Hao
Xiong, Liwen
Zhong, Hua
Nie, Wei
Han, Baohui
mTOR pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers
title mTOR pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers
title_full mTOR pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers
title_fullStr mTOR pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers
title_full_unstemmed mTOR pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers
title_short mTOR pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers
title_sort mtor pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9153162/
https://www.ncbi.nlm.nih.gov/pubmed/35642038
http://dx.doi.org/10.1186/s12967-022-03436-1
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