Cargando…

Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data

INTRODUCTION: Microbiome plays roles in lung adenocarcinoma (LUAD) development and anti-tumor treatment efficacy. Aberrant glycolysis in tumor might promote lactate production that alter tumor microenvironment, affecting microbiome, cancer cells and immune cells. We aimed to construct intratumor mic...

Descripción completa

Detalles Bibliográficos
Autores principales: Deng, Xiaheng, Chen, Xiru, Luo, Yu, Que, Jun, Chen, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469687/
https://www.ncbi.nlm.nih.gov/pubmed/37664112
http://dx.doi.org/10.3389/fmicb.2023.1202454
_version_ 1785099497940975616
author Deng, Xiaheng
Chen, Xiru
Luo, Yu
Que, Jun
Chen, Liang
author_facet Deng, Xiaheng
Chen, Xiru
Luo, Yu
Que, Jun
Chen, Liang
author_sort Deng, Xiaheng
collection PubMed
description INTRODUCTION: Microbiome plays roles in lung adenocarcinoma (LUAD) development and anti-tumor treatment efficacy. Aberrant glycolysis in tumor might promote lactate production that alter tumor microenvironment, affecting microbiome, cancer cells and immune cells. We aimed to construct intratumor microbiome score to predict prognosis of LUAD patients and thoroughly investigate glycolysis and lactate signature’s association with LUAD immune cell infiltration. METHODS: The Cancer Genome Atlas-LUAD (TCGA-LUAD) microbiome data was downloaded from cBioPortal and analyzed to examine its association with overall survival to create a prognostic scoring model. Gene Set Enrichment Analysis (GSEA) was used to find each group’s major mechanisms involved. Our study then investigated the glycolysis and lactate pattern in LUAD patients based on 19 genes, which were correlated with the tumor microenvironment (TME) phenotypes and immunotherapy outcomes. We developed a glycolysis-lactate risk score and signature to accurately predict TME phenotypes, prognosis, and response to immunotherapy. RESULTS: Using the univariate Cox regression analysis, the abundance of 38 genera were identified with prognostic values and a lung-resident microbial score (LMS) was then developed from the TCGA-LUAD-microbiome dataset. Glycolysis hallmark pathway was significantly enriched in high-LMS group and three distinct glycolysis-lactate patterns were generated. Patients in Cluster1 exhibited unfavorable outcomes and might be insensitive to immunotherapy. Glycolysis-lactate score was constructed for predicting prognosis with high accuracy and validated in external cohorts. Gene signature was developed and this signature was elevated in epithelial cells especially in tumor mass on single-cell level. Finally, we found that the glycolysis-lactate signature levels were consistent with the malignancy of histological subtypes. DISCUSSION: Our study demonstrated that an 18-microbe prognostic score and a 19-gene glycolysis-lactate signature for predicting prognosis of LUAD patients. Our LMS, glycolysis-lactate score and glycolysis-lactate signature have potential roles in precision therapy of LUAD patients.
format Online
Article
Text
id pubmed-10469687
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-104696872023-09-01 Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data Deng, Xiaheng Chen, Xiru Luo, Yu Que, Jun Chen, Liang Front Microbiol Microbiology INTRODUCTION: Microbiome plays roles in lung adenocarcinoma (LUAD) development and anti-tumor treatment efficacy. Aberrant glycolysis in tumor might promote lactate production that alter tumor microenvironment, affecting microbiome, cancer cells and immune cells. We aimed to construct intratumor microbiome score to predict prognosis of LUAD patients and thoroughly investigate glycolysis and lactate signature’s association with LUAD immune cell infiltration. METHODS: The Cancer Genome Atlas-LUAD (TCGA-LUAD) microbiome data was downloaded from cBioPortal and analyzed to examine its association with overall survival to create a prognostic scoring model. Gene Set Enrichment Analysis (GSEA) was used to find each group’s major mechanisms involved. Our study then investigated the glycolysis and lactate pattern in LUAD patients based on 19 genes, which were correlated with the tumor microenvironment (TME) phenotypes and immunotherapy outcomes. We developed a glycolysis-lactate risk score and signature to accurately predict TME phenotypes, prognosis, and response to immunotherapy. RESULTS: Using the univariate Cox regression analysis, the abundance of 38 genera were identified with prognostic values and a lung-resident microbial score (LMS) was then developed from the TCGA-LUAD-microbiome dataset. Glycolysis hallmark pathway was significantly enriched in high-LMS group and three distinct glycolysis-lactate patterns were generated. Patients in Cluster1 exhibited unfavorable outcomes and might be insensitive to immunotherapy. Glycolysis-lactate score was constructed for predicting prognosis with high accuracy and validated in external cohorts. Gene signature was developed and this signature was elevated in epithelial cells especially in tumor mass on single-cell level. Finally, we found that the glycolysis-lactate signature levels were consistent with the malignancy of histological subtypes. DISCUSSION: Our study demonstrated that an 18-microbe prognostic score and a 19-gene glycolysis-lactate signature for predicting prognosis of LUAD patients. Our LMS, glycolysis-lactate score and glycolysis-lactate signature have potential roles in precision therapy of LUAD patients. Frontiers Media S.A. 2023-08-17 /pmc/articles/PMC10469687/ /pubmed/37664112 http://dx.doi.org/10.3389/fmicb.2023.1202454 Text en Copyright © 2023 Deng, Chen, Luo, Que and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Deng, Xiaheng
Chen, Xiru
Luo, Yu
Que, Jun
Chen, Liang
Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data
title Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data
title_full Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data
title_fullStr Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data
title_full_unstemmed Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data
title_short Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data
title_sort intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469687/
https://www.ncbi.nlm.nih.gov/pubmed/37664112
http://dx.doi.org/10.3389/fmicb.2023.1202454
work_keys_str_mv AT dengxiaheng intratumormicrobiomederivedglycolysislactatesignaturesdepictsimmuneheterogeneityinlungadenocarcinomabyintegrationofmicrobiomictranscriptomicproteomicandsinglecelldata
AT chenxiru intratumormicrobiomederivedglycolysislactatesignaturesdepictsimmuneheterogeneityinlungadenocarcinomabyintegrationofmicrobiomictranscriptomicproteomicandsinglecelldata
AT luoyu intratumormicrobiomederivedglycolysislactatesignaturesdepictsimmuneheterogeneityinlungadenocarcinomabyintegrationofmicrobiomictranscriptomicproteomicandsinglecelldata
AT quejun intratumormicrobiomederivedglycolysislactatesignaturesdepictsimmuneheterogeneityinlungadenocarcinomabyintegrationofmicrobiomictranscriptomicproteomicandsinglecelldata
AT chenliang intratumormicrobiomederivedglycolysislactatesignaturesdepictsimmuneheterogeneityinlungadenocarcinomabyintegrationofmicrobiomictranscriptomicproteomicandsinglecelldata