Spatial meta-transcriptomics reveal associations of intratumor bacteria burden with lung cancer cells showing a distinct oncogenic signature.

lung neoplasms translational medical research tumor microenvironment

Journal

Journal for immunotherapy of cancer
ISSN: 2051-1426
Titre abrégé: J Immunother Cancer
Pays: England
ID NLM: 101620585

Informations de publication

Date de publication:
07 2022
Historique:
accepted: 31 05 2022
entrez: 6 7 2022
pubmed: 7 7 2022
medline: 9 7 2022
Statut: ppublish

Résumé

The lung intratumor microbiome influences lung cancer tumorigenesis and treatment responses, but detailed data on the extent, location, and effects of microbes within lung tumors are missing, information needed for improved prognosis and treatment. To address this gap, we developed a novel spatial meta-transcriptomic method simultaneously detecting the expression level of 1,811 host genes and 3 microbe targets (bacteria, fungi, and cytomegalovirus). After rigorous validation, we analyzed the spatial meta-transcriptomic profiles of tumor cells, T cells, macrophages, other immune cells, and stroma in surgically resected tumor samples from 12 patients with early-stage lung cancer. Bacterial burden was significantly higher in tumor cells compared with T cells, macrophages, other immune cells, and stroma. This burden increased from tumor-adjacent normal lung and tertiary lymphoid structures to tumor cells to the airways, suggesting that lung intratumor bacteria derive from the latter route of entry. Expression of oncogenic β-catenin was strongly correlated with bacterial burden, as were tumor histological subtypes and environmental factors. Intratumor bacteria were enriched with tumor cells and associated with multiple oncogenic pathways, supporting a rationale for reducing the local intratumor microbiome in lung cancer for patient benefit. NCT00242723, NCT02146170.

Sections du résumé

BACKGROUND
The lung intratumor microbiome influences lung cancer tumorigenesis and treatment responses, but detailed data on the extent, location, and effects of microbes within lung tumors are missing, information needed for improved prognosis and treatment.
METHODS
To address this gap, we developed a novel spatial meta-transcriptomic method simultaneously detecting the expression level of 1,811 host genes and 3 microbe targets (bacteria, fungi, and cytomegalovirus). After rigorous validation, we analyzed the spatial meta-transcriptomic profiles of tumor cells, T cells, macrophages, other immune cells, and stroma in surgically resected tumor samples from 12 patients with early-stage lung cancer.
RESULTS
Bacterial burden was significantly higher in tumor cells compared with T cells, macrophages, other immune cells, and stroma. This burden increased from tumor-adjacent normal lung and tertiary lymphoid structures to tumor cells to the airways, suggesting that lung intratumor bacteria derive from the latter route of entry. Expression of oncogenic β-catenin was strongly correlated with bacterial burden, as were tumor histological subtypes and environmental factors.
CONCLUSIONS
Intratumor bacteria were enriched with tumor cells and associated with multiple oncogenic pathways, supporting a rationale for reducing the local intratumor microbiome in lung cancer for patient benefit.
TRIAL REGISTRATION NUMBER
NCT00242723, NCT02146170.

Identifiants

pubmed: 35793869
pii: jitc-2022-004698
doi: 10.1136/jitc-2022-004698
pmc: PMC9260850
pii:
doi:

Banques de données

ClinicalTrials.gov
['NCT02146170', 'NCT00242723']

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: PD is an employee and stockholder at NanoString Technologies. All other authors declare no competing interests. YZ is currently an employee at GlaxoSmithKline. All other authors declare no competing interests.

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Auteurs

Abigail Wong-Rolle (A)

Thoracic and GI Malignancies Branch, National Cancer Institute, Bethesda, Maryland, USA.
Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, Bethesda, Maryland, USA.

Qiang Dong (Q)

Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Yunhua Zhu (Y)

Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology, NIAID, Bethesda, Maryland, USA.

Prajan Divakar (P)

NanoString Technologies Inc, Seattle, Washington State, USA.

Jyh Liang Hor (JL)

Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, Bethesda, Maryland, USA.

Noemi Kedei (N)

Collaborative Protein Technology Resource, NCI, Bethesda, Maryland, USA.

Madeline Wong (M)

CCR Genomics Core, National Cancer Institute, Bethesda, Maryland, USA.

Desiree Tillo (D)

CCR Genomics Core, National Cancer Institute, Bethesda, Maryland, USA.
Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA.

Elizabeth A Conner (EA)

CCR Genomics Core, National Cancer Institute, Bethesda, Maryland, USA.

Arun Rajan (A)

Thoracic and GI Malignancies Branch, National Cancer Institute, Bethesda, Maryland, USA.

David S Schrump (DS)

Thoracic Surgery Branch, National Cancer Institute, Bethesda, Maryland, USA.

Chengcheng Jin (C)

Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Ronald N Germain (RN)

Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, Bethesda, Maryland, USA.

Chen Zhao (C)

Thoracic and GI Malignancies Branch, National Cancer Institute, Bethesda, Maryland, USA chen.zhao@nih.gov.
Lymphocyte Biology Section, Laboratory of Immune System Biology, NIAID, Bethesda, Maryland, USA.

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Classifications MeSH