A computational pipeline for identifying gene targets and signalling pathways in cancer cells to improve lymphocyte infiltration and immune checkpoint therapy efficacy.

Antigen presentation Immune checkpoint blockade Immunotherapy SUN1 T cell infiltration Tumour microenvironment

Journal

EBioMedicine
ISSN: 2352-3964
Titre abrégé: EBioMedicine
Pays: Netherlands
ID NLM: 101647039

Informations de publication

Date de publication:
27 May 2024
Historique:
received: 21 12 2023
revised: 28 04 2024
accepted: 09 05 2024
medline: 29 5 2024
pubmed: 29 5 2024
entrez: 28 5 2024
Statut: aheadofprint

Résumé

Tumour-infiltrating lymphocytes (TILs) are crucial for effective immune checkpoint blockade (ICB) therapy in solid tumours. However, ∼70% of these tumours exhibit poor lymphocyte infiltration, rendering ICB therapies less effective. We developed a bioinformatics pipeline integrating multiple previously unconsidered factors or datasets, including tumour cell immune-related pathways, copy number variation (CNV), and single tumour cell sequencing data, as well as tumour mRNA-seq data and patient survival data, to identify targets that can potentially improve T cell infiltration and enhance ICB efficacy. Furthermore, we conducted wet-lab experiments and successfully validated one of the top-identified genes. We applied this pipeline in solid tumours of the Cancer Genome Atlas (TCGA) and identified a set of genes in 18 cancer types that might potentially improve lymphocyte infiltration and ICB efficacy, providing a valuable drug target resource to be further explored. Importantly, we experimentally validated SUN1, which had not been linked to T cell infiltration and ICB therapy previously, but was one of the top-identified gene targets among 3 cancer types based on the pipeline, in a mouse colon cancer syngeneic model. We showed that Sun1 KO could significantly enhance antigen presentation, increase T-cell infiltration, and improve anti-PD1 treatment efficacy. Moreover, with a single-cell multiome analysis, we identified subgene regulatory networks (sub-GRNs) showing Stat proteins play important roles in enhancing the immune-related pathways in Sun1-KO cancer cells. This study not only established a computational pipeline for discovering new gene targets and signalling pathways in cancer cells that block T-cell infiltration, but also provided a gene target pool for further exploration in improving lymphocyte infiltration and ICB efficacy in solid tumours. A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Sections du résumé

BACKGROUND BACKGROUND
Tumour-infiltrating lymphocytes (TILs) are crucial for effective immune checkpoint blockade (ICB) therapy in solid tumours. However, ∼70% of these tumours exhibit poor lymphocyte infiltration, rendering ICB therapies less effective.
METHODS METHODS
We developed a bioinformatics pipeline integrating multiple previously unconsidered factors or datasets, including tumour cell immune-related pathways, copy number variation (CNV), and single tumour cell sequencing data, as well as tumour mRNA-seq data and patient survival data, to identify targets that can potentially improve T cell infiltration and enhance ICB efficacy. Furthermore, we conducted wet-lab experiments and successfully validated one of the top-identified genes.
FINDINGS RESULTS
We applied this pipeline in solid tumours of the Cancer Genome Atlas (TCGA) and identified a set of genes in 18 cancer types that might potentially improve lymphocyte infiltration and ICB efficacy, providing a valuable drug target resource to be further explored. Importantly, we experimentally validated SUN1, which had not been linked to T cell infiltration and ICB therapy previously, but was one of the top-identified gene targets among 3 cancer types based on the pipeline, in a mouse colon cancer syngeneic model. We showed that Sun1 KO could significantly enhance antigen presentation, increase T-cell infiltration, and improve anti-PD1 treatment efficacy. Moreover, with a single-cell multiome analysis, we identified subgene regulatory networks (sub-GRNs) showing Stat proteins play important roles in enhancing the immune-related pathways in Sun1-KO cancer cells.
INTERPRETATION CONCLUSIONS
This study not only established a computational pipeline for discovering new gene targets and signalling pathways in cancer cells that block T-cell infiltration, but also provided a gene target pool for further exploration in improving lymphocyte infiltration and ICB efficacy in solid tumours.
FUNDING BACKGROUND
A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Identifiants

pubmed: 38805852
pii: S2352-3964(24)00202-0
doi: 10.1016/j.ebiom.2024.105167
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

105167

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests All authors declare no potential conflicts of interest.

Auteurs

Sahar Nasr (S)

Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, T2N 1N4, Canada.

Lin Li (L)

Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, T2N 1N4, Canada; Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, 116024, China. Electronic address: lli@dlut.edu.cn.

Mohammad Asad (M)

Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, T2N 1N4, Canada.

Mahroo Moridi (M)

Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, T2N 1N4, Canada.

Megan Wang (M)

Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, T2N 1N4, Canada.

Franz J Zemp (FJ)

Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, T2N 1N4, Canada.

Douglas J Mahoney (DJ)

Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, AB, T2N 1N4, Canada.

Edwin Wang (E)

Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, T2N 1N4, Canada. Electronic address: edwin.wang@ucalgary.ca.

Classifications MeSH