Interval breast cancer is associated with interferon immune response.


Journal

European journal of cancer (Oxford, England : 1990)
ISSN: 1879-0852
Titre abrégé: Eur J Cancer
Pays: England
ID NLM: 9005373

Informations de publication

Date de publication:
02 2022
Historique:
received: 03 08 2021
revised: 30 11 2021
accepted: 02 12 2021
pubmed: 14 1 2022
medline: 22 4 2022
entrez: 13 1 2022
Statut: ppublish

Résumé

The aggressive nature of breast cancers detected between planned mammographic screens, so-called interval cancers, remains elusive. Here, we aim to characterise underlying molecular features of interval cancer. From 672 patients with invasive breast cancer, we analysed gene expression differences between 90 'true' interval cancer cases (i.e. women with low-dense breasts defined as per cent mammographic density <25%) and 310 screen-detected tumours while accounting for PAM50 subtypes and thus overall tumour aggressiveness. We computed an interval cancer gene expression profile (IC-Gx) in a total of 2270 breast tumours (regardless of interval cancer status) and tested for association with expression-based immune subtypes in breast cancer. In addition, we investigated the contribution of inherited and somatic genetic variants in distinct features of interval cancer. We identified 8331 genes nominally associated with interval cancer (P-value < 0.05, fold-change > 1.5). Gene set enrichment analysis showed immune-related pathways as key processes altered in interval cancer. Our IC-Gx, based on 47 genes with the strongest associations (false discovery rate < 0.05), was found to be associated mainly with immune subtypes involving interferon response. We isolated an interaction network of interval cancer and interferon genes for which a significant load of somatic and germline variants in class I interferon genes was observed. We identified novel molecular features of interval breast cancer highlighting interferon pathways as a potential target for prevention or treatment.

Sections du résumé

BACKGROUND
The aggressive nature of breast cancers detected between planned mammographic screens, so-called interval cancers, remains elusive. Here, we aim to characterise underlying molecular features of interval cancer.
METHODS
From 672 patients with invasive breast cancer, we analysed gene expression differences between 90 'true' interval cancer cases (i.e. women with low-dense breasts defined as per cent mammographic density <25%) and 310 screen-detected tumours while accounting for PAM50 subtypes and thus overall tumour aggressiveness. We computed an interval cancer gene expression profile (IC-Gx) in a total of 2270 breast tumours (regardless of interval cancer status) and tested for association with expression-based immune subtypes in breast cancer. In addition, we investigated the contribution of inherited and somatic genetic variants in distinct features of interval cancer.
RESULTS
We identified 8331 genes nominally associated with interval cancer (P-value < 0.05, fold-change > 1.5). Gene set enrichment analysis showed immune-related pathways as key processes altered in interval cancer. Our IC-Gx, based on 47 genes with the strongest associations (false discovery rate < 0.05), was found to be associated mainly with immune subtypes involving interferon response. We isolated an interaction network of interval cancer and interferon genes for which a significant load of somatic and germline variants in class I interferon genes was observed.
CONCLUSION
We identified novel molecular features of interval breast cancer highlighting interferon pathways as a potential target for prevention or treatment.

Identifiants

pubmed: 35026490
pii: S0959-8049(21)01258-2
doi: 10.1016/j.ejca.2021.12.003
pii:
doi:

Substances chimiques

Interferons 9008-11-1

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

194-205

Informations de copyright

Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest statement The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.

Auteurs

Emilio Ugalde-Morales (E)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. Electronic address: emilio.ugalde.morales@ki.se.

Felix Grassmann (F)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Health and Medical University, Potsdam, Germany.

Keith Humphreys (K)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Swedish EScience Research Centre (SeRC), Karolinska Institutet Stockholm, SE-17177, Sweden.

Jingmei Li (J)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Human Genetics, Genome Institute of Singapore, Singapore, Singapore; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.

Mikael Eriksson (M)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Nicholas P Tobin (NP)

Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.

Linda S Lindström (LS)

Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.

Johan Vallon-Christersson (J)

Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Medicon Village 404-A2 Lund, SE-22381, Sweden; Lund University Cancer Center Lund, SE-22381, Sweden; CREATE Health Strategic Centre for Translational Cancer Research, Lund University Lund, SE-22381, Sweden.

Åke Borg (Å)

Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Medicon Village 404-A2 Lund, SE-22381, Sweden; Lund University Cancer Center Lund, SE-22381, Sweden; CREATE Health Strategic Centre for Translational Cancer Research, Lund University Lund, SE-22381, Sweden; Department of Clinical Sciences, SCIBLU Genomics, Lund University Lund, SE-22381, Sweden.

Per Hall (P)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Oncology, Södersjukhuset, Stockholm, Sweden.

Kamila Czene (K)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

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Classifications MeSH