Immune-related pan-cancer gene expression signatures of patient survival revealed by NanoString-based analyses

Alberto D'Angelo, Huseyin Kilili, Robert Chapman, Daniele Generali, Ingeborg Tinhofer, Stefano Luminari, Benedetta Donati, Alessia Ciarrocchi, Riccardo Giannini, Roberto Moretto, Chiara Cremolini, Filippo Pietrantonio, Navid Sobhani, Debora Bonazza, Robert Prins, Seung Geun Song, Yoon Kyung Jeon, Giuseppina Pisignano, Mattia Cinelli, Stefan BagbyAraxi O Urrutia

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Abstract

The immune system plays a central role in the onset and progression of cancer. A better understanding of transcriptional changes in immune cell-related genes associated with cancer progression, and their significance in disease prognosis, is therefore needed. NanoString-based targeted gene expression profiling has advantages for deployment in a clinical setting over RNA-seq technologies. We analysed NanoString PanCancer Immune Profiling panel gene expression data encompassing 770 genes, and overall survival data, from multiple previous studies covering 10 different cancer types, including solid and blood malignancies, across 515 patients. This analysis revealed an immune gene signature comprising 39 genes that were upregulated in those patients with shorter overall survival; of these 39 genes, three (MAGEC2, SSX1 and ULBP2) were common to both solid and blood malignancies. Most of the genes identified have previously been reported as relevant in one or more cancer types. Using Cibersort, we investigated immune cell levels within individual cancer types and across groups of cancers, as well as in shorter and longer overall survival groups. Patients with shorter survival had a higher proportion of M2 macrophages and γδ T cells. Patients with longer overall survival had a higher proportion of CD8+ T cells, CD4+ T memory cells, NK cells and, unexpectedly, T regulatory cells. Using a transcriptomics platform with certain advantages for deployment in a clinical setting, our multi-cancer meta-analysis of immune gene expression and overall survival data has identified a specific transcriptional profile associated with poor overall survival.

Original languageEnglish
Article numbere0280364
JournalPLoS ONE
Volume18
Issue number1
DOIs
Publication statusPublished - 17 Jan 2023

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Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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