Original ResearchOverexpression of transposable elements is associated with immune evasion and poor outcome in colorectal cancer
Introduction
Almost half of the human genome is comprised of transposable elements (TEs). They are also known as ‘jumping genes’, as some have the ability to move or make copies of themselves to other locations in the genome. TEs are divided into class 1 retrotransposons and class 2 DNA transposons, which are further subclassified into subclasses, superfamilies and over 1000 subfamilies [1]. Although most TEs are no longer active, existed evidence has suggested that the Alu, L1, SAV and possibly human endogenous retrovirus (HERV)-K elements remain active mobile in human genome [2]. These active transposons are capable to produce human genetic diversity and cause human diseases, including cancers, by integrating into human genes [3]. Generally, most TEs are mainly epigenetically silenced in normal tissues [4] but can become reactivated because of DNA hypomethylation in cancers [5], resulting in the transcription of retrotransposons into RNA or direct transposition of DNA transposons. One potential consequence of the reactivation of TEs is to stimulate the immune system via viral mimicry [6,7]. For instance, the human endogenous retrovirus was shown to be reactivated by DNA methyltransferase (DNMT) inhibitors, which was accompanied by the up-regulation of viral defence pathways in ovarian [8] and colorectal [6] cancer cells. Recently, it has been shown that some TEs such as HERVs can also serve as tumour antigen signals [7]. These observations have demonstrated the critical roles of TEs in anti-tumour immunity. Nonetheless, how TE expression influences anti-cancer immune response and clinical outcome remains unclear.
Patients whose cancer have higher immune cell infiltration tend to have a better prognosis. For instance, Immunoscore has been developed based on the density of CD3+ and cytotoxic CD8+ T cells in the tumour and the invasive margin in colorectal cancer (CRC) [9] and has been shown to have a prognostic value superior to American Joint Committee on Cancer stage classification [10]. Intriguingly, a recent study identified a high-risk subgroup of CRC patients with high tumour immune infiltration as indicated by high CD8A and CD274 (PD-L1) gene expression [11]. Termed ‘immune overdrive’, the subgroup of patients with this signature included both microsatellite instability (MSI) and stable status, increased transforming grow factor TGF)-β activation and overexpression of immune response and checkpoint genes. However, whether such patients are likely to benefit from immune checkpoint inhibitors therapy remain to be evaluated, and the underlying factor behind this phenotype is unknown.
Given the recent evidence for the role of TEs in triggering cancer immune response, in this study, we examine the role of TE expression in driving immune response in CRC. We find that TE overexpression is predictive of tumour immune infiltration and is associated with poor prognosis in an MSI and tumour mutation burden (TMB) independent manner. Importantly, we showed that TE overexpression promotes immune evasion by stimulating PD-L1 expression in immune cells via interferon (IFN) signalling activation. These findings highlight an important role for TE expression in CRC biology and patient prognosis.
Section snippets
Development of TE expression score for stratification of CRC patient samples
To explore the TE expression landscape in CRC, we first quantified the expression of ~1,000 TEs at the subfamily level in The Cancer Genome Atlas (TCGA) cohort (n = 590, Figs. S1A–C). To identify prognostically and biologically important TEs, we performed survival analysis based on patient end-points and correlative analysis against immunologically relevant gene sets, respectively (see Methods). This analysis identified 365 prognosis-associated TEs (Figs. S1D–F, Table S1), with most having a
Discussion
Molecular subtyping based on genomic and transcriptomic data has facilitated an improved understanding of molecular features in cancers and has guided targeted therapeutic strategies [32]. For instance, MSI is a critical subtype in CRC that has been associated with high immune infiltration (e.g. CD8+ T cells) [16] and a lower risk of relapse [33]. Generally, solid cancers, including CRC, with higher immune infiltration have better survival [9,15]. However, an immune overdrive phenotype has been
Quantification of transposable element expression
We used the REdiscoverTE pipeline to quantify TE subfamily expression based on RNA sequencing data as described by Kong et al. [12], which has been shown to outperform three existing methods, including Repenrich [48], SalmonTE [49] and the approach used by Rooney et al. [50]. In brief, the pipeline quantifies the number of reads mapping to each TE subfamily without uniquely identifying individual instances in the genome.
Raw counts for each TE subfamily from REdiscoverTE were normalised using
Authors contribution
XZ and JWHW conceived this study. HF, KG, and JAB helped to collect the public data. XZ and JWHW conducted statistical analysis. HF, KG, and JAB helped to interpret the results. XZ and JWHW wrote the manuscript.
Availability of data and material
TCGA CRC RNA sequencing data was directly analysed on Cancer Genomics Cloud (CGC) using the custom pipeline [http://www.cancergenomicscloud.org/]. The clinical data of TCGA CRC and methylaton 450K array data was obtained from [https://xenabrowser.net/]. CPTAC colon RNA sequencing data was downloaded from [https://portal.gdc.cancer.gov/]. The clinical data of CPTAC colon was downloaded from [http://linkedomics.org/cptac-colon/]. GEO datasets were downloaded from [https://www.ncbi.nlm.nih.gov/geo/
Funding
This work was supported by the Research Grants Council, HK (17100920 and C7028-19G) and seed funding from The University of Hong Kong (JWHW).
Conflict of interest statement
The authors have declared that no conflict of interest exists.
Acknowledgements
The authors thank the CGC team for helping to implement the TE analysis pipeline on CGC with pilot funds provided by Seven Bridges Genomics.
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