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Pan-cancer methylation analysis reveals an inverse correlation of tumor immunogenicity with methylation aberrancy

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Abstract

Tumor immunogenicity is driven by various genomic and transcriptomic factors but the association with the overall status of methylation aberrancy is not well established. We analyzed The Cancer Genome Atlas pan-cancer database to investigate whether the overall methylation aberrancy links to the immune evasion of tumor. We created the definitions of hypermethylation burden, hypomethylation burden and methylation burden to establish the values that represent the degree of methylation aberrancy from human methylation 450 K array data. Both hypermethylation burden and hypomethylation burden significantly correlated with global methylation level as well as methylation subtypes defined in previous literatures. Then we evaluated whether methylation burden correlates with tumor immunogenicity and found that methylation burden showed a significant negative correlation with cytolytic activity score, which represent cytotoxic T cell activity, in pan-cancer (Spearman rho = − 0.37, p < 0.001) and 30 of 33 individual cancer types. Furthermore, this correlation was independent of mutation burden and chromosomal instability in multivariate regression analysis. We validated the findings in the external cohorts and outcomes of patients who were treated with immune checkpoint inhibitors, which showed that high methylation burden group had significantly poor progression-free survival (Hazard ratio 1.74, p = 0.038). Overall, the degree of methylation aberrancy negatively correlated with tumor immunogenicity. These findings emphasize the importance of methylation aberrancy for tumors to evade immune surveillance and warrant further development of methylation biomarker.

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All data generated or analyzed during this study are included in this published article and its supplementary information files with an exception of clinical data of SMC cohort. The data of SMC cohort are available from the authors upon reasonable request.

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Acknowledgements

The results shown here are in part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2019R1C1C1004295), and the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI17C0048).

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Author notes

  1. Changhee Park and Kyeonghun Jeong have authors equally contributed the current study.

Authors and Affiliations

  1. Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea

    Changhee Park, Chan-Young Ock, Miso Kim, Bhumsuk Keam, Tae Min Kim, Dong-Wan Kim & Dae Seog Heo

  2. Division of Clinical Bioinformatics, Biomedical Research Institute, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea

    Kyeonghun Jeong, Joon-Hyeong Park & Sohee Jung

  3. Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea

    Jeong Mo Bae, Yoon Kyung Jeon, Gyeong Hoon Kang & Doo Hyun Chung

  4. Cancer Research Institute, Seoul National University, Seoul, Republic of Korea

    Bhumsuk Keam, Tae Min Kim, Dong-Wan Kim & Dae Seog Heo

  5. Division of Hematology/Oncology, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

    Se-Hoon Lee

  6. Department of Systems Biology, Division of Basic Sciences, MD Anderson Cancer Center, Houston, TX, USA

    Ju-Seog Lee

  7. Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, Republic of Korea

    Kwangsoo Kim

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  1. Changhee Park
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Contributions

Conceptualization: CYO and CP; Methodology and Software: KK, KJ, JHP and SJ; Validation and Formal Analysis, CYO, KK, CP, KJ and JHP; Funding Acquisition CYO; Supervision CYO, MK, BK, TMK, YKJ, SHL, JSL, DWK, GHK, DHC, and DSH; Visualization and Writing—Original Draft, CP and KJ; Writing—Review & Editing, Approval of Manuscript, all authors.

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Correspondence to Kwangsoo Kim or Chan-Young Ock.

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Park, C., Jeong, K., Park, JH. et al. Pan-cancer methylation analysis reveals an inverse correlation of tumor immunogenicity with methylation aberrancy. Cancer Immunol Immunother 70, 1605–1617 (2021). https://doi.org/10.1007/s00262-020-02796-1

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