Abstract
Purpose
The current evaluation methods for tumor infiltrating lymphocytes (TILs), particularly CD8 + TILs, mainly rely on semiquantitative immunohistochemistry with high variability. We aimed to construct an individualized DNA methylation-based signature for CD8 + TILs (CD8 + MeTIL) that may characterize melanoma immune microenvironment and guide therapeutic selection.
Methods
The transcriptome profiles and DNA methylation data of 457 melanoma patients from The Cancer Genome Atlas (TCGA) database were analyzed. Differential methylation analysis between groups with high and low CD8 + TILs was performed to select differentially methylated positions (DMPs) and define CD8 + MeTIL. The prognostic value of CD8 + MeTIL and its predictive value for immunotherapy response were investigated using multiple melanoma cohorts.
Results
We successfully constructed the CD8 + MeTIL signature based on four DMPs. The survival analyses showed that higher CD8 + MeTIL score was associated with worse survival outcomes in TCGA-SKCM and GSE144487 cohorts. The ROC curve for the predictive analysis revealed that the survival prediction of CD8 + MeTIL score was superior compared with CD8 + TILs (CIBERSORT) and CD8B mRNA expression. Furthermore, we founded that tumors with higher CD8 + MeTIL score were marked with immunosuppressive characteristics, including low immune score and downregulated immune-related pathways. More importantly, the CD8 + MeTIL score showed a potential predictive value for the benefit from immunotherapy in two published cohorts. When combined CD8 + MeTIL with PD-L1 expression, the patient classification showed significantly different immunotherapy response rates and long-term survival outcomes.
Conclusions
The CD8 + MeTIL signature might be as a novel method to evaluate CD8 + TILs and guide immunotherapy approaches.
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Data availability
The data of TCGA-SKCM cohort were downloaded from the UCSC Xena database (http://xena.ucsc.edu/) and cbioPortal (http://www.cbioportal.org). The data of GSE144487 cohort were downloaded from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). The data of Jung19 (GSE119144 and GSE135222) and Cho20 (GSE126043 and GSE126044) were downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/). All patients’ data analyzed from published studies are ref-erenced to and publicly available accordingly.
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Funding
This work was supported by grants from National Natural Science Foundation of China (82002906 and 81902789) and CSCO-Roche Cancer Research Fund 2019 (Y-Roche2019/2-0028).
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SC and JY contributed to the study conception and design. Material preparation, data collection and analysis were performed by JY, XW, and YZ. The first draft of the manuscript was written by JY and XW. All authors read and approved the final manuscript.
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Yan, J., Wu, X., Zhu, Y. et al. Genome-wide DNA methylation profile analysis identifies an individualized predictive signature for melanoma immune response. J Cancer Res Clin Oncol 149, 343–356 (2023). https://doi.org/10.1007/s00432-022-04566-1
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DOI: https://doi.org/10.1007/s00432-022-04566-1