DNA methylation–based immune response signature improves patient diagnosis in multiple cancers
Jana Jeschke, Martin Bizet, Christine Desmedt, Emilie Calonne, Sarah Dedeurwaerder, Soizic Garaud, Alexander Koch, Denis Larsimont, Roberto Salgado, Gert Van den Eynden, Karen Willard Gallo, Gianluca Bontempi, Matthieu Defrance, Christos Sotiriou, François Fuks
Jana Jeschke, Martin Bizet, Christine Desmedt, Emilie Calonne, Sarah Dedeurwaerder, Soizic Garaud, Alexander Koch, Denis Larsimont, Roberto Salgado, Gert Van den Eynden, Karen Willard Gallo, Gianluca Bontempi, Matthieu Defrance, Christos Sotiriou, François Fuks
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Clinical Research and Public Health Development Immunology

DNA methylation–based immune response signature improves patient diagnosis in multiple cancers

Abstract

BACKGROUND. The tumor immune response is increasingly associated with better clinical outcomes in breast and other cancers. However, the evaluation of tumor-infiltrating lymphocytes (TILs) relies on histopathological measurements with limited accuracy and reproducibility. Here, we profiled DNA methylation markers to identify a methylation of TIL (MeTIL) signature that recapitulates TIL evaluations and their prognostic value for long-term outcomes in breast cancer (BC). METHODS. MeTIL signature scores were correlated with clinical endpoints reflecting overall or disease-free survival and a pathologic complete response to preoperative anthracycline therapy in 3 BC cohorts from the Jules Bordet Institute in Brussels and in other cancer types from The Cancer Genome Atlas. RESULTS. The MeTIL signature measured TIL distributions in a sensitive manner and predicted survival and response to chemotherapy in BC better than did histopathological assessment of TILs or gene expression–based immune markers, respectively. The MeTIL signature also improved the prediction of survival in other malignancies, including melanoma and lung cancer. Furthermore, the MeTIL signature predicted differences in survival for malignancies in which TILs were not known to have a prognostic value. Finally, we showed that MeTIL markers can be determined by bisulfite pyrosequencing of small amounts of DNA from formalin-fixed, paraffin-embedded tumor tissue, supporting clinical applications for this methodology. CONCLUSIONS. This study highlights the power of DNA methylation to evaluate tumor immune responses and the potential of this approach to improve the diagnosis and treatment of breast and other cancers. FUNDING. This work was funded by the Fonds National de la Recherche Scientifique (FNRS) and Télévie, the INNOVIRIS Brussels Region BRUBREAST Project, the IUAP P7/03 program, the Belgian “Foundation against Cancer,” the Breast Cancer Research Foundation (BCRF), and the Fonds Gaston Ithier.

Authors

Jana Jeschke, Martin Bizet, Christine Desmedt, Emilie Calonne, Sarah Dedeurwaerder, Soizic Garaud, Alexander Koch, Denis Larsimont, Roberto Salgado, Gert Van den Eynden, Karen Willard Gallo, Gianluca Bontempi, Matthieu Defrance, Christos Sotiriou, François Fuks

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Figure 2

Measurement of TIL distributions with DNA methylation (MeTIL signature).

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Measurement of TIL distributions with DNA methylation (MeTIL signature)....
(A) Markers of the MeTIL signature showed highly differential methylation values in normal and cancerous breast epithelial cells (MCF10A, MCF-7, T47D, SKBR3, BT20, MDA-MB-231, MDA-MB-361, ZR-75-1) versus T lymphocytes (WEIS3E5, R12C9, and ex vivo T cells). (B) Unsupervised hierarchical clustering analysis of MeTIL marker β values in CD45+Epcam– (lymphocytes) and CD45–Epcam+ (epithelial) cells sorted from whole breast tumor samples. (C) Unsupervised hierarchical clustering analysis of cohort 1 based on β values of MeTIL markers. Note, a hypomethylated, an intermediate methylated, and a hypermethylated cluster appeared, all of which are associated with differences in BC subtypes, PaTILs, and MeTIL scores. Differences between methylation clusters were assessed with a 1-way ANOVA or χ2 test, and P values are shown in the upper right corner of the heatmap. (D) The MeTIL signature was transformed into a score, and MeTIL scores were computed for T cells, Tregs, B cells, NK cells, granulocytes, monocytes, and DCs. Infinium DNA methylation profiles for these sorted blood cell populations are publicly available in the NCBI’s GEO database (GEO GSE35069, GSE39981, GSE49667, and GSE59796), per the Methods section. The MeTIL score values are plotted on the y axis and blood cell subpopulations on the x axis. Differences in the MeTIL score between the groups including T cells, Tregs, B cells, and NK cells and the group of granulocytes, monocytes, and DCs were assessed with a Student’s t test (*P < 0.05). (E) MeTIL scores were computed in tumors enriched for CTLs with high expression of GZMB and PRF1 GZMB/PRF1-high and in tumors enriched for CTLs with low expression of GZMB and PRF1 GZMB/PRF1-low. The difference in MeTIL scores between the 2 groups was assessed with a Student’s t test, and the P value is shown. (F) MeTIL scores were correlated with the percentage of adipocytes, fibroblasts, and endothelial cells or PaTILs for 62 samples from cohort 1. MeTIL score values are plotted on the y axis and the percentage of cells on the x axis. The correlation was assessed with a Spearman’s rank correlation test. The Spearman’s rank correlation coefficient (rho) and its P value are shown for each plot. Note, because of methodological limitations, fibroblasts and endothelial cells were assessed as 1 cell type. (G) Color map showing the MeTIL score performance for simulations across noise (y axis) and the presence of additional cell type(s) (x axis) (randomly selected methylation values). With a SD of noise of 1, the performance (assessed using the Spearman’s correlation metric R) stayed higher than 0.7, even if the tissue consisted of more than 70% non–BC cells and non–T cells (yellow border). (H) Cohort 1 (105 samples) and cohort 2 (100 samples) were grouped by PaTILs, and MeTIL scores are shown by PaTIL group. MeTIL score values are plotted on the y axis and PaTIL groups on the x axis. Differences in the MeTIL score between groups were assessed with a 1-way ANOVA, and the P value is shown in each plot. (I) TIL distributions in BC subtypes based on MeTIL score (left panel) or PaTILs (right panel) in cohort 1 and cohort 2. Note that the MeTIL score showed greater differences within (especially in LumA and LumB) and between subtypes than did PaTILs. BC subtypes were defined on the basis of IHC results for the hormone receptors and HER2.