MEpurity: estimating tumor purity using DNA methylation data

Liu, Bowen; Yang, Xiaofei; Wang, Ting-Jie; Lin, Jiadong; Kang, Yongyong; Jia, Peng; Ye, Kai

doi:10.1093/bioinformatics/btz555

Cited by 7 publications

(5 citation statements)

References 11 publications

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“…DNA methylation measurements are also compromised by non-malignant cells such as adjacent normal and infiltrating immune cells resident in tumor tissues. In fact, DNA methylation is often used to assess the degree of tumor purity based on the extent to which genomic hypomethylation in tumor cells is diluted by non-malignant cells with normal methylation status (20,21,(23)(24)(25)(26). Such cellular heterogeneity should be accounted for by adjusting cell composition (27)(28)(29)(30) to remove artefactual intertumoral variations in methylation.…”

Section: Discussionmentioning

confidence: 99%

Genomic hypomethylation in cell-free DNA predicts responses to checkpoint blockade in lung and breast cancer

Kim,

Shin

et al. 2023

Preprint

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Genomic hypomethylation has recently been identified as a determinant of therapeutic responses to immune checkpoint blockade (ICB). However, tumor tissue is often unattainable, and tissue-based methylation profiling suffers from low tumor purity. In this study, we developed an assay named iMethyl to estimate the genomic hypomethylation status from cell-free DNA (cfDNA) as well as tissue by deep targeted sequencing of young LINE-1 elements with > 400,000 reads per sample. iMethyl was applied to a total of 653 ICB samples encompassing lung cancer (cfDNA n=167; tissue n=137; cfDNA early during treatment n=40), breast cancer (cfDNA n=91; tissue n=50; PBMC n=50; cfDNA at progression n=44), and ovarian cancer (tissue n=74). iMethyl-tissue had better predictive power than tumor mutation burden and PD-L1 expression. Furthermore, iMethyl-liquid predicted ICB responses accurately regardless of the tumor purity of tissue samples. iMethyl-liquid was also able to monitor therapeutic responses early during treatment (3 or 6 weeks after initiation of ICB) and detect progressive hypomethylation accompanying tumor progression. In conclusion, our method allows for reliable noninvasive prediction, early evaluation, and monitoring of clinical responses to ICB therapy.

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Section: Discussionmentioning

confidence: 99%

Genomic hypomethylation in cell-free DNA predicts responses to checkpoint blockade in lung and breast cancer

Kim,

Shin

et al. 2023

Preprint

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“…Secondly, HiTIMED uses DNA methylation signatures that are specific to tumor type. Most of the existing methods developed a universal reference library for all types of tumors [ 16 , 40 ]. Although, it is possible to estimate tumor purity with a signature that captures generalizable DNA methylation changes across all tumor types.…”

Section: Discussionmentioning

confidence: 99%

HiTIMED: hierarchical tumor immune microenvironment epigenetic deconvolution for accurate cell type resolution in the tumor microenvironment using tumor-type-specific DNA methylation data

et al. 2022

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Background Cellular compositions of solid tumor microenvironments are heterogeneous, varying across patients and tumor types. High-resolution profiling of the tumor microenvironment cell composition is crucial to understanding its biological and clinical implications. Previously, tumor microenvironment gene expression and DNA methylation-based deconvolution approaches have been shown to deconvolve major cell types. However, existing methods lack accuracy and specificity to tumor type and include limited identification of individual cell types. Results We employed a novel tumor-type-specific hierarchical model using DNA methylation data to deconvolve the tumor microenvironment with high resolution, accuracy, and specificity. The deconvolution algorithm is named HiTIMED. Seventeen cell types from three major tumor microenvironment components can be profiled (tumor, immune, angiogenic) by HiTIMED, and it provides tumor-type-specific models for twenty carcinoma types. We demonstrate the prognostic significance of cell types that other tumor microenvironment deconvolution methods do not capture. Conclusion We developed HiTIMED, a DNA methylation-based algorithm, to estimate cell proportions in the tumor microenvironment with high resolution and accuracy. HiTIMED deconvolution is amenable to archival biospecimens providing high-resolution profiles enabling to study of clinical and biological implications of variation and composition of the tumor microenvironment.

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“…We used a variety of tools to estimate tumour cell composition in the 54 primary siNETs from DNAm data. MEPurity [ 19 , 20 ] provided direct estimates of tumour purity. The epiSCORE R package [ 21 ] estimated proportions of broad cell types (e.g., immune cell, epithelial cell, etc.).…”

Section: Methodsmentioning

confidence: 99%

Chromosome 18 Loss of Heterozygosity in Small Intestinal Neuroendocrine Tumours: Multi-Omic and Tumour Composition Analyses

et al. 2023

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Background: Small intestinal neuroendocrine tumours (siNETs) are rare neoplasms which present with low mutational burden and can be subtyped based on copy number variation (CNV). Currently, siNETs can be molecularly classified as having chromosome 18 loss of heterozygosity (18LOH), multiple CNVs (MultiCNV), or no CNVs. 18LOH tumours have better progression free survival when compared to MultiCNV and NoCNV tumours, however the mechanism underlying this is unknown, and clinical practice does not currently consider CNV status. Methods: Here, we use genome-wide tumour DNA methylation (n=54) and gene expression (n=20 matched to DNA methylation) to better understand how gene regulation varies by 18LOH status. We then use multiple cell deconvolution methods to analyse how cell composition varies between 18LOH status, and determine potential associations with progression free survival. Results: We identified 27,464 differentially methylated CpG sites and 12 differentially expressed genes between 18LOH and non-18LOH (MultiCNV + NoCNV) siNETs. Although few differentially expressed genes were identified, these genes were highly enriched with the differentially methylated CpG sites compared to the rest of the genome. We identified differences in tumour micro-environment between 18LOH and non-18LOH tumours, including CD14+ infiltration in a subset of non-18LOH tumours which had the poorest clinical outcomes. Conclusions: We identify a small number of genes which appear to be linked to the 18LOH status of siNETs, and find evidence of potential epigenetic dysregulation of these genes. We also find a potential prognostic marker for worse progression free outcomes in the form of higher CD14 infiltration in non-18LOH siNETs.

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MEpurity: estimating tumor purity using DNA methylation data

Cited by 7 publications

References 11 publications

Genomic hypomethylation in cell-free DNA predicts responses to checkpoint blockade in lung and breast cancer

Genomic hypomethylation in cell-free DNA predicts responses to checkpoint blockade in lung and breast cancer

HiTIMED: hierarchical tumor immune microenvironment epigenetic deconvolution for accurate cell type resolution in the tumor microenvironment using tumor-type-specific DNA methylation data

Chromosome 18 Loss of Heterozygosity in Small Intestinal Neuroendocrine Tumours: Multi-Omic and Tumour Composition Analyses

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