The potential influence of underlying differences in relative leukocyte distributions in studies involving blood-based profiling of DNA methylation is well recognized and has prompted development of a set of statistical methods for inferring changes in the distribution of white blood cells using DNA methylation signatures. However, the extent to which this methodology can accurately predict cell-type proportions based on blood-derived DNA methylation data in a large-scale epigenome-wide association study (EWAS) has yet to be examined. We used publicly available data deposited in the Gene Expression Omnibus (GEO) database (accession number GSE37008), which consisted of both blood-derived epigenome-wide DNA methylation data assayed using the Illumina Infinium HumanMethylation27 BeadArray and complete blood cell (CBC) counts among a community cohort of 94 non-diseased individuals. Constrained projection (CP) was used to obtain predictions of the proportions of lymphocytes, monocytes and granulocytes for each of the study samples based on their DNA methylation signatures. Our findings demonstrated high consistency between the average CBC-derived and predicted percentage of monocytes and lymphocytes (17.9% and 17.6% for monocytes and 82.1% and 81.4% for lymphocytes), with root mean squared error (rMSE) of 5% and 6%, for monocytes and lymphocytes, respectively. Similarly, there was moderate-high correlation between the CP-predicted and CBC-derived percentages of monocytes and lymphocytes (0.60 and 0.61, respectively), and these results were robust to the number of leukocyte differentially methylated regions (L-DMRs) used for CP prediction. These results serve as further validation of the CP approach and highlight the promise of this technique for EWAS where DNA methylation is profiled using whole-blood genomic DNA.

Background

Blood leukocytes from patients with solid tumors exhibit complex and distinct cancer-associated patterns of DNA methylation. However, the biologic mechanisms underlying these patterns remain poorly understood. Because epigenetic biomarkers offer significant clinical potential for cancer detection, we sought to address a mechanistic gap in recently published works, hypothesizing that blood-based epigenetic variation may be due to shifts in leukocyte populations.

Methods

We identified differentially methylated regions (DMR) among leukocyte subtypes using epigenome-wide DNA methylation profiling of purified peripheral blood leukocyte subtypes from healthy donors. These leukocyte-tagging DMRs were then evaluated using epigenome-wide blood methylation data from three independent case-control studies of different cancers.

Results

A substantial proportion of the top 50 leukocyte DMRs were significantly differentially methylated among head and neck squamous cell carcinoma (HNSCC) cases and ovarian cancer cases compared with cancer-free controls (48 and 47 of 50, respectively). Methylation classes derived from leukocyte DMRs were significantly associated cancer case status (P < 0.001, P < 0.03, and P < 0.001) for all three cancer types: HNSCC, bladder cancer, and ovarian cancer, respectively and predicted cancer status with a high degree of accuracy (area under the curve [AUC] = 0.82, 0.83, and 0.67).

Conclusions

These results suggest that shifts in leukocyte subpopulations may account for a considerable proportion of variability in peripheral blood DNA methylation patterns of solid tumors.

Impact

This illustrates the potential use of DNA methylation profiles for identifying shifts in leukocyte populations representative of disease, and that such profiles may represent powerful new diagnostic tools, applicable to a range of solid tumors.

Epigenome-wide studies of DNA methylation using blood-derived DNA from cancer patients are complicated by the heterogeneity of cell types within blood and the associated cell lineage specification of DNA methylation signatures. Here, we applied a novel set of analytic approaches to assess the association between cancer case-status and DNA methylation adjusted for leukocyte variation using blood specimens from three case-control cancer studies (bladder: 223 cases, 205 controls; head and neck: 92 cases, 92 controls; and ovarian: 131 cases, 274 controls). Using previously published data on leukocyte-specific CpG loci and a recently described approach to deconvolute subject-specific blood composition, we performed an epigenome-wide analysis to examine the association between blood-based DNA methylation patterns and each of the three aforementioned solid tumor types adjusted for cellular heterogeneity in blood. After adjusting for leukocyte profile in our epigenome-wide analysis, the omnibus association between case-status and methylation was significant for all three studies (bladder cancer: P = 0.047; HNSCC: P = 0.013; ovarian cancer: P = 0.0002). Subsequent analyses revealed that CpG sites associated with cancer were enriched for transcription factor binding motifs involved with cancer-associated pathways. These results support the existence of cancer-associated DNA methylation profiles in the blood of solid tumor patients that are independent of alterations in normal leukocyte distributions. Adoption of the methods developed here will make it feasible to rigorously assess the influence of variability of normal leukocyte profiles when investigating cancer related changes in blood-based epigenome-wide association studies.

The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles ("MISEV") guidelines for the field in 2014. We now update these "MISEV2014" guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.