Epidemiological studies of DNA methylation (DNAm) profiles may hold substantial promise for identifying mechanisms through which genetic and environmental factors jointly contribute to disease risk. Different cell types are likely to have different DNAm patterns. We investigate the DNAm differences between two types of biospecimens available in many genetic epidemiology studies. We compared DNAm patterns in two different DNA samples from each of 34 participants in the Genetic Epidemiology Network of Arteriopathy study (20 Caucasians and 14 African-Americans). One was extracted from peripheral blood cells (PBC) and the other from transformed B-lymphocytes (TBL). The genome-wide DNAm profiles were compared at over 27,000 genome-wide methylation sites. We found that 26 out of the 34 participants had correlation coefficients higher than 0.9 between methylation profiles of PBC and TBL. Although a high correlation was observed in the DNAm profile between PBC and TBL, we also observed variation across samples from different DNA resources and donors. Using principal component analysis of the DNAm profiles, the two sources of the DNA samples could be accurately predicted. We also identified 3,723 autosomal DNAm sites that had significantly different methylation statuses in PBC compared to TBL (Bonferroni corrected p value <0.05). Both PBC and TBL provide a rich resource for understanding the DNAm profiles in humans participating in epidemiologic studies. While the majority of DNAm findings in PBC and TBL may be consistent, caution must be used when interpreting results because of the possibility of cell type-specific methylation modification.
Aberrant DNA methylation (DNAm) is a feature of most types of cancers. Genome-wide DNAm profiling has been performed successfully on tumor tissue DNA samples. However, the invasive procedure limits the utility of tumor tissue for epidemiological studies. While recent data indicate that cell-free circulating DNAm (cfDNAm) profiles reflect DNAm status in corresponding tumor tissues, no studies have examined the association of cfDNAm with cancer or precursors on a genome-wide scale. The objective of this pilot study was to evaluate the putative significance of genome-wide cfDNAm profiles in esophageal adenocarcinoma (EA) and Barrett esophagus (BE, EA precursor). We performed genome-wide DNAm profiling in EA tissue DNA (n = 8) and matched serum DNA (n = 8), in serum DNA of BE (n = 10), and in healthy controls (n = 10) using the Infinium HumanMethylation27 BeadChip that covers 27,578 CpG loci in 14,495 genes. We found that cfDNAm profiles were highly correlated to DNAm profiles in matched tumor tissue DNA (r = 0.92) in patients with EA. We selected the most differentially methylated loci to perform hierarchical clustering analysis. We found that 911 loci can discriminate perfectly between EA and control samples, 554 loci can separate EA from BE samples, and 46 loci can distinguish BE from control samples. These results suggest that genome-wide cfDNAm profiles are highly consistent with DNAm profiles detected in corresponding tumor tissues. Differential cfDNAm profiling may be a useful approach for the noninvasive screening of EA and EA premalignant lesions.
While genome-wide association studies are ongoing to identify sequence variation influencing susceptibility to major depressive disorder (MDD), epigenetic marks, such as DNA methylation, which can be influenced by environment, might also play a role. Here we present the first genome-wide DNA methylation (DNAm) scan in MDD. We compared 39 postmortem frontal cortex MDD samples to 26 controls. DNA was hybridized to our Comprehensive High-throughput Arrays for Relative Methylation (CHARM) platform, covering 3.5 million CpGs. CHARM identified 224 candidate regions with DNAm differences >10%. These regions are highly enriched for neuronal growth and development genes. Ten of 17 regions for which validation was attempted showed true DNAm differences; the greatest were in PRIMA1, with 12–15% increased DNAm in MDD (p = 0.0002–0.0003), and a concomitant decrease in gene expression. These results must be considered pilot data, however, as we could only test replication in a small number of additional brain samples (n = 16), which showed no significant difference in PRIMA1. Because PRIMA1 anchors acetylcholinesterase in neuronal membranes, decreased expression could result in decreased enzyme function and increased cholinergic transmission, consistent with a role in MDD. We observed decreased immunoreactivity for acetylcholinesterase in MDD brain with increased PRIMA1 DNAm, non-significant at p = 0.08.
While we cannot draw firm conclusions about PRIMA1 DNAm in MDD, the involvement of neuronal development genes across the set showing differential methylation suggests a role for epigenetics in the illness. Further studies using limbic system brain regions might shed additional light on this role.
Recently, it has been proposed that epigenetic variation may contribute to the risk of complex genetic diseases like cancer. We aimed to demonstrate that epigenetic changes in normal cells, collected years in advance of the first signs of morphological transformation, can predict the risk of such transformation.
We analyzed DNA methylation (DNAm) profiles of over 27,000 CpGs in cytologically normal cells of the uterine cervix from 152 women in a prospective nested case-control study. We used statistics based on differential variability to identify CpGs associated with the risk of transformation and a novel statistical algorithm called EVORA (Epigenetic Variable Outliers for Risk prediction Analysis) to make predictions.
We observed many CpGs that were differentially variable between women who developed a non-invasive cervical neoplasia within 3 years of sample collection and those that remained disease-free. These CpGs exhibited heterogeneous outlier methylation profiles and overlapped strongly with CpGs undergoing age-associated DNA methylation changes in normal tissue. Using EVORA, we demonstrate that the risk of cervical neoplasia can be predicted in blind test sets (AUC = 0.66 (0.58 to 0.75)), and that assessment of DNAm variability allows more reliable identification of risk-associated CpGs than statistics based on differences in mean methylation levels. In independent data, EVORA showed high sensitivity and specificity to detect pre-invasive neoplasia and cervical cancer (AUC = 0.93 (0.86 to 1) and AUC = 1, respectively).
We demonstrate that the risk of neoplastic transformation can be predicted from DNA methylation profiles in the morphologically normal cell of origin of an epithelial cancer. Having profiled only 0.1% of CpGs in the human genome, studies of wider coverage are likely to yield improved predictive and diagnostic models with the accuracy needed for clinical application.
The ARTISTIC trial is registered with the International Standard Randomised Controlled Trial Number ISRCTN25417821.
Comprehensive high-throughput arrays for relative methylation (CHARM) was recently developed as an experimental platform and analytic approach to assess DNA methylation (DNAm) at a genome-wide level. Its initial implementation was for human and mouse. We adapted it for rat and sought to examine DNAm differences across tissues and brain regions in this model organism. We extracted DNA from liver, spleen and three brain regions: cortex, hippocampus and hypothalamus from adult Sprague Dawley rats. DNA was digested with McrBC, and the resulting methyl-depleted fraction was hybridized to the rat CHARM array along with a mock-treated fraction. Differentially methylated regions (DMRs) between tissue types were detected using normalized methylation log-ratios. In validating 24 of the most significant DMRs by bisulfite pyrosequencing, we detected large mean differences in DNAm, ranging from 33–59%, among the most significant DMRs in the across-tissue comparisons. The comparable figures for the hippocampus vs. hypothalamus DMRs were 14–40%, for the cortex vs. hippocampus DMRs, 12–29%, and for the cortex vs. hypothalamus DMRs, 5–35%, with a correlation of r2 = 0.92 between the methylation differences in 24 DMRs predicted by CHARM and those validated by bisulfite pyrosequencing. Our adaptation of the CHARM array for the rat genome yielded highly robust results that demonstrate the value of this method in detecting substantial DNAm differences between tissues and across different brain regions. This platform should prove valuable in future studies aimed at examining DNAm differences in particular brain regions of rats exposed to environmental stimuli with potential epigenetic consequences.
epigenetics; DNA methylation; methylation array; genome-wide; rat; brain
Despite the success of genome-wide association studies (GWAS) in identifying loci associated with common diseases, a significant proportion of the causality remains unexplained. Recent advances in genomic technologies have placed us in a position to initiate large-scale studies of human disease-associated epigenetic variation, specifically variation in DNA methylation (DNAm). Such Epigenome-Wide Association Studies (EWAS) present novel opportunities but also create new challenges that are not encountered in GWAS. We discuss EWAS study design, cohort and sample selections, statistical significance and power, confounding factors, and follow-up studies. We also discuss how integration of EWAS with GWAS can help to dissect complex GWAS haplotypes for functional analysis.
Epigenomics; Disease Genetics; DNA Methylation; Epigenetics; Quantitative Trait
Alterations in DNA methylation (DNAm) in cancer have been known for 25 years, including hypomethylation of oncogenes and hypermethylation of tumor suppressor genes1. However, most studies of cancer methylation have assumed that functionally important DNAm will occur in promoters, and that most DNAm changes in cancer occur in CpG islands2,3. Here we show that most methylation alterations in colon cancer occur not in promoters, and also not in CpG islands but in sequences up to 2 kb distant which we term “CpG island shores.” CpG island shore methylation was strongly related to gene expression, and it was highly conserved in mouse, discriminating tissue types regardless of species of origin. There was a surprising overlap (45-65%) of the location of colon cancer-related methylation changes with those that distinguished normal tissues, with hypermethylation enriched closer to the associated CpG islands, and hypomethylation enriched further from the associated CpG island and resembling non-colon normal tissues. Thus, methylation changes in cancer are at sites that vary normally in tissue differentiation, and they are consistent with the epigenetic progenitor model of cancer4, that epigenetic alterations affecting tissue-specific differentiation are the predominant mechanism by which epigenetic changes cause cancer.
NK cells are a major component of the antitumor immune response and are involved in
controlling tumor progression and metastases in animal models. Here, we show that
dysfunction of these cells accompanies human breast tumor progression. We
characterized human peripheral blood NK (p-NK) cells and malignant mammary
tumor-infiltrating NK (Ti-NK) cells from patients with noninvasive and invasive
breast cancers. NK cells isolated from the peripheral blood of healthy donors and
normal breast tissue were used as controls. With disease progression, we found that
expression of activating NK cell receptors (such as NKp30, NKG2D, DNAM-1, and CD16)
decreased while expression of inhibitory receptors (such as NKG2A) increased and that
this correlated with decreased NK cell function, most notably cytotoxicity.
Importantly, Ti-NK cells had more pronounced impairment of their cytotoxic potential
than p-NK cells. We also identified several stroma-derived factors, including
TGF-β1, involved in tumor-induced reduction of normal NK cell function.
Our data therefore show that breast tumor progression involves NK cell dysfunction
and that breast tumors model their environment to evade NK cell antitumor immunity.
This highlights the importance of developing future therapies able to restore NK cell
cytotoxicity to limit/prevent tumor escape from antitumor immunity.
Epigenetic alterations in tissues targeted for cancer play a causal role in carcinogenesis. Changes in DNA methylation in nontarget tissues, specifically peripheral blood, can also affect risk of malignant disease. We sought to identify specific profiles of DNA methylation in peripheral blood that are associated with bladder cancer risk and therefore serve as an epigenetic marker of disease susceptibility.
We performed genome-wide DNA methylation profiling on participants involved in a population-based incident case-control study of bladder cancer.
In a training set of 112 cases and 118 controls, we identified a panel of 9 CpG loci whose profile of DNA methylation was significantly associated with bladder cancer in a masked, independent testing series of 111 cases and 119 controls (P < .0001). Membership in three of the most methylated classes was associated with a 5.2-fold increased risk of bladder cancer (95% CI, 2.8 to 9.7), and a model that included the methylation classification, participant age, sex, smoking status, and family history of bladder cancer was a significant predictor of bladder cancer (area under the curve, 0.76; 95% CI, 0.70 to 0.82). CpG loci associated with bladder cancer and aging had neighboring sequences enriched for transcription-factor binding sites related to immune modulation and forkhead family members.
These results indicate that profiles of epigenetic states in blood are associated with risk of bladder cancer and signal the potential utility of epigenetic profiles in peripheral blood as novel markers of susceptibility to this and other malignancies.
Epithelial ovarian cancer is one of the leading causes of gynaecological cancer morbidity and mortality in women. Early stage ovarian cancer is usually asymptomatic, therefore, is often first diagnosed when it is widely disseminated. Currently available diagnostics lack the requisite sensitivity and specificity to be implemented as community-based screening tests. The identification of additional biomarkers may improve the diagnostic efficiency of multivariate index assays. The aims of this study were to characterise and compare the ovarian tissue immunohistochemical localisation and plasma concentrations of three putative ovarian cancer biomarkers: human cationic antimicrobial protein-18 (hCAP-18); lactoferrin; and CD163 in normal healthy women and women with ovarian cancer.
In this case–control cohort study, ovarian tissue and blood samples were obtained from 164 women (73 controls, including 28 women with benign pelvic masses; 91 cancer, including 21 women with borderline tumours). Localisation of each antigen within the ovary was assessed by immunohistochemistry and serum concentrations determined by ELISA assays.
Immunoreactive (ir) hCAP-18 and lactoferrin were identified in epithelial cells, while CD163 was predominately localised in stromal cells. Tissue ir CD163 increased significantly (P<0.05) with disease grade. Median plasma concentrations of soluble (s)CD163 were significantly greater in the cases (3220 ng/ml) than in controls (2488 ng/ml) (P< 0.01). Median plasma concentrations of hCAP-18 and lactoferrin were not significantly different between cases and controls. The classification efficiency of each biomarker (as determined by the area under the receiver operator characteristic curve; AUC) was: 0.67± 0.04; 0.62 ± 0.08 and 0.51 ± 0.07 for sCD163, hCAP-18 and lactoferrin, respectively. When the 3 biomarkers were modelled using stochastic gradient boosted logistic regression, the AUC increased to 0.95 ± 0.03.
The data obtained in this study establishes the localisation and concentrations of CD163, hCAP-18, and lactoferrin in ovarian tumours and peripheral blood. Individually, the 3 biomarkers display only modest diagnostic efficiency as assessed by AUC. When combined in a multivariate index assay, however, diagnostic efficiency increases significantly. As such, the utility of the biomarker panel, as an aid in the diagnosis of cancer in symptomatic women, is worthy of further investigation in a larger phase 2 biomarker trial.
Ovarian cancer; hCAP-18; Lactoferrin; CD163
Since the identification of ligands for human and mouse DNAM-1, emerging evidence has suggested that DNAM-1 plays an important role in the T cell– and natural killer (NK) cell–mediated recognition and lysis of tumor cells. However, it remains undetermined whether DNAM-1 is involved in tumor immune surveillance in vivo. We addressed this question by using DNAM-1–deficient mice. DNAM-1–deficient cytotoxic T lymphocyte (CTL) and NK cells showed significantly less cytotoxic activity against DNAM-1 ligand-expressing tumors in vitro than wild-type (WT) cells. The methylcholanthrene (MCA)-induced fibrosarcoma cell line Meth A expressed the DNAM-1 ligand CD155, and DNAM-1–deficient mice showed increased tumor development and mortality after transplantation of Meth A cells. Moreover, the DNAM-1–deficient mice developed significantly more DNAM-1 ligand-expressing fibrosarcoma and papilloma cells in response to the chemical carcinogens MCA and 7,12-dimethylbenz[a]anthracene (DMBA), respectively, than did WT mice. These results indicate that DNAM-1 plays an important role in immune surveillance of tumor development.
NK cells use a variety of receptors to detect abnormal cells, including tumors and their metastases. However, in the case of melanoma, it remains to be determined what specific molecular interactions are involved and whether NK cells control metastatic progression and/or the route of dissemination. Here we show that human melanoma cell lines derived from LN metastases express ligands for natural cytotoxicity receptors (NCRs) and DNAX accessory molecule-1 (DNAM-1), two emerging NK cell receptors key for cancer cell recognition, but not NK group 2 member D (NKG2D). Compared with cell lines derived from metastases taken from other anatomical sites, LN metastases were more susceptible to NK cell lysis and preferentially targeted by adoptively transferred NK cells in a xenogeneic model of cell therapy. In mice, DNAM-1 and NCR ligands were also found on spontaneous melanomas and melanoma cell lines. Interference with DNAM-1 and NCRs by antibody blockade or genetic disruption reduced killing of melanoma cells. Taken together, these results show that DNAM-1 and NCRs are critical for NK cell–mediated innate immunity to melanoma cells and provide a background to design NK cell–based immunotherapeutic strategies against melanoma and possibly other tumors.
Natural killer (NK) cells contribute to the defense against infected and transformed cells through the engagement of multiple germline-encoded activation receptors. Stimulation of the Fc receptor CD16 alone is sufficient for NK cell activation, whereas other receptors, such as 2B4 (CD244) and DNAM-1 (CD226), act synergistically. After receptor engagement, protein kinases play a major role in signaling networks controlling NK cell effector functions. However, it has not been characterized systematically which of all kinases encoded by the human genome (kinome) are involved in NK cell activation.
A kinase-selective phosphoproteome approach enabled the determination of 188 kinases expressed in human NK cells. Crosslinking of CD16 as well as 2B4 and DNAM-1 revealed a total of 313 distinct kinase phosphorylation sites on 109 different kinases. Phosphorylation sites on 21 kinases were similarly regulated after engagement of either CD16 or co-engagement of 2B4 and DNAM-1. Among those, increased phosphorylation of FYN, KCC2G (CAMK2), FES, and AAK1, as well as the reduced phosphorylation of MARK2, were reproducibly observed both after engagement of CD16 and co-engagement of 2B4 and DNAM-1. Notably, only one phosphorylation on PAK4 was differentally regulated.
The present study has identified a significant portion of the NK cell kinome and defined novel phosphorylation sites in primary lymphocytes. Regulated phosphorylations observed in the early phase of NK cell activation imply these kinases are involved in NK cell signaling. Taken together, this study suggests a largely shared signaling pathway downstream of distinct activation receptors and constitutes a valuable resource for further elucidating the regulation of NK cell effector responses.
The majority of congenital heart defects (CHDs) are thought to result from the interaction between multiple genetic, epigenetic, environmental, and lifestyle factors. Epigenetic mechanisms are attractive targets in the study of complex diseases because they may be altered by environmental factors and dietary interventions. We conducted a population based, case-control study of genome-wide maternal DNA methylation to determine if alterations in gene-specific methylation were associated with CHDs. Using the Illumina Infinium Human Methylation27 BeadChip, we assessed maternal gene-specific methylation in over 27,000 CpG sites from DNA isolated from peripheral blood lymphocytes. Our study sample included 180 mothers with non-syndromic CHD-affected pregnancies (cases) and 187 mothers with unaffected pregnancies (controls). Using a multi-factorial statistical model, we observed differential methylation between cases and controls at multiple CpG sites, although no CpG site reached the most stringent level of genome-wide statistical significance. The majority of differentially methylated CpG sites were hypermethylated in cases and located within CpG islands. Gene Set Enrichment Analysis (GSEA) revealed that the genes of interest were enriched in multiple biological processes involved in fetal development. Associations with canonical pathways previously shown to be involved in fetal organogenesis were also observed. We present preliminary evidence that alterations in maternal DNA methylation may be associated with CHDs. Our results suggest that further studies involving maternal epigenetic patterns and CHDs are warranted. Multiple candidate processes and pathways for future study have been identified.
Epithelial ovarian cancer is a significant cause of mortality both in the United States and worldwide, due largely to the high proportion of cases that present at a late stage, when survival is extremely poor. Early detection of epithelial ovarian cancer, and of the serous subtype in particular, is a promising strategy for saving lives. The low prevalence of ovarian cancer makes the development of an adequately sensitive and specific test based on blood markers very challenging. We evaluated the performance of a set of candidate blood markers and combinations of these markers in detecting serous ovarian cancer.
Methods and Findings
We selected 14 candidate blood markers of serous ovarian cancer for which assays were available to measure their levels in serum or plasma, based on our analysis of global gene expression data and on literature searches. We evaluated the performance of these candidate markers individually and in combination by measuring them in overlapping sets of serum (or plasma) samples from women with clinically detectable ovarian cancer and women without ovarian cancer. Based on sensitivity at high specificity, we determined that 4 of the 14 candidate markers-MUC16, WFDC2, MSLN and MMP7-warrant further evaluation in precious serum specimens collected months to years prior to clinical diagnosis to assess their utility in early detection. We also reported differences in the performance of these candidate blood markers across histological types of epithelial ovarian cancer.
By systematically analyzing the performance of candidate blood markers of ovarian cancer in distinguishing women with clinically apparent ovarian cancer from women without ovarian cancer, we identified a set of serum markers with adequate performance to warrant testing for their ability to identify ovarian cancer months to years prior to clinical diagnosis. We argued for the importance of sensitivity at high specificity and of magnitude of difference in marker levels between cases and controls as performance metrics and demonstrated the importance of stratifying analyses by histological type of ovarian cancer. Also, we discussed the limitations of studies (like this one) that use samples obtained from symptomatic women to assess potential utility in detection of disease months to years prior to clinical detection.
The identification of sensitive biomarkers for the detection of ovarian cancer is of high clinical relevance for early detection and/or monitoring of disease recurrence. We developed a systematic multi-step biomarker discovery and verification strategy to identify candidate DNA methylation markers for the blood-based detection of ovarian cancer.
We used the Illumina Infinium platform to analyze the DNA methylation status of 27,578 CpG sites in 41 ovarian tumors. We employed a marker selection strategy that emphasized sensitivity by requiring consistency of methylation across tumors, while achieving specificity by excluding markers with methylation in control leukocyte or serum DNA. Our verification strategy involved testing the ability of identified markers to monitor disease burden in serially collected serum samples from ovarian cancer patients who had undergone surgical tumor resection compared to CA-125 levels.
We identified one marker, IFFO1 promoter methylation (IFFO1-M), that is frequently methylated in ovarian tumors and that is rarely detected in the blood of normal controls. When tested in 127 serially collected sera from ovarian cancer patients, IFFO1-M showed post-resection kinetics significantly correlated with serum CA-125 measurements in six out of 16 patients.
We implemented an effective marker screening and verification strategy, leading to the identification of IFFO1-M as a blood-based candidate marker for sensitive detection of ovarian cancer. Serum levels of IFFO1-M displayed post-resection kinetics consistent with a reflection of disease burden. We anticipate that IFFO1-M and other candidate markers emerging from this marker development pipeline may provide disease detection capabilities that complement existing biomarkers.
Human cytomegalovirus (HCMV) UL141 induces protection against natural killer cell-mediated cytolysis by downregulating cell surface expression of CD155 (nectin-like molecule 5; poliovirus receptor), a ligand for the activating receptor DNAM-1 (CD226). However, DNAM-1 is also recognized to bind a second ligand, CD112 (nectin-2). We now show that HCMV targets CD112 for proteasome-mediated degradation by 48 h post-infection, thus removing both activating ligands for DNAM-1 from the cell surface during productive infection. Significantly, cell surface expression of both CD112 and CD155 was restored when UL141 was deleted from the HCMV genome. While gpUL141 alone is sufficient to mediate retention of CD155 in the endoplasmic reticulum, UL141 requires assistance from additional HCMV-encoded functions to suppress expression of CD112.
Inflammatory processes may influence the risk of epithelial ovarian cancer, but available epidemiological evidence is limited and indirect. Circulating C-reactive protein (CRP), a sensitive marker of inflammation, may serve as a direct biological marker of an underlying association.
The association between ovarian cancer risk and pre-diagnostic circulating CRP was tested in a case–control study nested within three prospective cohorts from Sweden, USA, and Italy. The study included 237 cases and 427 individually matched controls. CRP was measured in stored blood samples by high-sensitivity immunoturbidimetric assay. Odds ratios (OR) and 95% confidence intervals (CI) were calculated by conditional logistic regression.
Overall, CRP was not related to risk of ovarian cancer. However, a marked increase in risk was observed for CRP concentrations > 10 mg/l: OR (95% CI) 4.4 (1.8–10.9), which remained significant after limiting analyses to cases diagnosed more than two or five years after blood donation (OR 3.0 (1.2–8.0) and 3.6 (1.0–13.2), respectively). Risk of mucinous tumors increased with high CRP, but the number of cases in this analysis was small.
Study results offer additional support to the concept that chronic inflammation plays a role in epithelial ovarian cancer.
C-reactive protein; Ovarian cancer; Inflammation; Prospective study
Head and neck cancer accounts for an estimated 47,560 new cases and 11,480 deaths annually in the United States, the majority of which are squamous cell carcinomas (HNSCC). The overall 5 year survival is approximately 60% and declines with increasing stage at diagnosis, indicating a need for non-invasive tests that facilitate the detection of early disease. DNA methylation is a stable epigenetic modification that is amenable to measurement and readily available in peripheral blood. We used a semi-supervised recursively partitioned mixture model (SS-RPMM) approach to identify novel blood DNA methylation markers of HNSCC using genome-wide methylation array data for peripheral blood samples from 92 HNSCC cases and 92 cancer-free control subjects. To assess the performance of the resultant markers, we constructed receiver operating characteristic (RJC) curves and calculated the corresponding area under the curve (AUC). Cases and controls were best differentiated by a methylation profile of six CpG loci (associated with FGD4, SERPINF1, WDR39, IL27, HYAL2 and PLEKHA6), with an AUC of 0.73 (95% CI: 0.62–0.82). After adjustment for subject age, gender, smoking, alcohol consumption and HPV16 serostatus, the AUC increased to 0.85 (95% CI: 0.76–0.92). We have identified a novel blood-based methylation profile that is indicative of HNSCC with a high degree of accuracy. This profile demonstrates the potential of DNA methylation measured in blood for development of non-invasive applications for detection of head and neck cancer.
semi-supervised RPMM; HNSCC; epigenetics; biomarkers; Infinium; methylation array
Because both ovarian and breast cancer are hormone-related and are known to have some predisposition genes in common, we evaluated 11 of the most significant hits (six with confirmed associations with breast cancer) from the breast cancer genome-wide association study for association with invasive ovarian cancer. Eleven SNPs were initially genotyped in 2927 invasive ovarian cancer cases and 4143 controls from six ovarian cancer case-control studies. Genotype frequencies in cases and controls were compared using a likelihood ratio test in a logistic regression model stratified by study. Initially, three SNPs (rs2107425 in MRPL23, rs7313833 in PTHLH, rs3803662 in TNRC9) were weakly associated with ovarian cancer risk and one SNP (rs4954956 in NXPH2) was associated with serous ovarian cancer in non-Hispanic white subjects (P-trend<0.1). These four SNPs were then genotyped in an additional 4060 cases and 6308 controls from eight independent studies. Only rs4954956 was significantly associated with ovarian cancer risk both in the replication study and in combined analyses. This association was stronger for the serous histological sub-type (per minor allele odds ratio (OR) 1.07 95%CI 1.01-1.13, P-trend=0.02 for all types of ovarian cancer and OR 1.14 95%CI 1.07-1.22, P-trend = 0.00017 for serous ovarian cancer). In conclusion, we found that rs4954956 was associated with increased ovarian cancer risk, particularly for serous ovarian cancer. However none of the six confirmed breast cancer susceptibility variants we tested were associated with ovarian cancer risk. Further work will be needed to identify the causal variant associated with rs4954956 or elucidate its function.
Because both ovarian and breast cancer are hormone-related and are known to have some predisposition genes in common, we evaluated 11 of the most significant hits (six with confirmed associations with breast cancer) from the breast cancer genome-wide association study for association with invasive ovarian cancer. Eleven SNPs were initially genotyped in 2927 invasive ovarian cancer cases and 4143 controls from six ovarian cancer case–control studies. Genotype frequencies in cases and controls were compared using a likelihood ratio test in a logistic regression model stratified by study. Initially, three SNPs (rs2107425 in MRPL23, rs7313833 in PTHLH, rs3803662 in TNRC9) were weakly associated with ovarian cancer risk and one SNP (rs4954956 in NXPH2) was associated with serous ovarian cancer in non-Hispanic white subjects (P-trend < 0.1). These four SNPs were then genotyped in an additional 4060 cases and 6308 controls from eight independent studies. Only rs4954956 was significantly associated with ovarian cancer risk both in the replication study and in combined analyses. This association was stronger for the serous histological subtype [per minor allele odds ratio (OR) 1.07 95% CI 1.01–1.13, P-trend = 0.02 for all types of ovarian cancer and OR 1.14 95% CI 1.07–1.22, P-trend = 0.00017 for serous ovarian cancer]. In conclusion, we found that rs4954956 was associated with increased ovarian cancer risk, particularly for serous ovarian cancer. However, none of the six confirmed breast cancer susceptibility variants we tested was associated with ovarian cancer risk. Further work will be needed to identify the causal variant associated with rs4954956 or elucidate its function.
Epigenetic gene silencing is one of the major causes of carcinogenesis. Its widespread occurrence in cancer genome could inactivate many cellular pathways including DNA repair, cell cycle control, apoptosis, cell adherence, and detoxification. The abnormal promoter methylation might be a potential molecular marker for cancer management.
For rapid identification of potential targets for aberrant methylation in gynecological cancers, methylation status of the CpG islands of 34 genes was determined using pooled DNA approach and methylation-specific PCR. Pooled DNA mixture from each cancer type (50 cervical cancers, 50 endometrial cancers and 50 ovarian cancers) was made to form three test samples. The corresponding normal DNA from the patients of each cancer type was also pooled to form the other three control samples. Methylated alleles detected in tumors, but not in normal controls, were indicative of aberrant methylation in tumors. Having identified potential markers, frequencies of methylation were further analyzed in individual samples. Markers identified are used to correlate with clinico-pathological data of tumors using χ2 or Fisher's exact test.
APC and p16 were hypermethylated across the three cancers. MINT31 and PTEN were hypermethylated in cervical and ovarian cancers. Specific methylation was found in cervical cancer (including CDH1, DAPK, MGMT and MINT2), endometrial cancer (CASP8, CDH13, hMLH1 and p73), and ovarian cancer (BRCA1, p14, p15, RIZ1 and TMS1). The frequencies of occurrence of hypermethylation in 4 candidate genes in individual samples of each cancer type (DAPK, MGMT, p16 and PTEN in 127 cervical cancers; APC, CDH13, hMLH1 and p16 in 60 endometrial cancers; and BRCA1, p14, p16 and PTEN in 49 ovarian cancers) were examined for further confirmation. Incidence varied among different genes and in different cancer types ranging from the lowest 8.2% (PTEN in ovarian cancer) to the highest 56.7% (DAPK in cervical cancer). Aberrant methylation for some genes (BRCA1, DAPK, hMLH1, MGMT, p14, p16, and PTEN) was also associated with clinico-pathological data.
Thus, differential methylation profiles occur in the three types of gynecologic cancer. Detection of methylation for critical loci is potentially useful as epigenetic markers in tumor classification. More studies using a much larger sample size are needed to define the potential role of DNA methylation as marker for cancer management.
Prior studies suggest that combining the Symptom Index (SI) with a serum HE4 test or a CA125 test may improve prediction of ovarian cancer. However, these three tests have not been evaluated in combination.
A prospective case-control study design including 74 women with ovarian cancer and 137 healthy women was used with logistic regression analysis to evaluate the independent contributions of HE4, CA125, and the SI to predict ovarian cancer status in a multivariate model. The diagnostic performance of various decision-rules for combinations of these tests was assessed to evaluate potential use in predicting ovarian cancer.
The SI, HE4, and CA125 all made significant independent contributions to ovarian cancer prediction. A decision-rule based on any one of the three tests being positive had a sensitivity of 95% with specificity of 80%. A rule based on any two of the three tests being positive had a sensitivity of 84% with a specificity of 98.5%. The SI alone had sensitivity of 64% with specificity of 88%. If the SI index is used to select women for CA125 and HE4 testing, specificity is 98.5% and sensitivity is 58% using the 2-of-3-positive decision rule.
A 2-of-3-positive decision rule yields acceptable specificity, and higher sensitivity when all 3 tests are performed than when the SI is used to select women for screening by CA125 and HE4. If positive predictive value is a high priority, testing by CA125 and HE4 prior to imaging may be warranted for women with ovarian cancer symptoms.
ovarian cancer; CA125; HE4; Symptom Index; sensitivity; specificity
Natural killer (NK) cells and CD8 T cells require adhesion molecules for migration, activation, expansion, differentiation, and effector functions. DNAX accessory molecule 1 (DNAM-1), an adhesion molecule belonging to the immunoglobulin superfamily, promotes many of these functions in vitro. However, because NK cells and CD8 T cells express multiple adhesion molecules, it is unclear whether DNAM-1 has a unique function or is effectively redundant in vivo. To address this question, we generated mice lacking DNAM-1 and evaluated DNAM-1–deficient CD8 T cell and NK cell function in vitro and in vivo. Our results demonstrate that CD8 T cells require DNAM-1 for co-stimulation when recognizing antigen presented by nonprofessional antigen-presenting cells; in contrast, DNAM-1 is dispensable when dendritic cells present the antigen. Similarly, NK cells require DNAM-1 for the elimination of tumor cells that are comparatively resistant to NK cell–mediated cytotoxicity caused by the paucity of other NK cell–activating ligands. We conclude that DNAM-1 serves to extend the range of target cells that can activate CD8 T cell and NK cells and, hence, may be essential for immunosurveillance against tumors and/or viruses that evade recognition by other activating or accessory molecules.
A panel of biomarkers may improve predictive performance over individual markers. Although many biomarker panels have been described for ovarian cancer, few studies used pre-diagnostic samples to assess the potential of the panels for early detection. We conducted a multi-site systematic evaluation of biomarker panels using pre-diagnostic serum samples from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) screening trial.
Using a nested case-control design, levels of 28 biomarkers were measured laboratory-blinded in 118 serum samples obtained before cancer diagnosis and 951 serum samples from matched controls. Five predictive models, each containing 6–8 biomarkers, were evaluated according to a pre-determined analysis plan. Three sequential analyses were conducted: blinded validation of previously established models (Step 1); simultaneous split-sample discovery and validation of models (Step 2); and exploratory discovery of new models (Step 3). Sensitivity, specificity, sensitivity at 98% specificity, and AUC were computed for the models and CA125 alone among 67 cases diagnosed within one year of blood draw and 476 matched controls. In Step 1, one model showed comparable performance to CA125, with sensitivity, specificity and AUC at 69.2%, 96.6% and 0.892, respectively. Remaining models had poorer performance than CA125 alone. In Step 2, we observed a similar pattern. In Step 3, a model derived from all 28 markers failed to show improvement over CA125.
Thus, biomarker panels discovered in diagnostic samples may not validate in pre-diagnostic samples; utilizing pre-diagnostic samples for discovery may be helpful in developing validated early detection panels.
Early Detection; Screening; Biomarkers; Validation; Study Design