Epigenetic biomarkers of T-cells in human glioma

Immune factors are thought to influence glioma risk and outcomes, but immune profiling studies to further our understanding of the immune response are limited by current immunodiagnostic methods. We developed a new assay to capture glioma immune biology based on quantitative methylation specific PCR (qMSP) of two T-cell genes (CD3Z: T-cells, and FOXP3: Tregs). Flow cytometry of T-cells correlated well with the CD3Z demethylation assay (r = 0.93; p < 2.2 × 10⁻¹⁶), demonstrating the validity of the assay. Furthermore, there was a high correlation between qMSP and immunohistochemistry (IHC) in quantifying tumor infiltrating T-cells (r = 0.85; p = 3.4 × 10⁻¹¹). Applying our qMSP methods to archival whole blood from 65 glioblastoma multiforme (GBM) cases and 94 non-diseased controls, GBM cases had highly statistically significantly lower T-cells (p = 1.7 × 10⁻⁹) as well as Tregs (p = 5.2 × 10⁻¹¹) and a modestly lower ratio of Tregs/T-cells (p = 0.024). Applying the methods to 120 excised glioma tumors, we observed that tumor infiltrating CD3+ T-cells were positively correlated with glioma tumor grade (p = 5.7 × 10⁻⁷), and that Tregs were enriched in tumors compared with peripheral blood indicating active chemoattraction of suppressive Tregs into the tumor compartment. Poorer patient survival was correlated with higher levels of tumor infiltrating T-cells (p = 0.01) and Tregs (p = 0.04). DNA methylation based immunodiagnostics represent a new generation of powerful laboratory tools offering many advantages over conventional methods that will facilitate large clinical epidemiologic studies and capitalize on stored archival blood and tissue banks.     

A 2015 survey of established or potential epigenetic biomarkers for the accurate detection of human cancers

Context The silencing or activation of cancer-associated genes by epigenetic mechanisms can ultimately lead to the clonal expansion of cancer cells. Objective The aim of this review is to summarize all relevant epigenetic biomarkers that have been proposed to date for the diagnosis of some prevalent human cancers. Methods A Medline search for the terms epigenetic biomarkers, human cancers, DNA methylation, histone modifications and microRNAs was performed. Results One hundred fifty-seven relevant publications were found and reviewed. Conclusion To date, a significant number of potential epigenetic cancer biomarkers of human cancer have been investigated, and some have advanced to clinical implementation.     

Epigenetic biomarkers in colorectal cancer: premises and prospects

Context: Colorectal cancer is one of the most common cancers worldwide. Epigenetic alterations play an important role in the pathogenesis of the colorectal cancer.

Objective: This review has focused on the most recent investigations, which has suggested potential epigenetic biomarkers in colorectal cancer.

Methods: Evidences were achieved by searching online medical databases including Google scholar, Pubmed, Scopus and Science Direct.

Results: Extensive studies have indicated that aberrant epigenetic modifications could serve as potential biomarkers for diagnosis, prognosis and prediction of colorectal cancer.

Conclusion: Advances in aberrant epigenetic modifications can open new avenues for exploration of reliable and robust biomarkers to improve the management of CRC patients.     

神经胶质瘤生物标志物研究进展

神经胶质瘤(glioma)是最常见的原发性脑肿瘤,占颅内肿瘤的81%。神经胶质瘤的诊断手段与预后评估主要以影像学为主,但因神经胶质瘤的浸润性生长特点,影像学不能完全作为诊断及预后评估依据。因此,发现和鉴定全新生物标志物对神经胶质瘤的诊断、治疗和预后评估显得尤为重要。最新研究结果表明,在神经胶质瘤患者组织和血液中,多种生物标志物可用于神经胶质瘤的辅助诊断和预后评估。其中,诊断标志物包括IDH1/2基因突变、BRAF基因突变与融合、p53基因突变、端粒酶活性增加、循环肿瘤细胞和非编码RNA等。预后标志物包括1p/19p共缺失、MGMT基因启动子甲基化及基质金属蛋白酶-28、胰岛素样生长因子结合蛋白-2和CD26的表达上调和Smad4的表达下调。本文重点介绍了上述神经胶质瘤生物标志物在诊断和预后评估方面的最新研究进展。     

Epigenetic regulation of extracellular-superoxide dismutase in human monocytes

Extracellular-superoxide dismutase (EC-SOD) is a major SOD isozyme mainly present in the vascular wall and plays an important role in normal redox homeostasis. We previously showed the significant reduction or induction of EC-SOD during human monocytic U937 or THP-1 cell differentiation induced by 12-O-tetradecanoylphorbol-13-acetate (TPA), respectively; however, its cell-specific expression and regulation have not been fully elucidated. It has been reported that epigenetic factors, such as DNA methylation and histone modification, are involved in several kinds of gene regulation. In this study, we investigated the involvement of epigenetic factors in EC-SOD expression and determined high levels of DNA methylation within promoter and coding regions of EC-SOD in THP-1 cells compared to those in U937 cells. Moreover, treatment with a DNA methyltransferase inhibitor, 5-azacytidine, significantly induced the expression of EC-SOD in THP-1 cells, indicating the importance of DNA methylation in the suppression of EC-SOD expression; however, the DNA methylation status did not change during THP-1 cell differentiation induced by TPA. On the other hand, we detected histone H3 and H4 acetylation during differentiation. Further, pretreatment with histone acetyltransferase inhibitors, CPTH2 or garcinol, significantly suppressed the TPA-inducible EC-SOD expression. We also determined the epigenetic suppression of EC-SOD in peripheral blood mononuclear cells. Treatment with granulocyte macrophage colony-stimulating factor (GM-CSF)/granulocyte-CSF induced that expression. Overall, these findings provide novel evidence that cell-specific and TPA-inducible EC-SOD expression are regulated by DNA methylation and histone H3 and H4 acetylation in human monocytic cells.     

Epigenetic profiling and mRNA expression reveal candidate genes as biomarkers for colorectal cancer

Colorectal cancer (CRC) is characterized by DNA methylation, which is associated with genomic instability and tumor initiation. As an important epigenetic regulation, DNA methylation can be used as a potential therapeutic target for CRC. In our study, we downloaded DNA methylation profiles (GSE17648 and GSE29490) and RNA sequencing microarray data (GSE25070 and GSE32323) from the Gene Expression Omnibus (GEO) database. As a result, 14 aberrantly methylated differentially expressed genes (DEGs) were screened according to the different criteria. We further validated these DEGs in The Cancer Genome Atlas (TCGA) database and obtained Pearson's correlation coefficient (COR) for the relationship between gene expression and DNA methylation. Three candidate genes (SOX9, TCN1, and TGFBI) with COR greater than 0.3 were screened out as Hub genes. The receiver operating characteristic result indicated that SOX9 and TGFBI effectively serve as biomarkers for the early diagnosis of CRC. Furthermore, the potential prognosis of the Hub genes for CRC patients was evaluated. Only TGFBI, which is regulated by methylation, can predict patient disease-free survival. Additionally, we examined the methylation level of the Hub genes in CRC cells in the Cancer Cell Line Encyclopedia database. Considering that methylation status tends to be highly modified on CpG islands in tumorigenesis, we screened the CpG island methylation of TGFBI based on the TCGA database and verified its diagnostic value in the GEO database. Our result revealed two Hub genes (TCN1 and TGFBI) whose aberrant expressions were regulated by DNA methylation. Additionally, we uncovered the hypermethylation of TGFBI on CpG islands and its clinical value in the diagnosis of CRC.     

Epigenetic changes in virus-associated human cancers

Epigenetics of human cancer becomes an area of emerging research direction due to a growing understanding of specific epigenetic pathways and rapid development of detection technologies. Aberrant promoter hypermethylation is a prevalent phenonmena in human cancers. Tumor suppressor genes are often hypermethylated due to the increased activity or deregulation of DNMTs. Increasing evidence also reveals that viral genes are one of the key players in regulating DNA methylation. In this review, we will focus on hypermethylation and tumor suppressor gene silencing and the signal pathways that are involved, particularly in cancers closely associated with the hepatitis B virus, simian virus 40 (SV40), and Epstein-Barr virus. In addition, we will discuss current technologies for genome-wide detection of epigenetically regulated targets, which allow for systematic DNA hypermethylation analysis. The study of epigenetic changes should provide a global view of gene profile in cancer, and epigenetic markers could be used for early detection, prognosis, and therapy of cancer.     

植物DNA甲基化及其表观遗传作用

表观遗传学(epigenetics)是研究没有DNA序列变化的、可遗传的基因表达的改变。目前研究表明,表观遗传学在植物生长发育过程中起着极其重要的作用,主要通过包括DNA甲基化、RNA干涉、基因组印记、转基因沉默等多个方面来调控植物的生长发育。其中,DNA甲基化是表观遗传学的最重要研究内容之一,是调节基因组功能的重要手段。现对植物DNA甲基化的特征、维持机制、调控机制、表观遗传作用及其研究方法进行简要论述。     

Epigenetic marks in melanoma

Melanoma is a highly heterogeneous cancer that comes in different flavors (lentigo maligna melanoma, superficial spreading melanoma, nodular melanoma, acral lentiginous/mucosal melanoma and other less common subtypes including malignant cellular blue nevus, desmoplastic melanoma, nevoid melanoma, and animal‐type melanoma) and colors (black/bluish or unpigmented). Pathologists have known for many years that melanoma displays notable changes in the nuclear architecture including thick chromatic rims, presence of mitosis, nuclear grooves, and more. It is now evident from other cancers that such changes reflect not only genomic alterations but also non‐genomic changes in both the structure of DNA and the structure of chromatin to which the DNA is bound (nucleosomes). Although aberrant gene expression resulting from DNA methylation has been known for many years, genome alterations resulting from histone modifications became evident in the current decade. In prostate and other cancers, some histone marks have clinical diagnostic and/or prognostic value. Here, we review the current data on epigenetic research in melanoma skin cancers, discuss ways to modify the epigenetic landscape of melanoma for inhibiting its growth, and propose strategies for identifying novel melanoma markers.     

The promising novel biomarkers and candidate small molecule drugs in lower-grade glioma: Evidence from bioinformatics analysis of high-throughput data

Overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past 30 years, with survival averaging approximately 7 years. This study aimed to identify novel promising biomarkers of LGG and reveal its potential molecular mechanisms by integrated bioinformatics analysis. The microarray datasets of GSE68848 and GSE4290 were selected from GEO database for integrated analysis. In total, 293 overlapping differentially expressed genes (DEGs) were detected using the limma package. One hundred and eighty-eight nodes with 603 interactions were obtained from the establishment of protein-protein interaction (PPI) network. Functional and signaling pathway enriched were significantly correlated with the synapse and calcium signaling pathway, respectively. Module analysis revealed eight hub genes with high connectivity, which included CHRM1, DLG2, GABRD, GRIN1, HTR2A, KCNJ3, KCNJ9, and NUSAP1, and they were markedly correlated with patients’ prognosis. The mining of the Gene Expression Profiling Interactive Analysis database and qPCR further confirmed the abnormal expression of these key genes with their prognostic value in LGG. We eventually predicted the 20 most vital small molecule drugs, which potentially reverse the carcinogenic state of LGG, as per the CMap (connectivity map) database and these DEGs, and MS-275 (enrichment score = −0.939) was considered as the most promising small molecule to treat LGG. In conclusion, our study provided eight reliable novel molecular biomarkers for diagnosis, prognosis prediction, and treatment targets for LGG. These conclusions will contribute to a better comprehension of molecular mechanisms fundamental to LGG occurrence and progression, and providing new insights for future development of genomic individualized treatment in LGG.     

A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression

Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.     

A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression

Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.     

Potential epigenetic biomarkers of obesity-related insulin resistance in human whole-blood

Obesity can increase the risk of complex metabolic diseases, including insulin resistance. Moreover, obesity can be caused by environmental and genetic factors. However, the epigenetic mechanisms of obesity are not well defined. Therefore, the identification of novel epigenetic biomarkers of obesity allows for a more complete understanding of the disease and its underlying insulin resistance. The aim of our study was to identify DNA methylation changes in whole-blood that were strongly associated with obesity and insulin resistance. Whole-blood was obtained from lean (n = 10; BMI = 23.6 ± 0.7 kg/m²) and obese (n = 10; BMI = 34.4 ± 1.3 kg/m²) participants in combination with euglycemic hyperinsulinemic clamps to assess insulin sensitivity. We performed reduced representation bisulfite sequencing on genomic DNA isolated from the blood. We identified 49 differentially methylated cytosines (DMCs; q < 0.05) that were altered in obese compared with lean participants. We identified 2 sites (Chr.21:46,957,981 and Chr.21:46,957,915) in the 5’ untranslated region of solute carrier family 19 member 1 (SLC19A1) with decreased methylation in obese participants (lean 0.73 ± 0.11 vs. obese 0.09 ± 0.05; lean 0.68 ± 0.10 vs. obese 0.09 ± 0.05, respectively). These 2 DMCs identified by obesity were also significantly predicted by insulin sensitivity (r = 0.68, P = 0.003; r = 0.66; P = 0.004). In addition, we performed a differentially methylated region (DMR) analysis and demonstrated a decrease in methylation of Chr.21:46,957,915–46,958,001 in SLC19A1 of ?34.9% (70.4% lean vs. 35.5% obese). The decrease in whole-blood SLC19A1 methylation in our obese participants was similar to the change observed in skeletal muscle (Chr.21:46,957,981, lean 0.70 ± 0.09 vs. obese 0.31 ± 0.11 and Chr.21:46,957,915, lean 0.72 ± 0.11 vs. obese 0.31 ± 0.13). Pyrosequencing analysis further demonstrated a decrease in methylation at Chr.21:46,957,915 in both whole-blood (lean 0.71 ± 0.10 vs. obese 0.18 ± 0.06) and skeletal muscle (lean 0.71 ± 0.10 vs. obese 0.30 ± 0.11). Our findings demonstrate a new potential epigenetic biomarker, SLC19A1, for obesity and its underlying insulin resistance.     

Integrative analysis of DNA methylation and gene expression through machine learning identifies stomach cancer diagnostic and prognostic biomarkers

DNA methylation is an early event in tumorigenesis. Here, by integrative analysis of DNA methylation and gene expression and utilizing machine learning approaches, we introduced potential diagnostic and prognostic methylation signatures for stomach cancer. Differentially-methylated positions (DMPs) and differentially-expressed genes (DEGs) were identified using The Cancer Genome Atlas (TCGA) stomach adenocarcinoma (STAD) data. A total of 256 DMPs consisting of 140 and 116 hyper- and hypomethylated positions were identified between 443 tumour and 27 nontumour STAD samples. Gene expression analysis revealed a total of 2821 DEGs with 1247 upregulated and 1574 downregulated genes. By analysing the impact of cis and trans regulation of methylation on gene expression, a dominant negative correlation between methylation and expression was observed, while for trans regulation, in hypermethylated and hypomethylated genes, there was mainly a negative and positive correlation with gene expression, respectively. To find diagnostic biomarkers, we used 28 hypermethylated probes locating in the promoter of 27 downregulated genes. By implementing a feature selection approach, eight probes were selected and then used to build a support vector machine diagnostic model, which had an area under the curve of 0.99 and 0.97 in the training and validation (GSE30601 with 203 tumour and 94 nontumour samples) cohorts, respectively. Using 412 TCGA-STAD samples with both methylation and clinical data, we also identified four prognostic probes by implementing univariate and multivariate Cox regression analysis. In summary, our study introduced potential diagnostic and prognostic biomarkers for STAD, which demands further validation.     

Epigenetic suppression of the anti-aging gene KLOTHO in human prostate cancer cell lines

KLOTHO was originally identified as an aging-suppressor gene that causes a human aging-like phenotype when tested in KLOTHO-deficient-mice. Recent evidence suggests that KLOTHO functions as a tumor suppressor by inhibiting Wnt signaling. KLOTHO gene silencing, including DNA methylation, has been observed in some human cancers. Aberrant activation of Wnt signaling plays a significant role in aging, and its silencing may be related to prostate cancer and other types of cancers. Thus, we investigated whether the expression of the anti-aging gene KLOTHO was associated with epigenetic changes in prostate cancer cell lines. KLOTHO mRNA was detected in the 22Rv1 cell line while it was not detected in DU145 and PC-3 cell lines. The restoration of KLOTHO mRNA in the DU145 and PC-3 cell lines was induced with a DNA methyltransferase inhibitor. Methylation-specific PCR was performed to determine the specific CpG sites in the KLOTHO promoter responsible for expression. In addition, the level of methylation was assessed in each CpG by performing bisulfite sequencing and quantitative pyrosequencing analysis. The results suggested a remarkable inverse relationship between KLOTHO expression and promoter methylation in prostate cancer cell lines.     

CD19 target-engineered T-cells accumulate at tumor lesions in human B-cell lymphoma xenograft mouse models

Adoptive T-cell therapy with CD19-specific chimeric antigen receptors (CARs) is promising for treatment of advanced B-cell malignancies. Tumor targeting of CAR-modified T-cells is likely to contribute therapeutic potency; therefore we examined the relationship between the ability of CD19-specific CAR (CD19-CAR)-transduced T-cells to accumulate at CD19⁺ tumor lesions, and their ability to provide anti-tumor effects in xenograft mouse models. Normal human peripheral blood lymphocytes, activated with immobilized RetroNectin and anti-CD3 antibodies, were transduced with retroviral vectors that encode CD19-CAR. Expanded CD19-CAR T-cells with a high transgene expression level of about 75% produced IL-2 and IFN-γ in response to CD19, and lysed both Raji and Daudi CD19⁺ human B-cell lymphoma cell lines. Furthermore, these cells efficiently accumulated at Raji tumor lesions where they suppressed tumor progression and prolonged survival in tumor-bearing Rag2^−/−γc^−/− immunodeficient mice compared to control cohorts. These results show that the ability of CD19-CAR T-cells to home in on tumor lesions is pivotal for their anti-tumor effects in our xenograft models, and therefore may enhance the efficacy of adoptive T-cell therapy for refractory B-cell lymphoma.