DNA methylation patterns in luminal breast cancers differ from non-luminal subtypes and can identify relapse risk independent of other clinical variables

Evaluation of agreement between common clustering strategies for DNA methylation-based subtyping of breast tumours

AIMS

Clustering algorithms have been widely applied to tumor DNA methylation datasets to define methylation-based cancer subtypes. This study aimed to evaluate the agreement between subtypes obtained from common clustering strategies.

MATERIALS & METHODS

We used tumor DNA methylation data from 409 women with breast cancer from the Melbourne Collaborative Cohort Study (MCCS) and 781 breast tumors from The Cancer Genome Atlas (TCGA). Agreement was assessed using the adjusted Rand index for various combinations of number of CpGs, number of clusters and clustering algorithms (hierarchical, K-means, partitioning around medoids, and recursively partitioned mixture models).

RESULTS

Inconsistent agreement patterns were observed for between-algorithm and within-algorithm comparisons, with generally poor to moderate agreement (ARI <0.7). Results were qualitatively similar in the MCCS and TCGA, showing better agreement for moderate number of CpGs and fewer clusters (K = 2). Restricting the analysis to CpGs that were differentially-methylated between tumor and normal tissue did not result in higher agreement.

CONCLUSION

Our study highlights that common clustering strategies involving an arbitrary choice of algorithm, number of clusters and number of methylation sites are likely to identify different DNA methylation-based breast tumor subtypes.

KIF2C/MCAK a prognostic biomarker and its oncogenic potential in malignant progression, and prognosis of cancer patients: a systematic review and meta-analysis as biomarker

KIF2C/MCAK (KIF2C) is the most well-characterized member of the kinesin-13 family, which is critical in the regulation of microtubule (MT) dynamics during mitosis, as well as interphase. This systematic review briefly describes the important structural elements of KIF2C, its regulation by multiple molecular mechanisms, and its broad cellular functions. Furthermore, it systematically summarizes its oncogenic potential in malignant progression and performs a meta-analysis of its prognostic value in cancer patients. KIF2C was shown to be involved in multiple crucial cellular processes including cell migration and invasion, DNA repair, senescence induction and immune modulation, which are all known to be critical during the development of malignant tumors. Indeed, an increasing number of publications indicate that KIF2C is aberrantly expressed in multiple cancer entities. Consequently, we have highlighted its involvement in at least five hallmarks of cancer, namely: genome instability, resisting cell death, activating invasion and metastasis, avoiding immune destruction and cellular senescence. This was followed by a systematic search of KIF2C/MCAK's expression in various malignant tumor entities and its correlation with clinicopathologic features. Available data were pooled into multiple weighted meta-analyses for the correlation between KIF2Chigh protein or gene expression and the overall survival in breast cancer, non-small cell lung cancer and hepatocellular carcinoma patients. Furthermore, high expression of KIF2C was correlated to disease-free survival of hepatocellular carcinoma. All meta-analyses showed poor prognosis for cancer patients with KIF2Chigh expression, associated with a decreased overall survival and reduced disease-free survival, indicating KIF2C's oncogenic potential in malignant progression and as a prognostic marker. This work delineated the promising research perspective of KIF2C with modern in vivo and in vitro technologies to further decipher the function of KIF2C in malignant tumor development and progression. This might help to establish KIF2C as a biomarker for the diagnosis or evaluation of at least three cancer entities.

CCDC12 gene methylation in peripheral blood as a potential biomarker for breast cancer detection

BACKGROUND

Aberrant DNA methylation has been identified as biomarkers for breast cancer detection. Coiled-coil domain containing 12 gene (CCDC12) implicated in tumorigenesis. This study aims to investigate the potential of blood-based CCDC12 methylation for breast cancer detection.

METHODS

DNA methylation level of CpG sites (Cytosine-phosphate Guanine dinucleotides) in CCDC12 gene was measured by mass spectrometry in 255 breast cancer patients, 155 patients with benign breast nodules and 302 healthy controls. The association between CCDC12 methylation and breast cancer risk was evaluated by logistic regression and receiver operating characteristic curve analysis.

RESULTS

A total of eleven CpG sites were analyzed. The CCDC12 methylation levels were higher in breast cancer patients. Compared to the lowest tertile of methylation level in CpG_6,7, CpG_10 and CpG_11, the highest quartile was associated with 82, 91 and 95% increased breast cancer risk, respectively. The CCDC12 methylation levels were associated with estrogen receptor (ER) and human epidermal growth factor 2 (HER2) status. In ER-negative and HER2-positive (ER-/HER2+) breast cancer subtype, the combination of four sites CpG_2, CpG_5, CpG_6,7 and CpG_11 methylation levels could distinguish ER-/HER2+ breast cancer from the controls (AUC = 0.727).

CONCLUSION

The hypermethylation levels of CCDC12 in peripheral blood could be used for breast cancer detection.

Computational deconvolution of DNA methylation data from mixed DNA samples

In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach. Moreover, in this study, we describe the impact of the platform used for the generation of methylation data (including microarrays and sequencing), the applied data pre-processing steps and the used reference dataset on the deconvolution performance. Next to reference-based methods, we also examine methods that require only partial reference datasets or require no reference set at all. In this review, we provide guidelines for the use of specific methods dependent on the DNA methylation data type and data availability.

Molecular Characterization and Subtyping of Breast Cancer Cell Lines Provide Novel Insights into Cancer Relevant Genes

Continuous cell lines are important and commonly used in vitro models in breast cancer (BC) research. Selection of the appropriate model cell line is crucial and requires consideration of their molecular characteristics. To characterize BC cell line models in depth, we profiled a panel of 29 authenticated and publicly available BC cell lines by mRNA-sequencing, mutation analysis, and immunoblotting. Gene expression profiles separated BC cell lines in two major clusters that represent basal-like (mainly triple-negative BC) and luminal BC subtypes, respectively. HER2-positive cell lines were located within the luminal cluster. Mutation calling highlighted the frequent aberration of TP53 and BRCA2 in BC cell lines, which, therefore, share relevant characteristics with primary BC. Furthermore, we showed that the data can be used to find novel, potential oncogenic fusion transcripts, e.g., FGFR2::CRYBG1 and RTN4IP1::CRYBG1 in cell line MFM-223, and to elucidate the regulatory circuit of IRX genes and KLF15 as novel candidate tumor suppressor genes in BC. Our data indicated that KLF15 was activated by IRX1 and inhibited by IRX3. Moreover, KLF15 inhibited IRX1 in cell line HCC-1599. Each BC cell line carries unique molecular features. Therefore, the molecular characteristics of BC cell lines described here might serve as a valuable resource to improve the selection of appropriate models for BC research.

Comprehensive analysis of HOXC8 associated with tumor microenvironment characteristics in colorectal cancer

Background

Accumulating evidence have highlighted the essential roles of HOX genes in embryonic development and carcinogenesis. As a member of the HOX gene family, the abnormal expression of HOXC8 gene is associated with the progression and metastasis of various tumors. However, potential roles of HOXC8 in colorectal cancer (CRC) prognosis and tumor microenvironment (TME) remodeling remain unclear.

Methods

We conducted an integrated analysis of clinical and molecular characteristics, relevant oncogenic and immune regulation roles and drug sensitivity features of HOXC8 in CRC.

Results

HOXC8 expression was markedly high expressed in CRC samples compared to normal samples, and the upregulated expression of HOXC8 was associated with poor prognosis. High HOXC8 expression was significantly associated with invasion-related pathways especially epithelial-mesenchymal transition (EMT). In vitro experiments showed significantly up-regulated HOXC8 expression in some CRC cell lines and its promoting effect on EMT and cell proliferation. TME categorization through transcriptomic analysis of CRC patients with high HOXC8 expression identified two different TME subtypes known as immune-enriched with fibrotic subtype and immune-depleted subtype. Patients with immune-enriched, fibrotic subtype exhibited significantly longer progression-free survival (PFS), upregulated PD-L1 and CTLA4 expression and higher TMB than those with the immune-depleted subtype.

Conclusions

HOXC8 overexpression was associated with poor prognosis and specific TME subtypes in CRC. This study provided valuable resource for further exploring the potential mechanisms and therapeutic targets of HOX genes in CRC.

DNA methylation differences in noncoding regions in ER negative breast tumors between Black and White women

Introduction

Incidence of estrogen receptor (ER)-negative breast cancer, an aggressive tumor subtype associated with worse prognosis, is higher among African American/Black women than other US racial and ethnic groups. The reasons for this disparity remain poorly understood but may be partially explained by differences in the epigenetic landscape.

Methods

We previously conducted genome-wide DNA methylation profiling of ER- breast tumors from Black and White women and identified a large number of differentially methylated loci (DML) by race. Our initial analysis focused on DML mapping to protein-coding genes. In this study, motivated by increasing appreciation for the biological importance of the non-protein coding genome, we focused on 96 DMLs mapping to intergenic and noncoding RNA regions, using paired Illumina Infinium Human Methylation 450K array and RNA-seq data to assess the relationship between CpG methylation and RNA expression of genes located up to 1Mb away from the CpG site.

Results

Twenty-three (23) DMLs were significantly correlated with the expression of 36 genes (FDR<0.05), with some DMLs associated with the expression of single gene and others associated with more than one gene. One DML (cg20401567), hypermethylated in ER- tumors from Black versus White women, mapped to a putative enhancer/super-enhancer element located 1.3 Kb downstream of HOXB2. Increased methylation at this CpG correlated with decreased expression of HOXB2 (Rho=-0.74, FDR<0.001) and other HOXB/HOXB-AS genes. Analysis of an independent set of 207 ER- breast cancers from TCGA similarly confirmed hypermethylation at cg20401567 and reduced HOXB2 expression in tumors from Black versus White women (Rho=-0.75, FDR<0.001).

Discussion

Our findings indicate that epigenetic differences in ER- tumors between Black and White women are linked to altered gene expression and may hold functional significance in breast cancer pathogenesis.

The Expression and Role Analysis of Methylation-Regulated Differentially Expressed Gene UBE2C in Pan-Cancer, Especially for HGSOC

Simple Summary

DNA methylation has attracted a great deal of scientific interest as an early biomarker and potential therapeutic target. HGSOC result in high mortality due to the absence of reliable biomarkers for early diagnosis and prognosis. In this study, we performed an integrated bioinformatic analysis and found that UBE2C was hypomethylation and overexpression in ovarian cancer, which was associated with advanced cancer stages and poor prognoses. Meantime, this finding was also confirmed in pan-cancer analysis. Furthermore, the experimental validation of the expression and role of UBE2C was performed on HGSOC tissues and cancer cell lines. Importantly, demethylation could upregulate the expression of UBE2C. Taken together, methylation-regulated UBE2C may be a novel biomarker for diagnosis and prognosis, not only for ovarian cancer but a variety of cancers.

Abstract

High-grade serous ovarian cancer (HGSOC) is the most fatal gynecological malignant tumor. DNA methylation is associated with the occurrence and development of a variety of tumor types, including HGSOC. However, the signatures regarding DNA methylation changes for HGSOC diagnosis and prognosis are less explored. Here, we screened differentially methylated genes and differentially expressed genes in HGSOC through the GEO database. We identified that UBE2C was hypomethylation and overexpression in ovarian cancer, which was associated with more advanced cancer stages and poor prognoses. Additionally, the pan-cancer analysis showed that UBE2C was overexpressed and hypomethylation in almost all cancer types and was related to poor prognoses for various cancers. Next, we established a risk or prognosis model related to UBE2C methylation sites and screened out the three sites (cg03969725, cg02838589, and cg00242976). Furthermore, we experimentally validated the overexpression of UBE2C in HGSOC clinical samples and ovarian cell lines using quantitative real-time PCR, Western blot, and immunohistochemistry. Importantly, we discovered that ovarian cancer cell lines had lower DNA methylation levels of UBE2C than IOSE-80 cells (normal ovarian epithelial cell line) by bisulfite sequencing PCR. Consistently, treatment with 5-Azacytidine (a methylation inhibitor) was able to restore the expression of UBE2C. Taken together, our study may help us to understand the underlying molecular mechanism of UBE2C in pan-cancer tumorigenesis; it may be a useful biomarker for diagnosis, treatment, and monitoring, not only of ovarian cancer but a variety of cancers.

HOXA1, a breast cancer oncogene

More than 25 years ago, the first literature records mentioned HOXA1 expression in human breast cancer. A few years later, HOXA1 was confirmed as a proper oncogene in mammary tissue. In the following two decades, molecular data about the mode of action of the HOXA1 protein, the factors contributing to activate and maintain HOXA1 gene expression and the identity of its target genes have accumulated and provide a wider view on the association of this transcription factor to breast oncogenesis. Large-scale transcriptomic data gathered from wide cohorts of patients further allowed refining the relationship between breast cancer type and HOXA1 expression. Several recent reports have reviewed the connection between cancer hallmarks and the biology of HOX genes in general. Here we take HOXA1 as a paradigm and propose an extensive overview of the molecular data centered on this oncoprotein, from what its expression modulators, to the interactors contributing to its oncogenic activities, and to the pathways and genes it controls. The data converge to an intricate picture that answers questions on the multi-modality of its oncogene activities, point towards better understanding of breast cancer aetiology and thereby provides an appraisal for treatment opportunities.

Killing two birds with one stone: Pregnancy is a sensitive window for endocrine effects on both the mother and the fetus

Pregnancy is a complex process requiring tremendous physiological changes in the mother in order to fulfill the needs of the growing fetus, and to give birth, expel the placenta and nurse the newborn. These physiological modifications are accompanied with psychological changes, as well as with variations in habits and behaviors. As a result, this period of life is considered as a sensitive window as impaired functional and physiological changes in the mother can have short- and long-term impacts on her health. In addition, dysregulation of the placenta and of mechanisms governing placentation have been linked to chronic diseases later-on in life for the fetus, in a concept known as the Developmental Origin of Health and Diseases (DOHaD). This concept stipulates that any change in the environment during the pre-conception and perinatal (in utero life and neonatal) period to puberty, can be "imprinted" in the organism, thereby impacting the health and risk of chronic diseases later in life. Pregnancy is a succession of events that is regulated, in large part, by hormones and growth factors. Therefore, small changes in hormonal balance can have important effects on both the mother and the developing fetus. An increasing number of studies demonstrate that exposure to endocrine disrupting compounds (EDCs) affect both the mother and the fetus giving rise to growing concerns surrounding these exposures. This review will give an overview of changes that happen during pregnancy with respect to the mother, the placenta, and the fetus, and of the current literature regarding the effects of EDCs during this specific sensitive window of exposure.

Epigenetic alterations at distal enhancers are linked to proliferation in human breast cancer

Aberrant DNA methylation is an early event in breast carcinogenesis and plays a critical role in regulating gene expression. Here, we perform genome-wide expression-methylation Quantitative Trait Loci (emQTL) analysis through the integration of DNA methylation and gene expression to identify disease-driving pathways under epigenetic control. By grouping the emQTLs using biclustering we identify associations representing important biological processes associated with breast cancer pathogenesis including regulation of proliferation and tumor-infiltrating fibroblasts. We report genome-wide loss of enhancer methylation at binding sites of proliferation-driving transcription factors including CEBP-β, FOSL1, and FOSL2 with concomitant high expression of proliferation-related genes in aggressive breast tumors as we confirm with scRNA-seq. The identified emQTL-CpGs and genes were found connected through chromatin loops, indicating that proliferation in breast tumors is under epigenetic regulation by DNA methylation. Interestingly, the associations between enhancer methylation and proliferation-related gene expression were also observed within known subtypes of breast cancer, suggesting a common role of epigenetic regulation of proliferation. Taken together, we show that proliferation in breast cancer is linked to loss of methylation at specific enhancers and transcription factor binding and gene activation through chromatin looping.

The p53 Pathway Related Genes Predict the Prognosis of Colon Cancer

Background

Colon cancer is a common gastrointestinal malignancy. This study aimed to explore the relationship between p53 pathway-related genes and prognosis of colon cancer.

Methods

The mRNA datasets of colon cancer and adjacent tissues were downloaded from The Cancer Genome Atlas (TCGA) database, and the differential expression of genes in two groups was analyzed. Then, P53 pathway-related genes were intersected with differentially expressed genes (DEGs) to obtain P53 pathway-related differentially expressed genes. Then, overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) in clusters were compared by consistent cluster analysis. Univariate and multivariate Cox regression analysis of DEGs was performed to obtain survival-related DEGs. Risk scores were calculated for each sample based on survival-related DEGs, and patients were divided into high/low risk scores. Prognostic differences, tumor immune cell infiltration levels, and immune pathway activation status were compared between the two groups.

Results

We identified 28 DEGs and two clusters. There are significant differences in PFS between the two clusters (P=0.011), and no significant difference between OS and DSS. We obtained 3 DEGs (CDKN2A, BAK1, BTG1) that were significantly related to PFS, and CDKN2A was considered an independent prognostic factor. PFS showed statistically significant difference between high/low risk score groups (P=0.015). There were significant differences in immune cell infiltration level and immune pathway activity between two groups.

Conclusion

The p53 pathway-related genes are significantly related to PFS in colon cancer patients and play an important role in regulating the tumor immune microenvironment.

Mechanisms behind context-dependent role of glucocorticoids in breast cancer progression

Glucocorticoids (GCs), mostly dexamethasone (dex), are routinely administered as adjuvant therapy to manage side effects in breast cancer. However, recently, it has been revealed that dex triggers different effects and correlates with opposite outcomes depending on the breast cancer molecular subtype. This has raised new concerns regarding the generalized use of GC and suggested that the context-dependent effects of GCs can be taken into potential consideration during treatment design. Based on this, attention has recently been drawn to the role of the glucocorticoid receptor (GR) in development and progression of breast cancer. Therefore, in this comprehensive review, we aimed to summarize the different mechanisms behind different context-dependent GC actions in breast cancer by applying a multilevel examination, starting from the association of variants of the GR-encoding gene to expression at the mRNA and protein level of the receptor, and its interactions with other factors influencing GC action in breast cancer. The role of GCs in chemosensitivity and chemoresistance observed during breast cancer therapy is discussed. In addition, experiences using GC targeting therapeutic options (already used and investigated in preclinical and clinical trials), such as classic GC dexamethasone, selective glucocorticoid receptor agonists and modulators, the GC antagonist mifepristone, and GR coregulators, are also summarized. Evidence presented can aid a better understanding of the biology of context-dependent GC action that can lead to further advances in the personalized therapy of breast cancer by the evaluation of GR along with the conventional estrogen receptor (ER) and progesterone receptor (PR) in the routine diagnostic procedure.

Identification of Crucial lncRNAs for Luminal A Breast Cancer through RNA Sequencing

BACKGROUND

The growing body of evidence indicates aberrant expression of long noncoding RNAs (lncRNAs) in breast cancer. Nevertheless, a few studies have focused on identifying key lncRNAs for patients with luminal A breast cancer. In our study, we tried to find key lncRNAs and mRNAs in luminal A breast cancer.

METHODS

RNA sequencing was performed to identify differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) in luminal A breast cancer. The protein-protein interaction (PPI), DElncRNA-DEmRNA coexpression, DElncRNA-nearby DEmRNA interaction networks, and functional annotation were performed to uncover the function of DEmRNAs. Online databases were used to validate the RNA sequencing result. The diagnostic value of candidate mRNAs was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

A total number of 1451 DEmRNAs and 272 DElncRNAs were identified. Several hub proteins were identified in the PPI network, including TUBB3, HIST2H3C, MCM2, MYOC, NEK2, LIPE, FN1, FOXJ1, S100A7, and DLK1. In the DElncRNA-DEmRNA coexpression, some hub lncRNAs were identified, including AP001528.2, LINC00968, LINC02202, TRHDE-AS1, LINC01140, AL354707.1, AC097534.1, MIR222HG, and AL662844.4. The mRNA expression result of TFF1, COL10A1, LEP, PLIN1, PGM5-AS1, and TRHDE-AD1 in the GSE98793 was consistent with the RNA sequencing result. The protein expression results of TUBB3, MCM2, MYOC, FN1, S100A7, and TFF1 were consistent with the mRNA expression result COL10A1, LEP, PLIN1, PGM5-AS1, and TRHDE-AD1 were capable of discriminating luminal A breast cancer and normal controls. Four lncRNA-nearby and coexpressed mRNA pairs of HOXC-AS3-HOXC10, AC020907.2-FXYD1, AC026461.1-MT1X, and AC132217.1-IGF2 were identified. AMPK (involved LIPE and LEP) and PPAR (involved PLIN1) were two significantly enriched pathways in luminal A breast cancer.

CONCLUSION

This study could be helpful in unraveling the pathogenesis and providing novel therapeutic strategies for luminal A breast cancer.

Identification and Validation of Immune-Related Methylation Clusters for Predicting Immune Activity and Prognosis in Breast Cancer

The role of DNA methylation of breast cancer-infiltrating immune cells has not been fully explored. We conducted a cohort-based retrospective study analyzing the genome-wide immune-related DNA methylation of 1057 breast cancer patients from the TCGA cohort and GSE72308 cohort. Based on patients' overall survival (OS), a prognostic risk score system using 18 immune-related methylation genes (IRMGs) was established and further validated in an independent cohort. Kaplan-Meier analysis showed a clear separation of OS between the low- and high-risk groups. Patients in the low-risk group had a higher immune score and stromal score compared with the high-risk group. Moreover, the characteristics based on 18-IRMGs signature were related to the tumor immune microenvironment and affected the abundance of tumor-infiltrating immune cells. Consistently, the 18-IRMGs signatures showed similar influences on immune modulation and survival in another external validation cohort (GSE72308). In conclusion, the proposed 18-IRMGs signature could be a potential marker for breast cancer prognostication.

Deciphering the nexus between the tumor immune microenvironment and DNA methylation in subgrouping estrogen receptor-positive breast cancer

BACKGROUND

Based on variable DNA methylation (DNAm), estrogen receptor (ER)-positive breast cancer (BRCA) is composed of two major subtypes, with the hypomethylated subgroup displaying good survival. Evidence indicates that the tumor microenvironment (TME) plays an important role in tumor progression and metastasis; however, its role and biological characteristics in DNAm-based subtypes of ER-positive BRCA remain largely unknown.

METHODS

Transcriptome data and matched clinical information of BRCA were downloaded from the Cancer Genome Atlas. Immune (ISs) and stromal scores (SSs) of BRCA patients were calculated using the ESTIMATE algorithm. Inferred fractions of 22 types of infiltrating immune cells of BRCA were collected from the Cancer Immunome Atlas.

RESULTS

The hypomethylated ER-positive BRCA subtype displayed high ISs, echoing the finding that higher ISs are associated with good BRCA survival. In addition, we analyzed the differentially expressed genes between the hypo-high-IS and hyper-low-IS BRCA subtypes in ER-positive patients and identified a co-expressed gene module (i.e., red module) enriched in immune-related biological processes (e.g., leukocyte activation involved in immune response). Moreover, four hub genes (i.e., PLEK, CD53, EVI2B, and CD4) in this module showed significant association between their expression and ER-positive BRCA survival.

CONCLUSIONS

We found differences in the tumor immune microenvironment (TIME) between DNAm-based BRCA subgroups in ER-positive patients and identified a specific module and hub genes involved to these differences. These findings elucidate the immunological basis for ER-positive BRCA progression and classification and provide potential gene biomarkers and targets for ER-positive BRCA diagnosis and treatment.

Luminal A Breast Cancer Co-expression Network: Structural and Functional Alterations

Luminal A is the most common breast cancer molecular subtype in women worldwide. These tumors have characteristic yet heterogeneous alterations at the genomic and transcriptomic level. Gene co-expression networks (GCNs) have contributed to better characterize the cancerous phenotype. We have previously shown an imbalance in the proportion of intra-chromosomal (cis-) over inter-chromosomal (trans-) interactions when comparing cancer and healthy tissue GCNs. In particular, for breast cancer molecular subtypes (Luminal A included), the majority of high co-expression interactions connect gene-pairs in the same chromosome, a phenomenon that we have called loss of trans- co-expression. Despite this phenomenon has been described, the functional implication of this specific network topology has not been studied yet. To understand the biological role that communities of co-expressed genes may have, we constructed GCNs for healthy and Luminal A phenotypes. Network modules were obtained based on their connectivity patterns and they were classified according to their chromosomal homophily (proportion of cis-/trans- interactions). A functional overrepresentation analysis was performed on communities in both networks to observe the significantly enriched processes for each community. We also investigated possible mechanisms for which the loss of trans- co-expression emerges in cancer GCN. To this end we evaluated transcription factor binding sites, CTCF binding sites, differential gene expression and copy number alterations (CNAs) in the cancer GCN. We found that trans- communities in Luminal A present more significantly enriched categories than cis- ones. Processes, such as angiogenesis, cell proliferation, or cell adhesion were found in trans- modules. The differential expression analysis showed that FOXM1, CENPA, and CIITA transcription factors, exert a major regulatory role on their communities by regulating expression of their target genes in other chromosomes. Finally, identification of CNAs, displayed a high enrichment of deletion peaks in cis- communities. With this approach, we demonstrate that network topology determine, to at certain extent, the function in Luminal A breast cancer network. Furthermore, several mechanisms seem to be acting together to avoid trans- co-expression. Since this phenomenon has been observed in other cancer tissues, a remaining question is whether the loss of long distance co-expression is a novel hallmark of cancer.

BTG1 Overexpression Might Promote Invasion and Metastasis of Colorectal Cancer via Decreasing Adhesion and Inducing Epithelial-Mesenchymal Transition

BTG (B-cell translocation gene) could inhibit cell proliferation, metastasis, and angiogenesis and regulate cell cycle progression and differentiation in a variety of cancer cell types. To clarify the role of BTG1 in invasion and metastasis, its expression was compared with the clinicopathological parameters of colorectal cancer by bioinformatics and immunohistochemical analyses. We also overexpressed BTG1 in HCT-15 cells and examined its effects on adhesion, migration, and metastasis with their related molecules screened. BTG1 mRNA expression was negatively correlated with its promoter methylation in colorectal cancer (P < 0.05). Among them, cg08832851 and cg05819371 hypermethylation and mRNA expression of BTG1 were positively related with poor prognosis of the colorectal cancer patients (P < 0.05). BTG1 expression was found to positively correlate with depth of invasion, venous invasion, lymph node metastasis, distant metastasis, and TNM staging of colorectal cancer (P < 0.05) but negatively with serum levels of CEA and CA19-9 (P < 0.05). According to the TCGA database, BTG1 mRNA expression was lower in well-, moderately, and poorly differentiated than mucinous adenocarcinomas and positively correlated with ras or BRAF mutation (P < 0.05). Kaplan–Meier analysis showed the negative correlation between BTG1 mRNA expression and overall survival rate of all cancer patients (P < 0.05). BTG1 overexpression weakened adhesion and strengthened migration and invasion of HCT-15 cells (P < 0.05). There was E-cadherin hypoexpression, N-cadherin and MMP-9 hyperexpression, Zeb1 and Vimentin mRNA overexpression, a high expression of CEA mRNA and protein, and a strong secretion of CEA in BTG1 transfectants, compared with the control or mock. It was suggested that BTG1 expression might promote invasion and metastasis by decreasing adhesion, and inducing epithelial–mesenchymal transition.

Dioxin Disrupts Dynamic DNA Methylation Patterns in Genes That Govern Cardiomyocyte Maturation

Congenital heart disease (CHD), the leading birth defect worldwide, has a largely unknown etiology, likely to result from complex interactions between genetic and environmental factors during heart development, at a time when the heart adapts to diverse physiological and pathophysiological conditions. Crucial among these is the regulation of cardiomyocyte development and postnatal maturation, governed by dynamic changes in DNA methylation. Previous work from our laboratory has shown that exposure to the environmental toxicant tetrachlorodibenzo-p-dioxin (TCDD) disrupts several molecular networks responsible for heart development and function. To test the hypothesis that the disruption caused by TCDD in the heart results from changes in DNA methylation and gene expression patterns of cardiomyocytes, we established a stable mouse embryonic stem cell line expressing a puromycin resistance selectable marker under control of the cardiomyocyte-specific Nkx2-5 promoter. Differentiation of these cells in the presence of puromycin induces the expression of a large suite of cardiomyocyte-specific markers. To assess the consequences of TCDD treatment on gene expression and DNA methylation in these cardiomyocytes, we subjected them to transcriptome and methylome analyses in the presence of TCDD. Unlike control cardiomyocytes maintained in vehicle, the TCDD-treated cardiomyocytes showed extensive gene expression changes, with a significant correlation between differential RNA expression and DNA methylation in 111 genes, many of which are key elements of pathways that regulate cardiovascular development and function. Our findings provide an important clue toward the elucidation of the complex interactions between genetic and epigenetic mechanisms after developmental TCDD exposure that may contribute to CHD.

Methylation of WT1, CA10 in peripheral blood leukocyte is associated with breast cancer risk: a case-control study

Background

Studies have shown that abnormal changes of specific-gene DNA methylation in leukocytes may be associated with an elevated risk of cancer. However, associations between the methylation of the zinc-related genes, WT1 and CA10, and breast cancer risk remain unknown.

Methods

The methylation of WT1 and CA10 was analyzed by methylation-sensitive high-resolution-melting (MS-HRM) in a case-control study with female subjects (N = 959). Logistic regression was used to analyze the associations, and propensity score (PS) method was used to adjust confounders.

Results

The results showed that WT1 hypermethylation was associated with an increased risk of breast cancer, with an odds ratio (OR) of 3.07 [95% confidence interval (CI): 1.67–5.64, P < 0.01]. Subgroup analyses showed that WT1 hypermethylation was specifically associated with an elevated risk of luminal A subtype (OR = 2.62, 95% CI: 1.11–6.20, P = 0.03) and luminal B subtype (OR = 3.23, 95% CI: 1.34–7.80, P = 0.01). CA10 hypermethylation was associated with an increased risk of luminal B subtype (OR = 1.80, 95% CI: 1.09–2.98, P = 0.02).

Conclusion

The results of the present study suggest that the hypermethylation of WT1 methylation in leukocytes is significantly associated with an increased risk of breast cancer. The hypermethylation of WT1 is associated with an increased risk of luminal subtypes of breast cancer, and the hypermethylation of CA10 is associated with an increased risk of luminal B subtype of breast cancer.

NK homeobox 2.2 functions as tumor suppressor in colorectal cancer due to DNA methylation

Aim: The role of NK homeobox 2.2 (NKX2.2) in human colorectal cancer (CRC) remains to be unveiled. This study was designed to explore the epigenetic regulation and function of NKX2.2 in human CRC.

Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to assess the methylation data of NKX2.2 in CRC. Six CRC cell lines (HCT116, SW480, HT29, LOVO, SW1116, SW640) and 20 pairs of primary CRC tumor and normal tissues were utilized to explore the function of NKX2.2 in CRC using Sequenom EpiTYPER®, verified by cloning-based bisulfite sequencing analysis, semi-quantitative reverse transcription PCR, western blot, cell viability assessment, plate clone formation assay , and transwell assays.

Results: Bioinformatic analysis showed that NKX2.2 was significantly hypermethylated in primary tumors compared to normal tissues (p < 0.05). Our study also found that NKX2.2 methylation was upregulated (p<0.05) in tumors than normal tissues. In vitro experiments demonstrated that 5-aza-2'-deoxycytidine downregulated the methylation of NKX2.2 and retrieved its expression of mRNA and protein levels (p<0.05). No significant association was found between the NKX2.2 methylation and sex, age, tumor differentiation, TNM stage, CEA, CA199, and fecal occult blood (p>0.05). Kaplan-Meier analysis indicated that NKX2.2 hypermethylation showed a trend but not statistical significance for predicting poor overall survival in CRC patients (p=0.33). NKX2.2 overexpression suppressed cell proliferation, colony formation, and inhibited tumor invasion and migration in CRC cells (both p<0.05).

Conclusions: This study indicates that NKX2.2 is a tumor suppressor in CRC due to hypermethylation.

Identification and validation of prognosis-related DLX5 methylation as an epigenetic driver in myeloid neoplasms

The deregulated DLX gene family members DLX1/2/3/4/5/6 (DLXs) caused by DNA methylation has been demonstrated in various cancers with therapeutic target value. However, the potential role of DLXs methylation in myeloid neoplasms such as acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) remains to be elucidated. Clinical significance of DLXs methylation/expression was analyzed in patient with AML and MDS. The functional roles of DLXs were determined in vitro. In the identification stage, we found that lower DLX5 expression was correlated with prognosis in AML among all DLXs analyzed by The Cancer Genome Atlas datasets. In the validation stage, we revealed that reduced DLX5 expression was frequently occurred, and was also correlated with promoter hypermethylation in AML evaluated by targeted bisulfite sequencing. Epigenetic studies also showed that DLX5 promoter DNA methylation was associated with its expression. By quantitative polymerase chain reaction, we also validated that DLX5 hypermethylation was frequent event in both AML and MDS, and also correlated with MDS transformation to leukemia. Moreover, DLX5 hypermethylation was associated with lower rate of complete remission and shorter time of leukemia‐free/overall survival, and was also confirmed by Logistic/Cox regression analysis. Functional studies revealed the antiproliferative and pro‐apoptotic effects of DLX5 in MDS‐derived AML cell‐line SKM‐1. Finally, bioinformatics analysis demonstrated that DLX5 functioned in leukemogenesis may be through the association with PI3K/Akt signaling pathway. Collectively, our findings demonstrated that DLX5 methylation, negatively correlated DLX5 expression, was a potential prognostic and predictive indicator in patients with AML and MDS, which could also act as an epigenetic driver in myeloid neoplasms.

The Role of ISL1 and LHX5 LIM Homeobox Genes in Bladder Tumourigenesis

Introduction

Lin-11, Isl-1 and Mec-3 domains (LIM) homeobox genes are among the most important sub-families of homeobox genes. These genes are thought to play an important role in cancer. In this study, the protein expression of these genes was examined in urothelial carcinoma of the bladder. The expression pattern of Islet-1 (ISL1) and LIM homeobox 5 (LHX5) across different cancer stages and grades, as well as the association between the protein expression of these genes and patient demographics and clinicopathological features, were examined.

Methods

A total of 100 formalin-fixed paraffin-embedded urothelial carcinoma tissues were selected from the Department of Pathology, Hospital Kuala Lumpur and the protein expression of ISL1 and LHX5 was determined using immunohistochemistry.

Results

Positive expression of ISL1 and LHX5 was detected in 94% and 98% of the samples, respectively. There were no distinct LHX5 expression patterns associated with different cancer stages, but the proportion of high-expressing tumours was higher in high-grade tumours. In addition, there was a significant association between the expression of LHX5 and tumour grade. The proportion of tumours expressing high levels of ISL1 was found to be highest in later stage tumours.

Conclusion

The high percentage of tumours expressing both these genes suggests that ISL1 and LHX5 play an important role in bladder tumourigenesis across multiple stages.

Genistein inhibited the proliferation of kidney cancer cells via CDKN2a hypomethylation: role of abnormal apoptosis

INTRODUCTION

Genistein is recognized as a potent anti-oxidant in soybean-enriched foods, which is a kind of phytoestrogen involved in anticancer activity in various cancers.

OBJECTIVE

The objective of this study was to investigate the molecular mechanism of CDKN2a hypomethylation involved in the anti-tumor effect of genistein on kidney cancer.

METHODS

The CDKN2a expression was measured using qRT-PCR. The level of CDKN2a methylation was detected using methylation-specific PCR. The apoptosis was detected via flow-cytometric analysis. The cell viability was detected using the 3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay.

RESULTS

Our results indicated that genistein induced cell apoptosis and inhibited the cell proliferation of kidney cancer cells. Moreover, genistein increased the expression of CDKN2a and decreased CDKN2a methylation.

CONCLUSIONS

Our results demonstrated that the anti-tumor effect of genistein might induce cell apoptosis and inhibit the proliferation of kidney cancer cells via regulating CDKN2a methylation.

Combining Bioinformatics and Experiments to Identify and Verify Key Genes with Prognostic Values in Endometrial Carcinoma

Endometrial carcinoma(EC) is the most common cancer of female reproductive system, thus requiring for new effective biomarkers which could predict the onset of EC and poor prognosis. Our study integrated two GEO datasets(i.e.GSE63678, GSE17025) and TCGA(The Cancer Genome Atlas ) UCEC data to screen out 344 common differentially expressed genes(DEGs), which were further analyzed by GO(gene ontology) functions and KEGG(Kyoto Encyclopedia of Gene and Genome) pathways. KEGG analysis results showed these DEGs were mainly enriched in cell cycle, oocyte meiosis, cellular senescence, carbon metabolism and p53 signaling pathway. Top 20 hub genes with higher degree were selected from PPI(protein-protein interaction) network and 15 of them were associated with the prognosis of EC, that is, CCNB2, CDC20, BUB1B, UBE2C, AURKB, FOXM1, NCAPG, RRM2, TPX2, DLGAP5, CDCA8, CDC45, MKI67, BUB1, KIF2C. UBE2C(Ubiquitin Conjugating Enzyme E2 C) was chosen for further validation in TCGA cohort on mRNA level and in our patient samples on protein level by immunohistochemistry. UBE2C was significantly highly expressed in endometrial carcinoma, and its expression level was associated with advanced FIGO staging and poor prognosis. Cox risk model demonstrated high UBE2C expression was an independent risk factor. Somatic mutations, elevated copy number, DNA hypomethylation all contributed to its overexpression. Therefore, by combination of bioinformatics and experiment, our study provided a unique insight into the pathogenesis and molecular mechanisms underlying EC and discovered new biomarkers for early diagnosis and prognostic prediction. UBE2C could serve as a potential marker to predict poor prognosis and as a therapeutic target.

Modifications of H3K4 methylation levels are associated with DNA hypermethylation in acute myeloid leukemia

The 'instructive model' of aberrant DNA methylation in human tumors is based on the observation that CpG islands prone to hypermethylation in cancers are embedded in chromatin enriched in H3K27me3 in human embryonic stem cells (hESC). Recent studies also link methylation of CpG islands to the methylation status of H3K4, where H3K4me3 is inversely correlated with DNA methylation. To provide insight into these conflicting findings, we generated DNA methylation profiles for acute myeloid leukemia samples from patients and leukemic cell lines and integrated them with publicly available ChIp-seq data, containing H3K4me3 and H3K27me3 CpG island occupation in hESC, or hematopoietic stem or progenitor cells (hHSC/MPP). Hypermethylated CpG islands in AML samples displayed H3K27me3 enrichments in hESC and hHSC/MPP; however, ChIp analysis of specific hypermethylated CpG islands revealed a significant reduction in H3K4me3 signal with a concomitant increase in H3K4me0 levels as opposed to a nonsignificant increase in H3K27me3 marks. The integration of AML DNA methylation profiles with the ChIp-seq data in hESC and hHSC/MPP also led to the identification of Iroquois homeobox 2 (IRX2) as a previously unknown factor promoting differentiation of leukemic cells. Our results indicate that in contrast to the 'instructive model', H3K4me3 levels are strongly associated with DNA methylation patterns in AML and have a role in the regulation of critical genes, such as the putative tumor suppressor IRX2.

Dysregulation of DNA methylation patterns may identify patients with breast cancer resistant to endocrine therapy: A predictive classifier based on differentially methylated regions

Endocrine therapy (ET) is one of a number of targeted therapies for estrogen receptor-positive breast cancer (BRCA); however, resistance to ET has become the primary issue affecting treatment outcome. In the present study, a predictive classifier was created using a DNA methylation dataset to identify patients susceptible to endocrine resistance. DNA methylation and RNA sequencing data, and the clinicopathological features of BRCA, were obtained from The Cancer Genome Atlas. Stringent criteria were set to select and classify patients into two groups, namely those resistant to ET (n=11) and sensitive to ET (n=21) groups. Bump hunting analysis revealed that 502 out of 135,418 genomic regions were differentially methylated between these two groups; these regions were differentially methylated regions (DMRs). The majority of the CpG sites contained in the DMRs mapped to the promoter region. Functional enrichment analyses indicated that a total of 562 specific genes encompassing these DMRs were primarily associated with 'biological progress of organ morphogenesis and development' and 'cell-cell adhesion' gene ontologies. Logistic regression and Pearson's correlation analysis were conducted to construct a predictive classifier for distinguishing patients resistant or sensitive to ET. The highest areas under the curve and relatively low Akaike information criterion values were associated with a total of 60 DMRs; a risk score retained from this classifier was revealed to be an unfavorable predictor of survival in two additional independent datasets. Furthermore, the majority of genes (55/63) exhibited a statistically significant association between DNA methylation and mRNA expression (P<0.05). The association between the mRNA expression of a number of genes (namely calcium release activated channel regulator 2A, Schlafen family member 12, chromosome 3 open reading frame 18, zinc finger protein 880, dual oxidase 1, major histocompatibility complex, class II, DP β1, C-terminal binding protein 1, ALG13 UDP-N-acetylglucosaminyltransferase subunit and RAS protein activator like 2) and the prognosis of patients with estrogen receptor-positive BRCA and ET resistance was determined using Kaplan-Meier Plotter. In summary, the predictive classifier proposed in the present study may aid the identification of patients sensitive or resistant to ET, and numerous genes maybe potential therapeutic targets to delay the development of resistance to ET.

Transcriptional regulation of normal human mammary cell heterogeneity and its perturbation in breast cancer

The mammary gland in adult women consists of biologically distinct cell types that differ in their surface phenotypes. Isolation and molecular characterization of these subpopulations of mammary cells have provided extensive insights into their different transcriptional programs and regulation. This information is now serving as a baseline for interpreting the heterogeneous features of human breast cancers. Examination of breast cancer mutational profiles further indicates that most have undergone a complex evolutionary process even before being detected. The consequent intra-tumoral as well as inter-tumoral heterogeneity of these cancers thus poses major challenges to deriving information from early and hence likely pervasive changes in potential therapeutic interest. Recently described reproducible and efficient methods for generating human breast cancers de novo in immunodeficient mice transplanted with genetically altered primary cells now offer a promising alternative to investigate initial stages of human breast cancer development. In this review, we summarize current knowledge about key transcriptional regulatory processes operative in these partially characterized subpopulations of normal human mammary cells and effects of disrupting these processes in experimentally produced human breast cancers.

Disadvantaged neighborhoods and racial disparity in breast cancer outcomes: the biological link

Neighborhoods encompass complex environments comprised of unique economic, physical, and social characteristics that have a profound impact on the residing individual's health and, collectively, on the community's wellbeing. Neighborhood disadvantage (ND) is one of several factors that prominently contributes to racial breast cancer (BC) health disparities in American women. African American (AA) women develop more aggressive breast cancer features, such as triple-negative receptor status and more advanced histologic grade and tumor stage, and suffer worse clinical outcomes than European American (EA) women. While the adverse effects of neighborhood disadvantage on health, including increased risk of cancer and decreased longevity, have recently come into focus, the specific molecular mechanisms by which neighborhood disadvantage increases BC risk and worsens BC outcomes (survivorship, recurrence, mortality) are not fully elucidated. This review illuminates the probable biological links between neighborhood disadvantage and predominantly BC risk, with an emphasis on stress reactivity and inflammation, epigenetics and telomere length in response to adverse neighborhood conditions.

Genome-wide miRNA methylome analysis in oral cancer: possible biomarkers associated with patient survival

AIM

The methylome associated with miRNA loci was investigated in oral cancer to explore tobacco specific methylation and potential biomarkers for patient survival.

METHODS

Methylome data was generated from 16 pairs of cancer-normal tissues by reduced representation bisulfite sequencing method. Differentially methylated regions were identified using the DMAP pipeline. In silico validation and Kaplan-Meier survival analyses were performed on The Cancer Genome Atlas data based on our miRNA methylome data.

RESULTS

A total of 4310 unique differentially methylated regions, mapping to 144 miRNA loci, were identified. Three distinct groups of miRNAs were differentially methylated in cancer tissues from smokers, chewers and mixed habitués. Hypermethylation of miR-503, miR-200a/b, miR-320b and miR-489 was associated with worse 5-year survival.

CONCLUSION

Differential methylation patterns in miRNA loci are associated with poor survival underscoring their potential as predictive and prognostic biomarkers in oral cancer.

Genome-wide methylotyping resolves breast cancer epigenetic heterogeneity and suggests novel therapeutic perspectives

Aim: To provide a breast cancer (BC) methylotype classification by genome-wide CpG islands bisulfite DNA sequencing. Materials & methods: XmaI-reduced representation bisulfite sequencing DNA methylation sequencing method was used to profile DNA methylation of 110 BC samples and 6 normal breast samples. Intrinsic DNA methylation BC subtypes were elicited by unsupervised hierarchical cluster analysis, and cluster-specific differentially methylated genes were identified. Results & conclusion: Overall, six distinct BC methylotypes were identified. BC cell lines constitute a separate group extremely highly methylated at the CpG islands. In turn, primary BC samples segregate into two major subtypes, highly and moderately methylated. Highly and moderately methylated superclusters, each incorporate three distinct epigenomic BC clusters with specific features, suggesting novel perspectives for personalized therapy.

Methylomic Analysis of Ovarian Cancers Identifies Tumor-Specific Alterations Readily Detectable in Early Precursor Lesions

PURPOSE

High-grade serous ovarian carcinoma (HGSOC) typically remains undiagnosed until advanced stages when peritoneal dissemination has already occurred. Here, we sought to identify HGSOC-specific alterations in DNA methylation and assess their potential to provide sensitive and specific detection of HGSOC at its earliest stages.

EXPERIMENTAL DESIGN

MethylationEPIC genome-wide methylation analysis was performed on a discovery cohort comprising 23 HGSOC, 37 non-HGSOC malignant, and 36 histologically unremarkable gynecologic tissue samples. The resulting data were processed using selective bioinformatic criteria to identify regions of high-confidence HGSOC-specific differential methylation. Quantitative methylation-specific real-time PCR (qMSP) assays were then developed for 8 of the top-performing regions and analytically validated in a cohort of 90 tissue samples. Lastly, qMSP assays were used to assess and compare methylation in 30 laser-capture microdissected (LCM) fallopian tube epithelia samples obtained from cancer-free and serous tubal intraepithelial carcinoma (STIC) positive women.

RESULTS

Bioinformatic selection identified 91 regions of robust, HGSOC-specific hypermethylation, 23 of which exhibited an area under the receiver-operator curve (AUC) value ≥ 0.9 in the discovery cohort. Seven of 8 top-performing regions demonstrated AUC values between 0.838 and 0.968 when analytically validated by qMSP in a 90-patient cohort. A panel of the 3 top-performing genes (c17orf64, IRX2, and TUBB6) was able to perfectly discriminate HGSOC (AUC 1.0). Hypermethylation within these loci was found exclusively in LCM fallopian tube epithelia from women with STIC lesions, but not in cancer-free fallopian tubes.

CONCLUSIONS

A panel of methylation biomarkers can be used to accurately identify HGSOC, even at precursor stages of the disease.

Up-regulation of the IRX2 gene predicts poor prognosis in nasopharyngeal carcinoma

Aberrant expression of the IRX2 gene contributes to the oncogenesis and progression of various cancers. In this study, we analyzed the clinical significance and the prognostic value of mRNA expression level of the IRX2 gene in nasopharyngeal carcinoma (NPC) patients, with the goal to find a novel prognostic biomarker for NPC. Tissue samples were collected prior to treatment from 71 NPC patients for the detection of mRNA expression level of a total of 31503 genes, with high throughput screening of the mRNA expression profile. The Kaplan-Meier curves and log-rank test were used for univariate analyses to determine if the mRNA expression level of IRX2 and other 31502 genes, as well as clinical characteristics were of prognostic value for overall survival (OS), distant metastasis-free survival (DMFS) and disease-free survival (DFS). Regularized Cox regression was performed to test the contribution of prognostic factors to OS, DMFS, and DFS of NPC patients. The Cox proportional hazard model was used to test the independence of prognostic effect of IRX2 and other clinical features. The receiver operator characteristic curve was drawn and the area under the curve (AUC) was calculated to evaluate the predictive power of IRX2 gene. Univariate analyses showed a higher mRNA expression level of the IRX2 gene correlated with shorter OS (P = 0.001), DMFS (P = 0.003), and DFS (P = 0.007). Regularized Cox regression and Cox proportional hazard model analyses further showed that ahigher mRNA expression level of the IRX2 gene in the primary NPC was an independent prognostic factor for OS (Coxnet beta = 0.03, Cox proportion hazard model P = 0.038), DMFS (Coxnet beta = 0.018, Cox proportion hazard model P = 0.01) and DFS (Coxnet beta = 0.008, Cox proportion hazard model P = 0.029). The AUC showed that the mRNA expression level of the IRX2 gene is a significant predictor for predicting the OS (AUC value = 0.7105) and DMFS (AUC value = 0.7027) of NPC patients. Our results demonstrated that the IRX2 gene may be a novel independent unfavorable prognostic factor for NPC patients.

Inferring Novel Tumor Suppressor Genes with a Protein-Protein Interaction Network and Network Diffusion Algorithms

Extensive studies on tumor suppressor genes (TSGs) are helpful to understand the pathogenesis of cancer and design effective treatments. However, identifying TSGs using traditional experiments is quite difficult and time consuming. Developing computational methods to identify possible TSGs is an alternative way. In this study, we proposed two computational methods that integrated two network diffusion algorithms, including Laplacian heat diffusion (LHD) and random walk with restart (RWR), to search possible genes in the whole network. These two computational methods were LHD-based and RWR-based methods. To increase the reliability of the putative genes, three strict screening tests followed to filter genes obtained by these two algorithms. After comparing the putative genes obtained by the two methods, we designated twelve genes (e.g., MAP3K10, RND1, and OTX2) as common genes, 29 genes (e.g., RFC2 and GUCY2F) as genes that were identified only by the LHD-based method, and 128 genes (e.g., SNAI2 and FGF4) as genes that were inferred only by the RWR-based method. Some obtained genes can be confirmed as novel TSGs according to recent publications, suggesting the utility of our two proposed methods. In addition, the reported genes in this study were quite different from those reported in a previous one.

Homeobox A11 hypermethylation indicates unfavorable prognosis in breast cancer

Homeobox A11 (HOXA11) is one of the hypermethylated genes in breast cancer and its function in breast tumorigenesis remains elusive. In this study, we analyzed the methylation status of HOXA11 in 264 paired breast cancer and normal tissue as well as in matched serum samples by MethyLight assay. Further, the function of HOXA11 in breast tumorigenesis was analyzed by cell proliferation and migration assays. We found that HOXA11 was hypermethylated in cancer tissues (45.08%), especially in invasive ductal carcinomas (P<0.001), patients with a family history of cancer (P=0.033), cases with metastatic lymph nodes (P=0.004) and P53 positive group (P=0.017). Kaplan-Meier survival analysis and Cox regression analysis revealed that HOXA11 hypermethylation is an independent predictor of poor outcomes. The over expression of HOXA11 suppressed cell growth in MDA-MB-231, MCF7, SKBR3 and BT474 cells. In conclusion, the hypermethylation of HOXA11 is an independent prognostic biomarker in breast cancer. Additionally, HOXA11 can be a potential tumor suppressor.

Comparative pan-cancer DNA methylation analysis reveals cancer common and specific patterns

Abnormal DNA methylation is an important epigenetic regulator involving tumorigenesis. Deciphering cancer common and specific DNA methylation patterns is essential for us to understand the mechanisms of tumor development. The Cancer Genome Atlas (TCGA) project provides a large number of samples of different cancers that enable a pan-cancer study of DNA methylation possible. Here we investigate cancer common and specific DNA methylation patterns among 5480 DNA methylation profiles of 15 cancer types from TCGA. We first define differentially methylated CpG sites (DMCs) in each cancer and then identify 5450 hyper- and 4433 hypomethylated pan-cancer DMCs (PDMCs). Intriguingly, three adjacent hypermethylated PDMC constitute an enhancer region, which potentially regulates two tumor suppressor genes BVES and PRDM1 negatively. Moreover, we identify six distinct motif clusters, which are enriched in hyper- or hypomethylated PDMCs and are associated with several well-known cancer hallmarks. We also observe that PDMCs relate to distinct transcriptional groups. Additionally, 55 hypermethylated and 7 hypomethylated PDMCs are significantly associated with patient survival. Lastly, we find that cancer-specific DMCs are enriched in known cancer genes and cell-type-specific super-enhancers. In summary, this study provides a comprehensive investigation and reveals meaningful cancer common and specific DNA methylation patterns.

DNA methylation at enhancers identifies distinct breast cancer lineages

Breast cancers exhibit genome-wide aberrant DNA methylation patterns. To investigate how these affect the transcriptome and which changes are linked to transformation or progression, we apply genome-wide expression-methylation quantitative trait loci (emQTL) analysis between DNA methylation and gene expression. On a whole genome scale, in cis and in trans, DNA methylation and gene expression have remarkably and reproducibly conserved patterns of association in three breast cancer cohorts (n = 104, n = 253 and n = 277). The expression-methylation quantitative trait loci associations form two main clusters; one relates to tumor infiltrating immune cell signatures and the other to estrogen receptor signaling. In the estrogen related cluster, using ChromHMM segmentation and transcription factor chromatin immunoprecipitation sequencing data, we identify transcriptional networks regulated in a cell lineage-specific manner by DNA methylation at enhancers. These networks are strongly dominated by ERα, FOXA1 or GATA3 and their targets were functionally validated using knockdown by small interfering RNA or GRO-seq analysis after transcriptional stimulation with estrogen.

An early biomarker and potential therapeutic target of RUNX 3 hypermethylation in breast cancer, a system review and meta-analysis

Runt-related transcription factor 3 (RUNX3) methylation plays an important role in the carcinogenesis of breast cancer (BC). However, the association between RUNX3 hypermethylation and significance of BC remains under investigation. The purpose of this study is to perform a meta-analysis and literature review to evaluate the clinicopathological significance of RUNX3 hypermethylation in BC. A comprehensive literature search was performed in Medline, Web of Science, EMBASE, Cochrane Library Database, CNKI and Google scholar. A total of 10 studies and 747 patients were included for the meta-analysis. Pooled odds ratios (ORs) with corresponding confidence intervals (CIs) were evaluated and summarized respectively. RUNX3 hypermethylation was significantly correlated with the risk of ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC), OR was 50.37, p < 0.00001 and 22.66, p < 0.00001 respectively. Interestingly, the frequency of RUNX3 hypermethylation increased in estrogen receptor (ER) positive BC, OR was 12.12, p = 0.005. High RUNX3 mRNA expression was strongly associated with better relapse-free survival (RFS) in BC patients. In summary, RUNX3 methylation could be a promising early biomarker for the diagnosis of BC. High RUNX3 mRNA expression is correlated to better RFS in BC patients. RUNX3 could be a potential therapeutic target for the development of personalized therapy.

Deconvolution of DNA methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes

Breast cancer is a complex disease consisting of four distinct molecular subtypes. DNA methylation-based (DNAm) studies in tumors are complicated further by disease heterogeneity. In the present study, we compared DNAm in breast tumors with normal-adjacent breast samples from The Cancer Genome Atlas (TCGA). We constructed models stratified by tumor stage and PAM50 molecular subtype and performed cell-type reference-free deconvolution to control for cellular heterogeneity. We identified nineteen differentially methylated gene regions (DMGRs) in early stage tumors across eleven genes (AGRN, C1orf170, FAM41C, FLJ39609, HES4, ISG15, KLHL17, NOC2L, PLEKHN1, SAMD11, WASH5P). These regions were consistently differentially methylated in every subtype and all implicated genes are localized to the chromosomal cytoband 1p36.3. Seventeen of these DMGRs were independently validated in a similar analysis of an external data set. The identification and validation of shared DNAm alterations across tumor subtypes in early stage tumors advances our understanding of common biology underlying breast carcinogenesis and may contribute to biomarker development. We also discuss evidence of the specific importance and potential function of 1p36 in cancer.

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

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.

Identification of early-stage lung adenocarcinoma prognostic signatures based on statistical modeling

BACKGROUND

Current staging methods are lack of precision in predicting prognosis of early-stage lung adenocarcinomas.

OBJECTIVE

We aimed to develop a gene expression signature to identify high- and low-risk groups of patients.

METHODS

We used the Bayesian Model Averaging algorithm to analyze the DNA microarray data from 442 lung adenocarcinoma patients from three independent cohorts, one of which was used for training.

RESULTS

The patients were assigned to either high- or low-risk groups based on the calculated risk scores based on the identified 25-gene signature. The prognostic power was evaluated using Kaplan-Meier analysis and the log-rank test. The testing sets were divided into two distinct groups with log-rank test p-values of 0.00601 and 0.0274 respectively.

CONCLUSIONS

Our results show that the prognostic models could successfully predict patients' outcome and serve as biomarkers for early-stage lung adenocarcinoma overall survival analysis.

TUSC3: a novel tumour suppressor gene and its functional implications

The tumour suppressor candidate 3 (TUSC3) gene is located on chromosome region 8p22 and encodes the 34 kD TUSC3 protein, which is a subunit of the oligosaccharyl transferase responsible for the N‐glycosylation of nascent proteins. Known to be related to autosomal recessive mental retardation for several years, TUSC3 has only recently been identified as a potential tumour suppressor gene. Based on the structure and function of TUSC3, specific mechanisms in various diseases have been investigated. Several studies have demonstrated that TUSC3 is an Mg²⁺‐transporter involved in magnesium transport and homeostasis, which is important for learning and memory, embryonic development and testis maturation. Moreover, dysfunction or deletion of TUSC3 exerts its oncological effects as a modulator by inhibiting glycosylation efficiency and consequently inducing endoplasmic reticulum stress and malignant cell transformation. In this study, we summarize the advances in the studies of TUSC3 and comment on the potential roles of TUSC3 in diagnosis and treatment of TUSC3‐related diseases, especially cancer.

DNA Methylation in Breast Tumor from High-risk Women in the Breast Cancer Family Registry

To examine DNA methylation profiles in breast tumors of women with a strong breast cancer family history, we measured methylation by bisulfite sequencing in 40 genes in 40 breast tumor tissues from women in the Breast Cancer Family Registry. We selected candidate genes from analysis of the Cancer Genome Atlas project (TCGA) breast data. Compared to TCGA breast cancer, BCFR cases are younger and more likely to be ER-negative. Overall, we found that many of the methylation differences between BCFR tumor and normal adjacent tissues were smaller than that in TCGA samples. We found only 32% of tested genes were hypermethylated in BCFR; the largest difference was 36.1% for SEPW1, and the smallest difference was 10% for RYR2. These data suggest the importance of examining breast cancer cases including familial cases enriched with early-onset cancers to identify methylation markers that can be examined in blood as biomarkers for early detection.

HOXC8 regulates self-renewal, differentiation and transformation of breast cancer stem cells

BACKGROUND

Homeobox genes are master regulators of cell fate during embryonic development and their expression is altered in cancer. By regulating the balance between cell proliferation and differentiation, they maintain homeostasis of normal tissues. Here, we screened the expression of homeobox genes in mammary stem cells to establish their role in stem cells transformation in breast cancer.

METHODS

Using a Homeobox Genes PCR array, we screened 83 homeobox genes in normal cancer breast stem/progenitor cells isolated by flow cytometry. The candidate gene HOXC8 epigenetic regulation was studied by DNA methylation and miRNA expression analyses. Self-renewal and differentiation of HOXC8-overexpressing or knockdown cells were assessed by flow cytometry and mammosphere, 3D matrigel and soft agar assays. Clinical relevance of in vitro findings were validated by bioinformatics analysis of patient datasets from TCGA and METABRIC studies.

RESULTS

In this study we demonstrate altered expression of homeobox genes in breast cancer stem/progenitor cells. HOXC8 was consistently downregulated in stem/progenitor cells of all breast molecular subtypes, thus representing an interesting tumour suppressor candidate. We show that downregulated expression of HOXC8 is associated with DNA methylation at the gene promoter and expression of miR196 family members. Functional studies demonstrated that HOXC8 gain of function induces a decrease in the CD44⁺/CD24^-/low cancer stem cell population and proportion of chemoresistant cells, with a concomitant increase in CD24⁺ differentiated cells. Increased HOXC8 levels also decrease the ability of cancer cells to form mammospheres and to grow in anchorage-independent conditions. Furthermore, loss of HOXC8 in non-tumorigenic mammary epithelial cells expands the cancer stem/progenitor cells pool, increases stem cell self-renewal, prevents differentiation induced by retinoic acid and induces a transformed phenotype.

CONCLUSIONS

Taken together, our study points to an important role of homeobox genes in breast cancer stem/progenitor cell function and establishes HOXC8 as a suppressor of stemness and transformation in the mammary gland lineage.

Identification of Genetic and Epigenetic Variants Associated with Breast Cancer Prognosis by Integrative Bioinformatics Analysis

INTRODUCTION

Breast cancer being a multifaceted disease constitutes a wide spectrum of histological and molecular variability in tumors. However, the task for the identification of these variances is complicated by the interplay between inherited genetic and epigenetic aberrations. Therefore, this study provides an extrapolate outlook to the sinister partnership between DNA methylation and single-nucleotide polymorphisms (SNPs) in relevance to the identification of prognostic markers in breast cancer. The effect of these SNPs on methylation is defined as methylation quantitative trait loci (meQTL).

MATERIALS AND METHODS

We developed a novel method to identify prognostic gene signatures for breast cancer by integrating genomic and epigenomic data. This is based on the hypothesis that multiple sources of evidence pointing to the same gene or pathway are likely to lead to reduced false positives. We also apply random resampling to reduce overfitting noise by dividing samples into training and testing data sets. Specifically, the common samples between Illumina 450 DNA methylation, Affymetrix SNP array, and clinical data sets obtained from the Cancer Genome Atlas (TCGA) for breast invasive carcinoma (BRCA) were randomly divided into training and test models. An intensive statistical analysis based on log-rank test and Cox proportional hazard model has established a significant association between differential methylation and the stratification of breast cancer patients into high- and low-risk groups, respectively.

RESULTS

The comprehensive assessment based on the conjoint effect of CpG–SNP pair has guided in delaminating the breast cancer patients into the high- and low-risk groups. In particular, the most significant association was found with respect to cg05370838–rs2230576, cg00956490–rs940453, and cg11340537–rs2640785 CpG–SNP pairs. These CpG–SNP pairs were strongly associated with differential expression of ADAM8, CREB5, and EXPH5 genes, respectively. Besides, the exclusive effect of SNPs such as rs10101376, rs140679, and rs1538146 also hold significant prognostic determinant.

CONCLUSIONS

Thus, the analysis based on DNA methylation and SNPs have resulted in the identification of novel susceptible loci that hold prognostic relevance in breast cancer.

DNA methylation signature (SAM40) identifies subgroups of the Luminal A breast cancer samples with distinct survival

Breast cancer patients with Luminal A disease generally have a good prognosis, but among this patient group are patients with good prognosis that are currently overtreated with adjuvant chemotherapy, and also patients that have a bad prognosis and should be given more aggressive treatment. There is no available method for subclassification of this patient group. Here we present a DNA methylation signature (SAM40) that segregates Luminal A patients based on prognosis, and identify one good prognosis group and one bad prognosis group. The prognostic impact of SAM40 was validated in four independent patient cohorts. Being able to subdivide the Luminal A patients may give the two-sided benefit of identifying one subgroup that may benefit from a more aggressive treatment than what is given today, and importantly, identifying a subgroup that may benefit from less treatment.

Subtype-specific CpG island shore methylation and mutation patterns in 30 breast cancer cell lines

Background

Aberrant epigenetic modifications, including DNA methylation, are key regulators of gene activity in tumorigenesis. Breast cancer is a heterogeneous disease, and large-scale analyses indicate that tumor from normal and benign tissues, as well as molecular subtypes of breast cancer, can be distinguished based on their distinct genomic, transcriptomic, and epigenomic profiles. In this study, we used affinity-based methylation sequencing data in 30 breast cancer cell lines representing functionally distinct cancer subtypes to investigate methylation and mutation patterns at the whole genome level.

Results

Our analysis revealed significant differences in CpG island (CpGI) shore methylation and mutation patterns among breast cancer subtypes. In particular, the basal-like B type, a highly aggressive form of the disease, displayed distinct CpGI shore hypomethylation patterns that were significantly associated with downstream gene regulation. We determined that mutation rates at CpG sites were highly correlated with DNA methylation status and observed distinct mutation rates among the breast cancer subtypes. These findings were validated by using targeted bisulfite sequencing of differentially expressed genes (n=85) among the cell lines.

Conclusions

Our results suggest that alterations in DNA methylation play critical roles in gene regulatory process as well as cytosine substitution rates at CpG sites in molecular subtypes of breast cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0356-2) contains supplementary material, which is available to authorized users.

Towards understanding the breast cancer epigenome: a comparison of genome-wide DNA methylation and gene expression data

Until recently, an elevated disease risk has been ascribed to a genetic predisposition, however, exciting progress over the past years has discovered alternate elements of inheritance that involve epigenetic regulation. Epigenetic changes are heritably stable alterations that include DNA methylation, histone modifications and RNA-mediated silencing. Aberrant DNA methylation is a common molecular basis for a number of important human diseases, including breast cancer. Changes in DNA methylation profoundly affect global gene expression patterns. What is emerging is a more dynamic and complex association between DNA methylation and gene expression than previously believed. Although many tools have already been developed for analyzing genome-wide gene expression data, tools for analyzing genome-wide DNA methylation have not yet reached the same level of refinement.

Here we provide an in-depth analysis of DNA methylation in parallel with gene expression data characteristics and describe the particularities of low-level and high-level analyses of DNA methylation data. Low-level analysis refers to pre-processing of methylation data (i.e. normalization, transformation and filtering), whereas high-level analysis is focused on illustrating the application of the widely used class comparison, class prediction and class discovery methods to DNA methylation data. Furthermore, we investigate the influence of DNA methylation on gene expression by measuring the correlation between the degree of CpG methylation and the level of expression and to explore the pattern of methylation as a function of the promoter region.

DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer

Germline pathogenic mutations in BRCA1 increase risk of developing breast cancer. Screening for mutations in BRCA1 frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate BRCA1-mutated from BRCA1-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carriers of unclassified variants. We selected 150 FFPE breast tumor DNA samples [47 BRCA1 pathogenic mutation carriers, 65 BRCAx (BRCA1-wild type), 38 BRCA1 test variants] and analyzed a subset (n=54) using the Illumina 450K methylation platform, using the remaining samples for bisulphite pyrosequencing validation. Three validated markers (BACH2, C8orf31, and LOC654342) were combined with sequence bioinformatics in a model to predict pathogenicity of 27 variants (independent test set).  Predictions were compared with standard multifactorial likelihood analysis. Prediction was consistent for c.5194-12G>A (IVS 19-12 G>A) (P>0.99); 13 variants were considered not pathogenic or likely not pathogenic using both approaches. We conclude that tumor DNA methylation data alone has potential to be used in prediction of BRCA1 variant pathogenicity but is not independent of estrogen receptor status and grade, which are used in current multifactorial models to predict pathogenicity.