scholarly journals An Integrated Epigenomic and Genomic View on Phyllodes and Phyllodes-Like Breast Tumors

2021 ◽  
Author(s):  
Juergen Hench ◽  
Tatjana Vlajnic ◽  
Savas Deniz Soysal ◽  
Ellen C Obermann ◽  
Stephan Frank ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Copy Number Variant ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Fish Analysis ◽  
Breast Cancers ◽  
Diagnostic Challenge ◽  
Cancer Dataset ◽  
Genomic Aberrations ◽  
Therapeutic Decision Making

Fibroepithelial lesions (FL) of the breast, in particular Phyllodes tumors (PT) and fibroadenomas, pose a significant diagnostic challenge. There are no generally accepted criteria that distinguish benign, borderline, malignant PT, and FA. Combined genome-wide DNA methylation and copy number variant (CNV) profiling is an emerging strategy to classify tumors. We compiled a series of patient-derived archival biopsy specimens reflecting the FL spectrum and histological mimickers including clinical follow-up data. DNA methylation and CNVs were determined by well-established microarrays. Comparison of the patterns with a pan-cancer dataset assembled from public resources including "The Cancer Genome Atlas" (TCGA) and "Gene Expression Omnibus" (GEO) suggests that FLs form a methylation class distinct from both control breast tissue as well as common breast cancers. Complex CNVs were enriched in clinically aggressive FLs. Subsequent fluorescence in situ hybridization (FISH) analysis detected respective aberrations in the neoplastic mesenchymal component of FLs only, confirming that the epithelial component is non-neoplastic. Of note, our approach could lead to the elimination of the diagnostically problematic category of borderline PT and allow for optimized prognostic patient stratification. Furthermore, the identified recurrent genomic aberrations such as 1q gains (including MDM4), CDKN2a/b deletions and EGFR amplifications may inform therapeutic decision-making.

scholarly journals Epigenetic Age Acceleration of Stomach Adenocarcinoma Associated With Tumor Stemness Features, Immunoactivation, and Favorable Prognosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Chunhong Hong ◽  
Shaohua Yang ◽  
Qiaojin Wang ◽  
Shiqiang Zhang ◽  
Wenhui Wu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Correlation Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Chronological Age ◽  
Favorable Prognosis ◽  
Molecular Features ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration ◽  
Stomach Adenocarcinoma

Background: Abnormal DNA methylation (DNAm) age has been assumed to be an indicator for canceration and all-cause mortality. However, associations between DNAm age and molecular features of stomach adenocarcinoma (STAD), and its prognosis have not been systematically studied.Method: We calculated the DNAm age of 591 STAD samples and 115 normal stomach samples from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) database using the Horvath’s clock model. Meanwhile, we utilized survival analysis to evaluate the prognostic value of DNAm age and epigenetic age acceleration shift. In addition, we performed weighted gene co-expression network analysis (WGCNA) to identify DNAm age-associated gene modules and pathways. Finally, the association between DNAm age and molecular features was performed by correlation analysis.Results: DNA methylation age was significantly correlated with chronological age in normal gastric tissues (r = 0.85, p < 0.0001), but it was not associated with chronological age in STAD samples (r = 0.060, p = 0.2369). Compared with tumor adjacent normal tissue, the DNAm age of STAD tissues was significantly decreased. Meanwhile, chronological age in STAD samples was higher than its DNAm age. Both DNAm age and epigenetic acceleration shift were associated with the prognosis of STAD patients. By using correlation analysis, we also found that DNAm age was associated with immunoactivation and stemness in STAD samples.Conclusion: In summary, epigenetic age acceleration of STAD was associated with tumor stemness, immunoactivation, and favorable prognosis.

scholarly journals Germline PARP4 mutations in patients with primary thyroid and breast cancers

2015 ◽  
Vol 23 (3) ◽  
pp. 171-179 ◽  
Author(s):  
Yuji Ikeda ◽  
Kazuma Kiyotani ◽  
Poh Yin Yew ◽  
Taigo Kato ◽  
Kenji Tamura ◽  
...  
Keyword(s):  
Rare Variants ◽  
Susceptibility Gene ◽  
Cowden Syndrome ◽  
Gene Expression Omnibus ◽  
Hazard Ratio ◽  
The Cancer Genome Atlas ◽  
Small Subset ◽  
Breast Cancers ◽  
Research Participants ◽  
Kaplan Meier

Germline mutations in the PTEN gene, which cause Cowden syndrome, are known to be one of the genetic factors for primary thyroid and breast cancers; however, PTEN mutations are found in only a small subset of research participants with non-syndrome breast and thyroid cancers. In this study, we aimed to identify germline variants that may be related to genetic risk of primary thyroid and breast cancers. Genomic DNAs extracted from peripheral blood of 14 PTEN WT female research participants with primary thyroid and breast cancers were analyzed by whole-exome sequencing. Gene-based case-control association analysis using the information of 406 Europeans obtained from the 1000 Genomes Project database identified 34 genes possibly associated with the phenotype with P<1.0×10−3. Among them, rare variants in the PARP4 gene were detected at significant high frequency (odds ratio=5.2; P=1.0×10−5). The variants, G496V and T1170I, were found in six of the 14 study participants (43%) while their frequencies were only 0.5% in controls. Functional analysis using HCC1143 cell line showed that knockdown of PARP4 with siRNA significantly enhanced the cell proliferation, compared with the cells transfected with siControl (P=0.02). Kaplan–Meier analysis using Gene Expression Omnibus (GEO), European Genome-phenome Archive (EGA) and The Cancer Genome Atlas (TCGA) datasets showed poor relapse-free survival (P<0.001, Hazard ratio 1.27) and overall survival (P=0.006, Hazard ratio 1.41) in a PARP4 low-expression group, suggesting that PARP4 may function as a tumor suppressor. In conclusion, we identified PARP4 as a possible susceptibility gene of primary thyroid and breast cancer.

scholarly journals Identification of Methylation Biomarkers for Early Detection of Prostate Cancer

2021 ◽  
Author(s):  
Yiyi Pu ◽  
Chao Li ◽  
Haining Yuan ◽  
Xiaoju Wang
Keyword(s):  
Prostate Cancer ◽  
Dna Methylation ◽  
Early Detection ◽  
Early Diagnosis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Prostate Tumors ◽  
Normal Tissues ◽  
Cancer Genome Atlas ◽  
Cancer Types

Abstract Background: DNA methylation has been widely used for development of cancer diagnosis biomarker. However, the clinical translational rate is low. Databases, such as The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), offer great opportunities for DNA methylation biomarker identification. By taking advantage of the public databases, we aimed to identify cancer specific biomarkers based on DNA methylation level for early detection purpose. Results: We performed a pan-cancer methylation analysis using datasets from TCGA and validated the results using GEO datasets. To identify early-diagnosis biomarkers, we focused on the localized tumors, and identified the biomarkers that can effectively distinguish the localized tumors from normal tissues. After comparing biomarkers for all cancer types, we identified a large group of cancer specific biomarkers. Within all 26 prostate cancer specific biomarkers selected, we confirmed three biomarker sets by multiplex analysis. First, 7 biomarkers (cg26140475, cg24891312, cg24522654, cg21359747, cg03254336, cg12697139, cg19034132) could detect localized prostate tumors from normal tissues (AUC > 0.9). Second, 9 biomarkers (cg17220055, cg26140475, cg24891312, cg09853702, cg22400059, cg16736279, cg27639613, cg06011086, cg00664697) could distinguish between low and high Gleason score prostate tumors (AUC = 0.79). Last, a single biomarker (cg26140475) completely separated prostate tumor from other urinary tumors (AUC = 1). Conclusions: Our study identified and validated a panel of methylation-based biomarkers which could be used for prostate cancer early diagnosis.

scholarly journals Pan-Cancer Genome-Wide DNA Methylation Analyses Revealed That Hypermethylation Influences 3D Architecture and Gene Expression Dysregulation in HOXA Locus During Carcinogenesis of Cancers

2021 ◽  
Vol 9 ◽  
Author(s):  
Gang Liu ◽  
Zhenhao Liu ◽  
Xiaomeng Sun ◽  
Xiaoqiong Xia ◽  
Yunhe Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cell Lines ◽  
Dna Interaction ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Topological Domains ◽  
Cancer Types ◽  
Pan Cancer

DNA methylation dysregulation during carcinogenesis has been widely discussed in recent years. However, the pan-cancer DNA methylation biomarkers and corresponding biological mechanisms were seldom investigated. We identified differentially methylated sites and regions from 5,056 The Cancer Genome Atlas (TCGA) samples across 10 cancer types and then validated the findings using 48 manually annotated datasets consisting of 3,394 samples across nine cancer types from Gene Expression Omnibus (GEO). All samples’ DNA methylation profile was evaluated with Illumina 450K microarray to narrow down the batch effect. Nine regions were identified as commonly differentially methylated regions across cancers in TCGA and GEO cohorts. Among these regions, a DNA fragment consisting of ∼1,400 bp detected inside the HOXA locus instead of the boundary may relate to the co-expression attenuation of genes inside the locus during carcinogenesis. We further analyzed the 3D DNA interaction profile by the publicly accessible Hi-C database. Consistently, the HOXA locus in normal cell lines compromised isolated topological domains while merging to the domain nearby in cancer cell lines. In conclusion, the dysregulation of the HOXA locus provides a novel insight into pan-cancer carcinogenesis.

scholarly journals DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients

2021 ◽  
Vol 28 ◽  
pp. 107327482098851
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Yan Zhou
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Molecular Subtypes ◽  
Methylation Status ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Consensus Clustering ◽  
Breast Cancer Patients ◽  
Cancer Subtypes ◽  
Novel Biomarkers

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

scholarly journals A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 854
Author(s):  
Yishu Wang ◽  
Lingyun Xu ◽  
Dongmei Ai
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Regression Model ◽  
The Cancer Genome Atlas ◽  
Low Rank ◽  
Expression Levels ◽  
Rank Regression ◽  
Prediction Of Prognosis ◽  
Gene Expression Levels

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.

scholarly journals Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ping Yan ◽  
Zuotian Huang ◽  
Tong Mou ◽  
Yunhai Luo ◽  
Yanyao Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Clinical Information ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
High Rate ◽  
Competing Endogenous Rna ◽  
Tissue Samples ◽  
Potential Biomarkers

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. Results With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. Conclusions In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

scholarly journals Screening the genome for HCC-specific CpG methylation signatures as biomarkers for diagnosis and prognosis evaluation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Rui-kun Zhang ◽  
Jia-lin Liu
Keyword(s):  
Cox Regression ◽  
Malignant Tumors ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Training Set ◽  
Cpg Sites ◽  
Diagnosis And Prognosis ◽  
Patient Prognosis ◽  
Prognosis Evaluation

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and invasive malignant tumors in the world. The change in DNA methylation is a key event in HCC. Methods Methylation datasets for HCC and 17 other types of cancer were downloaded from The Cancer Genome Atlas (TCGA). The CpG sites with large differences in methylation between tumor tissues and paracancerous tissues were identified. We used the HCC methylation dataset downloaded from the TCGA as the training set and removed the overlapping sites among all cancer datasets to ensure that only CpG sites specific to HCC remained. Logistic regression analysis was performed to select specific biomarkers that can be used to diagnose HCC, and two datasets—GSE157341 and GSE54503—downloaded from GEO as validation sets were used to validate our model. We also used a Cox regression model to select CpG sites related to patient prognosis. Results We identified 6 HCC-specific methylated CpG sites as biomarkers for HCC diagnosis. In the training set, the area under the receiver operating characteristic (ROC) curve (AUC) for the model containing all these sites was 0.971. The AUCs were 0.8802 and 0.9711 for the two validation sets from the GEO database. In addition, 3 other CpG sites were analyzed and used to create a risk scoring model for patient prognosis and survival prediction. Conclusions Through the analysis of HCC methylation datasets from the TCGA and Gene Expression Omnibus (GEO) databases, potential biomarkers for HCC diagnosis and prognosis evaluation were ascertained.

scholarly journals JOSD1 promotes proliferation and chemoresistance of head and neck squamous cell carcinoma under the epigenetic regulation of BRD4

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chao Jing ◽  
Dandan Liu ◽  
Qingchuan Lai ◽  
Linqi Li ◽  
Mengqian Zhou ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Gene Expression Omnibus ◽  
Neck Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
In Vivo Experiments

Abstract Background Deubiquitinating enzymes (DUBs) play critical roles in various cancers by modulating functional proteins post-translationally. Previous studies have demonstrated that DUB Josephin Domain Containing 1 (JOSD1) is implicated in tumor progression, however, the role and mechanism of JOSD1 in head and neck squamous cell carcinoma (HNSCC) remain to be explored. In this study, we aimed to identify the clinical significance and function of JOSD1 in HNSCC. Methods The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed to find novel DUBs in HNSCC. Immunohistochemistry assay was performed to determine the expression of JOSD1 in our cohort of 42 patients suffered with HNSCC. Kaplan–Meier analysis was used to identify the correlation between JOSD1 and the prognosis of HNSCC patients. The regulation of BRD4 on JOSD1 was determined by using pharmacological inhibition and gene depletion. The in vitro and in vivo experiments were conducted to elucidate the role of JOSD1 in HNSCC. Results The results of IHC showed that JOSD1 was aberrantly expressed in HNSCC specimens, especially in the chemoresistant ones. The overexpression of JOSD1 indicated poor clinical outcome of HNSCC patients. Moreover, JOSD1 depletion dramatically impaired cell proliferation and colony formation, and promoted cisplatin-induced apoptosis of HNSCC cells in vitro. Additionally, JOSD1 suppression inhibited the tumor growth and improved chemosensitivity in vivo. The epigenetic regulator BRD4 contributed to the upregulation of JOSD1 in HNSCC. Conclusions These results demonstrate that JOSD1 functions as an oncogene in HNSCC progression, and provide a promising target for clinical diagnosis and therapy of HNSCC.

scholarly journals Novel Epigenetic Eight-Gene Signature Predictive of Poor Prognosis and MSI-Like Phenotype in Human Metastatic Colorectal Carcinomas

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 158
Author(s):  
Valentina Condelli ◽  
Giovanni Calice ◽  
Alessandra Cassano ◽  
Michele Basso ◽  
Maria Grazia Rodriquenz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Poor Prognosis ◽  
Cpg Island ◽  
Colon Adenocarcinoma ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cpg Island Methylator Phenotype ◽  
Prognostic Information ◽  
Global Methylation

Epigenetics is involved in tumor progression and drug resistance in human colorectal carcinoma (CRC). This study addressed the hypothesis that the DNA methylation profiling may predict the clinical behavior of metastatic CRCs (mCRCs). The global methylation profile of two human mCRC subgroups with significantly different outcome was analyzed and compared with gene expression and methylation data from The Cancer Genome Atlas COlon ADenocarcinoma (TCGA COAD) and the NCBI GENE expression Omnibus repository (GEO) GSE48684 mCRCs datasets to identify a prognostic signature of functionally methylated genes. A novel epigenetic signature of eight hypermethylated genes was characterized that was able to identify mCRCs with poor prognosis, which had a CpG-island methylator phenotype (CIMP)-high and microsatellite instability (MSI)-like phenotype. Interestingly, methylation events were enriched in genes located on the q-arm of chromosomes 13 and 20, two chromosomal regions with gain/loss alterations associated with adenoma-to-carcinoma progression. Finally, the expression of the eight-genes signature and MSI-enriching genes was confirmed in oxaliplatin- and irinotecan-resistant CRC cell lines. These data reveal that the hypermethylation of specific genes may provide prognostic information that is able to identify a subgroup of mCRCs with poor prognosis.

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