Hypermethylation Of ADHFE1 Promotes The Proliferation Of Colorectal Cancer Cell Via Modulating Cell Cycle Progression

Research progress of DNA methylation in colorectal cancer (Review)

DNA methylation is one of the earliest and most significant epigenetic mechanisms discovered. DNA methylation refers, in general, to the addition of a methyl group to a specific base in the DNA sequence under the catalysis of DNA methyltransferase, with S‑adenosine methionine as the methyl donor, via covalent bonding and chemical modifications. DNA methylation is an important factor in inducing cancer. There are different types of DNA methylation, and methylation at different sites plays different roles. It is well known that the progression of colorectal cancer (CRC) is affected by the methylation of key genes. The present review did not only discuss the potential relationship between DNA methylation and CRC but also discussed how DNA methylation affects the development of CRC by affecting key genes. Furthermore, the clinical significance of DNA methylation in CRC was highlighted, including that of the therapeutic targets and biomarkers of methylation; and the importance of DNA methylation inhibitors was discussed as a novel strategy for treatment of CRC. The present review did not only focus upon the latest research findings, but earlier reviews were also cited as references to older literature.

Combined detection of SDC2/ADHFE1/PPP2R5C methylation in stool DNA for colorectal cancer screening

BACKGROUND

Colorectal cancer (CRC) is a disease of global concern, and its increasing incidence suggests the need for early and accurate diagnosis. The aim of this study was to investigate the value of combined detection of SDC2, ADHFE1 and PPP2R5C gene methylation in stool samples for early CRC screening.

METHODS

Stool samples from patients with CRC (n = 105), advanced adenoma (AA) (n = 54), non-advanced adenoma (NA) (n = 57), hyperplastic or other polyps (HOP) (n = 47) or no evidence of disease (NED) (n = 100) were collected from September 2021 to September 2022. The methylation levels of SDC2, ADHFE1 and PPP2R5C were quantified by quantitative methylation-specific polymerase chain reaction (qMSP), and faecal immunochemical testing (FIT) was performed. The diagnostic value was assessed using reporter operating characteristic (ROC) curve analysis.

RESULTS

The sensitivity of combined detection of SDC2/ADHFE1/PPP2R5C methylation in predicting CRC (0-IV) was 84.8%, the specificity was 98.0%, and the AUC was 0.930 (95% CI 0.889-0.970). Compared to FIT and serum tumour biomarkers, it showed better diagnostic performance for different stages of CRC.

CONCLUSION

The results of this study verified that the methylation levels of SDC2, ADHFE1 and PPP2R5C in stool DNA were significantly increased in CRC patients. Combined detection of SDC2/ADHFE1/PPP2R5C methylation is a potential non-invasive diagnostic method for CRC and precancerous lesion screening.

CLINICAL TRIAL REGISTRATION

Chinese Clinical Trials Registry, ChiCTR2100046662, registered on 26 May 2021, prospective registration.

A novel risk score model based on gamma-aminobutyric acid signature predicts the survival prognosis of patients with breast cancer

Background

Gamma-aminobutyric acid (GABA) participates in the migration, differentiation, and proliferation of tumor cells. However, the GABA-related risk signature has never been investigated. Hence, we aimed to develop a reliable gene signature based on GABA pathways-related genes (GRGs) to predict the survival prognosis of breast cancer patients.

Methods

GABA-related gene sets were acquired from the MSigDB database, while mRNA gene expression profiles and corresponding clinical data of breast cancer patients were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Univariate Cox regression analysis was used to identify prognostic-associated GRGs. Subsequently, LASSO analysis was applied to establish a risk score model. We also constructed a clinical nomogram to perform the survival evaluation. Besides, ESTIMATE and ssGSEA algorithms were used to assess the immune cell infiltration among the risk score subgroups.

Results

A GRGs-related risk score model was constructed in the TCGA cohort, and validated in the GSE21653 cohort. The risk score was significantly related to the overall survival of breast cancer patients, which could predict the survival prognosis of breast cancer patients independently of other clinical features. Breast cancer patients in the low-risk score group exhibited higher immune cell infiltration levels.

Conclusion

A novel prognostic model containing five GRGs could accurately predict the survival prognosis and immune infiltration of breast cancer patients. Our findings provided a novel insight into investigating the immunoregulation roles of GRGs.

DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden

Background

Immune checkpoint inhibitor (ICI) therapy has proven to be a promising treatment for colorectal cancer (CRC). We aim to investigate the relationship between DNA methylation and tumor mutation burden (TMB) by integrating genomic and epigenetic profiles to precisely identify clinical benefit populations and to evaluate the effect of ICI therapy.

Methods

A total of 536 CRC tissues from the Cancer Genome Atlas (TCGA) with mutation data were collected and subjected to calculate TMB. 80 CRC patients with high TMB and paired normal tissues were selected as training sets and developed the diagnostic and prognostic methylation models, respectively. In the validation set, the diagnostic model was validated in our in-house 47 CRC tissues and 122 CRC tissues from the Gene Expression Omnibus (GEO) datasets, respectively. And a total of 38 CRC tissues with high TMB from the COLONOMICS dataset verified the prognostic model.

Results

A positive correlation between differential methylation positions and TMB level was observed in TCGA CRC cohort (r=0.45). The diagnostic score that consisted of methylation levels of four genes (ADHFE1, DOK6, GPR75, and MAP3K14-AS1) showed high diagnostic performance in the discovery (AUC=1.000) and two independent validation (AUC=0.946, AUC=0.857) datasets. Additionally, these four genes showed significant positive correlations with NK cells. The prognostic score containing three genes (POU3F3, SYN2, and TMEM178A) had significantly poorer survival in the high-risk TMB samples than those in the low-risk TMB samples (P=0.016). CRC patients with low-risk scores combined with TMB levels represent a favorable survival.

Conclusions

By integrating analyses of methylation and mutation data, it is suggested that DNA methylation patterns combined with TMB serve as a novel potential biomarker for early screening in more high-TMB populations and for evaluating the prognostic effect of CRC patients with ICI therapy.

CpG Site-Based Signature Predicts Survival of Colorectal Cancer

BACKGROUND

A critical unmet medical need in clinical management of colorectal cancer (CRC) pivots around lack of noninvasive and or minimally invasive techniques for early diagnosis and prognostic prediction of clinical outcomes. Because DNA methylation can capture the regulatory landscape of tumors and can be measured in body fluids, it provides unparalleled opportunities for the discovery of early diagnostic and prognostics markers predictive of clinical outcomes. Here we investigated use of DNA methylation for the discovery of potential clinically actionable diagnostic and prognostic markers for predicting survival in CRC.

METHODS

We analyzed DNA methylation patterns between tumor and control samples to discover signatures of CpG sites and genes associated with CRC and predictive of survival. We conducted functional analysis to identify molecular networks and signaling pathways driving clinical outcomes.

RESULTS

We discovered a signature of aberrantly methylated genes associated with CRC and a signature of thirteen (13) CpG sites predictive of survival. We discovered molecular networks and signaling pathways enriched for CpG sites likely to drive clinical outcomes.

CONCLUSIONS

The investigation revealed that CpG sites can predict survival in CRC and that DNA methylation can capture the regulatory state of tumors through aberrantly methylated molecular networks and signaling pathways.

FMR1 promotes the progression of colorectal cancer cell by stabilizing EGFR mRNA in an m6A-dependent manner

FMR1, a new m⁶A reader, is known to be involved in the regulation of cancer progression. However, its role, regulatory mechanism, and clinical significance in colorectal cancer (CRC) are elusive. Here, we showed that FMR1 was upregulated in CRC, and it promoted proliferation and metastasis of CRC cells in vitro and in vivo. Mechanically, FMR1 recognized the m⁶A-modification site in EGFR mRNA, a key molecule in cancer occurrence and targeted therapy, sustained its stability and maintained its expression in an m⁶A-dependent manner, thereby promoting the tumorigenesis and metastasis of CRC. And the effect of FMR1 knockdown in CRC cells could be abolished by METTL3. Furthermore, FMR1 shRNA plasmid carried by attenuated Salmonella has an effective anti-tumor effect in vivo. Collectively, we identified the METTL3/FMR1/EGFR axis in the progression of CRC. This novel mechanism indicated that the METTL3/FMR1/EGFR axis is a potential target for early therapeutic intervention in CRC progression.

Nanoscale Force-Mapping-Based Quantification of Low-Abundance Methylated DNA

Methylation changes at cytosine-guanine dinucleotide (CpG) sites in genes are closely related to cancer development. Thus, detection and quantification of low-abundance methylated DNA is critical for early diagnosis. Here, we report an atomic force microscopy (AFM)-based quantification method for DNA that contains methyl-CpG at a specific site, without any treatment to the target DNA such as chemical labeling, fluorescence tagging, or amplification. We employed AFM-tip-tethered methyl-CpG-binding proteins to probe surface-captured methylated DNA. We observed a linear correlation (R² = 0.982) between the input copy number and detected copy number, in the low copy number regime (10 or fewer; subattomolar concentrations). For a mixture of methylated and nonmethylated DNA that resembles clinical samples, we were still able to quantify the methylated DNA. These results highlight the potential of our force-mapping-based quantification method for wide applications in early detection of diseases associated with methylated DNA.

Epigenome-Wide DNA Methylation Profiling in Colorectal Cancer and Normal Adjacent Colon Using Infinium Human Methylation 450K

The aims were to profile the DNA methylation in colorectal cancer (CRC) and to explore cancer-specific methylation biomarkers. Fifty-four pairs of CRCs and the adjacent normal tissues were subjected to Infinium Human Methylation 450K assay and analysed using ChAMP R package. A total of 26,093 differentially methylated probes were identified, which represent 6156 genes; 650 probes were hypermethylated, and 25,443 were hypomethylated. Hypermethylated sites were common in CpG islands, while hypomethylated sites were in open sea. Most of the hypermethylated genes were associated with pathways in cancer, while the hypomethylated genes were involved in the PI3K-AKT signalling pathway. Among the identified differentially methylated probes, we found evidence of four potential probes in CRCs versus adjacent normal; HOXA2 cg06786372, OPLAH cg17301223, cg15638338, and TRIM31 cg02583465 that could serve as a new biomarker in CRC since these probes were aberrantly methylated in CRC as well as involved in the progression of CRC. Furthermore, we revealed the potential of promoter methylation ADHFE1 cg18065361 in differentiating the CRC from normal colonic tissue from the integrated analysis. In conclusion, aberrant DNA methylation is significantly involved in CRC pathogenesis and is associated with gene silencing. This study reports several potential important methylated genes in CRC and, therefore, merit further validation as novel candidate biomarker genes in CRC.

Identification of early diagnostic biomarkers via WGCNA in gastric cancer

BACKGROUND

Gastric cancer (GC) is the world's second-leading cause of cancer-related mortality, continuing to make it a serious healthcare concern. Even though the prevalence of GC reduces, the prognosis for GC patients remains poor in terms of a lack of reliable biomarkers to diagnose early GC and predict chemosensitivity and recurrence.

METHODS AND MATERIAL

We integrated the gene expression patterns of gastric cancers from four RNAseq datasets (GSE113255, GSE142000, GSE118897, and GSE130823) from Gene Expression Omnibus (GEO) database to recognize differentially expressed genes (DEGs) between normal and GC samples. A gene co-expression network was built using weighted co-expression network analysis (WGCNA). Furthermore, RT-qPCR was performed to validate the in silico results.

RESULTS

The red modules in GSE113255, Turquoise in GSE142000, Brown in GSE118897, and the green-yellow module in GSE130823 datasets were found to be highly correlated with the anatomical site of GC. ITGAX, CCL14, ADHFE1, and HOXB13) as the hub gene are differentially expressed in tumor and non-tumor gastric tissues in this study. RT-qPCR demonstrated a high level of the expression of this gene.

CONCLUSION

The expression levels of ITGAX, CCL14, ADHFE1, and HOXB13 in GC tumor tissues are considerably greater than in adjacent normal tissues. Systems biology approaches identified that these genes could be possible GC marker genes, providing ideas for other experimental studies in the future.

Alternative Splicing-Based Differences Between Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: Genes, Immune Microenvironment, and Survival Prognosis

Alternative splicing (AS) event is a novel biomarker of tumor tumorigenesis and progression. However, the comprehensive analysis of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) is lacking. Differentially expressed analysis was used to identify the differentially expressed alternative splicing (DEAS) events between HCC or ICC tissues and their normal tissues. The correlation between DEAS events and functional analyses or immune features was evaluated. The cluster analysis based on DEAS can accurately reflect the differences in the immune microenvironment between HCC and ICC. Forty-five immune checkpoints and 23 immune features were considered statistically significant in HCC, while only seven immune checkpoints and one immune feature in ICC. Then, the prognostic value of DEAS events was studied, and two transcripts with different basic cell functions (proliferation, cell cycle, invasion, and migration) were produced by ADHFE1 through alternative splicing. Moreover, four nomograms were established in conjunction with relevant clinicopathological factors. Finally, we found two most significant splicing factors and further showed their protein crystal structure. The joint analysis of the AS events in HCC and ICC revealed novel insights into immune features and clinical prognosis, which might provide positive implications in HCC and ICC treatment.

Using Comorbidity Pattern Analysis to Detect Reliable Methylated Genes in Colorectal Cancer Verified by Stool DNA Test

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide in 2020. Colonoscopy and the fecal immunochemical test (FIT) are commonly used as CRC screening tests, but both types of tests possess different limitations. Recently, liquid biopsy-based DNA methylation test has become a powerful tool for cancer screening, and the detection of abnormal DNA methylation in stool specimens is considered as an effective approach for CRC screening. The aim of this study was to develop a novel approach in biomarker selection based on integrating primary biomarkers from genome-wide methylation profiles and secondary biomarkers from CRC comorbidity analytics. A total of 125 differential methylated probes (DMPs) were identified as primary biomarkers from 352 genome-wide methylation profiles. Among them, 51 biomarkers, including 48 hypermethylated DMPs and 3 hypomethylated DMPs, were considered as suitable DMP candidates for CRC screening tests. After comparing with commercial kits, three genes (ADHFE1, SDC2, and PPP2R5C) were selected as candidate epigenetic biomarkers for CRC screening tests. Methylation levels of these three biomarkers were significantly higher for patients with CRC than normal subjects. The sensitivity and specificity of integrating methylated ADHFE1, SDC2, and PPP2R5C for CRC detection achieved 84.6% and 92.3%, respectively. Through an integrated approach using genome-wide DNA methylation profiles and electronic medical records, we could design a biomarker panel that allows for early and accurate noninvasive detection of CRC using stool samples.

Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon Cancer

Objective

To identify the value of key differentially expressed genes (DEGs) regulated by differentially methylated regions (DMRs) in predicting the prognosis of human colon cancer.

Materials and Methods

RNA sequencing data and DNA methylation data of 455 colon adenocarcinoma (COAD) cases and 41 normal controls were downloaded from The Cancer Genome Atlas (TCGA). Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by the DAVID database. To identify the hub genes regulated by methylation, univariate Cox and multivariate Cox regression analyses were carried out. A nomogram based on the risk score was built to identify the power of the hub genes to predict prognosis in patients with colon cancer.

Results

A total of 133 DEGs regulated by DMRs were identified through analyzing RNA sequencing data and DNA methylation data from TCGA. GO functional enrichment and KEGG pathway enrichment analysis showed the genes involved in the initiation and progression of colon cancer. Univariate Cox regression analysis and multivariate Cox regression analysis focused on the seven hub genes (CDH4, CR2, KRT85, LGI4, NPAS4, RUVBL1 and SP140) associated with overall survival, the expression of which negatively correlated with their methylation level. The risk score and nomogram model showed that the hub genes served as potential biomarkers for the prognosis prediction of patients with colon cancer.

Conclusion

Our findings suggest that the DEGs regulated by DMRs are involved in the carcinogenesis and development of colon cancer, and the aberrantly methylated DEGs associated with overall survival of patients may be potential diagnostic and therapeutic targets for colon cancer.

TET2 as a tumor suppressor and therapeutic target in T-cell acute lymphoblastic leukemia

Pediatric T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy in need of novel targeted therapies to prevent relapse and lessen treatment toxicity. We reveal frequent (∼88%) transcriptional silencing or repression of the tumor suppressor TET2 in T-ALL. We show that loss of TET2 in T-ALL is correlated with hypermethylation of the TET2 promoter and that TET2 expression can be rescued by treatment with the DNA demethylating agent, 5-azacytidine (5-aza). We further reveal that the TET2 cofactor vitamin C exerts a strong synergistic effect on global transcriptional changes when added to 5-aza treatment. Importantly, 5-aza treatment results in increased cell death, specifically in T-ALL cells lacking TET2. Thus, we clearly identify 5-aza as a potentially targeted therapy for TET2-silenced T-ALL.

Pediatric T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy resulting from overproduction of immature T-cells in the thymus and is typified by widespread alterations in DNA methylation. As survival rates for relapsed T-ALL remain dismal (10 to 25%), development of targeted therapies to prevent relapse is key to improving prognosis. Whereas mutations in the DNA demethylating enzyme TET2 are frequent in adult T-cell malignancies, TET2 mutations in T-ALL are rare. Here, we analyzed RNA-sequencing data of 321 primary T-ALLs, 20 T-ALL cell lines, and 25 normal human tissues, revealing that TET2 is transcriptionally repressed or silenced in 71% and 17% of T-ALL, respectively. Furthermore, we show that TET2 silencing is often associated with hypermethylation of the TET2 promoter in primary T-ALL. Importantly, treatment with the DNA demethylating agent, 5-azacytidine (5-aza), was significantly more toxic to TET2-silenced T-ALL cells and resulted in stable re-expression of the TET2 gene. Additionally, 5-aza led to up-regulation of methylated genes and human endogenous retroviruses (HERVs), which was further enhanced by the addition of physiological levels of vitamin C, a potent enhancer of TET activity. Together, our results clearly identify 5-aza as a potential targeted therapy for TET2-silenced T-ALL.

ADHFE1 is a correlative factor of patient survival in cancer

Alcohol dehydrogenase iron containing 1 (ADHFE1) encodes a hydroxyacid-oxoacid transhydrogenase participating in multiple biological processes. The role of ADHFE1 in cancer has not been fully uncovered. Herein, we performed data analysis to investigate the expression of ADHFE1 and the underlying regulatory mechanisms, its relationship with cancer patients’ survival, and the relevant pathways in cancer. A range of recognized, web-available databases and bioinformatics tools were used in this in silico study. We found that ADHFE1 was frequently downregulated and hypermethylated in various cancer cell lines and tissue samples. High expression of ADHFE1 was positively associated with favorable patient prognosis in breast, colon, and gastric cancers. Pathway analysis revealed its potential role in cancer-related biological processes, including energy metabolism, DNA replication, and cell cycle regulation. AHDFE1 mRNA expression and DNA methylation can potentially be used as diagnostic markers in cancer and might be of great value in predicting the survival of patients with cancer.

MiR-30a and miR-379 modulate retinoic acid pathway by targeting DNA methyltransferase 3B in oral cancer

BACKGROUND

Epigenetic silencing of retinoic acid (RA) signaling-related genes have been linked with the pathogenesis and clinical outcome in oral squamous cell carcinoma (OSCC) carcinogenesis. However, the precise mechanisms underlying the abnormal silencing of RA signaling-related genes in OSCC have not been well investigated.

METHODS

Using combined analysis of genome-wide gene expression and methylation profile from 40 matched normal-tumor pairs of OSCC specimens, we found a set of retinoid signaling related genes are frequently hypermethylated and downregulated in OSCC patient samples, including alcohol dehydrogenase, iron containing 1 (ADHFE1) and aldehyde dehydrogenase 1 family, member A2 (ALDH1A2), which are the important rate-limiting enzymes in synthesis of RA. The expression of ADHFE1 and ALDH1A2 in OSCC patients was determine by quantitative real-time PCR (qRT-PCR) and immunohistochemistry. The binding sites of miR-30a and miR-379 with DNA methyltransferase 3B (DNMT3B) were predicted using a series of bioinformatic tools, and validated using dual luciferase assay and Western blot analyses. The functions of miR-30a, miR-379, and DNMT3B were accessed by growth and colony formation analyses using gain- and loss-of-function approaches. Chromatin immunoprecipitation (ChIP) was performed to explore the molecular mechanisms by arecoline and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) treatment.

RESULTS

We demonstrated that deregulated miR-30a and miR-379 could represent a mechanism for the silencing of ADHFE1 and ALDH1A2 in OSCC through targeting DNMT3B. Ectopic expression of miR-30a and miR-379 could induce re-expression of methylation-silenced ADHFE1 and ALDH1A2, and lead to growth inhibition in oral cancer cells. Furthermore, the dysregulation of the miRNAs and DNMT-3B may result from exposure to tobacco smoking and betel quid chewing.

CONCLUSIONS

Our results demonstrate that tobacco smoking and betel quid chewing could repress miR-30a and miR-379, which upregulate the DNMT3B expression, in turn, lead to the hypermethylation of ADHFE1 and ALDH1A genes, consequently, promote the oncogenic activity. These findings highlight the potential use of retinoids in combination with epigenetic modifiers for the prevention or treatment of oral cancer.